Selected Publications
My main emphasis is on presenting my work at premier data science and data engineering venues. For a list of my publications, please refer to DBLP and Google Scholar (however, it’s important to note that the information may not be up-to-date).
Year 2023
-
Contact tracing over uncertain indoor positioning data.
Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, and Harry Kai-Ho Chan.
IEEE Transactions on Knowledge and Data Engineering (TKDE).
-
Worker-churn-based task assignment with context-LSTM in spatial crowdsourcing.
Yan Zhao, Tinghao Lai, Ziwei Wang, Kaixuan Chen, Huan Li, and Kai Zheng.
IEEE Transactions on Knowledge and Data Engineering (TKDE).
-
Time-constrained indoor keyword-aware routing: Foundations and extensions.
Harry Kai-Ho Chan, Tiantian Liu, Huan Li, and Hua Lu.
Geoinformatica (Special Issue of SSTD21 Best Papers).
-
Efficiently computing alternative paths in game maps.
Lingxiao Li, Muhammad Aamir Cheema, Mohammed Eunus Ali, Hua Lu, and Huan Li.
World Wide Web Journal.
-
LightCTS: A lightweight framework for correlated time series forecasting.
Zhichen Lai, Dalin Zhang, Huan Li, Christian S. Jensen, Hua Lu, and Yan Zhao.
2023 ACM SIGMOD International Conference on Management of Data (SIGMOD).
-
Data imputation for sparse radio maps in indoor positioning.
Xiao Li, Huan Li, Harry Kai-Ho Chan, Hua Lu, and Christian S. Jensen.
The 39th IEEE International Conference on Data Engineering (ICDE).
-
FedBFPT: An efficient federated learning framework for Bert further pre-training.
Xin'ao Wang, Huan Li, Ke Chen, and Lidan Shou.
The 32nd International Joint Conference on Artificial Intelligence (IJCAI).
-
TPUF: Enhancing cross-domain sequential recommendation via transferring pre-trained user features.
Yujia Ding, Huan Li, Ke Chen, and Lidan Shou.
The 32nd ACM International Conference on Information & Knowledge Management (CIKM).
Year 2022
-
Spatial data quality in the Internet of Things: Management, exploitation, and prospects.
Huan Li, Hua Lu, Christian S. Jensen, Bo Tang, and Muhammad Aamir Cheema.
ACM Computing Surveys, 55(3) No.26: 1-41.
-
Spatial data analysis for intelligent buildings: Awareness of context and data uncertainty.
Huan Li, Tiantian Liu, Harry Kai-Ho Chan, and Hua Lu.
Frontiers in Big Data, Rising Stars in Data Mining and Management 2022.
-
Spatial data quality in the IoT era: Management and exploitation.
Huan Li, Bo Tang, Hua Lu, Muhammad Aamir Cheema, and Christian S. Jensen.
2022 ACM SIGMOD International Conference on Management of Data (SIGMOD).
-
GHive: A demonstration of GPU-accelerated query processing in Apache Hive.
Haotian Liu, Bo Tang, [et al., including Huan Li].
2022 ACM SIGMOD/PODS International Conference on Management of Data (SIGMOD).
-
Efficient and error-bounded spatiotemporal quantile monitoring in edge computing environments.
Huan Li, Lanjing Yi, Bo Tang, Hua Lu, and Christian S. Jensen.
The 48th International Conference on Very Large Data Bases (VLDB).
-
Continuous social distance monitoring in indoor space.
Harry Kai-Ho Chan, Huan Li, Xiao Li, and Hua Lu.
The 48th International Conference on Very Large Data Bases (VLDB).
-
IKAROS: An indoor keyword-aware routing system.
Tiantian Liu, Zijin Feng, Huan Li, Hua Lu, Lidan Shou, and Jianliang Xu.
The 38th IEEE International Conference on Data Engineering (ICDE).
-
GHive: Accelerating analytical query processing in Apache Hive via CPU-GPU heterogeneous computing.
Haotian Liu, Bo Tang, [et al., including Huan Li].
13th Symposium on Cloud Computing (ACM SoCC) -- SIGMOD and SIGOPS co-sponsored.
-
Diverse shortest paths in game maps: A comparative user study and experiments.
Lingxiao Li, Muhammad Aamir Cheema, Mohammed Eunus Ali, Hua Lu, and Huan Li.
2022 Australasian Database Conference (ADC).
Year 2021
-
Towards crowd-aware indoor path planning.
Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, and Lidan Shou.
The 47th International Conference on Very Large Data Bases (VLDB).
-
Towards indoor temporal-variation aware shortest path query.
Tiantian Liu, Zijin Feng, Huan Li, Hua Lu, Muhammad Aamir Cheema, Hong Cheng, and Jianliang Xu.
IEEE Transactions on Knowledge and Data Engineering (TKDE).
-
Indoor spatial queries: Modeling, indexing, and processing.
Tiantian Liu, Huan Li, Hua Lu, Muhammad Aamir Cheema, and Lidan Shou.
The 24th International Conference on Extending Database Technology (EDBT).
-
Time-constrained indoor keyword-aware routing.
Harry Kai-Ho Chan, Tiantian Liu, Huan Li, and Hua Lu.
The 17th International Symposium on Spatial and Temporal Databases (SSTD).
-
Impact of COVID-19 on adoption of IoT in healthcare, smart homes, smart buildings, smart cities, transportation and industrial IoT.
Muhammad Umair, Muhammad Aamir Cheema, Omer Cheema, Huan Li, and Hua Lu.
MDPI Sensors, 21(11), 3838.
Year 2020
-
Toward translating raw indoor positioning data into mobility semantics.
Huan Li, Hua Lu, Gang Chen, Ke Chen, Qinkuang Chen, and Lidan Shou.
ACM/IMS Transactions on Data Science (TDS), 1(4) No.26: 1-37.
-
Indoor mobility semantics annotation using coupled conditional Markov networks.
Huan Li, Hua Lu, Muhammad Aamir Cheema, Lidan Shou, and Gang Chen.
The 36th IEEE International Conference on Data Engineering (ICDE).
-
Shortest path queries for indoor venues with temporal variations.
Tiantian Liu, Zijin Feng, Huan Li, Hua Lu, Muhammad Aamir Cheema, Hong Cheng, and Jianliang Xu.
The 36th IEEE International Conference on Data Engineering (ICDE).
-
Indoor top-k keyword-aware routing query.
Zijin Feng, Tiantian Liu, Huan Li, Hua Lu, Lidan Shou, and Jianliang Xu.
The 36th IEEE International Conference on Data Engineering (ICDE).
Year 2019
-
Finding most popular indoor semantic locations using uncertain mobility data.
Huan Li, Hua Lu, Lidan Shou, Gang Chen, and Ke Chen.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(11): 2108-2123.
-
Finding most popular indoor semantic locations using uncertain mobility data (extended abstract).
Huan Li, Hua Lu, Lidan Shou, Gang Chen, and Ke Chen.
The 35th IEEE International Conference on Data Engineering (ICDE).
-
In search of indoor dense regions: An approach using indoor positioning data (extended abstract).
Huan Li, Hua Lu, Lidan Shou, Gang Chen, and Ke Chen.
The 35th IEEE International Conference on Data Engineering (ICDE).
Year 2018 and Before
-
TRIPS: A system for translating raw indoor positioning data into visual mobility semantics.
Huan Li, Hua Lu, Feichao Shi, Gang Chen, Ke Chen, and Lidan Shou.
The 44th International Conference on Very Large Data Bases (VLDB).
-
Vita: A versatile toolkit for generating indoor mobility data for real-world buildings.
Huan Li, Hua Lu, Xin Chen, Gang Chen, Ke Chen, and Lidan Shou.
The 42nd International Conference on Very Large Data Bases (VLDB).
-
In search of indoor dense regions: An approach using indoor positioning data.
Huan Li, Hua Lu, Lidan Shou, Gang Chen, and Ke Chen.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 30(8): 1481-1495.
-
E2C2: Efficient and effective camera calibration in indoor environments.
Huan Li, Pai Peng, Hua Lu, Lidan Shou, Ke Chen, and Gang Chen.
The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp).
Lecture Notes
Thesis
-
Uncertain indoor mobility data mining and analytics.
Author: Huan Li; Advisors: Gang Chen and Lidan Shou.
Zhejiang University, April, 2018.
For the provision of code, data, and supplementary materials (e.g., slides, posters, and videos) associated with the publications, please write to me via email.


Please use your mouse to draw a letter (e.g. E) in the box below. (To draw: Click and then drag your mouse)


--- title: "Scaling Tooltip" description: |
As its name, this tooltip shows content from the right corner with little icon. You can specific tooltip scale from right to left and all the way down or scale right to left and continue expand to left.
author: Aashish Nagpal category: standard type: tooltip order: 2 ---


DONATUSSIN DROPS - phenylephrine hydrochloride and guaifenesin liquid
Laser Pharmaceuticals, LLC
Disclaimer: Most OTC drugs are not reviewed and approved by FDA, however they may be marketed if they comply with applicable regulations and policies. FDA has not evaluated whether this product complies.
Active ingredients
(in each 1 mL dropperful)Phenylephrine Hydrochloride 1.5 mg
Guaifenesin 20.0 mg
Purpose
Nasal Decongestant
Expectorant
Uses
temporarily relieves these symptoms occurring with a
cold:
- nasal congestion
- cough due to minor throat and bronchial irritation
- helps loosen phlegm (mucus) and thin bronchial secretions to make coughs more productive
Warnings
Do not exceed recommended dosage.
Do not use this product
- if you or your child are now taking a prescription monoamine oxidase inhibitor (MAOI) (certain drugs for depression, psychiatric, or emotional conditions, or Parkinson's disease), or for two weeks after stopping the MAOI drug. If you do not know if you child's or your prescription drug contains and MAOI, ask a doctor or pharmacist before taking this product or giving it to your child.
Ask a doctor before use if you or your child has
- heart disease
- high blood pressure
- thyroid disease
- diabetes
- trouble urinating due to an enlarged prostate gland
- cough that occurs with too much phlegm (mucus)
- cough that lasts or is chronic such as occurs with asthma
Ask a doctor or pharmacist before use if you or your child are
sedatives or tranquilizers.
When using this product
- you may get drowsy
- avoid alcoholic drinks
- alcohol, sedative, and tranquilizers may increase drowsiness
- be careful when driving a motor vehicle or operating machinery
- excitability may occur, especially in children
Stop use and ask a doctor if
- nervousness, dizziness, or sleeplessness occurs
- if symptoms do not get better within 7 days or are accompanied by a fever.
- cough lasts more than 7 days, comes back, or is accompanied by fever, rash, or persistent headache.
If pregnant or breast-feeding,
ask a health professional before use.
Keep out of the reach of children.
In case of overdose, get medical help or contact a Poison Control Center right away.
Directions
- Do not exceed recommended dosage.
- Use enclosed dropper only. Do not use any other dosage device.
Children 6 to under 12 years of age:
|
2 dropperfuls (2 mL) every 4 to 6 hours, not to exceed 6 doses in 24 hours.
|
Children under 6 years of age:
|
Consult a doctor.
|
Other information
Store at controlled room temperature 59° -86°F (15° -30°C)
[see USP Controlled Room Temperature].
Inactive ingredients
Citric Acid, Sodium Citrate, Sodium Saccharin, Sorbitol 70% Solution, Glycerin 99.5% minimum, Propylene Glycol, Raspberry Flavor, FD and C Red #40, Purified Water.
Questions? Comments?
Call your doctor for medial advice about side effects. Serious side effects associated with use of this product may be reported to this number. 1-864-286-8229 (Mon-Fri) 8am-5pm EST.
PRODUCT PACKAGING
The packaging below represents labeling currently used:
Principal Display Panel and Side Panel for 30 mL Label:
NDC 16477-106-30
Donatussin DROPS
Nasal Decongestant
Expectorant
Sugar Free / Alcohol Free
Raspberry Flavored
Each dropperful (1.0 mL) for oral administration, contains:
Phenylephrine HCl.......................1.5 mg
Guaifenesin...............................20.0 mg
1 fl oz (30 mL)
Tamper evident by foil seal under cap. Do not use if foil seal is missing or broken.
Supplied in a tight, light-resistant container with a child-resistant closure.
Manufactured for:
Laser Pharmaceuticals, LLC
Greenville, SC 29615 Rev. 06/10


