1972 Chevrolet Corvette was purchased by the current owner in 2007 from a dealership in Reno Nevada. It had been a Nevada, California car its whole life resulting in a rust free chassis. At the time of the purchase he was provided with years of maintenance, restoration and upgrade receipts. Included is a receipt for the Goodwrench 350 engine from May 2005. The suspension has been upgraded with a performance suspension including sway bars front and rear and transverse springs. Body: Straight body that was painted in 2001. The original color was orange. The new color is midnight blue. Some orange is starting to show in the jams. There are small bubbles on the hood. I have a pic of them in the gallery. They are not easy to see. The front lower faring has some damage. Generally the paint shines and present very well. The car would benefit greatly from a color sand and rub.
Interior: The interior of the car was black. When repainted the interior was replaced with a factory blue. The seats, dash and console show well. The carpets are faded. The car is a factory air conditioned car, but there is not compressor. The rest of the system is installed. The heater is bypassed.
Drive-train Motor is a non matching number 350 built by Goodwrench. It is powerful. It runs well. A power tune could bring it to another levle. Clutch feels good. Transmission shift well. it appears to be a Muncie M20. I assume it is not original, but it could be. The rear end has no odd sounds. The suspension is very stiff, and is set up for roar race duties. This car
handles very well. The chassis is rust free.
Driving and running: I drove this car for a while. The headlight doors open and shut. One is a little slower, but appears normal compared to the other C3s I have worked with. The motor is response, and the transmission shifts nicly.
With some simple tuning and detail this could be a great driver. We have a large pile of receipts of work completed over the years. This car is for sale out side of the auction. Please call me to discuss the buy it now.<PHONE_NUMBER>
I have created a google link with many pictures and videos showing the car thoroughly.


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Man accused of opening fire on New Jersey officers arrested in NYC
by Eyewitness NewsMIDTOWN, Manhattan (WABC) -- A man accused of opening fire on officers in New Jersey was arrested at Penn Station on Thursday night.
Investigators say a Tuckerton Borough police officer exchanged gunfire with a man after a traffic stop.
The officer was not injured.
Schools in Tuckerton and Little Egg Harbor were locked down for most of the day.
The man is being held in New York and is expected to be extradited back to New Jersey.


Explain how to create a repository on GitHub and clone the repository to your local computer to a non-technical person.
Go to you github account and go to your profile you should see right next to Contributions a button for Repositories, click on that and underneath on the very right side you should see a New button hit on that and it will take you to create a new repository, once there type down your repository name , add description if you like it is not a mandatory , but make it Public for sure , add a Licence and click Create a repositry button, there you go ! Once it takes you to your repository page we gotta clone it to your computer so we could work on it locally , what we'll do is go to the bottom og the repository page where you'll see HTTPS(SSN) clone URL, copy paste the link, and go to your terminal ,navigate to the directory where you want to safe your repository and type : git clone paste your URL. Voila !once done you should be able to see it in your comp. files!
Describe what open source means.
Open Source software (OSS) or sometimes a (FOSS)Free open source sof., software where with its source code made available with a licence (of corse you gotta agree of terms of use to be able to use it , which gives you some kind of piece in mind at least for me )in which the copyrights holder provides the rights to study change and distribute the software to anyone and for any purpose . Software whose "source code" is available for modification by anyone licenced to suit his/her needs."Source Code"-is a part of the software that comp. users don't ever see, it is the code where programmers can manipulate to change, to make, share access to that code, add new features to make the program work correct etc.
What do you think about Open Source? Does it make you nervous or protective? Does it feel like utopia?
At the beggining till i completlly got the licence part i thougth how is this safe , i mean we deal with a lot of "hackers" lately they can use it for something bad where everything could be gone in a second, but i read about the licence some more and i felt much more secure about it where it allow me to see the good side of using it , i mean the source code is publicity accessible for everyone who could benefit from it, we can learn to make better websites by studying what others have written , we could fix and improve a program by adding , fixing parts that they don't work correct, it does really help especially to us newbees to become better programmers , not only codes but everything we do, creating music, writing books , etc.
Assess the importance of using licenses.
I think the most important part of it ,the stronger copyleft Llicence the safer you'll be and you should have a strong copyleft licence and work with a strong copyleft licenced people before you let others to build around your software because we live in a world that you don't know who you're dealing with , not to emphasize it but you really can't trust everyone about it.
What concepts were solidified in the challenge? Did you have any "aha" moments? What did you struggle with?
Everything was way much easier this time except that when i was trying to push the html file i didn't go exactlly by the steps i feel, first i push it then when i went to the repo to the file i saw it there but i could't pull it i mean there was no option as it it was there so i don't know if i did it right!
Did you find any resources on your own that helped you better understand a topic? If so, please list it.
Yes i definitelly did use other source like Opensource, and Wikipedia


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HANZ is a family owned company that was founded on a love for climbing. With a passion for sending tough routes and an idea to share our successes, we decided to create a resource for climbers where you can see where we’ve been and climb where we’ve climbed.


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Download the course material from the following link:
Copy the file to your home directory: % cp unixtut.tar.gz ~
change to your home directory: % cd ~
Unpack the tarball: % tar -zxvf unixtut.tar.gz
Now you should see a directory unixtut in your home directory.
Open the file index.html in your home directory in a web browser, e.g. firefox
adapted from<EMAIL_ADDRESS>© 1 November, 2002,abused by<EMAIL_ADDRESS>March 2014


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There are only two ways to live your life. One is as though nothing is a miracle. The other is as though everything is a miracle
Life is like riding a bicycle. To keep your balance, you must keep moving
The world as we have created it is a process of our thinking. It cannot be changed without changing our thinking.


