Decision Making for Robotics
Mini Project 1:
Blossom Algorithm
Authors: Pruthvi Sanghavi
Summary
Blossom Algorithm is a matchmaking algorithm used to produce a maximum matching on any graph. It was created by Jack Edmunds in 1961[9].
It has applications in a wide variety of fields of Robotics, Operations Theory, Biology, Mathematics etc. In this article, we will focus our attention on the applications in the domain of Robotics and Decision Making for Robotics.
A matching is a graph that occurs when all vertices are connected to at most one other vertex through a single edge.
A maximum matching occurs when the number of edges in the matching graph is maximized.
Before we dive deeper into the intrinsics of the algorithm. First we will discuss, what is graph theory[6][7] and its basic elements -
Graph theory: is the field of mathematics that deals with mathematical structures used to model pairwise relationships between objects.
Graph:A Graph G is an ordered pair of disjoint sets G = (V, E) where E => VxV. Set V is called the vertex or the node set and Set E is called the edge set of graph G.
Vertex:A fundamental unit with which a graph is constructed.
Edges:The objects which connect the vertices to form a graph.
Path:A path is a sequence of vertices traversed using edges.
Augmenting Path:An augmenting path starts and ends at a free vertex and alternates between unmatched and matched edges.
A Graph is represented by a set of vertices and the edges connecting these vertices. The true essence of the graph theory is its flexibility with
which it can be used to model a wide variety of problems. A Graph is used in the domain of computer science to model communication networks, data strucures, computer organizations and flow of computations
in the field of sociology to measure actors' prestige or to explore rumor spreading and in the field of Robotics to model multi robotics problem and task allocation problems. The Travelling Salesman Problem is an optimization problem and it can be used using the techniques applied to solve the problems
in graphs. In multi robot applications, robots and the task space are modelled as a graph and a matching algorithm is used to allot the specific task to the robot.
Visualizing the Algorithm
The visualization of the algorithm is produced using TU Munich' Edmond's Blossom Algorithm Visualizer [7]
Consider an undirected graph G as shown in the graphic.
- All the vertices are unmatched(free vertices) as shown in yellow. An augmenting path can be found to improve matching
- A node is selected and assigned as the root node(red). A Breadth first search is initiated from the node. A tree of alternating path is expanded until the we reach another free vertex
- A node is chosen from the queue and assigned as the active node (red) and its neighbours are explored to look for the free vertex
- The next neighbouring node (orange edge) is checked and if the next node is free(yellow), then there is an augmenting path between the current root and the new node
- The augmenting path is reconstructed and is highlighted as green
- The augmenting path is inverted to improve the matching. Inverting an augmenting path means that all unmatched edges along the path are changed to matched ones and vice versa. By doing so, the number of edges contained in the matching increases by 1. The new matching is colored blue.
- There are still unmatched vertices (yellow). We call them free vertices. We try to find an augmenting path to improve the matching. An augmenting path starts and ends at a free vertex and alternates between unmatched and matched edges.
- We pick one of the free vertices as the root node of a modified Breadth-First Search (BFS). Its stroke is colored red throughout the execution of the BFS. From the root node, we will construct a tree of alternating paths (BFS tree) until we reach another free vertex.
- Pick the next node from the BFS queue. We call this node the currently active node and color it red. From this node, we will explore its neighbors to look for a free vertex.
- We check the next neighbor (orange) and find that it is already matched.
- We add the neighbor and its mate to the BFS tree. The mate is further pushed to the BFS queue and we might continue our search from there later. The edges of the BFS tree are highlighted by a grey overlay.
- We check the next neighbor (orange) and find that this node is already contained in the BFS tree. Thus, there exists a cycle and we see that it has an odd number of edges. We call such a cycle a blossom.
- The odd-length cycle we found is contracted to a single supernode. Supernodes are highlighted by a larger radius compared to the other nodes. We further push the new supernode to the BFS queue.
- Pick the next node from the BFS queue. We call this node the currently active node and color it red. From this node, we will explore its neighbors to look for a free vertex.
- We check the next neighbor (orange edge) and find that it is a free vertex (yellow). Thus, there is an augmenting path between the root of the BFS and this vertex.
- The augmenting path is highlighted green. Before improving the matching we have to expand the supernodes contained in the graph.
- After the expansion of all supernodes the augmenting path is fully reconstructed and highlighted green.
- The augmenting path is inverted to improve the matching. Inverting an augmenting path means that all unmatched edges along the path are changed to matched ones and vice versa. By doing so, the number of edges contained in the matching increases by 1. The new matching is colored blue.
Formal definition using appropriate notation
Consider an undirected unweighted graph G(V, E), where V and E are the set of vertices and the set of edges respectively. Let M denote the numbers of matchings in the graph G
Given a graph G and a matching M, M is a maximum matching if and only if there exists no M-augmenting path.
Complexity of Algorithm[16]
Three outcomes of Blossom Algorithm:
- Maximum Matching
- An Augmenting Path
- Blossom
In worst case: The total runtime that the algorithm has is O(|E||V|^2) and each iteration takes in O(|E|).
Use in Decision Making for Robotics
One of the important research areas in Robotics where the Blossom Algorithm has been applied extensively is the task allocation problem.
From [1], Consider n robots colored black and m tasks colored gray as shown in the figure. The task allocation problem here can be defined as a bipartite(bigraphs) which are used to study and analyse the robot-task relationships.
A Bipartite graph is the one in which the vertices can be divided into two sets such that no two vertices of the same set can be connected by a common edge. The definition of the bipartite graph perfectly explains the scenario here
when we have two separate sets one for the robots and other for the tasks and as no two robots be related to each other but robot and tasks. The edges between the robots and the tasks are weighted in order to avoid the random allocation of
the tasks to the robots.
Once the weighted bipartite graph is produced, based on the weights of the edges a matching graph M is constructed which gives the optimized solution.
In electronic circuit design applications, the end effector of the manipulators need to design the path such that the vertical motion of the manipulator is minimum. In that case the problem can be formulated as a euclidean path planning algorithm and then the
Edmund`s Blossom Algorithm can be used to find the optimal path
Other Applications
Apart from the Robotics Applications such as Task Allocation and Target Tracking. Blossom' Algorithms is used in the solution of combinatorical problems such as the Hall' Marriage Problem and the path problem such as the Hamiltonian Path Problems.
Other areas where the Blossom Matching Algorithm finds its applications are:
- The Assignment Problem
- The oil well drilling problem
- Plotting Street Maps
- Scheduling Problems
- Set Packing Problems
Open research questions
In the robotics research, the blossom algorithm implementation can be optimized by the adoption of distributed parallelization and problem decomposition approaches.
References
- Ghassemi, Payam, and Chowdhury, Souma. "Decentralized Task Allocation in Multi-Robot Systems via Bipartite Graph Matching Augmented With Fuzzy Clustering." Proceedings of the ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 2A: 44th Design Automation Conference. Quebec City, Quebec, Canada. August 26–29, 2018. V02AT03A014. ASME. https://doi.org/10.1115/DETC2018-86161
- Edmonds, J. (1965). Paths, Trees, and Flowers. Canadian Journal of Mathematics, 17, 449-467. doi:10.4153/CJM-1965-045-4
- Blum, N. (2015). Maximum Matching in General Graphs Without Explicit Consideration of Blossoms Revisited. ArXiv, abs/1509.04927.
- Harold N. Gabow:Data Structures for Weighted Matching and Extensions to b-matching and f-factors. ACM Trans. Algorithms 14(3): 39:1-39:80 (2018)
- http://www.math.uwaterloo.ca/~bico//papers/cobook_select.pdf
- http://www.fang.ece.ufl.edu/eel6935/presentation/GraphTheory.pdf
- Elements of Graph Theory
- https://www-m9.ma.tum.de/graph-algorithms/matchings-blossom-algorithm/index_en.html
- https://www.eecs.tufts.edu/~gdicks02/Blossom/Blossom_Algorithm.html
- http://www.cs.cmu.edu/~anupamg/advalgos15/lectures/lecture08.pdf
- https://en.wikipedia.org/wiki/Graph_theory#Applications
- https://en.wikipedia.org/wiki/Bipartite_graph
- https://people.scs.carleton.ca/~maheshwa/courses/5703COMP/16Fall/Matching-Report.pdf
- http://web.eecs.utk.edu/~jplank/plank/classes/cs494/494/notes/Edmonds/index.html
- https://www.cs.tau.ac.il/~zwick/grad-algo-0910/match.pdf
- https://brilliant.org/wiki/blossom-algorithm/