|
Smartlock
|
Data Structures | |
| struct | _flash_prefetch_speculation_status |
| FTFx prefetch speculation status. More... | |
| struct | _ftfx_cache_config |
| FTFx cache driver state information. More... | |
Typedefs | |
| typedef struct _flash_prefetch_speculation_status | ftfx_prefetch_speculation_status_t |
| FTFx prefetch speculation status. | |
| typedef struct _ftfx_cache_config | ftfx_cache_config_t |
| FTFx cache driver state information. More... | |
Enumerations | |
| enum | _ftfx_cache_ram_func_constants { kFTFx_CACHE_RamFuncMaxSizeInWords = 16U } |
| Constants for execute-in-RAM flash function. More... | |
Functions | |
| status_t | FTFx_CACHE_Init (ftfx_cache_config_t *config) |
| Initializes the global FTFx cache structure members. More... | |
| status_t | FTFx_CACHE_ClearCachePrefetchSpeculation (ftfx_cache_config_t *config, bool isPreProcess) |
| Process the cache/prefetch/speculation to the flash. More... | |
| status_t | FTFx_CACHE_PflashSetPrefetchSpeculation (ftfx_prefetch_speculation_status_t *speculationStatus) |
| Sets the PFlash prefetch speculation to the intended speculation status. More... | |
| status_t | FTFx_CACHE_PflashGetPrefetchSpeculation (ftfx_prefetch_speculation_status_t *speculationStatus) |
| Gets the PFlash prefetch speculation status. More... | |
FTFx cache version | |
| #define | FSL_FTFX_CACHE_DRIVER_VERSION (MAKE_VERSION(3, 0, 0)) |
| Flexnvm driver version for SDK. More... | |
| #define FSL_FTFX_CACHE_DRIVER_VERSION (MAKE_VERSION(3, 0, 0)) |
Flexnvm driver version for SDK.
Version 1.0.0.
| typedef struct _ftfx_cache_config ftfx_cache_config_t |
FTFx cache driver state information.
An instance of this structure is allocated by the user of the flash driver and passed into each of the driver APIs.
| status_t FTFx_CACHE_ClearCachePrefetchSpeculation | ( | ftfx_cache_config_t * | config, |
| bool | isPreProcess | ||
| ) |
Process the cache/prefetch/speculation to the flash.
| config | A pointer to the storage for the driver runtime state. |
| process | The possible option used to control flash cache/prefetch/speculation |
| kStatus_FTFx_Success | API was executed successfully. |
| kStatus_FTFx_InvalidArgument | Invalid argument is provided. |
| kStatus_FTFx_ExecuteInRamFunctionNotReady | Execute-in-RAM function is not available. |
Process the cache/prefetch/speculation to the flash.
This function is used to perform the cache and prefetch speculation clear process to the flash.
| status_t FTFx_CACHE_Init | ( | ftfx_cache_config_t * | config | ) |
Initializes the global FTFx cache structure members.
This function checks and initializes the Flash module for the other FTFx cache APIs.
| config | Pointer to the storage for the driver runtime state. |
| kStatus_FTFx_Success | API was executed successfully. |
| kStatus_FTFx_InvalidArgument | An invalid argument is provided. |
| kStatus_FTFx_ExecuteInRamFunctionNotReady | Execute-in-RAM function is not available. |
| status_t FTFx_CACHE_PflashGetPrefetchSpeculation | ( | ftfx_prefetch_speculation_status_t * | speculationStatus | ) |
Gets the PFlash prefetch speculation status.
| speculationStatus | Speculation status returned by the PFlash IP. |
| kStatus_FTFx_Success | API was executed successfully. |
| status_t FTFx_CACHE_PflashSetPrefetchSpeculation | ( | ftfx_prefetch_speculation_status_t * | speculationStatus | ) |
Sets the PFlash prefetch speculation to the intended speculation status.
| speculationStatus | The expected protect status to set to the PFlash protection register. Each bit is |
| kStatus_FTFx_Success | API was executed successfully. |
| kStatus_FTFx_InvalidSpeculationOption | An invalid speculation option argument is provided. |


---
layout: default
---
Thanks to everyone who's provided content, reviewed my content or helped me with issues.
- Missy for helping me edit some content.
- Evan for being amazing.
- Unsplash.com for providing photos
- Everyone else who contributed in some way!


Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist radiologists in the interpretation of medical images. Imaging techniques in X-ray, CT, MRI, and ultrasound diagnostics yield a great deal of information that the radiologist has to analyze and evaluate comprehensively in a short time. CAD systems process digital images for typical appearances and highlights pathologies in order to offer input to support a decision taken by the professional.
Read More


{% extends "content_base.html" %} {% block head_title %}Gold Sponsor • Kontagent{% endblock %} {% block body %}
The Kontagent mission is to enable our customers to deliver the perfect customer experience through the use of actionable data. The Kontagent development team is responsible for developing the platform for efficient collection of this data and applications which enable customer insight. Currently our system supports millions of active users and processes trillions of events resulting in petabytes of data.
We use a number of Open Source products along with internally developed solutions to provide the Kontagent data platform and applications. External products include Kafka, Storm, Hadoop, Hive and MySQL. Internal solutions are developed in Python and Java. We continue to build out our product offerings with both Open Source software and internally developed solutions as appropriate to provide a flexible platform which efficiently scales and applications which provide deep insight.
We make use of Python a lot in our products and want to ensure its ongoing success. In addition, we want to be aware of the up and coming Python technologies that will allow us to further grow and scale our infrastructure. Finally, we want to build strong relationships with other members of the Python development community.
We are always focused on how to effectively scale our system which currently processes over six billion events per day. As the number of events continues to grow we must build systems which can scale by orders of magnitude beyond our current capabilities. In addition, we need to enable our customers to better utilize this data through applications which provide the deeper insight and broader automation. In order to achieve our mission, we need to develop the core technology and algorithms that help us understand complex systems and markets. This way we can anticipate a customer need before they know they need it.
Our teams are self managing and are encouraged to work together in a open environment. This includes daily stand ups for information sharing and collaborative discussions among team members throughout the day. We encourage iterative feature development with a focus on decreasing lead-time in order to increase the actual value of our deliverables. We utilize modern developer workflows using git and pull requests and strive for complete unit test coverage with continuous integration. We like to have fun which includes everything from discussing brain teasers over the company provided lunches to shooting a team member with a nerd dart to scavenger hunts and playing board games late into the evening.
{% endblock %}


WITNESS LIST State, Federal & International Relations Committee May 11, 1999-8:00A SB 655 For: Geurrero, Debra (City of San Antonio) Gonzaba, Chave (Greater Kelly Development Corporation) Roberson, Paul (Greater Kelly Development Corporation) Troilo, Arthur (Greater Kelly Development Corporation) Wells, Tullos (Greater Kelly Development Corporation) SB 1426 Registering, but not testifying: For: Cain, Randy (City of Lubbock) SB 1427 Registering, but not testifying: For: Cain, Randy (City of Lubbock) SB 1428 Registering, but not testifying: For: Cain, Randy (City of Lubbock) SCR 40 Registering, but not testifying: For: Cain, Randy (City of El Paso)


|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
public interface CollectionAnalytics
Interface that exposes a set of methods for performing analytic operations on a collection of Record objects.
| Method Summary | |
|---|---|
long |
getCountOfEstPopDecr(int year)
Count of states with estimated population decrease |
long |
getCountOfEstPopIncr(int year)
Count of states with estimated population increase. |
java.lang.String |
getStateWithLeastPop(int year)
Get the State with the least population. |
java.lang.String |
getStateWithMostPop(int year)
Get the State with the most population. |
| Method Detail |
|---|
long getCountOfEstPopIncr(int year)
year
- integer value equal to either 2010 or 2011.
long getCountOfEstPopDecr(int year)
year
- integer value equal to either 2010 or 2011
java.lang.String getStateWithMostPop(int year)
year
- integer value equal to either 2010 or 2011
java.lang.String getStateWithLeastPop(int year)
year
- integer value equal to either 2010 or 2011
|
|||||||||
| PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
| SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |


§804-6 Bail bond after conviction. Unless otherwise ordered by the court the bail bond given by any defendant prior to the defendant's conviction, shall, in cases where bail after conviction is permitted either absolutely or by order of the court, be continued as the bail of the defendant after conviction, and until the final determination of any subsequent proceedings in the cause. [L 1892, c 32, §4; RL 1925, §3981; RL 1935, §5435; RL 1945, §10736; RL 1955, §256-6; HRS §709-6; ren L 1972, c 9, pt of §1; gen ch 1985]
Rules of Court
Bail; bond, see HRPP rule 46.
Case Notes
Condition of bond; notice to principals. 19 H. 5 (1908).