File containing CRS (compressed row storage) type and functions. More...
Go to the source code of this file.
Data Structures | |
| struct | ntw_crs |
| A Compressed Row Storage struct. More... | |
| struct | ntw_CRSEdge |
| A struct for storing web-graph edges. More... | |
| struct | ntw_CRSReshapeSequence |
| A struct for fast crs id reshaping. More... | |
Typedefs | |
| typedef struct ntw_crs | ntw_crs |
| A Compressed Row Storage struct. More... | |
| typedef struct ntw_CRSEdge | ntw_CRSEdge |
| A struct for storing web-graph edges. More... | |
| typedef struct ntw_CRSReshapeSequence | ntw_CRSReshapeSequence |
| A struct for fast crs id reshaping. | |
Functions | |
| ntw_crs * | NTW_CRS_new (const uint32_t nodeNum, const uint32_t edgeNum, uint32_t rowPtr[static nodeNum+1], uint32_t colInd[static edgeNum], double val[static edgeNum]) |
| Creates a new CRS structure to store a matrix. More... | |
| void | NTW_CRS_free (ntw_crs *crs) |
| Frees a ntw_crs from memory (frees allocated memory). More... | |
| ntw_CRSReshapeSequence * | NTW_CRS_reshapeSec_new (const uint32_t nodeNum, uint32_t new_pos[static nodeNum], uint32_t look_up[static nodeNum]) |
| Creates a new ntw_CRSReshapeSequence structure. More... | |
| void | NTW_CRS_reshapeSec_free (ntw_CRSReshapeSequence *reshSeq) |
| Frees a ntw_CRSReshapeSequence object from memory. More... | |
| void | NTW_CRS_cmult (ntw_crs crs[static 1], const double c) |
| Multiplies the values of the sparse table in the CRS form crs with the constant value c. More... | |
| void | NTW_CRS_vmult (const ntw_crs crs[static 1], const double vector[static 1], double product[static crs->node_num]) |
| Calculates the product of the CRS table crs with the vector and stores the result in product. More... | |
| double * | NTW_CRS_vmultAlloc (const ntw_crs crs[static 1], const double vector[static 1]) |
| Calculates the product of the CRS table crs with the vector and return the result. More... | |
| void | NTW_CRS_vmultTranspose (const ntw_crs crs[static 1], const double vector[static 1], double product[static 1]) |
| Calculates the product of the transpose of the CRS table crs with the vector and stores the result in product. More... | |
| void | NTW_CRS_stochasticizeRows (ntw_crs crs[static 1]) |
| Makes the rows of the CRS table stochastic. More... | |
| void | NTW_CRS_stochasticizeCols (ntw_crs crs[static 1]) |
| Makes the columns of the CRS table stochastic. More... | |
| void | NTW_CRSP_stochasticizeCols (ntw_crs crs[static 1]) |
| Makes the columns of the CRS table stochastic using openMP. More... | |
| uint32_t | NTW_CRS_getEmptyRowsNum (const ntw_crs crs[static 1]) |
| Returns the number of empty rows of the crs. More... | |
| uint32_t * | NTW_CRS_getEmptyRowIndices (const ntw_crs crs[static 1], uint32_t *restrict outIndicesNum) |
| Returns a vector with the indices of empty rows of the crs. More... | |
| ntw_vector * | NTW_CRS_getColoredGroups (const ntw_crs *const crs) |
| Divides the crs matrix into groups with lower-only dependencies. More... | |
| ntw_CRSReshapeSequence * | NTW_CRS_getColorOptimizedIds (ntw_vector *colors, const uint32_t nodes) |
| How the crs should be reshaped for color optimization? More... | |
| void | NTW_CRS_RowReshape (ntw_crs *restrict crs, const uint32_t *const rowIdArray) |
| Reshapes the crs matrix' rows based on rowIdArray. More... | |
| void | NTW_CRS_IdReshape (ntw_crs *restrict crs, const ntw_CRSReshapeSequence *const reshapeData) |
| Reshapes the crs matrix' id's based on reshapeData. More... | |
| double | NTW_CRS_valueAt (const ntw_crs crs[static 1], uint32_t row, uint32_t col) |
| Returns the value at (row, col) of the matrix of the CRS. More... | |
| void | NTW_CRS_print (FILE *restrict stream, const ntw_crs crs[static 1]) |
| A function for visualizing a CRS. More... | |
| void | NTW_CRS_printFullMatrix (FILE *restrict stream, const ntw_crs crs[static 1]) |
| A function for printing the full matrix of the CRS. More... | |
| void | NTW_CRS_transposeEdges (const uint32_t n, ntw_CRSEdge edges[static n]) |
| Transposes the edges of a graph described with edges. More... | |
| int | NTW_CRSEdgeCompareForT (const void *restrict edgeA, const void *restrict edgeB) |
| Compares two edges, used for sorting with qsort(). More... | |
File containing CRS (compressed row storage) type and functions.
Definition in file ntw_crs.h.
A Compressed Row Storage struct.
Used to save web graph tables in RAM.
The represented matrix can be easily converted into a probability matrix and the dangling nodes (all zero rows) can be found easily as well because row_ptr[i] == row_ptr[i+1] if the node i is dangling.
See CRS Format
| typedef struct ntw_CRSEdge ntw_CRSEdge |
A struct for storing web-graph edges.
Useful for preparing edges before applying a Pagerank algorithm. For example, the gauss sneidel method needs sorted edges.
| void NTW_CRS_cmult | ( | ntw_crs | crs[static 1], |
| const double | c | ||
| ) |
| void NTW_CRS_free | ( | ntw_crs * | crs | ) |
| ntw_vector* NTW_CRS_getColoredGroups | ( | const ntw_crs *const | crs | ) |
Divides the crs matrix into groups with lower-only dependencies.
For example: a node with color 3 will only have dependencies with nodes of colors 1 and 2.
| crs | The crs representation of the matrix. |
Definition at line 215 of file ntw_crs.c.
| ntw_CRSReshapeSequence* NTW_CRS_getColorOptimizedIds | ( | ntw_vector * | colors, |
| const uint32_t | nodes | ||
| ) |
How the crs should be reshaped for color optimization?
Rebasing the crs based on the returned sequence should reduce cache-misses resulting from color based access to the matrix.
Don't forget to free() the returned sequence when not needed anymore.
| colors | The color groups of the nodes. |
| nodes | The number of nodes in the matrix. |
Definition at line 286 of file ntw_crs.c.
| uint32_t* NTW_CRS_getEmptyRowIndices | ( | const ntw_crs | crs[static 1], |
| uint32_t *restrict | outIndicesNum | ||
| ) |
| uint32_t NTW_CRS_getEmptyRowsNum | ( | const ntw_crs | crs[static 1] | ) |
| void NTW_CRS_IdReshape | ( | ntw_crs *restrict | crs, |
| const ntw_CRSReshapeSequence *const | reshapeData | ||
| ) |
| ntw_crs* NTW_CRS_new | ( | const uint32_t | nodeNum, |
| const uint32_t | edgeNum, | ||
| uint32_t | rowPtr[static nodeNum+1], | ||
| uint32_t | colInd[static edgeNum], | ||
| double | val[static edgeNum] | ||
| ) |
Creates a new CRS structure to store a matrix.
Should be freed using the NTW_CRS_free when non needed anymore.
| nodeNum | The number of nodes (rows) of the matrix. |
| edgeNum | The number of non-zero elements of the matrix (edges). |
| rowPtr | Array of nodeNum + 1 elements with the indeces of the val where each row begins and the end of the val array (where last row ends). |
| colInd | Array of edgeNum elements with the columns of each non zero element of the matrix. |
| val | Array of edgeNum elements with the non zero values of the matrix. |
Definition at line 11 of file ntw_crs.c.
| void NTW_CRS_print | ( | FILE *restrict | stream, |
| const ntw_crs | crs[static 1] | ||
| ) |
| void NTW_CRS_printFullMatrix | ( | FILE *restrict | stream, |
| const ntw_crs | crs[static 1] | ||
| ) |
| void NTW_CRS_reshapeSec_free | ( | ntw_CRSReshapeSequence * | reshSeq | ) |
Frees a ntw_CRSReshapeSequence object from memory.
| reshSeq | Pointer to the structure that will be freed. |
Definition at line 58 of file ntw_crs.c.
| ntw_CRSReshapeSequence* NTW_CRS_reshapeSec_new | ( | const uint32_t | nodeNum, |
| uint32_t | new_pos[static nodeNum], | ||
| uint32_t | look_up[static nodeNum] | ||
| ) |
Creates a new ntw_CRSReshapeSequence structure.
| nodeNum | The number of elements in the sequence. |
| new_pos | The new sequence of the array elements. |
| look_up | Where each element ended up. |
Definition at line 40 of file ntw_crs.c.
| void NTW_CRS_RowReshape | ( | ntw_crs *restrict | crs, |
| const uint32_t *const | rowIdArray | ||
| ) |
| void NTW_CRS_stochasticizeCols | ( | ntw_crs | crs[static 1] | ) |
| void NTW_CRS_stochasticizeRows | ( | ntw_crs | crs[static 1] | ) |
| void NTW_CRS_transposeEdges | ( | const uint32_t | n, |
| ntw_CRSEdge | edges[static n] | ||
| ) |
| double NTW_CRS_valueAt | ( | const ntw_crs | crs[static 1], |
| uint32_t | row, | ||
| uint32_t | col | ||
| ) |
Returns the value at (row, col) of the matrix of the CRS.
Use it sparingly because it's relatively slow. (Depends on how sparse the row is with O(n) where n is the non-zero elements of the row).
| crs | The CRS data. |
| row | The row of the returned value. |
| col | The column of the returned value. |
| void NTW_CRS_vmult | ( | const ntw_crs | crs[static 1], |
| const double | vector[static 1], | ||
| double | product[static crs->node_num] | ||
| ) |
| double* NTW_CRS_vmultAlloc | ( | const ntw_crs | crs[static 1], |
| const double | vector[static 1] | ||
| ) |
Calculates the product of the CRS table crs with the vector and return the result.
The memory of the result should be freed afterwards.
| crs | The CRS representation of the matrix \(A\). |
| vector | The vector \(v\). |
| void NTW_CRS_vmultTranspose | ( | const ntw_crs | crs[static 1], |
| const double | vector[static 1], | ||
| double | product[static 1] | ||
| ) |
Calculates the product of the transpose of the CRS table crs with the vector and stores the result in product.
Not cache efficient function. Therefore slow.
| crs | The CRS representation of the matrix \(A\). |
| vector | The vector \(v\). |
| product | The product \(A^T*v\). |
| int NTW_CRSEdgeCompareForT | ( | const void *restrict | edgeA, |
| const void *restrict | edgeB | ||
| ) |
| void NTW_CRSP_stochasticizeCols | ( | ntw_crs | crs[static 1] | ) |


--- creation_epoch:<PHONE_NUMBER> lastmod_epoch:<PHONE_NUMBER> categories: ['Computer Problems'] title: Java ignores /dev/urandom or slow Tomcat SHA1PRNG SSL --- I discovered that since Java 1.5 Sun decided to make some hack that always ignores /dev/urandom as a possible device for SHA1PRNG.
Perhaps a good choice for security reasons, but if you have Tomcat in a development environment, and you wanted to test SSL it can take Tomcat forever to startup due to it waiting on entropy.
The recommended solutions online must have been written back in Java 1.4 with Tomcat days where you could set RANDFILE or -Djava.security.egd=file:/dev/urandom, etc. to fix it. However using "/dev/urandom" is ignored as per http://bugs.sun.com/bugdatabase/view_bug.do?bug_id=6202721.
Some people like to use /dev/./urandom to fool Java into not overridding it with /dev/random. Others even use /dev/zero. Annoying that Sun decided this isn't a bug and didn't ever bother to document this anywhere like in the java.security file.
Options to fix:
#1 is your best option to get real security. The other options are useful for test/dev environments where you aren't using real SSL certificates and security doesn't matter.