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'Cry of the Curlew' to be launched at Scrub Hill 1869
by Ben HopkinsA collection of artistic talent from around the Ballarat region is set to be showcased in Newlyn as the Moorabool Writers Craft launch their new anthology book, 'Cry of the Curlew'.
Contributing writer and musician Vanessa Craven said she is excited to launch the project which features fiction, non-fiction and a collection of poems.
"It's so exciting to be releasing it because it's been born of hard work... people who are enthusiastic and want to create," she said.
The free festival will feature live readings from the new book, along with music, art, food and drinks at Newlyn's Scrub Hill 1869.
Ms Craven said having a free festival on offer is very important in promoting art to the wider community and encourage involvement within groups like the Moorabool Writers Craft.
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Further Reading
If using tab groups on iOS, see the "Tab Bar" section of Apple's official iOS UI Element Usage Guidelines .
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Finishes a batch update of the View's layout properties and schedules a layout pass of the view tree.
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| event | [Dictionary] | A dictionary of keys and values to add to the Titanium.Event object sent to the listeners. |
Gets the value of the activeTabBackgroundColor property.
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Gets the value of the top property.
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Removes a child view from this view's hierarchy.
Arguments
| view | [Titanium.UI.View] | View to remove from this view's hierarchy. |
Removes the specified callback as an event listener for the named event.
Arguments
| name | [String] | Name of the event. |
| callback | [Callback<Object>] | Callback function to remove. Must be the same function passed to addEventListener. |
Removes a tab from the tab group.
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| tab | [Titanium.UI.Tab] | Tab to remove. |
Selects the currently active tab in a tab group.
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| indexOrObject | [NumberTitanium.UI.Tab] | Index or object of the tab to switch to. |
Sets the value of the activeTabBackgroundColor property.
Arguments
| activeTabBackgroundColor | [String] | New value for the property. |
Sets the value of the activeTabBackgroundDisabledColor property.
Arguments
| activeTabBackgroundDisabledColor | [String] | New value for the property. |
Sets the value of the activeTabBackgroundDisabledImage property.
Arguments
| activeTabBackgroundDisabledImage | [String] | New value for the property. |
Sets the value of the activeTabBackgroundFocusedColor property.
Arguments
| activeTabBackgroundFocusedColor | [String] | New value for the property. |
Sets the value of the activeTabBackgroundFocusedImage property.
Arguments
| activeTabBackgroundFocusedImage | [String] | New value for the property. |
Sets the value of the activeTabBackgroundImage property.
Arguments
| activeTabBackgroundImage | [String] | New value for the property. |
Sets the value of the activeTabBackgroundSelectedColor property.
Arguments
| activeTabBackgroundSelectedColor | [String] | New value for the property. |
Sets the value of the activeTabBackgroundSelectedImage property.
Arguments
| activeTabBackgroundSelectedImage | [String] | New value for the property. |
Sets the value of the allowUserCustomization property.
Arguments
| allowUserCustomization | [Boolean] | New value for the property. |
Sets the value of the anchorPoint property.
Arguments
| anchorPoint | [Point] | New value for the property. |
Sets the value of the backgroundColor property.
Arguments
| backgroundColor | [String] | New value for the property. |
Sets the value of the backgroundDisabledColor property.
Arguments
| backgroundDisabledColor | [String] | New value for the property. |
Sets the value of the backgroundDisabledImage property.
Arguments
| backgroundDisabledImage | [String] | New value for the property. |
Sets the value of the backgroundFocusedColor property.
Arguments
| backgroundFocusedColor | [String] | New value for the property. |
Sets the value of the backgroundFocusedImage property.
Arguments
| backgroundFocusedImage | [String] | New value for the property. |
Sets the value of the backgroundGradient property.
Arguments
| backgroundGradient | [Gradient] | New value for the property. |
Sets the value of the backgroundImage property.
Arguments
| backgroundImage | [String] | New value for the property. |
Sets the value of the backgroundLeftCap property.
Arguments
| backgroundLeftCap | [Number] | New value for the property. |
Sets the value of the backgroundRepeat property.
Arguments
| backgroundRepeat | [Boolean] | New value for the property. |
Sets the value of the backgroundSelectedColor property.
Arguments
| backgroundSelectedColor | [String] | New value for the property. |
Sets the value of the backgroundSelectedImage property.
Arguments
| backgroundSelectedImage | [String] | New value for the property. |
Sets the value of the backgroundTopCap property.
Arguments
| backgroundTopCap | [Number] | New value for the property. |
Sets the value of the barColor property.
Arguments
| barColor | [String] | New value for the property. |
Sets the value of the borderColor property.
Arguments
| borderColor | [String] | New value for the property. |
Sets the value of the borderRadius property.
Arguments
| borderRadius | [Number] | New value for the property. |
Sets the value of the borderWidth property.
Arguments
| borderWidth | [Number] | New value for the property. |
Sets the value of the bottom property.
Arguments
| bottom | [NumberString] | New value for the property. |
Sets the value of the center property.
Arguments
| center | [Point] | New value for the property. |
Sets the value of the editButtonTitle property.
Arguments
| editButtonTitle | [String] | New value for the property. |
Sets the value of the focusable property.
Arguments
| focusable | [Boolean] | New value for the property. |
Sets the value of the height property.
Arguments
| height | [NumberString] | New value for the property. |
Sets the value of the horizontalWrap property.
Arguments
| horizontalWrap | [Boolean] | New value for the property. |
Sets the value of the keepScreenOn property.
Arguments
| keepScreenOn | [Boolean] | New value for the property. |
Sets the value of the layout property.
Arguments
| layout | [String] | New value for the property. |
Sets the value of the left property.
Arguments
| left | [NumberString] | New value for the property. |
Sets the value of the opacity property.
Arguments
| opacity | [Number] | New value for the property. |
Sets the value of the right property.
Arguments
| right | [NumberString] | New value for the property. |
Sets the value of the softKeyboardOnFocus property.
Arguments
| softKeyboardOnFocus | [Number] | New value for the property. |
Sets the value of the tabDividerColor property.
Arguments
| tabDividerColor | [String] | New value for the property. |
Sets the value of the tabDividerWidth property.
Arguments
| tabDividerWidth | [NumberString] | New value for the property. |
Sets the value of the tabHeight property.
Arguments
| tabHeight | [NumberString] | New value for the property. |
Sets the value of the tabs property.
Arguments
| tabs | [Array<Titanium.UI.Tab>] | New value for the property. |
Sets the value of the tabsAtBottom property.
Arguments
| tabsAtBottom | [Boolean] | New value for the property. |
Sets the value of the tabsBackgroundColor property.
Arguments
| tabsBackgroundColor | [String] | New value for the property. |
Sets the value of the tabsBackgroundDisabledColor property.
Arguments
| tabsBackgroundDisabledColor | [String] | New value for the property. |
Sets the value of the tabsBackgroundDisabledImage property.
Arguments
| tabsBackgroundDisabledImage | [String] | New value for the property. |
Sets the value of the tabsBackgroundFocusedColor property.
Arguments
| tabsBackgroundFocusedColor | [String] | New value for the property. |
Sets the value of the tabsBackgroundFocusedImage property.
Arguments
| tabsBackgroundFocusedImage | [String] | New value for the property. |
Sets the value of the tabsBackgroundImage property.
Arguments
| tabsBackgroundImage | [String] | New value for the property. |
Sets the value of the tabsBackgroundSelectedColor property.
Arguments
| tabsBackgroundSelectedColor | [String] | New value for the property. |
Sets the value of the tabsBackgroundSelectedImage property.
Arguments
| tabsBackgroundSelectedImage | [String] | New value for the property. |
Sets the value of the top property.
Arguments
| top | [NumberString] | New value for the property. |
Sets the value of the touchEnabled property.
Arguments
| touchEnabled | [Boolean] | New value for the property. |
Sets the value of the transform property.
Arguments
| transform | [Titanium.UI.2DMatrixTitanium.UI.3DMatrix] | New value for the property. |
Sets the value of the visible property.
Arguments
| visible | [Boolean] | New value for the property. |
Sets the value of the width property.
Arguments
| width | [NumberString] | New value for the property. |
Sets the value of the zIndex property.
Arguments
| zIndex | [Number] | New value for the property. |
Returns an image of the rendered view, as a Blob.
Arguments
| callback | [Callback<Titanium.Blob>] | Function to be invoked upon completion. If non-null, this method will be performed asynchronously. If null, it will be performed immediately. |
| honorScaleFactor | [Boolean] | Determines whether the image is scaled based on scale factor of main screen. (iOS only) When set to true, image is scale factor is honored. When set to false, the image in the blob has the same dimensions for retina and non-retina devices. |
Performs a batch update of all supplied layout properties and schedules a layout pass after they have been updated.
Arguments
| params | [Dictionary] | Layout properties to be updated. |
Event properties
| index |
[Number] Index of the current active tab. On iOS, a value of |
| previousIndex |
[Number] Index of the previous active tab. On iOS, a value of |
| previousTab |
[Titanium.UI.Tab] Previous active tab. On iOS, a value of |
| source |
[Object] Source object that fired the event. |
| tab |
[Titanium.UI.Tab] Active tab. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| index |
[Number] Index of the current active tab. |
| previousIndex |
[Number] Index of the previous active tab. |
| previousTab |
[Titanium.UI.Tab] Previous active tab. |
| source |
[Object] Source object that fired the event. |
| tab |
[Titanium.UI.Tab] Active tab. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| scale |
[Number] The scale factor relative to the points of the two touches in screen coordinates. |
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| velocity |
[Number] The velocity of the pinch in scale factor per second. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| direction |
[String] Direction of the swipe--either 'left', 'right', 'up', or 'down'. |
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event's endpoint from the |
| y |
[Number] Y coordinate of the event's endpoint from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |
Event properties
| source |
[Object] Source object that fired the event. |
| type |
[String] Name of the event fired. |
| x |
[Number] X coordinate of the event from the |
| y |
[Number] Y coordinate of the event from the |