sparkling water
Perrier Sparkling Natural Mineral Water, the source for which dates back over 100 million years, became part of the Nestle Waters North America family of brands in 1992. Perrier Sparkling Natural Mineral Water comes from a source in the south of France. Located near the small village of Vergeze, in Provence, the spring’s unique balance of minerals and addition of light effervescence provides its distinctively fresh, clean taste. It is this singular blend of gases and minerals which has made Perrier the world’s most requested sparkling natural water.
About
Source Perrier has been the subject of careful study by a generatiom of scrintists. Scientiests trace the source back moe than 100 million years to the Cretaceous Era, when limestone deposits formed faults and fissures, which captued water deep within the earth,
Unique Mixed Water
Limestones of garrigues hill nothes of nimes is one of the sources
Percolated through a gravel aquifer beneath the Languedoc plain
Hot water of deep volcanic origin
Quality Control
Water tested as it comes to the plant
State of art technology form a light balance of water and minerals
Water is checked hoursly to guarantee the quality
Sparkling Process
The Calcium Carbonate Layers, Forming Carbonated Gas
Water And Gas Collect And Combine Separately
Removed The Natural Impurities In The Gas


|
Anchors
Basic metacharacters
Character classes
Comments
Control and code
Grouping
Look around
Mode modifiers
Quantifiers
Specific characters
|
Usually match modes, e.g. whether the match should be case-insensitive or not, are set outside of the regular expression. Mode modifiers allow you to set them inside and for parts of an expression.
Basic structure
Mode modifiers
Basic structure
| |
Item
|
|
Meaning:
|
|
| |
(?M)
|
|
Turn modifier M on for the rest of the expression or until it is turned off.
|
|
| |
(?-M)
|
|
Turn modifier M off for the rest of the expression or until it is turned on.
|
|
| |
(?M:…)
|
|
Turn modifier M on for the expression between the non capturing parentheses.
(Note: the modifier is followed by colon.)
|
|
| |
|
In the table “…” stands for any one or more characters.
|
| |
Mode modifiers |
| |
Item
|
|
Mode:
|
|
| |
i
|
|
Case-insensitive mode.
|
|
| |
m
|
|
Multiline mode
Allow ^ and $ to match at embedded newlines.
|
|
| |
s
|
|
Dot matches all mode.
Dot (. ) will match any character including newline.
|
|
| |
x
|
|
Free flow mode.
Ignores (most) whitespace and permits comments preceded by “# ” in an expression.
|
|
| |
You can combine multiple modifiers, turning some on and some of. For example (?i-m) will turn case-insensitivity on and multiline mode off.
|


{% extends "main.html" %} {% block content %}
In the dropdown menu that appear when you hover on the logo hover on to Manage to see the sub dropdown menu.Then click on the classes and add the classes and the subjects to be taught to the class one by one. If there is a typo delete button can be used to delete the response. Then go to sub drop down menu and click on subjects. Add the subjects and the frequency of the subject per week.You can update and delete a subject details.Then click on teachers in the sub drop down list.Add teacher name and select the subject he/she teaches in the drop down list of subjects. Then go back to sub drop down menu and click on slots to add time-slots.Select whether the time-slot should be class or break.Then go back to drop down menu and selct open. Select the teacher or the class for which you want to see the timetable.
{% endblock %}


Cell: +59899956294
Email<EMAIL_ADDRESS>Skype: andres.canavesi
Linkedin: https://www.linkedin.com/in/andrescanavesi/
Blog: https://andrescanavesi.wordpress.com/
Github: https://github.com/andrescanavesi
Google me!
32 year old Software Engineer with over 9 years of experience in software development. Experience in designing and implementing mobile development, web applications and desktop applications using mainly Java,
Android and Salesforce.
I was a dependent as well as an independent employee, often working remotly.
I'm from Montevideo, Uruguay where I currently live. I'm wiling to relocate, depending on conditions.
5 years professional career at UDE university (Montevideo, Uruguay). Career oriented to management and a strong knowledge in mathematics and software development using Java and C++


Everything here you can navigate via HTML and programmatically via JSON, all accessible from this single sitemap.


Andrew's 2048
{{gameLogic.currentScore}}
{{gameLogic.highScore}}
Join the numbers and get to the 2048 tile!
How to play: Use your arrow keys to move the tiles. When two tiles with the same number touch, they merge into one!


{% extends "layout.html" %} {% block page_title %} GOV.UK prototype kit {% endblock %} {% block content %} Home Sign out Warwickshire college UKPRN:12345678 Apprenticeship service Details and employer requests Contracts and agreements 2 new alerts to review Funding claims 3 new alerts to review Payment history View your payments Subcontractor declaration Manage your declarations {% endblock %}
UKPRN:12345678


this is a
sample
italics
paragrah
a
2
+ b
2
+ 2*a*b=(a+b)
2
a
k
=a
i
+a
j
quoted text
abcd
qwerrty
text1
text2


Shooting Dates
-
Shooting Dates
-
Shooting Completed
{{ completed | date: 'shortDate' }}
-
Shooting In Progress
{{ progress | date: 'shortDate' }}
-
Shooting Planned
From
{{ planned | toLabel: 'shootingPeriod' }}
{{ planned | titlecase }}
{{ planned }}
to
{{ planned | toLabel: 'shootingPeriod' }}
{{ planned | titlecase }}
{{ planned }}
-
Shooting Locations
-
{{ location.country | toLabel: 'territories' }} - {{ location.cities.join(', ') | titlecase }}
-
Expected Premiere
{{ event }}
-
{{ date | date: 'MMMM y' }}


Name: Lollypops
Number of beads: 12
Description: A bite sized lollypop not for eating!
Name: Lollypops
Number of beads: 12
Description: A bite sized lollypop not for eating!
Name: Pizza
Number of beads: 15
Description: Pepperoni, but no cheese please!
Name: Facebook
Number of beads: 36
Description: Fantastic Facebook logo.
Name: YouTube
Number of beads: 26
Description: Like and subscribe with this YouTube logo.
Name: Toucan
Number of beads: 62
Description: Terrific toucan.
Name: Toast 🍞
Number of beads:34
Description: Adorable food is my speciality.
Name: Unicorn 🦄
Number of beads: 35
Description: Mystical, magical and marvelous.
Anton is a passionate footballer and always tries 110%. He enjoys being creative and experimenting with his Hama Beads. Anton is trying out coding with the help of his dad. He can sew and is learning to knit. Anton is a brilliant multitasker and is always up for a challenge.
He is also the younger host of the hit podcast, The Curiosity of a Child.


-
Most Of The U.S. Saw Little Recovery In 2013
fivethirtyeight.com
Energy and apps are driving strong economic recoveries in parts of the United States. But the rest of the country has been far less lucky. The ...
-
NFL Week 3 Elo Ratings And Playoff Odds
fivethirtyeight.com
It’s been hard for me to escape the feeling that something's off about NFL games this year. But that may be the league’s off-field problems coloring ...
-
Derek Jeter Will Go Down As One Of The 500 Best Players Of All Time
www.clickhole.com
Tonight, Derek Jeter will play his last Major League baseball game at Yankee Stadium, bidding farewell to the city and fans who have given him so ...
-
1901-02 Orioles Removed from Yankees History » Sports Reference
www.sports-reference.com
Stats, Analysis and History
-
Qatar will not host 2022 World Cup, says FIFA's Zwanziger
uk.mobile.reuters.com
BERLIN (Reuters) - The 2022 World Cup will not be held in Qatar because of the scorching temperatures in the Middle East country, FIFA Executive ...
-
Advanced Football Analytics Win Probability - Current Games
live.advancednflstats.com
This content requires JavaScript.
-
Sorry, Matt Bai, but I don’t think Gary Hart was gonna get elected ...
www.washingtonpost.com
Gary Hart wasn't on track to win the 1988 presidential election.
-
Baseball Prospectus | BP Daily Podcast: Effectively Wild Episode 538: Nate ...
www.baseballprospectus.com
Ben and Sam talk to Nate Silver about baseball analysis and the first six months of FiveThirtyEight.
-
A Statistical Appreciation Of Li Na
fivethirtyeight.com
Li Na, the two-time Grand Slam champion who on Friday announced her retirement, was the greatest Asian tennis player of all time. She was much more ...
-
How the Ray Rice scandal unfolded
espn.go.com
Outside the Lines: A pattern of misinformation and misdirection was employed by the Baltimore Ravens and the NFL after Ray Rice hit his wife.
-
Senate Update: Democrats Add By Subtraction In Kansas
fivethirtyeight.com
You know it’s a strange election year when a party benefits from the removal of its own candidate from the ballot. But that’s exactly what’s happened ...
-
New York Publishing jobs - Director Business Development ...
jobs.espncareers.com
Director Business Development FiveThirtyEight.com in New York currently available at ESPN. Additional New York Publishing jobs also available at ESPN.
-
Adrian Gray sur Twitter : "Senate: Updated this morning (with Kansas). GOP ...
twitter.com
Mot de passe oublié ? Vous utilisez déjà Twitter via SMS ?
-
Beneath The Premier League Stands The Great Football Pyramid Of England
fivethirtyeight.com
On Saturday, Swansea City will host Southampton in an English Premier League fixture in South Wales. Southampton was a founding member of the Premier ...
-
Why Pollsters Think They Underestimated 'No' In Scotland
fivethirtyeight.com
With two notable exceptions, opinion polls released this month about Scotland's independence referendum vote gave an accurate picture: "No," a vote ...
-
The Scotland Independence Polls Were Pretty Bad
fivethirtyeight.com
About a year ago, I was on a book tour in Edinburgh and was asked by a couple of reporters about Scotland’s upcoming vote on whether to secede from ...
-
Patrick Murray sur Twitter : "Re #ScotlandIndependence #polls, assume most ...
twitter.com
Mot de passe oublié ? Vous utilisez déjà Twitter via SMS ?
-
Breaking: In #KSSEN, Court Rules Taylor Off the Ballot: Analysis | ...
electionlawblog.org
Election Law Blog - Rick Hasen's blog
-
The Rate of Domestic Violence Arrests Among NFL Players
fivethirtyeight.com
Last week, the NFL suspended Baltimore Ravens running back Ray Rice for two games over an incident in which Rice was charged with knocking his ...
-
Skeptical Football: Goatslingers, Manning vs. Messi, And The Andrew Luck ...
fivethirtyeight.com
In last week’s column, I pointed out the importance of teams’ early records when trying to predict their playoff fates. This prompted a few skeptical ...
-
A Rough Guide To Watching The Scottish Independence Vote
fivethirtyeight.com
On Thursday, Scottish residents 16 and older will vote in a referendum to decide whether Scotland will leave the United Kingdom and become an ...
-
British Politics Betting Odds | Politics Betting
www.oddschecker.com
British Politics Betting Odds. View all available outright and match odds, plus get news, tips, free bets and money-back offers. All you need to bet.
-
Monday final: Senate 51D-49R, House 230R-205D
election.princeton.edu
In the Senate: In critical states there are so many polls that fairly exact statements can be made. The probability of the Senate remaining ...
-
A quick note on the PEC Senate model
election.princeton.edu
[Update, Friday 1:00pm: The Election Day prediction now takes into account the new Kansas Senate race, scoring it as a tie.]
-
How The FiveThirtyEight Senate Forecast Model Works
fivethirtyeight.com
The FiveThirtyEight Senate forecast model launched earlier this month. Right now, it shows Republicans with about a 53 percent chance of picking up ...
-
For Some MLB Playoff Teams, There's No Place Like Road
fivethirtyeight.com
In our quest to solve baseball riddles, we sometimes turn to our friends on Twitter for assistance for topics worth tackling. This one, from ...
-
Pollsters Shouldn't Take Mulligans
fivethirtyeight.com
I was troubled by a survey released Monday by Mitchell Research in Michigan. It wasn't that the results -- which showed Democratic Rep. Gary Peters ...
-
iPhone camera evolution: How does the iPhone 6 camera compare to previous ...
snapsnapsnap.photos
How does the iPhone 6 camera stack up against previous hardware? In her ongoing series, professional iPhone photographer Lisa Bettany takes a hard ...
-
The Great Lightbulb Conspiracy - IEEE Spectrum
spectrum.ieee.org
The Phoebus cartel engineered a shorter-lived lightbulb and gave birth to planned obsolescence


module type SeededHashedType = Hashtbl.SeededHashedType;
type t;
let equal: (t, t) => bool;
let hash: (int, t) => int;
equal x y
is true,
then hash seed x = hash seed y
for any value of seed
.
A suitable choice for hash
is the function Hashtbl.seeded_hash
below.


