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Introduction to CircuitML: Modeling Local Processing Units in the Drosophila Brain

Introduction to CircuitML: Modeling Local Processing Units i...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Chevitarese, Daniel Salles Szwarcman, Dilza Vellasco, Madey IBM Res Brazil Rio De Janeiro Brazil UEZO Dept Comp Sci Rio De Janeiro Brazil Pontificia Univ Catolica Rio de Janeiro Dept Elect Engn Rio De Janeiro Brazil

ISBN: (纸本)9781479919598

The brain of the fruit fly Drosophila Melanogaster is an attractive system for studying the logic underlying neural circuits because it implements a rich behavior repertoire with a number of neural components that is five orders of magnitude smaller than that of vertebrates. Analysis of the fly's connectome using a powerful toolkit of well-developed genetic techniques and advanced electrophysiological recording tools enables the fly's neural circuitry to be experimentally mapped into functional units, called Local Processing Units (LPU). Many tools are already available to enable neuroscientists to create an accurate model of the entire fly brain, but none of them provides a method to specify those circuits in a way that both biologists and engineers can work together. Also, the development of plausible LPU models requires the ability to specify and instantiate subcircuits without explicit reference to their constituent neurons and internal connections. To this end, we present a neural circuit specification language called CircuitML for construction of LPUs. CircuitML has been designed as an extension to NeuroML;it provides constructs for defining subcircuits that comprise neural primitives supported by NeuroML. Subcircuits are endowed with interface ports that enable connections to other subcircuits via neural connectivity patterns. We have used CircuitML to specify an LPU-based model of the fly olfactory system.

关键词： Drosophila melanogaster simulation models XML python language CUDA

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AHP -Entropy Method Credit Risk Assessment Based on python

AHP -Entropy Method Credit Risk Assessment Based on Python

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Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS)

作者： Wang, Ruoyu Harbin Inst Technol Weihai Sch Informat Sci & Engn Weihai Peoples R China

ISBN: (纸本)9781728176499

In order to improve the ability of credit risk control, AHP- Entropy method is adopted to establish the credit risk assessment digital analysis system based on python computer program. The system has 3 levels and evaluates 18 credit risk indicators. Combined with the characteristics of the enterprise, this paper analyzes 99 small, medium and micro enterprises with relatively small scale and lack of mortgage assets. The research shows that the AHP- Entropy method credit risk assessment digital system based on python is concise and objective, which reflects the credit risk of various enterprises more accurately, and is worthy of further promotion and application.

关键词： python language AHP-Entropy method Risk assessment Example analysis

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ANDES: A python-Based Cyber-Physical Power System Simulation Tool

ANDES: A Python-Based Cyber-Physical Power System Simulation...

引用

North American Power Symposium (NAPS)

作者： Cui, Hantao Li, Fangxing Univ Tennessee Dept Elect Engn & Comp Sci Knoxville TN 37996 USA

ISBN: (纸本)9781538671382

This paper introduces the design and implementation of a python-based software package for cyber-physical power system research called Andes. Andes is developed in an attempt to bridge the gap between the traditional power system analysis and the fast-growing needs for cybersecurity studies. First, the architecture design is proposed to accommodate for power grid prototyping, communication network set up, and the interactions between the two. Design considerations are discussed from the research and development perspective. Examples are shown using Andes for modeling, monitoring, and visualization of cyber-physical power system studies.

关键词： Cyber-physical system computer simulation python language software-defined network (SDN)

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Research on the design of a data processing-based buzzword mining system for the times 7

Research on the design of a data processing-based buzzword m...

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7th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO)

作者： Wang, Mingxin Liaoning Normal Univ Sch Comp & Informat Technol Dalian Peoples R China

ISBN: (纸本)9781665433860

In today's constantly iterating online world, a large amount of information appears in spurts, causing certain difficulties for social governance. In this paper, we establish a big data monitoring system, use web crawler technology to obtain data and then use python language to analyze data to obtain reference models and various correlation variables and indicator data to help the government monitor online public opinion. Specifically, this paper combines cloud word graphs and data visualization techniques to analyze comments on hot topics on Weibo, extracting keywords from the text more intuitively and accurately, and then analyzing the sentiment direction of keywords, which can quickly predict the public's opinions, views and social values on a certain topic.