Oh yeah, and if you haven't checked out http://beesandbeans.com/ you owe yourself. Salted caramel nom nom nom...
4/30/2010, 10:38:33 PM
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Oh yeah, and if you haven't checked out http://beesandbeans.com/ you owe yourself. Salted caramel nom nom nom...
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Up: Defined Values and Handles
Next: MPI-1.2 C Bindings
Previous: Info Keys
false
random
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sequential
true
write_mostly
write_once
Up: Defined Values and Handles
Next: MPI-1.2 C Bindings
Previous: Info Keys
Return to MPI-2 Standard Index
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MPI-2.0 of July 18, 1997
HTML Generated on September 10, 2001


Vegan substitution for everyday pantry basics
14 Sep 2014Understanding the basics of what different types of ingredients do to dough
Things I have been thinking about
- Do I want to continue using chemical leaveners?
- What are really great egg substitutes? Flax seed?
- How much is too processed? (I’d like to keep it to things that could be made at home, if you had a reasonable set of tools, but might prefer to buy fresh from the store, e.g. Almond Milk that is only almonds and water)
- Can you use carbonated water as a leavener? Beer?


In Firefox, the squares may be blurry (and change as the page resizes). Press me to pixel-align the svgs.


Open Beta
Here you can find everything.
From Armors and weapons to all misc items.
Level
Get XP and SP.
Convert my Sex
Become Male of Female.
10k CRP
For all skills.
10k Fame
To make your items PvP.
Noblesse
Get Noblesse status.
Hero
Become Hero now!
Free Items
Bring all here.