About Me
I am an Assistant Professor in the Department of Computer Science at Middlebury College. I am teaching Introduction to Computing (CSCI 0145) in Fall 2023.
My research interests are at the intersection of Natural Language Processing (NLP) and Computational Social Science. My Ph.D. thesis focused on modeling change in language over time for individuals with depression, primarily using social media data. I have also done work on perspectivism in NLP, bias in language, and Clinical NLP.
I completed my Ph.D. in 2023 at the University of Michigan, and earned my B.A. in computer science from Carleton College in 2016. I have also spent time in industry, including a summer as an intern IBM Research working on Clinical NLP and two years as a full-time software engineer at Pinterest working on database systems.
Education
University of Michigan
Computer Science and Engineering, PhD
August 2023
Advised by Dr. Rada Mihalcea
Research Area: natural language processing and computational social science
University of Michigan
Computer Science and Engineering, MS
May 2020
Coursework: Advanced Artificial Intelligence, Advanced Database Systems, Microarchitecture, Natural Language Processing, Psychology of Language, Research Seminar in Science, Tech and Public Policy, Ethics for AI and Robotics (audit)
Carleton College
Computer Science, BA
June 2016
Elective Coursework: Artificial Intelligence, Computational Models of Cognition, Natural Language Processing, Operating Systems, Parallel and Distributed Computing
Publications
* denotes equal contribution
Lexical Measurement of Teaching Qualities
Laura Biester, Ian Stewart, Laura Hirshfield, Rada Mihalcea, and Sara Pozzi
ASEE 2023 (Educational Research and Methods Division)
Improving Mental Health Classifier Generalization with Pre-Diagnosis Data
Yujian Liu*, Laura Biester*, Rada Mihalcea
ICWSM 2023
We Are in This Together: Quantifying Community Subjective Wellbeing and Resilience
MeiXing Dong, Ruixuan Sun*, Laura Biester*, Rada Mihalcea
ICWSM 2023
Emotional and Cognitive Changes Surrounding Online Depression Identity Claims
Laura Biester, James Pennebaker, Rada Mihalcea
PLOS ONE (2022)
Analyzing the Effects of Annotator Gender Across NLP Tasks
Laura Biester, Vanita Sharma, Ashkan Kazemi, Naihao Deng, Steven Wilson, Rada Mihalcea
NLPerspectives Workshop at LREC 2022
IBM @ TREC Clinical Trials Track 2021
Laura Biester, Venkata Joopudi, Bhrarath Dandala
Proceedings of the Thirtieth Text REtrieval Conference (TREC 2021)
Understanding the Impact of COVID-19 on Online Mental Health Forums
Laura Biester, Katie Matton, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea
ACM Transactions on Management Information Systems: Special Issue on Using AI and DATA Science to Handle Pandemic and Related Disruptions (2021)
Building Location Embeddings from Physical Trajectories and Textual Representations
Laura Biester, Carmen Banea, Rada Mihalcea
AACL-IJCNLP 2020
Experience
University of Michigan
Instructor
Winter 2022
Primary instructor for EECS 183, Elementary Programming Concepts. Responsibilities include bi-weekly lectures, office hours, updating assignments, grading, and writing exams.
University of Michigan
Engineering Teaching Consultant (ETC)
Fall 2021 - Winter 2023
Worked in the Center for Research on Learning and Teaching (CRLT) as a ETC. Responsibilities included leading learning cohorts of 20 students as part of the graduate student instructor/instructional aid training (GSI/IA), one-on-one consultations with GSIs/IAs, and conducting midterm student feedback sessions.
IBM
Research Intern
Summer 2021
Worked on the EMRA (electronic medical records analysis) team on the TREC 2021 Clinical Trials Track challenge. My project involved matching patient descriptions to clinical trials using deep learning.
University of Michigan
Instructor
Fall 2019, Fall 2020
Primary instructor for EECS 198 (now EECS 110), Discover Computer Science. Responsibilities include weekly lectures, grading, curriculum/assignment design, and managing a team of two undergraduate teaching assistants.
Software Engineer
August 2016 - August 2018
Worked primarily on large scale storage systems on top of MySQL and HBase. Projects include an inconsistency detection framework for distributed graph databases, and sharding strategies/implementation for advertiser data.
Carleton College
Computer Science Grader
Spring 2016
Graded three assignments per week for 30 students in Mathematics of Computer Science, the introductory discrete mathematics course for computer science majors.
Carleton College
Computer Science Prefect
Spring 2014, Winter 2015, Spring 2015, Fall 2015, Winter 2016
Spent three terms as a prefect for Mathematics of Computer Science and two terms as a prefect for Data Structures. Responsibilities included preparing worksheets and leading twice-weekly study sessions for 10-40 students (depending on the class), in addition to providing 1-1 tutoring for students as requested.


“Passa cittakataṁ bimbaṁ,
arukāyaṁ samussitaṁ;
Āturaṁ bahusaṅkappaṁ,
yassa natthi dhuvaṁ ṭhiti.
“See this fancy puppet,
a body built of sores,
diseased, obsessed over,
in which nothing lasts at all.
Passa cittakataṁ rūpaṁ,
maṇinā kuṇḍalena ca;
Aṭṭhiṁ tacena onaddhaṁ,
saha vatthehi sobhati.
See this fancy figure,
with its gems and earrings;
it is bones wrapped in skin,
made pretty by its clothes.
Alattakakatā pādā,
mukhaṁ cuṇṇakamakkhitaṁ;
Alaṁ bālassa mohāya,
no ca pāragavesino.
Rouged feet
and powdered face
may be enough to beguile a fool,
but not a seeker of the far shore.
Aṭṭhapadakatā kesā,
nettā añjanamakkhitā;
Alaṁ bālassa mohāya,
no ca pāragavesino.
Hair in eight braids
and eyeliner
may be enough to beguile a fool,
but not a seeker of the far shore.
Añjanīva navā cittā,
pūtikāyo alaṅkato;
Alaṁ bālassa mohāya,
no ca pāragavesino.
A rotting body all adorned
like a freshly painted makeup box
may be enough to beguile a fool,
but not a seeker of the far shore.
Odahi migavo pāsaṁ,
nāsadā vāguraṁ migo;
Bhutvā nivāpaṁ gacchāma,
kandante migabandhake.
The hunter laid his snare,
but the deer didn’t spring the trap.
I’ve eaten the bait and now I go,
leaving the trapper to lament.
Chinno pāso migavassa,
nāsadā vāguraṁ migo;
Bhutvā nivāpaṁ gacchāma,
socante migaluddake.
The hunter’s snare is broken,
but the deer didn’t spring the trap.
I’ve eaten the bait and now I go,
leaving the deer-hunter to grieve.”
Passāmi loke sadhane manusse,
Laddhāna vittaṁ na dadanti mohā;
Luddhā dhanaṁ sannicayaṁ karonti,
Bhiyyova kāme abhipatthayanti.
“I see rich people in the world who,
because of delusion, give not the wealth they’ve earned.
Greedily, they hoard their riches,
yearning for ever more sensual pleasures.
Rājā pasayhappathaviṁ vijetvā,
Sasāgarantaṁ mahimāvasanto;
Oraṁ samuddassa atittarūpo,
Pāraṁ samuddassapi patthayetha.
A king who conquered the earth by force,
ruling the land from sea to sea,
unsatisfied with the near shore of the ocean,
would still yearn for the further shore.
Rājā ca aññe ca bahū manussā,
Avītataṇhā maraṇaṁ upenti;
Ūnāva hutvāna jahanti dehaṁ,
Kāmehi lokamhi na hatthi titti.
Not just the king, but others too,
reach death not rid of craving.
They leave the body still wanting,
for in this world sensual pleasures never satisfy.
Kandanti naṁ ñātī pakiriya kese,
Aho vatā no amarāti cāhu;
Vatthena naṁ pārutaṁ nīharitvā,
Citaṁ samodhāya tato ḍahanti.
Relatives lament, their hair disheveled,
saying ‘Ah! Alas! They’re not immortal!’
They take out the body wrapped in a shroud,
heap up a pyre, and burn it there.
So ḍayhati sūlehi tujjamāno,
Ekena vatthena pahāya bhoge;
Na mīyamānassa bhavanti tāṇā,
Ñātī ca mittā atha vā sahāyā.
It’s poked with stakes while being burnt,
in just a single cloth, all wealth gone.
Relatives, friends, and companions
can’t help you when you’re dying.
Dāyādakā tassa dhanaṁ haranti,
Satto pana gacchati yena kammaṁ;
Na mīyamānaṁ dhanamanveti kiñci,
Puttā ca dārā ca dhanañca raṭṭhaṁ.
Heirs take your riches,
while beings fare on according to their deeds.
Riches don’t follow you when you die;
nor do children, wife, wealth, nor kingdom.
Na dīghamāyuṁ labhate dhanena,
Na cāpi vittena jaraṁ vihanti;
Appaṁ hidaṁ jīvitamāhu dhīrā,
Asassataṁ vippariṇāmadhammaṁ.
Longevity isn’t gained by riches,
nor does wealth banish old age;
for the wise say this life is short,
it’s perishable and not eternal.
Aḍḍhā daliddā ca phusanti phassaṁ,
Bālo ca dhīro ca tatheva phuṭṭho;
Bālo hi bālyā vadhitova seti,
Dhīro ca no vedhati phassaphuṭṭho.
The rich and the poor feel its touch;
the fool and the wise feel it too.
But the fool lies stricken by their own folly,
while the wise don’t tremble at the touch.
Tasmā hi paññāva dhanena seyyā,
Yāya vosānamidhādhigacchati;
Abyositattā hi bhavābhavesu,
Pāpāni kammāni karoti mohā.
Therefore wisdom’s much better than wealth,
since by wisdom you reach consummation in this life.

Upeti gabbhañca parañca lokaṁ,
Saṁsāramāpajja paramparāya;
Tassappapañño abhisaddahanto,
Upeti gabbhañca parañca lokaṁ.
One who enters a womb and the world beyond,
will transmigrate from one life to the next.
While someone of little wisdom, placing faith in them,
also enters a womb and the world beyond.
Coro yathā sandhimukhe gahīto,
Sakammunā haññati pāpadhammo;
Evaṁ pajā pecca paramhi loke,
Sakammunā haññati pāpadhammo.
As a bandit caught in the door
is punished for his own bad deeds;
so after departing, in the world beyond,
people are punished for their own bad deeds.
Kāmā hi citrā madhurā manoramā,
Virūparūpena mathenti cittaṁ;
Ādīnavaṁ kāmaguṇesu disvā,
Tasmā ahaṁ pabbajitomhi rāja.
Sensual pleasures are diverse, sweet, delightful,
appearing in disguise they disturb the mind.
Seeing danger in the many kinds of sensual stimulation,
I went forth, O King.
Dumapphalānīva patanti māṇavā,
Daharā ca vuḍḍhā ca sarīrabhedā;
Etampi disvā pabbajitomhi rāja,
Apaṇṇakaṁ sāmaññameva seyyo.
As fruit falls from a tree, so people fall,
young and old, when the body breaks up.
Seeing this, too, I went forth, O King;
the ascetic life is guaranteed to be better.”
Saddhāyāhaṁ pabbajito,
upeto jinasāsane;
Avañjhā mayhaṁ pabbajjā,
anaṇo bhuñjāmi bhojanaṁ.
“I went forth out of faith
joining the victor’s dispensation.
My going forth wasn’t wasted;
I enjoy my food free of debt.
Kāme ādittato disvā,
Jātarūpāni satthato;
Gabbhavokkantito dukkhaṁ,
Nirayesu mahabbhayaṁ.
I saw sensual pleasures as burning,
gold as a cutting blade,
conception in a womb as suffering,
and the hells as very fearful.
Etamādīnavaṁ ñatvā,
saṁvegaṁ alabhiṁ tadā;
Sohaṁ viddho tadā santo,
sampatto āsavakkhayaṁ.
Knowing this danger,
I was struck with a sense of urgency.
I was stabbed, but then I found peace,
attaining the end of defilements.
Pariciṇṇo mayā satthā,
kataṁ buddhassa sāsanaṁ;
Ohito garuko bhāro,
bhavanetti samūhatā.
I’ve served the teacher
and fulfilled the Buddha’s instructions.
The heavy burden is laid down,
the attachment to rebirth is eradicated.
Yassatthāya pabbajito,
agārasmānagāriyaṁ;
So me attho anuppatto,
sabbasaṁyojanakkhayo”ti.
… Raṭṭhapālo thero ….
I’ve reached the goal
for the sake of which I went forth
from the lay life to homelessness—
the ending of all fetters.”