关键词： Data processing social governance python language LDA model crawler technology

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Automatic Parallelization of python Programs for Distributed Heterogeneous Computing 28th

Automatic Parallelization of Python Programs for Distributed...

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28th International Conference on Parallel and Distributed Computing (Euro-Par)

作者： Shirako, Jun Hayashi, Akihiro Paul, Sri Raj Tumanov, Alexey Sarkar, Vivek Georgia Inst Technol Atlanta GA 30332 USA Intel Corp Austin TX 78746 USA

ISBN: (纸本)9783031125973;9783031125966

This paper introduces a new approach to automatic ahead-of-time (AOT) parallelization and optimization of sequential python programs for execution on distributed heterogeneous platforms. Our approach enables AOT source-to-source transformation of python programs, driven by the inclusion of type hints for function parameters and return values. These hints can be supplied by the programmer or obtained by dynamic profiler tools;multi-version code generation guarantees the correctness of our AOT transformation in all cases. Our compilation framework performs automatic parallelization and sophisticated high-level code optimizations for the target distributed heterogeneous hardware platform. It introduces novel extensions to the polyhedral compilation framework that unify user-written loops and implicit loops present in matrix/tensor operators, as well as automated selection of CPU vs. GPU code variants. Finally, output parallelized code generated by our approach is deployed using the Ray runtime for scheduling distributed tasks across multiple heterogeneous nodes in a cluster, thereby enabling both intra-node and inter-node parallelism. Our empirical evaluation shows significant performance improvements relative to sequential python in both single-node and multi-node experiments, with a performance improvement of over 20,000x when using 24 nodes and 144 GPUs in the OLCF Summit supercomputer for the Space-Time Adaptive Processing (STAP) radar application.

关键词： Parallelizing compilers python language Parallel computing Heterogeneous computing Distributed computing

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Using python and Julia for efficient implementation of natural computing and complexity related algorithms 20

Using Python and Julia for efficient implementation of natur...

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20th International Conference on System Controls and Computer Science 2015

作者： Dogaru, Ioana Dogaru, Radu Univ Politehn Bucuresti Nat Comp Lab Appl Elect & Informat Engn Bucharest Romania

ISBN: (纸本)9781479917808

Computational efficiency and several other criteria are investigated from the perspective of using python and Julia languages when used in natural computing and complexity related algorithms. While such algorithms often require high computational power, portability and easiness of implementing various algorithms, it is important to identify freely available platforms for high performance, high portability and high productivity (HP3). Using several examples, we conclude that python is a very good choice for researchers already fluent in either Matlab/Octave environments, while Julia, a newcomer with similar features to python but less package offer the promise of better speed.

关键词： high performance computing computational modeling fractals python language Julia language

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Issues in the Software Implementation of Stochastic Numerical Runge-Kutta 21st

Issues in the Software Implementation of Stochastic Numerica...

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21st International Conference on Distributed and Computer and Communication Networks (DCCN)

作者： Gevorkyan, Migran N. Demidova, Anastasiya V. Korolkova, Anna V. Kulyabov, Dmitry S. RUDN Univ Peoples Friendship Univ Russia Dept Appl Probabil & Informat 6 Miklukho Maklaya Str Moscow 117198 Russia Joint Inst Nucl Res Lab Informat Technol 6 Joliot Curie Dubna 141980 Moscow Region Russia

ISBN: (纸本)9783319994475;9783319994468

This paper discusses the application of stochastic Runge-Kutta-like numerical methods with weak and strong convergences for systems of stochastic differential equations in Ito form. At the beginning a brief overview of available publications about stochastic numerical methods and information from the theory of stochastic differential equations are given. Then the difficulties that arise when trying to implement stochastic numerical methods and motivate to use source code generation are described. We discuss some implementation details, such as program languages (python, Julia) and libraries (Jinja2, Numpy). Also the link to the repository with source code is provided in the article.

关键词： Stochastic differential equations Stochastic numerical methods Automatic code generation python language Julia language Template engine

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Real-Time Image Segmentation and Object Tracking for Autonomous Vehicles 3

Real-Time Image Segmentation and Object Tracking for Autonom...