We at Paramparik Foods (Shreejew Foods & Beverages Pvt. Ltd.) select best quality raw materials of Spices, Pulses & etc. from the best regions across India, blend them carefully for the best quality of flavor and aroma for the best recipes. We pack them in clean and hygienic conditions to preserve the maximum aroma and flavor. By placing high quality and authentic ingredients we ensure the best quality should reach you without any compromise. We always seek to bring the finest quality at best price.
To deliver premium quality products prepared under hygenic conditions, processed under several multilayered filtering process, prepared by top class ingredients & raw materials to the customers.
To become the most preffered household name in Eastern India within next five years. We are committed to produce the best quality products at best price. We will provide most innovative and customized products in the FMCG segment at a very reasonable price.
* Fully automated hygenic state-of-art manufacturing unit.
* Innovative and Hygenical Packaging.
* Prepared from best quality raw materials.
The brand "PARAMPARIK" was launched in 2014. It is manufactured by M/s Shreejew Foods & Beverages (P) Ltd. which is aiming for a goodwill within next five years in food industry in Odisha and India.
SFB or Shreejew Foods & Beverages (P) Ltd. is the mother company of the brand "PARAMPARIK" which was estd. on June 2014. Shreejew foods & beverages pvt. ltd. is an emerging spices and dietery supplement production company in Odisha,India. The company is well known for its quality all around its customers across Odisha and Outstate. Shreejew foods & beverages pvt. ltd. indulges itself with Trust, Purity and Integrity.
PARAMPARIK always aims to maintain the best quality for which it has always been known. Now PARAMPARIK almost covers over 16-18 districts over Odisha within this short period of time. Now PARAMPARIK is looking forward to serve each & every corner of Odisha with high quality products with reasonable and affordable price.
A career at Shreejew Foods & Beverages pvt. ltd can be very rewarding, especially to the hard-working & creative employees. To the dilligent, a career with us sets the pace for personal development. We believe that in every growing organization, human resources plays a most prominent role and must therefore be taken care of. At SFB each of our departments & units has been designed to make our employees actualize their dreams. Your career with us has only one progressive direction-Upward.
Shreejew Foods and Beverages Pvt. Ltd.
New Industrial Estate, Jagatpur
Cuttack, Odisha (IN) - 754021
Email -<EMAIL_ADDRESS>Ph. No. 0671-6575755,<PHONE_NUMBER>


Places I've Been
Add a location:
Country name
Capital name
Landmarks
Time Last Visited
Notes
Another fact
Add
Locations:
Country name:
Capital name:
Facts:


ZXing License Attribution:
Portions of this module contain ZXing -- an open-source, multi-format 1D/2D barcode image processing library with clients for Android, Java. ZXing is licensed under the Apache License, Version 2.0. You may obtain a copy of the License at: http:www.apache.org/licenses/LICENSE-2.0


|
|
|
As a demonstration of the Java Debug Interface (JDI), we are providing source code for the jdb debugger, re-written to use the JDI. It contains a few features not found in the pre-JDI jdb, including some expression evaluation, but some features of the standard jdb have not been implemented. jdb man pagesjdb man pages for Windows
Invoking jdbThe jdb sample can be run by executing: java tty.TTY <options>.. <class-name>where <class-name> is the name you would normally place on the java command line. The -help
option provides information on options.
Note: Be sure that the Java 2 SDK's lib/tools.jar file is on
the class path used to invoke tty.TTY. The tools.jar
file includes the JDI Library and to
the compiled jdb class files.
For more information on invoking and connecting see Connection and Invocation Details section of the JPDA documentation, particularly the section on jdb. Source for jdbFull source code for jdb is included as part of the example code in the Java 2 SDK'slib/jpda directory, in examples.jar .
(Use jar xvf examples.jar to extract the contents of examples.jar.)
Note: this file also includes the source for javadt .
Source code of these example application is included to provide
concrete examples for debugger developers. Example code may be used,
modified
and redistributed by debugger developers providing they adhere to the
terms in the copyright notice.
jdb uses the following packages (found in the
Building jdbTo completely rebuild the jdb classes from the provided source files, you need only to compile them. No special options are required, aside from those which set your classpath to include the JDI Library. However, if want to modify the expression parser in the fileExpr.jj , you will need the JavaCC parser generator.
| ||||
|
|


Engineer. Results-oriented, utilizing 9 years of extensive technical background, field experience, and customer support. Experienced in research, design, analysis, deployment, and continued product support. Recognized for strong ability to identify trends, develop competitive strategies, and execute customized projects.


Health Info
Theme
Simple
Helix
Citrus
Blood
Electro
MAPS
Year
RESET
Health
COMPARISON
Country 1
Country 2
Table
LOADING
Select a
health
statistic to show data


{% extends "index.html" %} {% block content %}
Promotions ending with * are not available yet.
Below are the weight classes along with the maximum allowed weight for each class. Different promotions offer different weight classes.
| Male | Lbs. |
| Strawweight | 115 |
| Flyweight | 125 |
| Bantamweight | 135 |
| Featherweight | 145 |
| Lightweight | 155 |
| Welterweight | 170 |
| Middleweight | 185 |
| Light Heavyweight | 205 |
| Heavyweight | 265 |
| Female | Lbs. |
| Atomweight | 105 |
| Strawweight | 115 |
| Flyweight | 125 |
| Bantamweight | 135 |
| Featherweight | 145 |


Select Reporting Platform
Choose QS report
Select Dashboard
Choose dashboard
Help & Tutorials
Choose guide