--- title: About Me layout: page ---
Hi, I'm Annie Schwartz. I am a computer science student at the University of Minnesota, graduating in December 2020. My Clifton StrengthsFinder themes are Adaptability, Restorative, Woo, Communication, and Empathy. This means I'm a natural problem solver who is always looking to improve the current status quo, but also thrive around people. I'm also a proven leader, having grown my school's ACM-W chapter from a tiny group to a healthy, self-sustaining chapter that has the bandwidth to put on many events to benefit our school community.


CrimPapers
Articles published on 6 January 2018
On 6 January 2018, 9 new articles were published in 8 journals.
 Factors Associated With Citizen Support For the Militarization of the Police by Brian Lockwood, Matthew D. Doyle, John G. Comiskey
Moving Beyond Anger and Depression: the Effects of Anxiety and Envy on Maladaptive Coping by Ana Z. Daniels, Kristy Holtfreter
Psychological Inertia Revisited: Replicating and Extending the Differential Effect of Proactive and Reactive Criminal Thinking on Crime Continuity by Glenn D. Walters
Terrorism Risk Forecasting By Ideology
Cu-Traits and Hpa-Axis Reactivity Conjointly Relate to Treatment Effect in Adolescents With Severe Antisocial Behavior
The Conflicted Juvenile Delinquency Court After Gault: A Qualitative Examination of Actors and Processes in Two Contemporary Courts by Liana Pennington
The Neural Basis of Reactive Aggression and Its Development in Adolescence by Rachael A. Lickley, Catherine L. Sebastian
Pakistan's Approach to Countering Violent Extremism (cve): Reframing the Policy Framework For Peacebuilding and Development Strategies by Saira Bano Orakzai
Note: although this article was published on 11 December 2017, the publisher only added it to the journal RSS feed on 6 January 2018, which is why it is shown in the list of articles for that date.


Corinna Schumacher says Michael wants to keep his health private
by Adam NewtonMichael Schumacher's wife Corinna says that he wants to keep his health a secret as he continues to recover from a skiing accident in 2013. Little is known about the seven time F1 champion's condition, with the family preferring to keep it an in-house matter.
Schumacher's son Mick is racing in F2, and Michael knows how his son is getting on, but his wife Corinna says that he prefers his own condition to be kept private.
Corinna told She Mercedes magazine: "You can be sure that he is in the best hands and we do everything humanly possible to help him.
"Please understand that we are following Michael's desire and that we have such a sensitive subject as his health, as always has been private."
It is nearly six years since Schumacher's accident, and we hope the German does make a full recovery.


Money Exchange
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AnylineAbstractModuleView Class Reference
| Inherits from | UIView |
|---|---|
| Declared in | AnylineAbstractModuleView.h |
Overview
The AnylineAbstractModuleView is a programmatic interface for an object that manages easy access to Anylines scanning modes. It is a subclass of UIView. You should sublcass this class to build Anyline modules.
Overwrite startScanningAndReturnError: to add additional initilization before scanning begins.
Overwrite cancelScanningAndReturnError: to do additional clean-up after scanning ends.
Overwrite reportScanResultState: to check the various scanning states
currentConfiguration
The UI Configuration for the scanning UI
@property (nonatomic, strong) ALUIConfiguration *currentConfiguration
Declared In
AnylineAbstractModuleView.h
strokeWidth
Sets the width of the views border
@property (nonatomic) IBInspectable NSInteger strokeWidth
Declared In
AnylineAbstractModuleView.h
strokeColor
Sets the color of the views border
@property (nonatomic, strong) IBInspectable UIColor *strokeColor
Declared In
AnylineAbstractModuleView.h
cornerRadius
Sets the corner radius of the views border
@property (nonatomic) IBInspectable NSInteger cornerRadius
Declared In
AnylineAbstractModuleView.h
outerColor
Sets the color of the space surrounding the view
@property (nonatomic, strong) IBInspectable UIColor *outerColor
Declared In
AnylineAbstractModuleView.h
outerAlpha
Sets the alpha of the space surrounding the view
@property (nonatomic) IBInspectable CGFloat outerAlpha
Declared In
AnylineAbstractModuleView.h
flashImage
Sets image the user uses to toggle the flash
@property (nonatomic, strong) IBInspectable UIImage *flashImage
Declared In
AnylineAbstractModuleView.h
flashButtonAlignment
Sets the alignment of the flash button. Possible values are: ALFlashAlignmentTop, ALFlashAlignmentTopLeft, ALFlashAlignmentTopRight, ALFlashAlignmentBottomLeft, ALFlashAlignmentBottom and ALFlashAlignmentBottomRight
@property (nonatomic) ALFlashAlignment flashButtonAlignment
Declared In
AnylineAbstractModuleView.h
flashButtonOffset
Property for the flash button offset.
@property (nonatomic) CGPoint flashButtonOffset
Declared In
AnylineAbstractModuleView.h
flashStatus
Reads the status of the flash
@property (nonatomic) ALFlashStatus flashStatus
Declared In
AnylineAbstractModuleView.h
cancelOnResult
This property tells Anyline if it should stop reading once a result was found
@property (nonatomic) IBInspectable BOOL cancelOnResult
Declared In
AnylineAbstractModuleView.h
beepOnResult
This property tells Anyline if it should beep once a result was found
@property (nonatomic) IBInspectable BOOL beepOnResult
Declared In
AnylineAbstractModuleView.h
blinkOnResult
This property tells Anyline if it should blink once a result was found
@property (nonatomic) IBInspectable BOOL blinkOnResult
Declared In
AnylineAbstractModuleView.h
vibrateOnResult
This property tells Anyline if it should vibrate once a result was found
@property (nonatomic) IBInspectable BOOL vibrateOnResult
Declared In
AnylineAbstractModuleView.h
cutoutRect
Returns the bounding Rect of the visible Cutout with the correct location on the Module View.
@property (nonatomic, readonly) CGRect cutoutRect
Discussion
Warning: May be nil before the layout process is completed.
Declared In
AnylineAbstractModuleView.h
watermarkRect
Returns the bounding Rect of the visible WatermarkView with the correct location on the Module View.
@property (nonatomic, readonly) CGRect watermarkRect
Discussion
Warning: May be nil before the layout process is completed or the license is not community.
Declared In
AnylineAbstractModuleView.h
– startScanningAndReturnError:
Starts the scanning process or sets the error object
- (BOOL)startScanningAndReturnError:(NSError **)error
Parameters
error |
The error that occured |
|---|
Return Value
Boolean indicating if the scanning could be started
Declared In
AnylineAbstractModuleView.h
– cancelScanningAndReturnError:
Stops the scanning process or sets the error object
- (BOOL)cancelScanningAndReturnError:(NSError **)error
Parameters
error |
The error that occured |
|---|
Return Value
Boolean indicating if the scanning could be stopped
Declared In
AnylineAbstractModuleView.h
– enableReporting:
Reporting ON Switch, off by default
- (void)enableReporting:(BOOL)enable
Parameters
enable |
if YES, anyline will report for QA failed scan tries. Use reportImageForLog in ALC file, and use the reportScanResultState: for reporting |
|---|
Declared In
AnylineAbstractModuleView.h
– reportScanResultState:
Report scan result
- (void)reportScanResultState:(ALScanResultState)scanResultState
Parameters
scanResultState |
There are 3 different possible states. ALScanResultUserDidAbortState - The App should report this state to Anyline when the user stopped scanning / switched to manual entry without scanning 1 successful entry. When there was a successful scan stopping should be ignored. ALScanResultScanSuccessfulState - The App should report this state to Anyline when Anyline returned a value and the value was validated by the backend or the user. ALScanResultScanErrorWrongResultState - The App should report this state to Anyline when the result from Anyline was wrong or the user edited the values. |
|---|
Declared In
AnylineAbstractModuleView.h
– isRunning
Boolean indicating if a scanning is in progress.
- (BOOL)isRunning
Return Value
Boolean indicating if a scanning is in progress.
Declared In
AnylineAbstractModuleView.h