Blacklight "demos" for 5 UCB Museums
Caveat lector!
These are demos, and not everything works and many bits are speculative or sketchy! In particular:
Click on a logo below to visit that museum's Blacklight demo:
Berkeley Art Museum |
|
UC Botanical Garden |
|
Pacific File Archive |
|
Phoebe A. Hearst Museum of Anthropology |
|
University and Jepson Herbaria |


| Interface | Description |
|---|---|
| AddBinoTrailFragment.FragmentInteractionListener | |
| AddNnCBTrailFragment.FragmentInteractionListener | |
| RvAdapter.OnItemClickListener | |
| RvAdapter.OnItemLongClickListener |
| Class | Description |
|---|---|
| AddBinoTrailFragment |
This class add Binomial trail to a experiment
|
| AddNnCBTrailFragment |
AddNnCBTrailFragment
perform add, delete Non-negative countBase trail
|
| AllMapViewFragment |
AllMapViewFragment
generate location view
click to select location
|
| Answer |
This is an Answer class
This class gives a single frame of an answer
|
| answerCustomList |
This class customize the context of answers in the listview of question activity
|
| AnswerDatabaseController |
Connecting to the database
perform add, delete and modify answers
|
| AnswerFragment |
This fragment allows people to brose and modify the answer of a question
|
| AppTest |
Test view, add question and view, add answer.
|
| BinomialTest |
Test view, add question and view, add answer.
|
| CountTest |
Test view, add question and view, add answer.
|
| CustomizeScanActivity |
This class custom the frame of scanning
|
| DatabaseController |
Connect to the Database
perform add, delete, modify Experiment
|
| ExampleInstrumentedTest |
Instrumented test, which will execute on an Android device.
|
| Experiment |
This is Experiment Class
This class gives frame of a single experiment
|
| ExperimentAdapter |
This is ExperimentAdapter
Adapter for experiment List
|
| Location |
This is Location Class
This class gives frame of a single Location
|
| LoginActivity |
This class shows the program start interface.
|
| LoginTest |
Test class for LoginActivity.
|
| MainActivity |
MainActivity
Switch Home, subscription, profile on main page
initialize shared attribute
|
| MapFragment |
This class shows the Map.
|
| MeasurementTest | |
| ModifyExperimentFragment |
This is ModifyExperimentFragment
Use to add or modify Experiment
|
| NonNegativeTest |
Test view, add question and view, add answer.
|
| QrcodeFragment |
QrcodeFragment
|
| Question |
This is Question class
This class gives a frame of a single question
|
| Question_AnswerTest |
Test view, add question and view, add answer.
|
| QuestionActivity |
This activity shows the questions asked by others of an unique experiment
It also alows people to click to brose and modify answers of the question
|
| questionCustomList |
This class customize the context of questions in the listview of question activity
|
| QuestionDatabaseController |
Connecting to the database
perform add, delete and modify questions
|
| ReadBarCodeActivity |
This activity read Barcode
|
| RegActivity |
This class shows the registered interface.
|
| RegTest | |
| ResultFragment |
This class show the result of the trails, which includes six numbers and two plots.
|
| RvAdapter |
This class is customList of UserEntity.
|
| ScanActivity |
This class the default frame of scanning
|
| SearchResult |
SearchResult class
Perform search and show result
called from MainActivity
|
| searchTest | |
| TrailList_Bino |
This class is customList of Binomial experiment.
|
| TrailList_OtherFrags |
This class is customList of other experiment.
|
| Trails |
This class prepare an instance of a trail
|
| TrailsActivity |
This class is a terminal and called from homeFragment and contain multiple functionality
|
| TrailsDatabaseController |
Connect to the Database
|
| TrailsDataBaseUnitTest | |
| UserEntity |
This class prepare an instance of a UserEntity
|


Your app must have a 128x128px app icon.
Choose an icon file, if you already have one.
Click the Edit Icon button to edit the icon or create a new one.


Hardware review: AOKZOE A1
I kickstarted the AOKZOE A1 when I was utterly convince that I would never get a Steam Deck.
Joke’s on me; the Deck arrived before the A1.
I primarily use this system as my sole Win11 machine, so it does a lot of light desktop work. It is also my “travel” laptop; when I’m travelling I take this and not my Steam Deck. Everything is tunable, but it draws way more power than a Deck and generally lasts about the same amount of time even with the larger battery.
The bundled OS is pretty close to stock Win11 and contains very little bloat. The A1 sidebar app that shows up when you press the turbo button is servicable, and themable. I went from the obnoxious gamer green UI to something more muted and transparent.
One annoying thing about the “community” is you have to join thew AOKZOE Discord to find out the latest software updates, etc. Since AOKZOE is primarily a Chinese company, and a young one at that, much of the injformation about the device is locked away in Chinese-language web sites and you need the Discord to find and filter out the important parts.
I cannot say enough good things about the display. Blows the Deck out of the water.
TL;DR: The hardware is amazing, the support not so much. The screen and the gaming power are the big draws.
The A1 has been supplanted by the A1 Pro at this point, so you should be able to find A1s much cheaper now.


Sales Guy v. Web Dude, Parts 2-4. Oh, Yeah.
Most of you have probably seen Sales Guy v. Web Dude, a hilarious video on the joys of tech support. If you havenâ€™t seen it, kiss ten minutes goodbye and start there. It ranks up there with the stuff on Best Page In The Universe in entertainment and laugh value.
The creator was quiet for a long time after that video. But in the last few months have been productive for him. And he now has three new videos and posted them on The Website Is Down. All, including the original, are embedded below:
Episode 1 â€“ Sales Guy vs. Web Dude
The original website is down video web dude tries desperately to get his important work done while assaulted on all sides by rampant incompetence. Will he survive???
Episode 2 â€“ Excel Hell
Video #2 from the website is down! Chip takes us on a wild ride into the life of a master salesman. How many sales can he make in a single video? One? Maybe?
Episode 3 â€“ Remain Calm
Chip Demonstrates his special procedure for a hot-swap hardrive replacement using only his steel-toed boot and his razor thin patience. Watch and Learn!

Crunch Network: CrunchGear drool over the sexiest new gadgets and hardware.


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Friction in straight pipe with walls of nonuniform roughness (commercial pipes) in the region that does not depend on the Reynolds-number
The loss factors are given for mass flow rates from port_a to port_b as:
turbulent flow (Idelchik 1994, diagram 2-5, p. 117) zeta = (L/D)/(2*lg(3.7 / Δ))^2, for Re >= 560/Δ for Re ≥ 560/Δ the loss factor does not depend on the Reynolds number. For Re ≥ 4000, the flow is turbulent, but depends both on Δ and slightly on Re. laminar flow (Idelchik 1994, diagram 2-1, p. 110): zeta = 64*(L/D)/Re
where
Since the LossFactorData record can only describe loss factors that depend on geometry (but, e.g., not on the Reynolds number), only the region with Re ≥ 560/Δ is described by this data. Still, the turbulent region with the above zeta is defined to start at Re=4000, since otherwise the approximation for Re < 560/Δ is too bad.
The absolute roughness d has usually to be estimated. In [Idelchik 1994, pp. 105-109, Table 2-5; Miller 1990, p. 190, Table 8-1] many examples are given. As a short summary:
| Smooth pipes | Drawn brass, copper, aluminium, glass, etc. | d = 0.0025 mm |
| Steel pipes | New smooth pipes | d = 0.025 mm |
| Mortar lined, average finish | d = 0.1 mm | |
| Heavy rust | d = 1 mm | |
| Concrete pipes | Steel forms, first class workmanship | d = 0.025 mm |
| Steel forms, average workmanship | d = 0.1 mm | |
| Block linings | d = 1 mm |
encapsulated function wallFriction import Modelica.Fluid.Fittings.BaseClasses.QuadraticTurbulent.LossFactorData; import lg = Modelica.Math.log10; import SI = Modelica.SIunits; input SI.Length length "Length of pipe" annotation( Dialog); input SI.Diameter diameter "Inner diameter of pipe" annotation( Dialog); input SI.Length roughness(min = 1e-10) "Absolute roughness of pipe (> 0 required, details see info layer)" annotation( Dialog); output LossFactorData data "Pressure loss factors for both flow directions"; end wallFriction;


I am an undergraduate student of Computer Science at the University of Memphis,
and I have a partially completed degree in Computer Engineering and Electrical Engineering,
which I plan on completing after my Computer Science degree. I also plan on pursuing a Master's
Degree soon after receiving my Bachelor's Degree in Computer Science .
I work for McVean Trading and Investments in Memphis, Tennessee as a Trade Operations Specialist,
and I develop for a small mobile software startup, Froghat LLC. I love to develop in my spare time,
and my favorite technologies to utilize Swift, Python, Docker, and Amazon Web Services.