Strong Typing With Better.js
============================
This part check the type of variables and property.
It is used in various place in better.js to check
property type for examples
or
if the arguments your function received are like expected.
Everytime the strong type is define the same way.
## Definition of a strong type for variables
Here we describe the details about how to express the strong typing
is expressed for a single variable.
* a strong typing definition is an array of type
* [Number, String] means the variable may be be either Number or String
* [Vector3] means the variable must of an ```instanceof``` Vector3
* [Number, undefined] means the variable is an optional number,
as undefined would be value when it isnt provided
As a shortcut, if you provide a non array value, it will be put in a array.
so ```Vector3``` will be converted as ```[Vector3]```.
It may be nice in case your variable has a single type.
There is some special case like :
* ```any```: it will accept any type
* ```never```: it will never say it is valid
* ```nonan```: it will not accept nan
## Definition of a strong typing for function arguments
When a function is called, it received arguments,
so like an array of variables.
In this case, you simply provide an array of strong type for single variables.
## Validator, the cherry on the cake
As a bonus, it is possible to have ```validators```.
Those are functions which return true if the value is ok with the variable, false otherwise.
You can do you own tho. here is one for range checking. Let's say the variable is an age.
So a Number between 0 and 130. Here is the validator.
```
[Number, StrongTyping.Validator(function(value){
return value >= 0 && value <= 130
})]
```
Here is one in case your value is a selection among options, e.g. 'low', 'normal', 'high'
```
[StrongTyping.Validator(function(value){
return ['low', 'normal', 'high'].indexof(value) !== -1
})]
```


Hi
,
Thank you for shopping from our Food Order Store.
Order Detail Number:
Billing Details
Payment Information
Shipping Address
Card Name
Card Number
Your Order summary
Food Name
Price (PLN)
Quantity
Total (PLN)
Subtotal (PLN)
Tax 8% (PLN)
Total (PLN)


Never has a conversation gone wronger faster
Sarah: Food is an experience for all 5 senses.
Fried: I don't know about you, but I don't feel up my food.
Isaac: What do you do with it in your mouth?

Fried: ...
Sarah: ... yeah... but.. going out instead of in...
Isaac: Eh. Hits all the same spots.
Fried: This conversation just got a lot less appetizing.


Milk
Bread
Carrot
Wake up
Brush teeth
Shower
Eat breakfast
Title:
An Imaginary Book Title
Author:
Brad Schiff
John Doe
Number of Pages:
500


Arctic Coverage
Typically, communications satellites use a geostationary orbit to provide constant coverage over an area. Other orbit examples are low earth orbits in the case of the Iridium constellation and the Tundra orbit used for the Sirius constellation. These orbits are not an efficient method of canvasing all of Canada's arctic.
Two alternate options for high latitude coverage are the Molniya orbit and Polar orbit. Molniya orbits work well for stationary coverage in northern latitudes with wide a longitudinal area. Polar orbits are capable of providing coverage for both southern and northern latitudes with highly variable perturbation and less coverage longitudinally.
In order to canvas Canada's arctic an orbit must allow for coverage at high latitudes across a wide longitudinal area and have minimal perturbation. A satellite with a Molniya orbit would accomplish this.
Molniya Orbit
Invented in the 1960s for telecommunication satellite coverage over northern Russia, the Molniya orbit is elliptical with high inclination. Unlike their geostationary counterparts, satellites in a Molniya orbit are not stationary relative to their ground position and require the use of a constellation of multiple satellites to provide constant coverage over an area. This orbit is almost unaffected by the oblateness of the earth, which causes perturbations in the argument of perigee, and makes use of an apogee of approximately 40,000km with a low altitude perigee. Due to Kepler's laws of planetary motion, this means that satellites in a Molniya orbit spend considerably more time at their apogee than their perigee; allowing for a long period of coverage during each orbital period. This orbit's low altitude perigee provides for cheaper launch costs than typical geostationary orbit insertion.
To achieve a Molniya orbit, a satellite must have the following orbital constants:
Due to a Molniya satellite's motion around the earth, a constellation of multiple satellites is required to provide constant coverage over the north. This orbit allows for 8 hours of coverage for each day, meaning that a minimum of three satellites are required. Each satellite's Right Ascension of the Ascending Node, the angle between the vernal equinox and where the orbit crosses the equator going northward, must be separated by 120 degrees in order to form a net around the globe.
Sample ground track of a single satellite in Molniya orbit.


Evil Dead 2 (1987) * * * 1/2 A movie review by Serdar Yegulalp Copyright 1998 by Serdar Yegulalp
CAPSULE: The funniest horror movie ever made; a melange of Dario Argento and Wile E. Coyote.
EVIL DEAD 2: DEAD BY DAWN is the result of an unstable fusion of Warner Bros. cartoon slapstick and _giallo_ horror-movie conventions. It's a flick with the mind of a splatter film and the heart of a Mack Sennett two-reeler. In plain, non-fanboy language, it's a ton of disgusting fun. Example: A monster of the undead rises from the cellar, only to have its head smashed in the trapdoor. Its eyeball pops out and flies into the mouth of one of the three screaming girls in the movie. GULP.
The plot, what there is of it, is simple to the point of irrelevancy.  The girl dies horribly and the man (square-jawed Bruce Campbell) lives -- but as what? Horrendous mutations strike him like epileptic fits. The dead rise out of their graves and inflict ghastly punishments and tortures on him. His own hand rebels against him (and the punishment he exacts on it is howlingly painful).
The majority of the movie is one long, roaring blast of slime, guts, special effects and ear-drilling sound effects, but it's put together in a way that gets more than a fair amount of good laughs. EVIL DEAD 2 is most likely *the* item that started the whole trend of sly, self-referential horror movies (culminating, of course, in the brilliantly nasty SCREAM), although it's a lot more freakish and far-out.
The film gets a little predictable towards the end, which is kind of sad. If the whole movie had moved with the manic inventiveness of the first thirty minutes, we would have really had something here. But as it stands, it's more than enough to, uh, turn a few heads. And the ending is *really* off the wall, if that's any additional compensation.
<EMAIL_ADDRESS>EFNet IRC: GinRei [new email address coming soon] ICQ: 934998 http://www.io.com/~syegul another worldly device... NEW WEB SITE: http://cablehouse.dyn.ml.org ...and the mandate of heaven you can crush me as I speak/write on rocks what you feel/now feel this truth
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


| assign_dichotomous_value {gtsummary} | R Documentation |
For dichotomous data, returns that value that will be printed in table.
assign_dichotomous_value(data, variable, summary_type, class, value)
data |
data frame |
variable |
character variable name in |
summary_type |
the type of summary statistics that will be calculated |
class |
class of |
value that will be printed in table for dichotomous data
Daniel D. Sjoberg


Python 2.6 reached the end of its life on 29 October 2013. It's about time to drop support for Python 2.6.
This site shows the top 360 most-downloaded packages on PyPI showing which have dropped support for Python 2.6.
Packages that are known to be deprecated are not included (for example distribute). If your package is incorrectly listed, please create a ticket.
This is not an official website, just a nice visual way to measure progress. To see the authoritative guide on wheels and other aspects of python packaging, see the Python Packaging User Guide.
Remove the Trove classifier from setup.py.
'Programming Language :: Python :: 2.6'
Remove Python 2.6 from your CI. For example Travis CI's .travis.yml:
python: - 2.6
And for example from Appveyor's appveyor.yml:
C:\Python26 C:\Python26-x64
And tox.ini:
envlist=py26
Remove old Python 2.6-specific code and documentation. Common files to check:
For example, no need to install or import unittest2 any more. This:
try: import unittest2 as unittest # Python 2.6 except ImportError: import unittest
…can be replaced with:
import unittest
Search your code for stuff like:
if sys.version_info < (2, 7): # Python 2.6 stuff if platform.python_version == "2.6": # Python 2.6 stuff ver = platform.python_version_tuple() if float('{0}.{1}'.format(*ver[:2])) < 2.7: # Python 2.6 stuff try: # Python 2.6 import something except ImportError: # Python 2.7+ import something_else // In C code #if PY_VERSION_HEX < 0x02070000 -#endif
Also search for 2.6
and 26
.
If you test with coverage, look for code which was tested before removing 2.6 from your CI.
Finally, consider dropping support for Python 3.2 and 3.3, which reached EOL on 2016-02-27 and 2017-09-29 respectively.
See what's new. For example:
Use set literals:
set([1, 2, 3]) # This can be replaced... {1, 2, 3} # ... with this
Update string formatters:
# These can be replaced... '%s %s' % ('one', 'two') '{1} {2}'.format('one', 'two') # ... with this '{} {}'.format('one', 'two')
OrderedDict
and Counter
from collections
Fantastic, a problem found is a problem fixed. Please create a ticket!
You can also submit a pull request.
Thanks to Python Wheels and Python 3 Wall of Superpowers for the concept and making their code open source.


Use this website to create a random, strong password.
Password length will appear here.
Your password will appear here.


learning 🎅 ❄ 🎄 🎁 🔀 ⛄ 🔔
learning : A collection of all kinds of resources, videos, pdf, blogs, codes...
Welcome to this website!
box-shadow
box-shadow-2sides-symmetry
box-shadow-4sides-symmetry
box-shadow-inset
box-shadows-3D-looking
Canvas Clock
Interviews
ES6-UMD-CommonJs-AMD


Hi Please ignore my last message. I utterly failed in checking the correct line. :-D So there are no inconsistencies and I just did not see the bug that has now been fixed Sorry for that one. Regards, Patrick


Abbott, Sam, Joel Hellewell, Robin N. Thompson, Katharine Sherratt, Hamish P. Gibbs, Nikos I. Bosse, James D. Munday, et al. 2020. “Estimating the Time-Varying Reproduction Number of SARS-CoV-2 Using National and Subnational Case Counts.” Wellcome Open Research 5 (December): 112. http://dx.doi.org/10.12688/wellcomeopenres.16006.2
Sherratt, Katharine, Sam Abbott, Sophie R. Meakin, Joel Hellewell, James D. Munday, Nikos Bosse, Null Null, Mark Jit, and Sebastian Funk. 2021. “Exploring Surveillance Data Biases When Estimating the Reproduction Number: With Insights into Subpopulation Transmission of COVID-19 in England.” Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 376 (1829): 20200283. http://dx.doi.org/10.1098/rstb.2020.0283
Bosse, Nikos I., Sam Abbott, Johannes Bracher, Habakuk Hain, Billy J. Quilty, Mark Jit, Centre for the Mathematical Modelling of Infectious Diseases COVID-19 Working Group, Edwin van Leeuwen, Anne Cori, and Sebastian Funk. 2022. “Comparing Human and Model-Based Forecasts of COVID-19 in Germany and Poland.” PLoS Computational Biology 18 (9): e1010405. http://dx.doi.org/10.1371/journal.pcbi.1010405
Davies, Nicholas G., Sam Abbott, Rosanna C. Barnard, Christopher I. Jarvis, Adam J. Kucharski, James D. Munday, Carl A. B. Pearson, et al. 2021. “Estimated Transmissibility and Impact of SARS-CoV-2 Lineage B.1.1.7 in England.” Science 372 (6538). https://doi.org/10.1126/science.abg3055.
Meakin, Sophie, Sam Abbott, Nikos Bosse, James Munday, Hugo Gruson, Joel Hellewell, Katharine Sherratt, CMMID COVID-19 Working Group, and Sebastian Funk. 2022. “Comparative Assessment of Methods for Short-Term Forecasts of COVID-19 Hospital Admissions in England at the Local Level.” BMC Medicine 20 (1): 86. http://dx.doi.org/10.1186/s12916-022-02271-x


Conceptualized in 2009, bitcoin is a digital currency that leverages peer-to-peer technology to facilitate instant payments. Its value dramatically plummeted over the past couple of years, but it seems that this cryptocurrency is ready to put this turbulent p…


< back
Profile:
Select the courses you are interested in:
Cybersecurity
Machine Learning
Python
JavaScript
Financial Markets
Artificial Intelligence
Data Science
Computer Networking
Problem Solving
Designing
Save
Send feedback


| Home | Trees | Indices | Help |
|---|
|
|
Some test functions for bivariate interpolation.
Most of these have been yoinked from ACM TOMS 792. http://netlib.org/toms/792
| Classes | |
| LinearTester | |
| NNTester | |
| TestData | |
| TestDataSet |
| Functions | |||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
|||
|
| Variables | |
allfuncs =
|
|
data = {'uniform9': <octant.extern.delaunay.testfuncs.TestData
|
| Function Details |
Compute a quality factor (the quantity r**2 from TOMS792). interpolator must be in ('linear', 'nn'). |
| Variables Details |
allfuncs
|
data
|
| Home | Trees | Indices | Help |
|---|
| Generated by Epydoc 3.0.1 on Tue May 20 16:56:03 2008 | http://epydoc.sourceforge.net |


To use MNE-Python, you need two things:
Step-by-step instructions to accomplish this are given below.
Steps
Note
Users who work at a facility with a site-wide install of MNE-Python (e.g. Martinos center) are encouraged to contact their technical staff about how to access and use MNE-Python, as the instructions might differ.