--- layout: page title: "About" description: "Hey, this is Rain." header-img: "img/clarkson.jpg" ---
Somerset, New Jersey 08873 |<PHONE_NUMBER> |
<EMAIL_ADDRESS>| LinkedIn: https://www.linkedin.com/in/runfeng-xu | GitHub: https://github.com/runfengxu
Rutgers University, New Brunswick, NJ 01/2019 - 12/2020 Master of Science in Computer Science GPA: 3.7/4.0
Fudan University, Shanghai, China 09/2014 - 07/2018 Bachelor of Science in Physics
Programming Languages: Python, C, Html/Javascript, SQL, CUDA Concepts: Database, Deep Learning, Operating System Programming, Unix, Full-stack
Software Engineer Inter, Vouched, Seattle 05/2020 – now
• Designed and Implemented efficient detector model and landmarking model for edge-devices, the final model is only 100Kb
and able to perform real time detection on low end mobile devices. Wrote testing web application and benchmarked speed
and resource consumption in TensorflowJS+NodeJs developing environment.
• Updated the current text recognition model by combining semi self-learning based model with EfficientNet Structure,
improved the accuracy on our customed dataset from 70% to 95%.
• Deployed a online cross-platform multiple poker player written in redis, node.js and socket.io as the social event for
company’s chat time.
Research Assistant, Rutgers Computational Biomedicine Imaging and Modeling Center, Piscataway, 08/2019 – 11/2019
Non-manual features recognition in American-Sign Language,
• Used CNN+LSTM based neural network to extract non-manual features( including eyebrow motion and aperture motion) from 1000+ sign videos
Manual Features detection in American-Sign Language
• Used proposal-based neural network to detect and segment manual-sign event in temporal scale, eventually recognize all manual sign events and their meaning in over 1000 sign videos.
Data Engineer Intern, Minsheng Bank, Shanghai, China 07/2018 - 08/2018
• Crawled data from real estate agent websites and e-commece platforms through Python Scrapy framework. Used crawled data to analysis regional consumption level to help the bank provide personalized services for their customers. • Build a visualization of the analysis using Baidu map API.
Intern, China Union Pay, Shanghai, China 07/2017 – 08/2017
• Extracted keywords from documents in database using TFIDF algorithm and built a documents matching algorithm to search for similar document in the database. With similar old documents for referencing purpose, my colleagues could handle new requested query more efficiently. • Build a web frontend for searching matched documents using ASP.net and SQL Server.
NCAA online predicting engine, Rutgers (AWS EC2/S3, Mysql, Redshift, mongoDB) 04/2019
• Collected NCAA tournaments and final games stats for the last 10 years. Designed and implemented a database query engine using redshift and MongoDB, We build a game prediction model using KNN algorithm over the data and a webpage to support online stats searching and predicting. the service is built on AWS cloud service.
Colorization Black-White photos, Rutgers (python) 06/2019
• Designed a neural network based on CNN to colorize gray photos, all code including forward/backward propagation are hand-written.
Rail Track Detection, Rutgers 05/2019
• Used python to detect rail track in the video and use Yolo framework to segment the pedestrian and vehicle in the same view
CUDA PIFO task scheduler, Rutgers 12/2019
• Designed and implemented a GPU scheduler on CUDA runtime level which combined the principle of PIFO scheduling policy and CUDA asynchronous executing fashion. It decides the order in which received tasks are executed to use the limited data transfer pipeline and GPU kernel resource more efficiently and reduce overall run time and response time.
E-commerce recommending system, Rutgers 05/2019
• Designed and implemented an online shopping and recommending system using python an flask. The data were from a Brazil shopping platform which includes over 1000 items and 70k transactions. The recommending engine is built using AR model and Apriori Algorithm.


Introduction
Introduction
Are you self-proclaimed know-it-all the geek? Prove your worth and show that you can be the winner of tech quiz competition of North Bengal’s biggest techno management fest answering tech trivia questions.
Do you know who started Apple? (Easy!)
Do you know who made first commercial computers? Do you know which automobile has first four Wheel Drive? (Little more complicated right?)
Worry not, the purpose of quiz is not to embarrass anyone, but to make sure everyone is on the same page.
We are coming up with the quizzes varying from general sciences to technology. If you miss to participate you are missing the most important event of the fest where knowledge would be the output for the zero input of yours.
Problem Statement
Problem Statement
1. Each team needs to register their team name along with the name of the team members a day before the contest.
2. Use of electronic devices like calculators, mobile phones etc is strictly prohibited.
3. Participants are required to bring their own pen for the prelims.
4. Changing teammates at any stage of the competition for any reason whatsoever is strictly not allowed.
Rules
Prelims
1. Quiz will be of two rounds viz. prelims and finals
2. Prelims will be completely a written round where each groups will be provided with a paper consisting of 20 questions to be answered in 1hours.
3. Questions of prelims will be categorized into three sections namely easy, intermediate and advanced.
4. There would be 5 easy questions each carrying 1 Points, 10 intermediate questions carrying 3 points each and 5 advanced questions carrying 5 points each.
Finals
5. A total of 7 teams will be selected for the finals.
6. If two or more team scores equal points in the prelims, team attempting more questions from advanced section would be considered for the finals.
7. Finals shall be an oral round.
8. Each team will be asked five questions and will be given 3 minutes per question to discuss their answer with their team members.
9. In case of tie between two teams, the team which answered the questions in lesser time will be preferred.
FAQs
Can students from different years together make a team?
Yes, Students from different years together can make a team for the contest.
When will be the deadline for the registration?
Registration will be open until an hour before the beginning of the contest.
When will be the results of prelims announced?
Results of prelims will be announced a day before the finals.
Prize
Certificate Policy
1. Certificate of Excellence will be provided to the participants who qualify for the FINALS.
2. Certificate of Participation will be provided to all the participants taking part in the event.
3. The teams which get disqualified due to disobeying any of the rules provided will not be entertained with any kind of certification.
Prize money worth: Rs. 28,000


https://docs.wso2.com/display/MG310/Quick+Start+Guide+-+Docker
https://docs.wso2.com/display/MG310/
Reporting Issues
We encourage you to report issues, documentation faults, and feature requests regarding WSO2 API Microgateway through the Github Issues.
Contributing Code
Read through project Contribution Guidelines to learn how to contribute with code.
Mailing Lists
Join our mailing list and receive updates on product development. Developer List<EMAIL_ADDRESS>--WSO2 API Manager Team--


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Program
UPDATE: The workshop will be held in room G449 in the Stata Center, and will be available to livestream at this link.
The full program of the workshop will take place on June 26 at the Ray and Maria Stata Center on MIT's campus at 32 Vassar Street, Cambridge, MA 02139. A PDF of the program is available for download.
| Time | Event | Authors |
|---|---|---|
| 9:00-9:10 | Opening Remarks | |
| 9:10-9:50 | Invited Talk: Good Markets (Really Do) Make Good Neighbors | Scott Duke Kominers |
| 9:50-10:10 | How (Not) to Allocate Affordable Housing [link] | Nick Arnosti and Peng Shi |
| 10:10-10:30 | Targeting High Ability Entrepreneurs Using Community Information: Mechanism Design In The Field | Reshmaan Hussam, Natalia Rigol, and Benjamin Roth |
| 10:30-11:00 | Break | |
| 11:00-11:40 | Invited Talk: Making Health Insurance Work through Market Design | Mark Shepard |
| 11:40-11:55 | Truthful Mechanisms for Medical Surplus Product Allocation* [link] | Can Zhang, Atalay Atasu, Turgay Ayer, and Beril Toktay |
| 11:55-12:10 | Opting Into Optimal Matchings* [link] | Avrim Blum, Ioannis Caragiannis, Nika Haghtalab, Ariel Procaccia, Eviatar Procaccia, and Rohit Vaish |
| 12:10-12:30 | Analysis of Medicare Pay-for-Performance Contracts [link] | Hamsa Bastani, Mohsen Bayati, Mark Braverman, Ramki Gummadi, and Ramesh Johari |
| 12:30-2:00 | Lunch and Poster Session | |
| 2:00-2:15 | A Personalized BDM Mechanism for Efficient Market Intervention Experiments* | Imanol Arrieta Ibarra and Johan Ugander |
| 2:15-2:30 | Mechanism Design with Financially Constrained Agents and Costly Verification* [link] | Yunan Li |
| 2:30-2:50 | Assortment Planning in School Choice [link] | Peng Shi |
| 2:50-3:30 | Invited Talk: Mechanism Design for Education | Parag Pathak |
| 3:30-4:00 | Break | |
| 4:00-4:15 | Demand Response Contract Design for Energy Markets* [link] and Generalizing Demand Response Through Reward Bidding* [link] | Hongyao Ma, Reshef Meir, David C Parkes, and Valentin Robu |
| 4:15-4:30 | Rules for Choosing Societal Tradeoffs* [link] | Vincent Conitzer, Rupert Freeman, Markus Brill, and Yuqian Li |
| 4:30-5:30 | Panel Discussion | Ashish Goel, Carla P. Gomes, Kevin Leyton-Brown, Parag Pathak, and Glen Weyl |
Poster Session:
- "Affirmative Action, Percent Plans, and Segregation's Impact on Minority Enrollment" by Michelle Jiang
- "Designing Markets for Altruistic Supply" [link] by Robert Slonim and Carmen Wang
- "Matching with Quantity" by David Delacretaz
- "Near-feasible stable matchings with budget constraints" [link] by Yasushi Kawase and Atsushi Iwasaki
- "Optimization-based Mechanisms for the Course Allocation Problem" by Hoda Atef Yekta and Robert Day
- *will also present a poster


What is JBehave?
JBehave is a framework for Behaviour-Driven
Development (BDD). BDD is an evolution of test-driven development (TDD)
and acceptance-test driven design, and is intended to make these
practices more accessible and intuitive to newcomers and experts alike.
It shifts the vocabulary from being test-based to behaviour-based, and
positions itself as a design philosophy.
Features of JBehave include:
- Pure Java implementation, which plays well with Java-based
enterprises
- Allows users to specify and run text-based scenarios, which
allows "out-in" development.
- Annotation-based binding of textual steps to Java methods
- Auto-conversion of string arguments to any parameter type
(including generic types) via custom parameter converters.
- Scenario reporter - outputs scenarios executed in
human-readable form
- Auto-generation of pending steps so the build is not broken
by a missing step, but has option to configure breaking build for
pending steps.
- Scenario can be run as JUnit tests, providing easy
integration with your favourite IDE. Using alternative
annotation-based unit test frameworks is equally easy.
- Ant integration: allows scenarios to be run via Ant task
- Maven integration: allows scenarios to be run via Maven
plugin at given build phase
Want to learn more?
The Getting Started
page will get you up and running in no time.