Locate the example_conf.py file on your computer:
Copy the file to your home directory and name it django_chuck_conf.py:
Your config file is just a normal Python file so you need to follow the Python syntax, use Python datatypes and you can even dynamically generate the config using functions, external modules, database settings or whatever you like. The config get’s loaded like a normal Python module.
Here’s a brief description of the default settings you can configure.
| setting | description |
|---|---|
| debug | Turn on debugging mode |
| default_modules | Comma-seperated list of module that should always be included when creating a new project |
| django_settings | Default Django settings file |
| module_basedirs | Comma-seperated list of directories where chuck should search for modules . will be replaced with the Django Chuck modules dir |
| module_aliases | A dictionary of lists containing module alias names and list of modules they install |
| project_basedir | Where to store your projects |
| python_version | Python version to use in virtualenv activate (default is version of current interpreter) |
| template_engine | Template engine module to use. For example if you want to use Cheetah or Mako instead of Chucks default engine. |
| use_virtualenvwrapper | Indicates if we should use virtualenvwrapper |
| version_control_system | Version control system to use (can be cvs, svn, git or hg) |
| virtualenv_basedir | Where to store your virtualenvs |
You can add every command parameter to you config settings by using it’s dest parameter.
("-mbs", {
"help": "Comma separated list of dirs where chuck should look for modules",
"dest": "module_basedir",
"default": None,
"nargs": "?",
}),
This parameter can be set by using module_basedir in the config file.
You have some sets of modules that you want to install quite often and you don’t want to type the list of modules over and over again? No problem. Just give your module list an alias name and install that instead.
module_aliases = {
"test": ["unittest", "jenkins"]
}
Now every time you specify the alias test in either the command line call or a config parameter, the modules unittest and jenkins will get installed.


Cyberpunk is Breathtaking
Div with No Corner Cut
Sample Separator
Div with Top Left Corner Cut
Div with Top Right Corner Cut
Div with Bottom Right Corner Cut
Div with Bottom Left Corner Cut
Div with Cross TLBR Corner Cut
Div with Cross TRBL Corner Cut
Div with Cross TRBL Corner Cut and with Shadow
Learn More
Face corporate leaders, underground hustlers, and all of the most
feared people in Night City — those who will do everything in
their power to possess the prototype chip.
Learn More


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{{ site.data.company.contact_email_address }}


Welcome
Hello
Hello Again
Change between components "Hello" & "Hello Again"!
Simple example of spa page with vue-router and transitions between components
Vue Router
Vue Transitions
Hello World!
Hello Again!


Police investigating Makaha stabbing that left man in critical condition | Honolulu Star-Advertiser
Honolulu police are investigating a stabbing that occurred in Makaha Wednesday night.
Emergency Medical Services responded to Mauna Lahilahi Beach Park at about 11:45 p.m. where a 28-year-old man allegedly told responders he was stabbed near 7-Eleven on Makaha Valley Road which is located near the beach, according to a spokeswoman.
Police said a suspect stabbed the victim multiple times. He was taken in critical condition to a hospital.
The circumstances leading up to the stabbing are under investigation.
There are no arrests at this time.
A description of the suspect was not immediately available.
Anyone who may have witnessed the stabbing is urged to call CrimeStoppers at 955-8300.