There are multiple options available for getting a suitable Python interpreter running on your system. However, for a fast and up to date scientific Python environment that resolves all dependencies, we highly recommend following installation instructions for the Anaconda Python distribution.  It is included by default in Anaconda, which makes it
preferable to some other potentially viable Python interpreter
options (e.g., using brew
in OSX or sudo apt-get install
on Ubuntu to get a usable Python interpreter).
If everything is set up correctly, you should be able to check the version
of conda
that is installed (your version number will probably be newer)
and which python
will be called when you run python
:
$ conda --version
conda 3.19.1
$ which python
/home/agramfort/anaconda/bin/python
If your installation doesn’t look something like this, something went wrong and you should try to fix it. We recommend looking through the Anaconda documentation a bit, and Googling for Anaconda install tips (StackExchange results are often helpful).
Once Anaconda works properly, you can do this to resolve the MNE-Python dependencies:
$ conda install scipy matplotlib scikit-learn
To test that everything works properly, open up IPython:
$ ipython --matplotlib=qt
Now that you have a working Python environment you can install MNE-Python.
If you want to have an environment with a clean MATLAB-like interface, consider using Spyder, which can easily be installed with Anaconda as:
$ conda install spyder
There are a many options for installing MNE-Python, but two of the most useful and common are:
Use the stable release version of MNE-Python. It can be installed as:
$ pip install mne --upgrade
MNE-Python tends to release about once every six months, and this command can be used to update the install after each release.
Use the development master version of MNE-Python. If you want to be able to update your MNE-Python version between releases (e.g., for bugfixes or new features), this will set you up for frequent updates:
$ git clone git://github.com/mne-tools/mne-python.git
$ cd mne-python
$ python setup.py develop
A cool feature of python setup.py develop
is that any changes made to
the files (e.g., by updating to latest master
) will be reflected in
mne
as soon as you restart your Python interpreter. So to update to
the latest version of the master
development branch, you can do:
$ git pull origin master
and your MNE-Python will be updated to have the latest changes. If you plan to contribute to MNE-Python, you should follow a variant of this approach outlined in the contribution instructions.
To check that everything went fine, in ipython, type:
>>> import mne
If you get a new prompt with no error messages, you should be good to go!
A good place to start is on our Tutorials page or with our Examples Gallery.
Along the way, make frequent use of Python API Reference and User Manual to understand the capabilities of MNE.
We have developed specialized routines to make use of NVIDIA CUDA GPU processing to speed up some operations (e.g. FIR filtering) by up to 10x. If you want to use NVIDIA CUDA, you should install:
For example, on Ubuntu 15.10, a combination of system packages and git
packages can be used to install the CUDA stack:
# install system packages for CUDA
$ sudo apt-get install nvidia-cuda-dev nvidia-modprobe
# install PyCUDA
$ git clone http://git.tiker.net/trees/pycuda.git
$ cd pycuda
$ ./configure.py --cuda-enable-gl
$ git submodule update --init
$ make -j 4
$ python setup.py install
# install skcuda
$ cd ..
$ git clone https://github.com/lebedov/scikit-cuda.git
$ cd scikit-cuda
$ python setup.py install
To initialize mne-python cuda support, after installing these dependencies and running their associated unit tests (to ensure your installation is correct) you can run:
$ MNE_USE_CUDA=true MNE_LOGGING_LEVEL=info python -c "import mne; mne.cuda.init_cuda()"
Enabling CUDA with 1.55 GB available memory
If you have everything installed correctly, you should see an INFO-level log message telling you your CUDA hardware’s available memory. To have CUDA initialized on startup, you can do:
>>> mne.utils.set_config('MNE_USE_CUDA', 'true')
You can test if MNE CUDA support is working by running the associated test:
$ nosetests mne/tests/test_filter.py
If MNE_USE_CUDA=true
and all tests pass with none skipped, then
MNE-Python CUDA support works.
In IPython, we strongly recommend using the Qt matplotlib backend for fast and correct rendering:
$ ipython --matplotlib=qt
On Linux, for example, QT is the only matplotlib backend for which 3D rendering will work correctly. On Mac OS X for other backends certain matplotlib functions might not work as expected.
To take full advantage of MNE-Python’s visualization capacities in combination with IPython notebooks and inline displaying, please explicitly add the following magic method invocation to your notebook or configure your notebook runtime accordingly:
In [1]: %matplotlib inline
If you use another Python setup and you encounter some difficulties please report them on the MNE mailing list or on github to get assistance.
Mayavi is currently only available for Python2.7. The easiest way to install mayavi is to do the following with Anaconda:
$ conda install mayavi
For other methods of installation, please consult the Mayavi documentation.
The PySurfer package, which is used for visualizing cortical source estimates, uses Mayavi and can be installed using:
$ pip install PySurfer
Some users may need to configure PySurfer before they can make full use of our visualization capabilities. Please refer to the PySurfer installation page for up to date information.
If you run into trouble when visualizing source estimates (or anything else using mayavi), you can try setting ETS_TOOLKIT environment variable:
>>> import os
>>> os.environ['ETS_TOOLKIT'] = 'qt4'
>>> os.environ['QT_API'] = 'pyqt'
This will tell Traits that we will use Qt with PyQt bindings.
If you get an error saying:
ValueError: API 'QDate' has already been set to version 1
you have run into a conflict with Traits. You can work around this by telling the interpreter to use QtGui and QtCore from pyface:
>>> from pyface.qt import QtGui, QtCore
This line should be added before any imports from mne-python.
For more information, see http://docs.enthought.com/mayavi/mayavi/building_applications.html.


This is not a well-formed preThis is not a well-formed preSo this can be a header
This is not a well-formed preSo this can be a header too
This is a well-formed pre ### So this cannot be a headerThis is a well-formed pre ### So this cannot be a header### Nor this


| facet_grid {ggplot2} | R Documentation |
facet_grid()
forms a matrix of panels defined by row and column
faceting variables. It is most useful when you have two discrete
variables, and all combinations of the variables exist in the data.
If you have only one variable with many levels, try facet_wrap()
.
facet_grid( rows = NULL, cols = NULL, scales = "fixed", space = "fixed", shrink = TRUE, labeller = "label_value", as.table = TRUE, switch = NULL, drop = TRUE, margins = FALSE, facets = NULL )
rows, cols |
A set of variables or expressions quoted by
For compatibility with the classic interface, |
scales |
Are scales shared across all facets (the default,
|
space |
If |
shrink |
If |
labeller |
A function that takes one data frame of labels and
returns a list or data frame of character vectors. Each input
column corresponds to one factor. Thus there will be more than
one with |
as.table |
If |
switch |
By default, the labels are displayed on the top and
right of the plot. If |
drop |
If |
margins |
Either a logical value or a character
vector. Margins are additional facets which contain all the data
for each of the possible values of the faceting variables. If
|
facets |
This argument is soft-deprecated, please use |
p <- ggplot(mpg, aes(displ, cty)) + geom_point() # Use vars() to supply variables from the dataset: p + facet_grid(rows = vars(drv)) p + facet_grid(cols = vars(cyl)) p + facet_grid(vars(drv), vars(cyl)) # To change plot order of facet grid, # change the order of variable levels with factor() # If you combine a facetted dataset with a dataset that lacks those # faceting variables, the data will be repeated across the missing # combinations: df <- data.frame(displ = mean(mpg$displ), cty = mean(mpg$cty)) p + facet_grid(cols = vars(cyl)) + geom_point(data = df, colour = "red", size = 2) # Free scales ------------------------------------------------------- # You can also choose whether the scales should be constant # across all panels (the default), or whether they should be allowed # to vary mt <- ggplot(mtcars, aes(mpg, wt, colour = factor(cyl))) + geom_point() mt + facet_grid(vars(cyl), scales = "free") # If scales and space are free, then the mapping between position # and values in the data will be the same across all panels. This # is particularly useful for categorical axes ggplot(mpg, aes(drv, model)) + geom_point() + facet_grid(manufacturer ~ ., scales = "free", space = "free") + theme(strip.text.y = element_text(angle = 0)) # Margins ---------------------------------------------------------- # Margins can be specified logically (all yes or all no) or for specific # variables as (character) variable names mg <- ggplot(mtcars, aes(x = mpg, y = wt)) + geom_point() mg + facet_grid(vs + am ~ gear, margins = TRUE) mg + facet_grid(vs + am ~ gear, margins = "am") # when margins are made over "vs", since the facets for "am" vary # within the values of "vs", the marginal facet for "vs" is also # a margin over "am". mg + facet_grid(vs + am ~ gear, margins = "vs")


Show all offers
Seller is a new trading platform that offers trainings and courses from trusted companies.
Do you want to get new skills? Don't wait. Search!


Android framework provides no support for creating a TextView that can fit its content to its size. There are some libraries out there that try to solve this problem, like: AutoFitTextView android-autofittextview But no one of them seems to work in every situation. Looking into stackoverflow I’ve come to this post which ... Read more 09 Sep 2016 - less than 1 minute read
Oggi si è tenuto al FabLab di Padova un Workshop sull’Internet of Things, durante il quale ho avuto il piacere di anticipare l’intervento di Intel con un intervento dal titolo #Google, #Android, #IoT. Durante questo intervento ho fornito agli attendenti una panoramica sui servizi che Google mette a disposizione per l’universo dell’Int... Read more 18 Jun 2016 - less than 1 minute read
When you run your Android tests (like espresso tests), you may want to be able to force the locale of your device to some specific value at runtime (during test execution). This could be really helpful if you want to test some features of your app against multiple locales. You can do this by using Junit4 rules. The rule implementation looks lik... Read more 09 May 2016 - 1 minute read
Sometimes some fetaures of your app must behave differently for different flavors o build type. Think about when you need to enable logging for a specific flavor only, or you have to disable crash reporting for your “dev build”. All this behaviours can be configured at compile time, insted of using many if/else blocks that are evaluated at runti... Read more 28 Jan 2016 - 3 minute read
Have you ever got a OutOfMemoryError while compiling an Android project, just like this? :app:dexDebug Unknown source file : Uncaught translation error: java.util.concurrent.ExecutionException: java.lang.OutOfMemoryError: Java heap space Unknown source file : 1 error; aborting :app:dexDebug FAILED FAILURE: Build failed with an exception. * W... Read more 15 Nov 2015 - less than 1 minute read


The Console API automatically sends console.log
calls to the native log system on each respective platform. This enables, for example,
console.log
calls to be rendered in the Xcode and Android Studio log windows.
Currently it's not possible to disable it, but that feature is coming.
console.log('I really enjoy Avocado Toast, and I\'m not ashamed to admit it');
The string will show up in your Xcode or Android Studio log stream.


Hello, I'm Victor, an incoming sophomore pursuing a Bachelor's Degree in Computer Science at UC San Diego. I'm passionate about using my experience in math and programming to benefit the people around me through the impact of my projects. Ultimately I wish to improve and learn from my experiences, and use them to benefit the world.
I'm currently seeking positions for Software Engineering internships for Summer 2017, where I can learn from talented programmers during these internships and develop projects and applications that will impact others. Scroll down to learn more about me, or use the navigation tabs above.
UCSD CSE Tutor
SAP
Vessel Science
Springlight Education Institute
Autograder
CoupleTones
Match Alert
Neural Style
LED Echonest
Mafia Helper
Personality Quiz
Bachelor of Science, Computer Science
Some image


-
The Ultimate Guide on Interpretability: Interpretable Machine Learning (book!)
- The Building Blocks of Interpretability (distill)
- Explaining a Black-box Using Deep Variational Information Bottleneck Approach
- Paper Dissected: Understanding Black Box Predictions via Influence Functions Explained (blog)
- Interpretability via attentional and memory-based interfaces, using TensorFlow (blog!)
- Explainable Artificial Intelligence – Model Interpretation Strategies (blog)
- Black-box vs. white-box models - Interpretability Techniques (blog)
- Ideas on Machine Learning Interpretability (H2O Vid)
-
Interpretable Models:
- Linearity: Typically we have a linear model if the association between features and target is modeled linearly.
- Monotonicity: A monotonic model ensures that the relationship between a feature and the target outcome is always in one consistent direction (increase or decrease) over the feature (in its entirety of its range of values).