There is no denying that we are becoming more and more dependent of technology. Because of that, technology is becoming cheaper and better. As world's need for technology grows however, more and more of us are getting concerned that our privacy is in danger. Electronic monitoring of people, interception and reading of emails, companies sharing customers' private information and so forth. Technology's ability to invade our privacy is endless.
On the other hand, I don't think any of us are willing to give up the good side of technology either. So the question is 'do we really need to give up technology if we want our privacy?'. But the truth is that some technology actually helps protect our privacy. Banks prevent fraud by sharing information about people who are going from one bank to another committing illegal acts such as trying to pass checks. In an effort to combat terrorism, banks are required to notify the federal government when certain transactions meet the guideline that are deemed suspicious by law. Seung-Hui Cho massacred thirty two people at Virginia Tech. The incident happened despite the fact that he had serious mental problems and was considered very dangerous. This tragedy might have been avoided if the aforementioned type of information was included in the normal background checks that are performed when somebody tries to purchase a firearm.
So maybe we don't need to give up technology as long as there is a balance between taking advantage of technology and overuse of it. As technology improves, we have to be responsible and be conscious about both good and bad sides of technology.


Kindle - PyTorch no-code model builder
Kindle is an easy model build package for PyTorch. Building a deep learning model became so simple that almost all model can be made by copy and paste from other existing model codes. So why code? when we can simply build a model with yaml markup file.
Kindle builds a model with no code but yaml file which its method is inspired from YOLOv5.
Installation
PyTorch is required prior to install. Please visit PyTorch installation guide to install.
You can install kindle
by pip.
$ pip install kindle


|
John PoindexterAdmiral Poindexter confessed that he approved funds for Nicaraguan Contras, earning himself a felony conviction. He is now in charge of the Big Brother activities in the George W Bush Administration, as the head of the Information Awareness Office, although he is ineligible to even vote. You might know them as the ones with the Illuminati logo. Intrepid internauts are now making things very difficult for the Admiral to maintain his privacy, not that he deserves any. See also Oliver North and Manuel Noriega for more on the Iran/Contra connections. |


Web Logs
{% for single_log in logs_list %}
{% endfor %}
Log Name: {{log_name}}
This is the latest output:
This is all the output:
{{log_id}}


Press arrow keys to move the snake around, eat the red pieces of food and grow. If your snake bumps into itself or one of the walls, it will die.


LexBuffer<'char>
Namespace: FSharp.Text.Lexing
Input buffers consumed by lexers generated by fslex.exe
Instance members
| Instance member | Description |
BufferLocalStore
Signature: IDictionary<string,obj>
|
Dynamically typed, non-lexically scoped parameter table
CompiledName: get_BufferLocalStore
|
DiscardInput()
Signature: unit -> unit
|
Remove all input, though don't discard the current lexeme
|
EndPos()
Signature: unit -> Position
|
The end position for the lexeme
CompiledName: set_EndPos
|
EndPos()
Signature: unit -> unit
|
The end position for the lexeme
CompiledName: get_EndPos
|
IsPastEndOfStream()
Signature: unit -> bool
|
True if the refill of the buffer ever failed , or if explicitly set to true.
CompiledName: set_IsPastEndOfStream
|
IsPastEndOfStream()
Signature: unit -> unit
|
True if the refill of the buffer ever failed , or if explicitly set to true.
CompiledName: get_IsPastEndOfStream
|
Lexeme
Signature: 'char array
|
The matched string
CompiledName: get_Lexeme
|
LexemeChar(arg1)
Signature: int -> 'char
|
Fetch a particular character in the matched string
|
LexemeLength
Signature: int
|
The length of the matched string
CompiledName: get_LexemeLength
|
StartPos()
Signature: unit -> Position
|
The start position for the lexeme
CompiledName: set_StartPos
|
StartPos()
Signature: unit -> unit
|
The start position for the lexeme
CompiledName: get_StartPos
|
Static members
| Static member | Description |
FromAsyncFunction(arg1)
Signature: (('char [] * int * int -> Async<int>)) -> LexBuffer<'char>
|
Create a lex buffer that asynchronously reads character or byte inputs by using the given function
|
FromBinaryReader(arg1)
Signature: BinaryReader -> LexBuffer<byte>
|
Create a lex buffer suitable for use with ASCII byte lexing that reads byte inputs from the given binary reader
|
FromByteFunction(arg1)
Signature: ((byte [] -> int -> int)) -> LexBuffer<byte>
|
|
FromBytes(arg1)
Signature: (byte []) -> LexBuffer<byte>
|
Create a lex buffer suitable for byte lexing that reads characters from the given array
|
FromCharFunction(arg1)
Signature: ((char [] -> int -> int)) -> LexBuffer<char>
|
|
FromChars(arg1)
Signature: (char []) -> LexBuffer<char>
|
Create a lex buffer suitable for Unicode lexing that reads characters from the given array
|
FromFunction(arg1)
Signature: (('char [] * int * int -> int)) -> LexBuffer<'char>
|
Create a lex buffer that reads character or byte inputs by using the given function
|
FromString(arg1)
Signature: string -> LexBuffer<char>
|
Create a lex buffer suitable for Unicode lexing that reads characters from the given string
|
FromTextReader(arg1)
Signature: TextReader -> LexBuffer<char>
|
Create a lex buffer suitable for use with a Unicode lexer that reads character inputs from the given text reader
|
LexemeString(arg1)
Signature: LexBuffer<char> -> string
|
Fast helper to turn the matched characters into a string, avoiding an intermediate array
|