Business Research: A Cheat Sheet
By Dr. Janaka Low
This guide is applicable to both master and doctoral students. Please bear in mind that there are significant differences between master and doctoral research. In addition to higher expectation on rigor in design and analysis, doctoral research requires significant theoretical contributions to the field of study.
In the following section, I will go through a typical research report structure. To make the cheat sheet more useful, I have included (i) frequently asked questions (FAQ) you will face during viva sessions, and (ii) a checklist at the end of each chapter.
In the last section, I will give general advice on managing the research project. These pieces of advice are quite important. Most students who fail to complete their research was due to the problems mention in this section. Note that this guide is biased toward quantitative methods due to my limited experience in qualitative and mixed-mode research. Also, the guide mainly deals with academic research rather than the industry research.
Most higher learning institutions require the students to structure their thesis/report into a 5-6 chapter write up. Typically, 5-chapter structure will include (1) Introduction, (2) Literature review, (3) Methodology, (4) Analysis and results, (5) Discussion and Conclusion. 6-chapter structure usually has a dedicated chapter on the research theoretical framework after literature review, resulting in (1) Introduction, (2) Literature review, (3) Theoretical framework, (4) Methodology, (5) Analysis and Results, (6) Discussion and Conclusion. In Europe, it is common to see literature review and analysis expend to multiple chapters.
Do not start or end your chapter abruptly. Each chapter should start with an introductory paragraph. Usually it will mention what the chapter is about. Each chapter should end with a concluding paragraph. Usually it summarizes what you said in the chapter. Similarly do this for every major section in your thesis or report. For sections that are closely linked with the subsequent sections, write a leading sentence to prepare or lead your reader for the following sections.
The following sections describe what you should (and should not) write in each chapter.
The introduction chapter should include the background of the issue or problem in which your research is conducted. In this chapter, you will need to state your research gap clearly.
Gaps are “holes” in the knowledge, which you are trying to patch. We find gaps when an issue is not addressed in the literature (perhaps due to new development in the business environment such as the advancement of social media), or when there is inconsistency between a number of studies, or when there is an unresolved issue in the literature.
Gaps are usually expressed in the research problem statement. It can be a national problem (e.g.., competitiveness of a country), a company problem (e.g.., your company is facing sales problem), an industry problem (e.g.., the hospitality industry is facing a problem), a business function problem (e.g.., the operation of your company is inefficient), a theoretical problem (e.g.., a theory proposed by the previous research is not generalizable), or a methodology problem (e.g.., a research method used in a previous research was inappropriate). Problem statement should include: (i) what you know, (ii) what you don’t know, and (iii) what you want to know.
After explaining the background situation, you bring out the need to perform further research in a specific area. This will be your research objectives.
Once you have the research objectives, you list down all your questions that your research will attempt to answer. This will be your research questions.
Following this, you should emphasize the possible significance of your research. Your research significance should answer these few questions:
You will need to be explicit in your unit of analysis. If you are analyzing companies, your unit of analysis will be at the company level. If you are researching individual employee or consumer, then your unit of analysis will be at the individual level.
Be very careful about your ability to collect enough data from companies.
Viva FAQ
Start your literature review on the broadest concept. Then gradually narrow down to specific concept.
For example, if you are researching about marketing control, start with the review of the broad concept of “control” and “marketing”. Then explain how other authors gradually focus on the issue of marketing control.
Another example, let’s say you are using observational learning theory to frame your research, you should start with introduction to learning theories, then down to external learning approach, then down to environment-driven learning, then only you go to observational learning theory. See figure below.
In many universities, you are required
to use “underlying” or “underpinning”, or “parent” theories to support your
hypotheses or framework. This requirement has been a major trauma for many
students whom I have worked with. This is simply because in the academic world,
everything has to be supported by “theories”.
Most of the management and business concepts have their roots on basic philosophical theories. As business and management are closely related to economic theories, many theories have their root in economics.
The "Encyclopedia of Management Theory" (http://goo.gl/qU2Nn2) gives us a list of management theories. Alternatively, you can get the eBook from Google Play Book Store (see http://goo.gl/35eo51) and read it on your smart devices.
Theories can also be called “model”, “principle”, or sometimes just the name itself, e.g., “hierarchy of needs”.
Accounting researcher may benefit from accounting theories (See http://highered.mcgraw-hill.com/sites/dl/free/0070277265/695504/DeeganFAT_3e_Chapter_01.pdf).
Organization theories can be used for management and HR research (See http://www.academy-british.co.uk/Library-eng/organizational-theory.pdf, p. 12.)
You can use a variety of expression to accurately describe the authors’ positions. For example:
Avoid vague and weak expression such as “Kotler stated that…”, or “Kotler mentioned that …”. A better choice of verb includes the following: assert, emphasize, posit, argue, maintain, suggest, propose, point out, claim and consider. You can also use these verbs to indicate that an author has made certain findings: confirm, report, conclude, identify, found, reveal, demonstrate, and discover.
For the field of business and management, ideally you should have 40% of your literature taken from recent publications, i.e., within the past 5 years.
Based on what you want to do (research objectives) and literature reviews, you should have decided what you want to prove.
Usually you want to show that different concepts are related (correlated with each other, one variable causes another, some are grouped together) and you can draw your theoretical framework.
All key concepts in your research must be measurable. When a concept is measured on a scale, it is referred to as variable. When a concept is measured with several scale items, it is referred to as a construct.
Hypotheses should be phrased clearly and it must be testable.
The most common forms of the theoretical framework diagrams have the independent variables (IV) on the left and dependent variables (DV) on the right.
Note that this is a very simplistic framework. You may have moderating variable (MV) in between:
It is important to understand that moderating variables weaken, amplify or even reverse effects of IV on DV. MV does not directly affect DV. For example, we suspect that psychotherapy may reduce depression – more for men than for women; we would say that gender (MV) moderates the relationship between psychotherapy (IV) and depression (DV).
In some cases, you may have intervening (IVV) variables: Intervening variables are also known as mediating variables.
Also, you should specify all your hypotheses in this chapter.
In this chapter, you should discuss about your methodologies.
Here you can also review literature, but only on their methodologies. You can borrow survey questions from other authors which are established in their fields.
In this chapter, you present the overview of the data collected. Indicate if your data collection efforts is successful. You should also present a table showing the profile of the respondents.
Then you can show a descriptive statistics table with at least mean and standard deviation values for each variable you measured.
A correlation matrix is a useful way to show whether there are correlations between your variables. So include it.
You should at least perform reliability tests to the data. Typically, this is done with Cronbach alpha analysis. Drop the items that contribute to low reliability statistic.
You should perform factor analysis on variables to summarize them.
Then you proceed to test all your hypotheses.
In this chapter, you summarize the findings of your research, offer possible explanations of the results, discuss the theoretical and managerial implications, and mention about the limitations of the research. You should also include suggestion for future research, usually based on the limitation of the research, or new ideas that you have that do not fit into the current research.
You can use the following check list to ensure that you meet the requirements of the research report.
Overall Check list
Abstract can be overlooked easily by many students and it is often written haphazardly without much thought. A good abstract should include the following elements: (i) Purpose, (ii) Design / methodology / approach, (iii) Findings, (iv) Research limitations / implications, and (v) originality/value of the research. For example, here is an appropriate abstract:
The primary purpose of this paper is to examine empirically the significant determinant for supply chain partnering (SCP) that can be applied by the firms to increase their effectiveness in SCP efforts. Next, the paper intends to examine the impact of scalable partnering towards the effectiveness of SCP. To address the research problem, a survey instrument is developed and a structured model is hypothesized and tested using SPSS tool. Data are collected from a field research on a sample of 584 companies in Malaysia. The result of this research indicates that resource sharing has positive influences on SCP. Increasing scalable partnering would also lead to increases in the effectiveness of SCP. One of the limitations of the study is that the use of a single key informant for the data collection from the respective companies. A more stringent test of the relationships between scalable partnering and its impact in SCP requires a longitudinal study. Managers must also recognize the influential role of scalable partnering which motivates channel partners to continue their investment in SCM initiatives. Thus, managers should pay more attention to the need of channel member to generate a higher level of confidence in scalable partnering. While SCP and its determinant exist in prior research, this paper contributes a new variable “Scalable Partnering” towards strengthening the relationship among the supply chain partners.
Dissecting the abstract, we see the 5 elements:
Like any other projects, your research must be carefully planned and put in the necessary commitments and resources.
Here are some tips:
Generally, there are 3 considerations: (a) choose an area that you are familiar with; (b) you must be able to collect data; (c) you have passion in the chosen area.
Being familiar with a topic is very important especially when you are defending your proposal or findings. You will face both broad and in-depth questions during your defense session. Your examiners can quickly form a negative opinion about you if your answers as superficial.
Ability to collect data is crucial. Without data, you will not be able to proceed with your research beyond proposal.
Your passion in the chosen research area is important because you need the drive and motivation to complete the often long and arduous research journey. In addition, the examiners will feel positive about you if you speak passionately about your research during your defense. Generally, examiners despise candidates who don’t take interest in his or her research topic.
The biggest and most frequent mistake students make is underestimating the time required to conduct and complete the research.
The very fact that it is a "re"search implies that you will need several rounds of trials and errors. As much as we would like it to be structured, its nature is unstructured, ambiguous, unpredictable and full of surprises. As such, you should give yourself plenty of buffer time.
If you are part-time students, prepare to take some leaves from your work during the initial period of your research. Give yourself enough time to immerse yourself in the research topic.
Imagine if you need 30 minutes to boil a kettle of water, 10 minutes of boiling distributed over 3 days won’t do it. You must boil it in one go.
Working on research means working at the edge of human knowledge. In that place, you do not find a lot of agreements among the people living there. Not only experts disagree with the concepts and theories, they also have strong disagreement in styles and approaches. One university can place high importance on quantitative method while another university has distaste on number crunching. In other words, there are different “research culture” in different research institutions. Be mindful of the acceptable boundary of your “stakeholders” – your supervisor, your university and your potential examiners.
There are two reasons for this. First, you want to be able to get familiar with the concepts used in the field so that you can understand the literature and discuss with your supervisor intelligently. Secondly, you want to avoid making conceptual mistakes. A term used commonly in daily conversation can have very different meaning in research. In research, you should avoid using terms in a very general sense, especially the concepts related to the key variables in your research. For example, the term “impact” is used in our daily language, but need to be defined very specifically in your research.
There are two ways to get you up to speed quickly: talk to people and read others’ works.
Talking to people does not mean talking to anyone. There are specific techniques you can use. Start with purposeful interview with the leading experts in the field, and conduct focus groups if your research involves practical issues. Since most business research projects are not basic research projects, you can almost be certain that you will benefit from a focus group.
Reading others’ work is not as obvious as you think. You may be tempted to start reading the world leading journal in the field. However, you will miss a lot of points for skipping the past research done at your very own university. Remember that the research papers done locally are the ones that fulfill the acceptable boundaries. Reading them get you to have realistic plan early.
Unless this is your 10th research project, your main objective in the project should be just learning the research methods and acquiring the research skills.
Too often novice researchers are expecting their first research to solve their real world problems. While it is true that your interest in solving certain problem leads you to taking up the master or doctoral degree, do not expect your research to solve your real problem. If it eventually does solve the problem, cool, otherwise, it is perfectly okay. Remember your research project has enough burdens to meet many requirements – especially those set by your institution. Do not impose further requirements on it, or you risk killing it.  Leave it for another day.
Research should be done by matured individuals. That is why research is only done by master and doctorate level students.
Most supervisors expect you to take the driver seat.  No babysitting, no spoon feeding.
Matured students take initiatives and take ownership of the research efforts. Some compassionate supervisors will try their best to help you. Even so, they can quickly get dishearten if you are not interested to help yourself.
The easiest way to help yourself is to quickly set up the rhythm of your meeting with the supervisor. Once the project has started, make a point to meet your supervisor regularly. Fortnightly or monthly is appropriate. If you do not contact your supervisor several months in a row, you risk your supervisor losing interest in helping you.
Regularly meeting your supervisor also gives yourself extra push to complete the work. Use the meeting as mini-checkpoints, which force you to show your supervisor some progress.
I use the term “rhythm” intentionally. Think of it as your heart beat.
You may be tech-savvy. But you cannot change the human behavior. It is tempting for part-time students to rely on emails to communicate with their supervisors. That can be a big mistake! I have seen many students failed or nearly failed because of their refusal to meet face-to-face.
When you meet your supervisor, a lot more things are going on than just exchange of information and facts. There are body language and other non-verbal communications going on. More importantly, your supervisor may need to get across many emotional messages that cannot be embedded in words inside emails. It is not because your supervisor is unable to express them in typed words. He or she simply does not want to communicate it through formal “black and white” channel. Strong emotions, such as being pleased with your progress or frustrated with your failures, will never be written in emails. Just imagine, who is willing to have a conversation with you if he or she knows that you have turned on a voice recorder? These emotional clues are extremely important messages that the supervisors would want you to receive.
The best is still having face-to-face meeting. Otherwise, try Skype or Google Hangout. If that still is not possible, make phone calls. Use email only as the last resort for discussion. Email should only be used for completed works for review.
It is very important for you to have a positive and professional relationship with your supervisor. Here are some useful principles:
The key to defending your research is to prepare yourself for challenges from your supervisor or examiners. You should proactively justify everything:
I still see student typing out the table of contents by hand. You should spend some time learning the critical skills on these features:
Generally, you should not exceed 20% similarity. You should check with your institution the expected threshold.
Doing a research is not simple and requires detailed planning and execution. You should understand the requirements and the rule of the game clearly as early as possible. Commit time, learn quickly, set up work rhythm and communicate face-to-face with your supervisor often.
P/S: I wish you all the best in your research. If you have questions or comments, please email to<EMAIL_ADDRESS>This document is not meant to be a comprehensive guide. It focuses on practical issues and provides quick answers and solutions to common problems faced by postgraduate level business students. As research methods can be highly controversial, the author does not wish to get into debates on the approach suggested in this document.