-
Interactions: You can always add interaction features, non-linearity to a model with manual feature engineering. Some models create it automatically also.
- Complexity of Learned Functions (increasing):
- Linear, Monotonic
- Non-linear, Monotonic
- Non-linear, Non-monotonic
- Approaches to interpretability of ML models based on agnosticism:


--- layout: page title: Python大法好 header: Python大法好 group: navigation tag: Python --- {% include JB/setup %} {% for tag in site.tags %}


German is a West Germanic language spoken mainly in Germany, Austria, Switzerland, Liechtenstein, Belgium, Luxembourg and Italy. It is recognised as a minority language in Czech Republic, Denmark, Hungary, Kazakhstan, Ukraine, Namibia, Poland, Romania, Russia, Slovakia, Slovenia, Croatia, Serbia, South Africa, Vatican City and Venezuela. There are also significant German-speaking communities in the USA, Canada, Brazil, Argentina, Mexico, Australia, South Africa, Chile, Paraguay, New Zealand and Peru.
Day 1
“ Öffne dein Herz und sei Kreativ !
Topic: Football/ Culture of India and Germany
Two participants per team
One team per school
Time limit: 45 minutes
Materials and props to be brought by participants
Day 1
“ Wissen ist ein Schatz,der seinen Besitzer überall hin begleitet”
A quiz on Germany- its culture, history, literature, food etc.
There will be 3 rounds, first one being the deciding/elimination round.
Two students per team
One team per school
Time: 45 minutes.
Day 2
“ Wo man singt, da lass dich ruhig nieder,böse Menschen haben keine Lieder !!!
Participants will perform a German song of their own choice.
10-12 participants per team.
One team per school
Song must be 2-3 minutes long.
Instruments to be brought if required.
Day 2
“ Das schönste Märchen ist das Leben selbst”
Participants will need to enact any famous Grimm Brothers' fiary tale in English on stage
6-8 participants per team max.
One team per school
Skit should be 10 minutes long
Costumes and props to be brought if required.


SQLite Plugin not available for {{this.platform}} Platform
Open Database successful
Execute Creation Tables successful
Execute Insert Users successful
Execute Insert Messages successful
Query Two Users successful
Query Two Messages successful
Create One User with sqlcmd and values successful
Create One User with sqlcmd successful
Query Four Users successful
Query Users age > 30 successful
Create One Image with sqlcmd and values successful
Create Second Image with sqlcmd and values successful
Query all images successful
Execute Insert Tests successful
Execute Insert One Test successful
Closing the database was successful
The test database was successful
The test database failed
The test update version was successful
The test update version failed
The test import from JSON was successful
The test import from JSON failed
The test full export to JSON was successful
The test full export to JSON failed
The test partial export to JSON was successful
The test partial export to JSON failed
The two imports schema/data was successful
The two imports schema/data failed
The test executeset was successful
The test executeset failed
The test to encrypt the database was successful
The test to encrypt the database failed
The test encrypted database was successful
The test encrypted database failed
The test wrong password was successful
The test wrong password failed
The test new password was successful
The test new password failed
The test new password database was successful
The test new password database failed
The set of tests was successful
The set of tests failed


Fixed point math routinesThese functions are declared in the main Allegro header file: #include <allegro5/allegro.h>
typedef int32_t al_fixed;
A fixed point number. Allegro provides some routines for working with fixed point numbers, and defines the type al_fixed to be a signed 32-bit integer. The high word is used for the integer part and the low word for the fraction, giving a range of -32768 to 32767 and an accuracy of about four or five decimal places. Fixed point numbers can be assigned, compared, added, subtracted, negated and shifted (for multiplying or dividing by powers of two) using the normal integer operators, but you should take care to use the appropriate conversion routines when mixing fixed point with integer or floating point values. Writing fixed_point_1 + fixed_point_2 is OK, but fixed_point + integer is not. The only advantage of fixed point math routines is that you don't require a floating point coprocessor to use them. This was great in the time period of i386 and i486 machines, but stopped being so useful with the coming of the Pentium class of processors. From Pentium onwards, CPUs have increased their strength in floating point operations, equaling or even surpassing integer math performance. Depending on the type of operations your program may need, using floating point types may be faster than fixed types if you are targeting a specific machine class. Many embedded processors have no FPUs so fixed point maths can be useful there. al_fixed al_itofix(int x);
Converts an integer to fixed point. This is the same thing as x<<16. Remember that overflows (trying to convert an integer greater than 32767) and underflows (trying to convert an integer lesser than -32768) are not detected even in debug builds! The values simply "wrap around". Example: al_fixed number;
/* This conversion is OK. */
number = al_itofix(100);
assert(al_fixtoi(number) == 100);
number = al_itofix(64000);
/* This check will fail in debug builds. */
assert(al_fixtoi(number) == 64000);
Return value: Returns the value of the integer converted to fixed point ignoring overflows. See also: al_fixtoi, al_ftofix, al_fixtof. int al_fixtoi(al_fixed x);
Converts fixed point to integer, rounding as required to the nearest integer. Example: int result;
/* This will put 33 into `result'. */
result = al_fixtoi(al_itofix(100) / 3);
/* But this will round up to 17. */
result = al_fixtoi(al_itofix(100) / 6);
See also: al_itofix, al_ftofix, al_fixtof, al_fixfloor, al_fixceil. int al_fixfloor(al_fixed x);
Returns the greatest integer not greater than x. That is, it rounds towards negative infinity. Example: int result;
/* This will put 33 into `result'. */
result = al_fixfloor(al_itofix(100) / 3);
/* And this will round down to 16. */
result = al_fixfloor(al_itofix(100) / 6);
See also: al_fixtoi, al_fixceil. int al_fixceil(al_fixed x);
Returns the smallest integer not less than x. That is, it rounds towards positive infinity. Example: int result;
/* This will put 34 into `result'. */
result = al_fixceil(al_itofix(100) / 3);
/* This will round up to 17. */
result = al_fixceil(al_itofix(100) / 6);
See also: al_fixtoi, al_fixfloor. al_fixed al_ftofix(double x);
Converts a floating point value to fixed point. Unlike al_itofix, this function clamps values which could overflow the type conversion, setting Allegro's errno to ERANGE in the process if this happens. Example: al_fixed number;
number = al_itofix(-40000);
assert(al_fixfloor(number) == -32768);
number = al_itofix(64000);
assert(al_fixfloor(number) == 32767);
assert(!al_get_errno()); /* This will fail. */
Return value: Returns the value of the floating point value converted to fixed point clamping overflows (and setting Allegro's errno). See also: al_fixtof, al_itofix, al_fixtoi, al_get_errno double al_fixtof(al_fixed x);
Converts fixed point to floating point. Example: float result;
/* This will put 33.33333 into `result'. */
result = al_fixtof(al_itofix(100) / 3);
/* This will put 16.66666 into `result'. */
result = al_fixtof(al_itofix(100) / 6);
See also: al_ftofix, al_itofix, al_fixtoi. al_fixed al_fixmul(al_fixed x, al_fixed y);
A fixed point value can be multiplied or divided by an integer with the normal * and / operators. To multiply two fixed point values, though, you must use this function. If an overflow occurs, Allegro's errno will be set and the maximum possible value will be returned, but errno is not cleared if the operation is successful. This means that if you are going to test for overflow you should call al_set_errno(0) before calling al_fixmul. Example: al_fixed result;
/* This will put 30000 into `result'. */
result = al_fixmul(al_itofix(10), al_itofix(3000));
/* But this overflows, and sets errno. */
result = al_fixmul(al_itofix(100), al_itofix(3000));
assert(!al_get_errno());
Return value: Returns the clamped result of multiplying x by y , setting Allegro's errno to ERANGE if there was an overflow. See also: al_fixadd, al_fixsub, al_fixdiv, al_get_errno. al_fixed al_fixdiv(al_fixed x, al_fixed y);
A fixed point value can be divided by an integer with the normal / operator. To divide two fixed point values, though, you must use this function. If a division by zero occurs, Allegro's errno will be set and the maximum possible value will be returned, but errno is not cleared if the operation is successful. This means that if you are going to test for division by zero you should call al_set_errno(0) before calling al_fixdiv. Example: al_fixed result;
/* This will put 0.06060 `result'. */
result = al_fixdiv(al_itofix(2), al_itofix(33));
/* This will put 0 into `result'. */
result = al_fixdiv(0, al_itofix(-30));
/* Sets errno and puts -32768 into `result'. */
result = al_fixdiv(al_itofix(-100), al_itofix(0));
assert(!al_get_errno()); /* This will fail. */
Return value: Returns the result of dividing x by y . If y is zero, returns the maximum possible fixed point value and sets Allegro's errno to ERANGE. See also: al_fixadd, al_fixsub, al_fixmul, al_get_errno. al_fixed al_fixadd(al_fixed x, al_fixed y);
Although fixed point numbers can be added with the normal + integer operator, that doesn't provide any protection against overflow. If overflow is a problem, you should use this function instead. It is slower than using integer operators, but if an overflow occurs it will set Allegro's errno and clamp the result, rather than just letting it wrap. Example: al_fixed result;
/* This will put 5035 into `result'. */
result = al_fixadd(al_itofix(5000), al_itofix(35));
/* Sets errno and puts -32768 into `result'. */
result = al_fixadd(al_itofix(-31000), al_itofix(-3000));
assert(!al_get_errno()); /* This will fail. */
Return value: Returns the clamped result of adding x to y , setting Allegro's errno to ERANGE if there was an overflow. See also: al_fixsub, al_fixmul, al_fixdiv. al_fixed al_fixsub(al_fixed x, al_fixed y);
Although fixed point numbers can be subtracted with the normal - integer operator, that doesn't provide any protection against overflow. If overflow is a problem, you should use this function instead. It is slower than using integer operators, but if an overflow occurs it will set Allegro's errno and clamp the result, rather than just letting it wrap. Example: al_fixed result;
/* This will put 4965 into `result'. */
result = al_fixsub(al_itofix(5000), al_itofix(35));
/* Sets errno and puts -32768 into `result'. */
result = al_fixsub(al_itofix(-31000), al_itofix(3000));
assert(!al_get_errno()); /* This will fail. */
Return value: Returns the clamped result of subtracting y from x , setting Allegro's errno to ERANGE if there was an overflow. See also: al_fixadd, al_fixmul, al_fixdiv, al_get_errno. The fixed point square root, sin, cos, tan, inverse sin, and inverse cos functions are implemented using lookup tables, which are very fast but not particularly accurate. At the moment the inverse tan uses an iterative search on the tan table, so it is a lot slower than the others. On machines with good floating point processors using these functions could be slower Always profile your code. Angles are represented in a binary format with 256 equal to a full circle, 64 being a right angle and so on. This has the advantage that a simple bitwise 'and' can be used to keep the angle within the range zero to a full circle. const al_fixed al_fixtorad_r = (al_fixed)1608;
This constant gives a ratio which can be used to convert a fixed point number in binary angle format to a fixed point number in radians. Example: al_fixed rad_angle, binary_angle;
/* Set the binary angle to 90 degrees. */
binary_angle = 64;
/* Now convert to radians (about 1.57). */
rad_angle = al_fixmul(binary_angle, al_fixtorad_r);
See also: al_fixmul, al_radtofix_r. const al_fixed al_radtofix_r = (al_fixed)2670177;
This constant gives a ratio which can be used to convert a fixed point number in radians to a fixed point number in binary angle format. Example: al_fixed rad_angle, binary_angle;
...
binary_angle = al_fixmul(rad_angle, radtofix_r);
See also: al_fixmul, al_fixtorad_r. al_fixed al_fixsin(al_fixed x);
This function finds the sine of a value using a lookup table. The input value must be a fixed point binary angle. Example: al_fixed angle;
int result;
/* Set the binary angle to 90 degrees. */
angle = al_itofix(64);
/* The sine of 90 degrees is one. */
result = al_fixtoi(al_fixsin(angle));
assert(result == 1);
Return value: Returns the sine of a fixed point binary format angle. The return value will be in radians. al_fixed al_fixcos(al_fixed x);
This function finds the cosine of a value using a lookup table. The input value must be a fixed point binary angle. Example: al_fixed angle;
float result;
/* Set the binary angle to 45 degrees. */
angle = al_itofix(32);
/* The cosine of 45 degrees is about 0.7071. */
result = al_fixtof(al_fixcos(angle));
assert(result > 0.7 && result < 0.71);
Return value: Returns the cosine of a fixed point binary format angle. The return value will be in radians. al_fixed al_fixtan(al_fixed x);
This function finds the tangent of a value using a lookup table. The input value must be a fixed point binary angle. Example: al_fixed angle, res_a, res_b;
float dif;
angle = al_itofix(37);
/* Prove that tan(angle) == sin(angle) / cos(angle). */
res_a = al_fixdiv(al_fixsin(angle), al_fixcos(angle));
res_b = al_fixtan(angle);