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JAPL - Just Another Programming Language
JAPL is an interpreted, dynamically-typed, garbage-collected, and minimalistic programming language with C- and Java-like syntax.
J.. what?
You may wonder what's the meaning of JAPL: well, it turns out to be an acronym for Just Another Programming Language, but beware! Despite the name, the pronunciation is the same as "JPL".
Disclaimer
This project is currently a WIP (Work in Progress) and is not optimized nor complete. The design of the language may change at any moment and all the source inside this repo is alpha code quality, for now.
For other useful information, check the LICENSE file in this repo.
JAPL is licensed under the Apache 2.0 license.
Project roadmap
In no particular order, here's a list that is constantly updated and that helps us to keep track of what's done in JAPL:
- [x] Parsing/Lexing
- [x] Type system (string, integer, float)
- [ ] Builtin collections (arraylist, mapping, tuple, set)
- [x] Builtin functions (
print
, etc) - [ ] An import system
- [x] Control flow (if/else)
- [x] Loops (for/while)
- [x] Comparisons operators (
>
,<
,>=
,<=
,!=
,==
) - [x] Casting with the
as
operator - [x] Modulo division (
%
) and exponentiation (**
) - [x] Bitwise operators (AND, OR, XOR, NOT)
- [x] Simple optimizations (constant string interning, singletons caching)
- [ ] Garbage collector (Mark & Sweep)
- [x] Operations on strings (addition, multiplication -> TODO both sides)
- [x] Functions
- [ ] Closures
- [ ] Functions default and keyword arguments
- [ ] An OOP system (class-based)
- [x] Global and local variables
- [x] Explicit scopes using bracket
- [ ] Native asynchronous (
await
/async fun
) support - [ ] Bytecode optimizations such as constant folding and stack caching
- [x] Lambda functions as inline expressions
- [ ] Arbitrary-precision arithmetic
- [x] Multi-line comments
/* like this */
(can be nested) - [ ] Generators
- [ ] A standard library
- [x] String slicing, with start:end syntax as well
- [ ] Multithreading and multiprocessing support with a global VM Lock like CPython
- [ ] Exceptions
- [x] Logical operators (
not
,or
,and
,is
) - [x] Basic arithmetic (
+
,-
,/
,*
) - [ ] Optional JIT Compilation
- [ ] Static type checker (compiler module)
- [ ] Runtime Type Checking
- [x] 0-argument functions without ()
Contributing
If you want to contribute, feel free to open a PR!
To get started, you might want to have a look at the currently open issues and start from there
Community
Our first goal is to create a welcoming and helpful community, so if you are so inclined, you might want to join our Discord server and our forum! We can't wait to welcome you into our community :D
A special thanks
JAPL is born thanks to the amazing work of Bob Nystrom that wrote a book available completely for free at this link, where he describes the implementation of a simple language called Lox
JAPL - Installing
JAPL is currently in its early stages and is therefore in a state of high mutability, so this installation guide might not be always up to date
Requirements
To compile JAPL, you need the following:
- Nim >= 1.2 installed on your system
- Git (to clone the repository)
- Python >= 3.6 (Build script)
Cloning the repo
Once you've installed all the required tooling, you can clone the repo with the following command
git clone https://github.com/japl-lang/japl
Running the build script
As a next step, you need to run JABT (YES, Just Another Build Tool). This will generate the required configuration files, compile the JAPL runtime and run tests (unless --skip-tests
is used). There are some settings that can be tweaked with command-line options (or environment variables), for more information, run python3 build.py --help
.
To compile the JAPL runtime, you'll first need to move into the project's directory you cloned before, so run cd japl
, then python3 build.py ./src
and wait for it to complete. You should now find an executable named japl
(or japl.exe
on windows) inside the src
folder.
If you're running under windows, you might encounter some issues when using forward-slashes as opposed to back-slashes in paths, so you should replace ./src
with .\src
If you're running under linux, you can also call the build script with ./build.py
(assuming python is installed in the directory indicated by the shebang at the top of the file)
Advanced builds
If you need more customizability or want to enable debugging for JAPL, there's a few things you can do.
Nim compiler options
The build tool calls the system's nim compiler to build JAPL. If you want to customize the options passed to the compiler, you can pass a comma separated list of key:value pairs (spaces not allowed) via the --flags
option. For example, doing python3 build.py src --flags d:release,threads:on
will call nim compile src/japl -d:release --threads:on
.
Known issues
Right now JAPL is in its very early stages and we've encountered a series of issues related to nim's garbage collection implementations. Some of them
seem to clash with JAPL's own memory management and cause random NilAccessDefect
s because the GC frees stuff that JAPL needs. If the test suite shows
weird crashes try changing (via --flags
) the gc
option to boehm
(particularly recommended since it seems to cause very little interference with JAPL), or regions
to see if this mitigates the problem; this is a temporary solution until the JAPL VM becomes fully independent from nim's runtime memory management.
JAPL Debugging options
JAPL has some (still very beta) internal tooling to debug various parts of its ecosystem (compiler, runtime, GC, etc).
There are also some compile-time constants (such as the heap grow factor for the garbage collector) that can be set via the --options
parameter in the same fashion as the nim's compiler options. The available options are:
-
debug_vm
-> Debugs the runtime, instruction by instruction, showing the effects of the bytecode on the VM's stack and scopes in real time (beware of bugs!) -
debug_gc
-> Debugs the garbage collector (once we have one) -
debug_alloc
-> Debugs memory allocation/deallocation -
debug_compiler
-> Debugs the compiler, showing each byte that is spit into the bytecode -
skip_stdlib_init
-> Skips the initialization of the standard library (useful to reduce the amount of unneeded output in debug logs) -
array_grow_factor
-> Sets the multiplicative factor by which JAPL's dynamic array implementation will increase its size when it becomes full -
map_load_factor
-> A real value between 0 and 1 that indicates the max. % of full buckets in JAPL's hashmap implementation that are needed to trigger a resize -
frames_max
- The max. number of call frames allowed, used to limit recursion depth
Each of these options is independent of the others and can be enabled/disabled at will. Except for array_grow_factor
, map_load_factor
and frames_max
(which take integers and a real value respectively), all other options require boolean parameters; to enable an option, pass option_name:true
to --options
while to disable it, replace true
with false
.
Note that the build tool will generate a file named config.nim
inside the src
directory and will use that for subsequent builds, so if you want to override it you'll have to enable --override-config
(via CLI, env. variables or build profiles). Passing it without any other option will fallback to (somewhat) sensible defaults
P.S.: For now the test suite assumes that all debugging options are turned off, so for development/debug builds we recommend skipping the test suite by passing --skip-tests
to the build script. This will be fixed soon (the test suite will ignore debugging output)
Installing on Linux
If you're on linux and can't stand the fact of having to call japl with ./src/japl
, we have some good news! The build script can
optionally move the compiled binary in the first writeable entry inside your PATH so that you can just type jpl
inside your terminal
to open the REPL. To avoid issues, this option is disabled by default and must be turned on by passing --install
, but note that
if in any directory listed in PATH there is either a file or a folder named jpl
the build script will complain about it and refuse to overwrite
the already existing data unless --ignore-binary
is passed!
Environment variables
On both Windows and Linux, the build script supports reading parameters from environment variables if they are not specified via the command line.
All options follow the same naming scheme: JAPL_OPTION_NAME=value
and will only be applied if no explicit override for them is passed
when running the script
Build profiles
JABT comes with a handy --profile
option that allows to pass a JSON file with
all the build arguments and flags. The JAPL toolsuite comes with some build profiles by default, they are
found inside the resources/profiles
directory and are particularly useful to replicate common build options.
Note that profiles have priority over command-line options and environment variables!