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kgp.tree
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So today I am gonna tell you about how to compile and run Faster R-CNN on Ubuntu in CPU Mode.
In my previous posts, I have done a project Real-time Object Recognition (you can find it here: Real-time Object Recognition). The result received was pretty good, but as you might notice, that it got a problem (a big problem). The problem is that the trained Model could recognize one object per frame. So if I want it to recognize two or more objects (and even tell me where each of them locates), it will raise the white flag!
So it came to my next mission that I have to find a way to deal with Object Detection. Of course I knew some of them before, but what I wanted is something which applied Convolutional Neural Network. Among some great papers people had done out there, I chose Faster R-CNN.
In today’s post, I have no intention to talk about how Faster R-CNN works. I just leave it for a future post, when I finish my task. Today I am just going to talk about how to compile and run Faster R-CNN on Ubuntu - in CPU Mode. And if you ever wonder why I am doing this post although I can find a great deal of tutorials on the net, the answer is: just like Caffe in CPU Mode, compiling Faster R-CNN was hard like hell too!
Faster R-CNN was originally implemented in MATLAB, but they also provided a Python reimplementation code (phew!). So let’s grab it from GitHub:
Just make sure that you didn’t forget the –recursive flag. After the download completes, jump to the lib folder:
Here we are compiling Faster R-CNN for CPU Mode, so we have to make several changes. Let me guide you through this tough guy. First, let’ open the setup.py file, then comment out all the lines below:
From this:
To this:
After saving the file, now we can compile the lib folder. Let’s execute the command below:
You should now go through without any error. If some error still occurs, make sure that you didn’t miss any line above. Next, we will compile caffe and pycaffe. You may remember that I made a post about how to install caffe on Ubuntu in CPU Mode, so why don’t we just use the results we got, instead of doing the same thing over again? Well, that is because they had made some changes to the caffe original codes (implementing some necessary classes, methods, …), we have to compile a new set in order to run their codes. But don’t worry, there are things which we can re-use. I will tell you below. Now let’s jump to the caffe-fast-rcnn folder:
Similar to what we did with caffe before, this time we are likely to make some change to the Makefile files. But actually, they are just files which tell the compile how to compile things (like where to look for include files, library files, etc), so we can re-use our old Makefile which we have already modified. In case you haven’t had a look at my old post yet, you can find it here: Installing Caffe on Ubuntu.
So what we are gonna do is going to where we placed caffe, copy the Makefile and Makefile.config files, and paste them into the caffe-fast-rcnn folder.
But even after we did that, there is still one tiny change we have to make, let’s open the Makefile.config file, uncomment the line below:
From this:
To this
And we have done. Now go ahead and make it:
This time should run smoothly too. Congratulations, you have successfully compiled caffe for Faster R-CNN.
It seems like we have just made some tiny changes up to now. But don’t be complacent too soon, although we have sucessfully compiled caffe for Faster R-CNN, we still cannot run their demo code now. There are some other places we have to modify too.
The command above will download the pre-trained model in order to run the demo code. After the download finishes, let’s apply the changes below:
File: lib/fast_rcnn/nms_wrapper.py, from this:
To this:
File: lib/fast_rcnn/config.py, from this:
To this:
That is it. We should now be able to run the demo project now. So let’s do it:
Note that you must provide the –cpu flag to tell it to run in CPU Mode. It will take a while to run, because it will process all images before outputting the results (in my case it took approximately 22s per image). The output should look like this:
So, I have shown you how to compile and run the demo code of Faster R-CNN. It was not so hard especially if you experienced the caffe installation before. I will be glad if you find this post helpful. And even if you followed all the instructions above but you still couldn’t make it through the frustrating errors, don’t hesitate to leave me a comment below, I will help you as soon as possible, I promise!
And as I promised above, I will do some posts related to my current work using Faster R-CNN, and I will tell you more about Faster R-CNN too. So stay tuned! I’ll be back.
Reference:
Faster R-CNN GitHub page: https://github.com/rbgirshick/py-faster-rcnn