dif = al_fixtof(al_fixsub(res_a, res_b));
printf("Precision error: %f\n", dif);
Return value: Returns the tangent of a fixed point binary format angle. The return value will be in radians. al_fixed al_fixasin(al_fixed x);
This function finds the inverse sine of a value using a lookup table. The input value must be a fixed point value. The inverse sine is defined only in the domain from -1 to 1. Outside of this input range, the function will set Allegro's errno to EDOM and return zero. Example: float angle;
al_fixed val;
/* Sets `val' to a right binary angle (64). */
val = al_fixasin(al_itofix(1));
/* Sets `angle' to 0.2405. */
angle = al_fixtof(al_fixmul(al_fixasin(al_ftofix(0.238)), al_fixtorad_r));
/* This will trigger the assert. */
val = al_fixasin(al_ftofix(-1.09));
assert(!al_get_errno());
Return value: Returns the inverse sine of a fixed point value, measured as fixed point binary format angle, or zero if the input was out of the range. All return values of this function will be in the range -64 to 64. al_fixed al_fixacos(al_fixed x);
This function finds the inverse cosine of a value using a lookup table. The input value must be a fixed point radian. The inverse cosine is defined only in the domain from -1 to 1. Outside of this input range, the function will set Allegro's errno to EDOM and return zero. Example: al_fixed result;
/* Sets result to binary angle 128. */
result = al_fixacos(al_itofix(-1));
Return value: Returns the inverse sine of a fixed point value, measured as fixed point binary format angle, or zero if the input was out of range. All return values of this function will be in the range 0 to 128. al_fixed al_fixatan(al_fixed x)
This function finds the inverse tangent of a value using a lookup table. The input value must be a fixed point radian. The inverse tangent is the value whose tangent is x . Example: al_fixed result;
/* Sets result to binary angle 13. */
result = al_fixatan(al_ftofix(0.326));
Return value: Returns the inverse tangent of a fixed point value, measured as a fixed point binary format angle. al_fixed al_fixatan2(al_fixed y, al_fixed x)
This is a fixed point version of the libc atan2() routine. It computes the arc tangent of y / x , but the signs of both arguments are used to determine the quadrant of the result, and x is permitted to be zero. This function is useful to convert Cartesian coordinates to polar coordinates. Example: al_fixed result;
/* Sets `result' to binary angle 64. */
result = al_fixatan2(al_itofix(1), 0);
/* Sets `result' to binary angle -109. */
result = al_fixatan2(al_itofix(-1), al_itofix(-2));
/* Fails the assert. */
result = al_fixatan2(0, 0);
assert(!al_get_errno());
Return value: Returns the arc tangent of y / x in fixed point binary format angle, from -128 to 128. If both x and y are zero, returns zero and sets Allegro's errno to EDOM. al_fixed al_fixsqrt(al_fixed x)
This finds out the non negative square root of x . If x is negative, Allegro's errno is set to EDOM and the function returns zero. al_fixed al_fixhypot(al_fixed x, al_fixed y)
Fixed point hypotenuse (returns the square root of x*x + y*y ). This should be better than calculating the formula yourself manually, since the error is much smaller. |


{{ partial "header.html" . }} {{ partial "nav.html" . }} Oops, page not found. :( gopass is a simple but powerful password manager for your terminal. {{ partial "footer.html" . }}
gopass is a simple but powerful password manager for your terminal.


| I l@ve RuBoard |
The Windows NT Performance Monitor is a tool and API that allows applications to provide performance data in a consistent way. Administrators can use the Performance Monitor tool to view this data graphically, or programs can themselves use this data for more advanced purposes, such as taking daily samples of performance data and logging to a database.
Using the Performance Monitor has a number of benefits for both the administrator and programmer. The administrator can use a single, consistent interface for monitoring performance, regardless of the application in question; indeed, the administrator can simultaneously view performance information from two unrelated applications to assist in diagnosing performance bottlenecks. For you, the programmer, the biggest advantage is that you can provide detailed performance information for your application, but don't need to deliver any tools for viewing or analyzing this data; Windows NT and third-party tools provide all the functionality anyone could need!
In the next section we discuss the concepts behind the Performance Monitor, and how you can read Performance Monitor data using Python. Later in this chapter we will present how Python can provide Performance Monitor data for our sample Windows NT Service.
To use the Performance Monitor, an application must register one or more Performance Monitor objects. An object is a logical grouping of Performance Monitor data; it is quite common for an application to have a single object, grouping all performance-related data from the application in this single object.
For each object, the application must register one or more counters . A counter provides a single piece of performance data. Attributes about a counter include the units and the default scale for the final value. The units indicate how the counter values are to be transformed (for example, turned into a rate per second), while the scale defines a multiplication factor applied before the value is displayed or graphed.
For example, let's assume the application needs to keep a counter for connections per second made to it. The application is fast, so expect a hit rate in the thousands of connections per second. You would define your counter as having units of "per second" and a scale of "divide by 100." All the application needs to do is increment the counter once for each connection established, and the Performance Monitor itself will handle the transformation of the raw counter data to a value in the range 1 to 100 that represents the connections per second. The Performance Monitor has kept track of how many counter increments were made in the last second and applied the appropriate conversions.
As you can see, from the application's point of view it's quite simple and unobtrusive; once the counters are defined, simply increment a counter whenever you do something interesting. The Performance Monitor manages the translation to useful units. For the program that wishes to view Performance Monitor information, it's also simple: the Performance Monitor itself has already translated the raw values into user-friendly values ready to display. Unfortunately, as we shall see later, the installation and definition of these counters isn't particularly easy, but once that is mastered, the actual usage of the counters in your application is simple.
In addition to objects and counters, the final Performance Monitor concept we mention is that of an instance . A counter can optionally have any number of instances associated with it. An instance is used where a single counter applies to multiple things. The most basic example is the Performance Monitor data for the CPU in your computer. Windows NT defines the object and a few counters for data related to a CPU. However, as there may be multiple CPUs installed in a PC, each counter can have an instance, one for each CPU. Thus, when you need to collect performance data for a specific CPU, you need to know the instance you are interested in, or you can ask to collect data for all instances. Most counters provided by applications don't have instances associated with them. In our previous example where we kept total client connections, no instance would be associated with the counter. In all the Performance Monitor examples that follow, we don't use counters with instances, but the concept is mentioned for completeness.
To see these concepts, the simplest thing is to start the Windows NT Performance Monitor (from the Administrative Tools group under the Windows NT Start menu), and select Edit Add to chart. In the dialog that's presented, you can clearly see the list of objects, counters, and instances. As you select different objects, the available counters will change. Depending on the counter you select, instances may or may not be available. Python can also display this list, so we will move on to Python and the Performance Monitor.
Python exposes the ability to read Performance Monitor information from the win32pdh and win32pdhutil modules. These modules use a Microsoft API to access the Performance Monitor known as the Performance Data Helper, or PDH, hence the name of the Python modules.
To get a feel for these Python modules, let's start with a demonstration of displaying a dialog for the user to browse and select the counters on this or any machine.
The win32pdhutil module provides a function browse() that displays such a dialog. As the user selects the Add button in the dialog, a function you provide is called with the selected counter. This callback function is supplied as a parameter to win32pdhutil.browse() . The first step is to provide the callback function, which takes a single parameter—the name of the counter. Our example simply prints this name.
Thus, the callback function can be defined as follows:
>>> def CounterCallback( counter ): ... print "Counter is", counter ... >>>
You can display the dialog by importing the win32pdhutil module and calling the browse() function passing the callback:
>>> import win32pdhutil >>> win32pdhutil.browse(CounterCallback)
A dialog is presented that allows you to select all the counters available on the system and even other systems! Select the Add button and your function is called, printing the selected counter. Figure 18.1 shows the code running under Python-Win, just after selecting the Add button.
The counter definition is a simple string, with the machine, object, counter, and instance portions all embedded in the string. The win32pdh module contains functions for parsing a string of this format into the constituent parts and for building such a string from the parts; see the win32pdhutil module source code for more details.
Once you've determined the counters you want, obtaining the information is quite simple: use the win32pdhutil.GetPerformanceAttributes() function. In the simple case of a counter on the local machine without instances, you need pass only the object name and the counter name. For example, an object called Memory provides a number of counters, including one called Available Bytes. To obtain the value, use the code:
>>> win32pdhutil.GetPerformanceAttributes("Memory", "Available Bytes") 18358272 >>>
This demonstrates an interesting use of the Performance Monitor. There is some information about the system that's not easily available from the Windows API, but is available from the Performance Monitor. Statistics about processes (including its process ID) or about the memory in the system can often be obtained in far more detail by using the Performance Monitor than by using the API.
| I l@ve RuBoard |


--- layout: default title: Piston css : /assets/css/sig.css ---
Piston is a SIG dedicated to the engineering applications of Mechanical, Automation, Civil, Chemical and Material Sciences. The SIG functions as a platform for students interested in learning and advancing specific areas of knowledge and technology. The SIG members co-operate, communicate, and organise meets, talks and conferences to discuss the latest technological advancements and applications.
The SIG specializes on a lot of areas like Aerospace Engineering, Automobile Engineering, Bio-Mechanical Applications, Chemical and Thermal Engineering, Heat and Renewable Energy Engineering, Robotics, Controls & Mechatronics and Structures & Materials.
{{ project.Abstract }}


Former U.S. President Carter recovering in hospital after successful brain procedure
(Reuters) - Former U.S. President Jimmy Carter was recovering at an Atlanta hospital on Tuesday after safely undergoing a procedure to relieve pressure on his brain from bleeding caused by recent falls, the Carter Center said in a statement.
The country’s oldest living president at age 95, Carter was admitted to Emory University Hospital on Monday evening for the scheduled procedure, which took place three weeks after he suffered a minor pelvic fracture in a fall at his home in Plains, Georgia.
“There are no complications from the surgery. President Carter will remain in the hospital as long as advisable for observation,” the statement said.
Carter had another fall earlier in October which required stitches to his face, but he resumed work soon after on a homebuilding project for the nonprofit group Habitat for Humanity.
In May, the former Democratic president broke his hip, also at home, requiring him to undergo surgery.. He was hospitalized briefly in 2017 for dehydration and was diagnosed with skin cancer in 2015.
Carter, a former peanut farmer and Georgia governor, defeated Republican President Gerald Ford in 1976 to become the nation’s 39th president, serving a single four-year term in the White House.
His presidency was overshadowed by an economic recession, an energy crisis and the taking of U.S. hostages by Iran, but he also played a leading role in brokering the Camp David Accords leading to an Egypt-Israel peace treaty.
He lost his 1980 re-election bid to Republican Ronald Reagan.
After leaving office in 1981, Carter went on to become an international fixture and a noted humanitarian. He won the Nobel Peace Prize in 2002 for his efforts toward finding peaceful solutions to international conflicts, advancing democracy and human rights and promoting economic and social development.
He and his wife founded the Carter Center in 1982 to carry on their international and humanitarian work.
Carter has lived longer after leaving the White House than any former president in U.S. history.