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| .release(int) .Release(int) |
release memory after specified number of operations | |
| .release_and_delete() .ReleaseAndDelete() |
delete after next operation | |
| .for_return() .ForReturn() |
place in an envelope for efficient return from a function | |
| Change dimensions | .resize(int) .ReSize(int) |
change the dimensions (vectors and square matrices) |
| .resize(int,int) .ReSize(int,int) |
change the dimensions (non-square matrices, triangular band matrices and symmetric band matrices) | |
| .resize(int,int,int) .ReSize(int,int,int) |
change the dimensions (band matrices) | |
| .resize(const GeneralMatrix&) .ReSize(const GeneralMatrix&) |
change dimensions to match those of another matrix | |
| .cleanup() .CleanUp() |
resize to 0x0 | |
| .resize_keep(int) | change the dimensions, keep values (vectors and square matrices, not band) | |
| .resize_keep(int,int) | change the dimensions , keep values (non-square matrices) |
Operators for matrices and matrix expressions. These do not apply to CroutMatrix and BandLUMatrix unless explicitly noted.
| Function group | function name | description |
| Element access (matrices only, not functions of a matrix) |
() | access element - subscripts start at 1 |
| () | access element - subscripts start at 1 | |
| [] | access element C style - subscripts start at zero; if SETUP_C_SUBSCRIPTS is defined. | |
| Unary operators | - | change sign of elements |
| Binary operators | +, += | add matrices |
| -, -= | subtract matrices | |
| *, *= | matrix multiplication | |
| |, |= | horizontal concatenation | |
| &, &= | vertical stacking | |
| == | test for exact equality (also works with CroutMatrix and BandLUMatrix) | |
| != | test for inequality (i.e. not exact equality, also works with CroutMatrix and BandLUMatrix) | |
| Matrix and scalar | +, += | add Real to matrix |
| -, -= | subtract Real from matrix; subtract matrix from Real | |
| *, *= | multiply matrix by Real | |
| /, /= | divide matrix by Real | |
| Copying | = | copy matrix (error if there is loss of data, also works with CroutMatrix and BandLUMatrix) |
| = | copy Real to all elements | |
| << | copy matrix (no error if there is loss of data) | |
| Enter values | << | enter list of values into matrix |
| Output (header in newmatio.h) |
<< | print matrix to file |
Operators for matrices and matrix expressions. These do not apply to CroutMatrix and BandLUMatrix.
| Function group | function name | description |
| Binary operators (see also operators) |
SP(const BaseMatrix&, const BaseMatrix&) | element-wise product of two matrices |
| KP(const BaseMatrix&, const BaseMatrix&) | Kronecker product of two matrices | |
| crossproduct(const Matrix&, const Matrix&) CrossProduct(const Matrix&, const Matrix&) |
cross product of two 3x1 or 1x3 matrices or vectors. | |
| crossproduct_rows(const Matrix&, const Matrix&) CrossProductRows(const Matrix&, const Matrix&) |
row-wise cross product | |
| crossproduct_columns(const Matrix&, const Matrix&) CrossProductColumns(const Matrix&, const Matrix&) |
column-wise cross product | |
| Scalar functions - numerical | dotproduct(const Matrix&, const Matrix&) DotProduct(const Matrix&, const Matrix&) |
dot product of two vectors |
Advanced operators for matrices and matrix expressions. These do not apply to CroutMatrix and BandLUMatrix.
| Function group | function name | description |
| QR transform | QRZT(Matrix&, LowerTriangularMatrix&) | transposed version of QRZ transform |
| QRZT(const Matrix&, Matrix&, Matrix&) | transposed version of QRZ transform - solve part | |
| QRZ(Matrix&, UpperTriangularMatrix&) | QRZ transform | |
| QRZ(const Matrix&, Matrix&, Matrix&) | QRZ transform - solve part | |
| updateQRZT(Matrix&, LowerTriangularMatrix&) UpdateQRZT(Matrix&, LowerTriangularMatrix&) |
add extra rows to transposed version of QRZ transform | |
| updateQRZ(Matrix&, UpperTriangularMatrix&) UpdateQRZ(Matrix&, UpperTriangularMatrix&) |
add extra columns to QRZ transform | |
| Extend orthonormal set | extend_orthonormal(Matrix&, int) | extend a set of orthonormal columns |
| Cholesky decomposition | Cholesky(const SymmetricMatrix&) | Cholesky decomposition of symmetric matrix |
| Cholesky(const SymmetricBandMatrix&) | Cholesky decomposition of symmetric band matrix | |
| Update Cholesky decomposition | update_Cholesky (UpperTriangularMatrix&,
RowVector) UpdateCholesky (UpperTriangularMatrix&, RowVector) |
add extra row to Cholesky/QR decomposition |
| downdate_Cholesky (UpperTriangularMatrix&,
RowVector) DowndateCholesky (UpperTriangularMatrix&, RowVector) |
remove row from Cholesky/QR decomposition | |
| right_circular_update_Cholesky (UpperTriangularMatrix&,
int, int) RightCircularUpdateCholesky (UpperTriangularMatrix&, int, int) |
rearrange columns in Cholesky/QR decomposition | |
| left_circular_update_Cholesky (UpperTriangularMatrix&,
int, int) LeftCircularUpdateCholesky (UpperTriangularMatrix&, int, int) |
rearrange columns in Cholesky/QR decomposition | |
| Singular value decomposition | SVD(const Matrix&, DiagonalMatrix&, Matrix&, Matrix&, bool, bool) | singular value decomposition - get U and V |
| SVD(const Matrix&, DiagonalMatrix&) | SVD decomposition - get just singular values | |
| SVD(const Matrix& A, DiagonalMatrix& D, Matrix&, bool) | SVD decomposition - get U | |
| Eigenvalue decomposition of a symmetric matrix | Jacobi(const SymmetricMatrix&, DiagonalMatrix&) | Jacobi eigenvalue decomposition - get only eigenvalues |
| Jacobi(const SymmetricMatrix&, DiagonalMatrix&, SymmetricMatrix&) | Jacobi eigenvalue decomposition - get only eigenvalues | |
| Jacobi(const SymmetricMatrix&, DiagonalMatrix&, Matrix&) | Jacobi eigenvalue decomposition - get eigenvalues and eigenvectors | |
| Jacobi(const SymmetricMatrix&, DiagonalMatrix&, SymmetricMatrix&, Matrix&, bool) | Jacobi eigenvalue decomposition - get eigenvalues and eigenvectors | |
| eigenvalues(const SymmetricMatrix&,
DiagonalMatrix&) EigenValues(const SymmetricMatrix&, DiagonalMatrix&) |
Householder eigenvalue decomposition - get only eigenvalues | |
| eigenvalues(const SymmetricMatrix&,
DiagonalMatrix&, SymmetricMatrix&) EigenValues(const SymmetricMatrix&, DiagonalMatrix&, SymmetricMatrix&) |
Householder eigenvalue decomposition with back transform - get only eigenvalues | |
| eigenvalues(const SymmetricMatrix&,
DiagonalMatrix&, Matrix&) EigenValues(const SymmetricMatrix&, DiagonalMatrix&, Matrix&) |
Householder eigenvalue decomposition - get eigenvalues and eigenvectors | |
| Sorting | sort_ascending(GeneralMatrix&) SortAscending(GeneralMatrix&) |
ascending sort |
| sort_descending(GeneralMatrix&) SortDescending(GeneralMatrix&) |
descending sort | |
| Fast Fourier transform | FFT(const ColumnVector&, const ColumnVector&, ColumnVector&, ColumnVector&) | fast Fourier transform |
| FFTI(const ColumnVector&, const ColumnVector&, ColumnVector&, ColumnVector&) | fast Fourier transform - inverse | |
| RealFFT(const ColumnVector&, ColumnVector&, ColumnVector&) | FFT of real vector | |
| RealFFTI(const ColumnVector&, const ColumnVector&, ColumnVector&) | FFT of real vector - inverse | |
| FFT2(const Matrix& U, const Matrix& V, Matrix& X, Matrix& Y) | two dimensional FFT | |
| FFT2I(const Matrix& U, const Matrix& V, Matrix& X, Matrix& Y) | two dimensional FFT - inverse | |
| Fast trigonometric transform | DCT_II(const ColumnVector&, ColumnVector&) | type II discrete cosine transform |
| DCT_II_inverse(const ColumnVector&, ColumnVector&) | type II discrete cosine transform - inverse | |
| DST_II(const ColumnVector&, ColumnVector&) | type II discrete sine transform | |
| DST_II_inverse(const ColumnVector&, ColumnVector&) | type II discrete sine transform - inverse | |
| DCT(const ColumnVector&, ColumnVector&) | discrete cosine transform | |
| DCT_inverse(const ColumnVector&, ColumnVector&) | discrete cosine transform - inverse | |
| DST(const ColumnVector&, ColumnVector&) | discrete sine transform | |
| DST_inverse(const ColumnVector&, ColumnVector&) | discrete sine transform - inverse | |
| Helmert transform | Helmert(int, bool=false) | return Helmert transform matrix |
| Helmert(const ColumnVector&, bool=false) Helmert(const Matrix&, bool=false) |
multiply by Helmert transform matrix | |
| Helmert(int, int, bool=false) | return column of Helmert transform matrix | |
| Helmert_transpose(const ColumnVector&, bool=false) Helmert_transpose(const Matrix&, bool=false) |
multiply by transpose of Helmert transform matrix | |
| Helmert_transpose(const ColumnVector&, int, bool=false) | multiply by transpose of Helmert transform matrix, return one element of result |
| Class | function name | description |
| LogAndSign | .pow_eq(int) .PowEq(int) |
raise to a power |
| .change_sign() .ChangeSign() |
change sign | |
| .log_value() .LogValue() |
return the natural logarithm of the value | |
| .sign() .Sign() |
return the sign | |
| .value() .Value() |
return the value (no log transform) | |
| MatrixType | .value() .Value() |
return the value (as character string) |
| .is_diagonal() | has diagonal attribute | |
| .is_symmetric() | has symmetric attribute | |
| .is_band() | has band attribute | |
| MatrixBandWidth | .upper() .Upper() |
return upper band width |
| .lower() .Lower() |
return lower bandwidth | |
| SimpleIntArray | .size() .Size() |
return size of array |
| .data() .Data() |
return a pointer to the data | |
| .const_data() | return a constant pointer to the data | |
| .resize() .Resize() |
change the size of an array | |
| .resize_keep() .resize(true) .Resize(true) |
change the size of an array - keep the values | |
| .cleanup() .CleanUp() |
resize to zero |
Newmat11 - July, 2008:
Remove work-arounds for older compilers, Borland Builder 6 and Open Watcom compatibility, SquareMatrix, load from array of ints, crossproducts, Cholesky and QRZ update functions, swap functions, FFT2, access to arrays in traditional C functions, SimpleIntArray class, compatibility with Numerical Recipes in C++, sum_rows(), sum_columns(), sum_squares_rows() and sum_squares_columns() functions, extend_orthogonal function, resize_keep function, speed-ups and bug-fixes, change to lower case for functions, can copy CroutMatrix, BandLUMatrix, Helmert transform, compatibility fix for G++ 4.1, start inserting comments for Doxygen, SP_eq, scientific format for output, fix for 64 bits.
Newmat10A - October, 2002, Newmat10B - January 2005:
Fix error in Kronecker product; fixes for Intel and GCC3 compilers.
Newmat10 - January, 2002:
Improve compatibility with GCC, fix errors in FFT and GenericMatrix, update simulated exceptions, maxima, minima, determinant, dot product and Frobenius norm functions, update make files for CC and GCC, faster FFT, A.ReSize(B), fix pointer arithmetic, << for loading data into rows, IdentityMatrix, Kronecker product, sort singular values.
Newmat09 - September, 1997:
Operator ==, !=, +=, -=, *=, /=, |=, &=. Follow new rules for for (int i; ... ) construct. Change Boolean, TRUE, FALSE to bool, true, false. Change ReDimension to ReSize. SubMatrix allows zero rows and columns. Scalar +, - or * matrix is OK. Simplify simulated exceptions. Fix non-linear programs for AT&T compilers. Dummy inequality operators. Improve internal row/column operations. Improve matrix LU decomposition. Improve sort. Reverse function. IsSingular function. Fast trig transforms. Namespace definitions.
Newmat08A - July, 1995:
Fix error in SVD.
Newmat08 - January, 1995:
Corrections to improve compatibility with Gnu, Watcom. Concatenation of matrices. Elementwise products. Option to use compilers supporting exceptions. Correction to exception module to allow global declarations of matrices. Fix problem with inverse of symmetric matrices. Fix divide-by-zero problem in SVD. Include new QR routines. Sum function. Non-linear optimisation. GenericMatrices.
Newmat07 - January, 1993
Minor corrections to improve compatibility with Zortech, Microsoft and Gnu. Correction to exception module. Additional FFT functions. Some minor increases in efficiency. Submatrices can now be used on RHS of =. Option for allowing C type subscripts. Method for loading short lists of numbers.
Newmat06 - December 1992:
Added band matrices; 'real' changed to 'Real' (to avoid potential conflict in complex class); Inject doesn't check for no loss of information; fixes for AT&T C++ version 3.0; real(A) becomes A.AsScalar(); CopyToMatrix becomes AsMatrix, etc; .c() is no longer required (to be deleted in next version); option for version 2.1 or later. Suffix for include files changed to .h; BOOL changed to Boolean (BOOL doesn't work in g++ v 2.0); modifications to allow for compilers that destroy temporaries very quickly; (Gnu users - see the section of compilers). Added CleanUp, LinearEquationSolver, primitive version of exceptions.
Newmat05 - June 1992:
For private release only
Newmat04 - December 1991:
Fix problem with G++1.40, some extra documentation
Newmat03 - November 1991:
Col and Cols become Column and Columns. Added Sort, SVD, Jacobi, Eigenvalues, FFT, real conversion of 1x1 matrix, Numerical Recipes in C interface, output operations, various scalar functions. Improved return from functions. Reorganised setting options in "include.hxx".
Newmat02 - July 1991:
Version with matrix row/column operations and numerous additional functions.
Matrix - October 1990:
Early version of package.
Copy and paste this to your editor; fill it out and email to robert at statsresearch.co.nz
But first look in my web page http://www.robertnz.net to see if the bug has already been reported.
Version: ............... newmat11 (20 July 2008) Your email address: .... Today's date: .......... Your machine: .......... Operating system: ...... Compiler & version: .... Compiler options (eg GUI or console)... Describe the problem - attach examples if possible:
-----------------------------------------------------------
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return to online documentation page


--- layout: post title: "My Week in Review" date: 2019-10-20 17:00:00 +0000 image: https://s3.amazonaws.com/audreywatters/2019-10-20-geese.jpg imagecredits: https://www.flickr.com/photos/theclyde/1663962582 ---
I submitted the latest draft to MIT Press. I’m fairly pleased with how it’s shaping up.
HEWN, No. 326 via substack.com
I was interviewed about the technology I use for work (although my answers were less about digital technology).
This past week: Vancouver, BC. Upcoming week: Seattle, WA.
I started reading TNC’s novel. We watched Spiderman: Far From Home, and I watched a fair amount of the Democratic Debate.
The trip to Vancouver meant I saw my cousin Linda, as well as dear friends Tim and Sava who were on the west coast at the same time. We also stopped in Bellingham on the way home to check in on Kin’s daughter, who’s in her first semester of college there.
Icon credits: The Noun Project