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If they accept the proposal, the points will be allocated as you proposed.
If the reject the proposal, neither you nor your partner will receive any points.


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QuantLib: a free/open-source library for quantitative finance
Fully annotated sources - version 1.30
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#include <ql/models/marketmodels/products/pathwise/pathwiseproductcaplet.hpp>
Public Member Functions | |
| MarketModelPathwiseMultiDeflatedCaplet (const std::vector< Time > &rateTimes, const std::vector< Real > &accruals, const std::vector< Time > &paymentTimes, const std::vector< Rate > &strikes) | |
| MarketModelPathwiseMultiDeflatedCaplet (const std::vector< Time > &rateTimes, const std::vector< Real > &accruals, const std::vector< Time > &paymentTimes, Rate strike) | |
| ~MarketModelPathwiseMultiDeflatedCaplet () override=default | |
| std::vector< Size > | suggestedNumeraires () const override |
| const EvolutionDescription & | evolution () const override |
| std::vector< Time > | possibleCashFlowTimes () const override |
| Size | numberOfProducts () const override |
| Size | maxNumberOfCashFlowsPerProductPerStep () const override |
| bool | alreadyDeflated () const override |
| void | reset () override |
| during simulation put product at start of path More... | |
| bool | nextTimeStep (const CurveState ¤tState, std::vector< Size > &numberCashFlowsThisStep, std::vector< std::vector< MarketModelPathwiseMultiProduct::CashFlow > > &cashFlowsGenerated) override |
| return value indicates whether path is finished, TRUE means done More... | |
| std::unique_ptr< MarketModelPathwiseMultiProduct > | clone () const override |
| returns a newly-allocated copy of itself More... | |
| Public Member Functions inherited from MarketModelPathwiseMultiProduct | |
| virtual | ~MarketModelPathwiseMultiProduct ()=default |
| virtual std::vector< Size > | suggestedNumeraires () const =0 |
| virtual const EvolutionDescription & | evolution () const =0 |
| virtual std::vector< Time > | possibleCashFlowTimes () const =0 |
| virtual Size | numberOfProducts () const =0 |
| virtual Size | maxNumberOfCashFlowsPerProductPerStep () const =0 |
| virtual bool | alreadyDeflated () const =0 |
| virtual void | reset ()=0 |
| during simulation put product at start of path More... | |
| virtual bool | nextTimeStep (const CurveState ¤tState, std::vector< Size > &numberCashFlowsThisStep, std::vector< std::vector< MarketModelPathwiseMultiProduct::CashFlow > > &cashFlowsGenerated)=0 |
| return value indicates whether path is finished, TRUE means done More... | |
| virtual std::unique_ptr< MarketModelPathwiseMultiProduct > | clone () const =0 |
| returns a newly-allocated copy of itself More... | |
Private Attributes | |
| std::vector< Real > | rateTimes_ |
| std::vector< Real > | accruals_ |
| std::vector< Time > | paymentTimes_ |
| std::vector< Rate > | strikes_ |
| Size | numberRates_ |
| Size | currentIndex_ |
| EvolutionDescription | evolution_ |
Definition at line 91 of file pathwiseproductcaplet.hpp.
| MarketModelPathwiseMultiDeflatedCaplet | ( | const std::vector< Time > & | rateTimes, |
| const std::vector< Real > & | accruals, | ||
| const std::vector< Time > & | paymentTimes, | ||
| const std::vector< Rate > & | strikes | ||
| ) |
| MarketModelPathwiseMultiDeflatedCaplet | ( | const std::vector< Time > & | rateTimes, |
| const std::vector< Real > & | accruals, | ||
| const std::vector< Time > & | paymentTimes, | ||
| Rate | strike | ||
| ) |
|
overridedefault |
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overridevirtual |
Implements MarketModelPathwiseMultiProduct.
Definition at line 247 of file pathwiseproductcaplet.cpp.
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overridevirtual |
Implements MarketModelPathwiseMultiProduct.
Definition at line 256 of file pathwiseproductcaplet.cpp.
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overridevirtual |
Implements MarketModelPathwiseMultiProduct.
Definition at line 261 of file pathwiseproductcaplet.cpp.
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overridevirtual |
Implements MarketModelPathwiseMultiProduct.
Definition at line 266 of file pathwiseproductcaplet.cpp.
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overridevirtual |
Implements MarketModelPathwiseMultiProduct.
Definition at line 271 of file pathwiseproductcaplet.cpp.
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overridevirtual |
Implements MarketModelPathwiseMultiProduct.
Definition at line 138 of file pathwiseproductcaplet.cpp.
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overridevirtual |
during simulation put product at start of path
Implements MarketModelPathwiseMultiProduct.
Definition at line 277 of file pathwiseproductcaplet.cpp.
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overridevirtual |
return value indicates whether path is finished, TRUE means done
Implements MarketModelPathwiseMultiProduct.
Definition at line 209 of file pathwiseproductcaplet.cpp.
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overridevirtual |
returns a newly-allocated copy of itself
Implements MarketModelPathwiseMultiProduct.
Definition at line 242 of file pathwiseproductcaplet.cpp.
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private |
Definition at line 132 of file pathwiseproductcaplet.hpp.
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private |
Definition at line 133 of file pathwiseproductcaplet.hpp.
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private |
Definition at line 134 of file pathwiseproductcaplet.hpp.
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private |
Definition at line 135 of file pathwiseproductcaplet.hpp.
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private |
Definition at line 136 of file pathwiseproductcaplet.hpp.
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private |
Definition at line 138 of file pathwiseproductcaplet.hpp.
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private |
Definition at line 140 of file pathwiseproductcaplet.hpp.


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