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International Conference on Advances in Computing, Communication and Applied Informatics (ACCAI)

作者： Priya, S. Kumar, Sanduru Sanath Lavanya, P. Sadik, Shaik Kumar, Ata. Kishore Mohan Babu Univ Dept ECE Erstwhile Sree Vidyanikethan Engn Coll Tirupati Andhra Pradesh India Mohan Babu Univ Sch Engn Dept ECE Erstwhile Sree Vidyanikethan Engn Coll Tirupati Andhra Pradesh India

ISBN: (纸本)9798350389432;9798350389449;9798350389456

Autonomous vehicles rely on advanced perception systems to navigate dynamically changing environments. This research aims to develop a real- time image segmentation and object tracking system, leveraging deep learning techniques, to enhance the perceptual capabilities of autonomous vehicles. Thanks to developments in sensing, machine learning, and artificial intelligence, autonomous cars are getting closer to reality. Vehicle detection is one of the most important parts of autonomous driving systems, and it's critical to the effectiveness and safety of these systems. The main intention of this research is to enquire how autonomous vehicles employ the cutting- edge YOLOv8 (You Only Look Once version 8) algorithm for vehicle recognition. A real-time object detection model called YOLOv8 has demonstrated remarkable results in identifying and categorising items in pictures and videos. It is the most recent model in the YOLO series and is renowned for striking a balance between accuracy and speed of detection.

关键词： python language Open CV ANACONDA PyCharm Pytorch Accuracy R-CNN Cutting-edge YOLO v8 algorithm Precision Recall F1-Score

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ROBO - Autonomous Football Robot

ROBO - Autonomous Football Robot

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International Conference on Computational Intelligence and Knowledge Economy (ICCIKE)

作者： Alalouni, Ahmed Alghamdi, Ayad Zikria, Mohamed Alzubaidi, Loay Saudi Aramco Oil Co EXPEC Adv Res Ctr Dhahran Saudi Arabia Saudi Aramco Total Refining & Petrochem Co SATORP Dept Informat Commun Technol Jubail Ind City Saudi Arabia Prince Muhammad bin Fahd Univ Dept Comp Engn & Sci Khobar Saudi Arabia

ISBN: (纸本)9781728137780

The autonomous football robot (ROBO) was designed to enhance the knowledge in the field of robotics and computer vision through the robot development. The goal was to learn the use of robotic kits, the Raspberry Pi micro-controller to control the robot motion, the Raspbian operating system (Linux based OS), the python programming language and the computer vision library (OpenCV). The robot design consists of hardware and software designs. For the robot hardware design and implementation, the robotic kit were built, tested, and attached to a 3D custom printing gripper and kicker along with the 180 degrees rotational Raspberry Pi camera by servo motor. Lastly, a small breadboard was attached to set up the pulse, voltage, and the ground for the servo motors. For the robot software design, there are two algorithms or modes in the program, ball mode and goal mode. The ball mode start with ball detection and end with the ball grab. The goal mode start with the goal search and end with kick the ball into the goal. A 150 experiments done for three different configuration of the robot. Each configuration consists of 50 experiments. The results were 2% task error for the first configuration, 10% for the second, and 22% for the third. The task errors were because of the mechanical failure of the kicker. The kicker was unable to reach the ball into the goal from far distance. A future work can be a better kicker with more power.

关键词： mobile robotics computer vision object recognition OpenCV library python language

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A Distributed Approach for Mining Moroccan Hashtags using Twitter Platform 19

A Distributed Approach for Mining Moroccan Hashtags using Tw...

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2nd International Conference on Networking, Information Systems and Security (NISS)

作者： El Abdouli, Abdeljalil Hassouni, Larbi Anoun, Houda Hassan II Univ Casablanca Ecole Super Technol CED Engn Sci RITM Lab Casablanca Morocco

ISBN: (纸本)9781450366458

Twitter is a social networking service, on which users can share thoughts and interact with events. In this paper, the authors propose a distributed approach to combine the multilingualism analysis of hashtags generated by Moroccan users in the social network Twitter, to discover and understand the hot subjects that attract the community. The analysis of Moroccan twitter hashtags is a challenge for two main reasons. Firstly, since the Moroccan society is characterized by linguistic diversity, hashtags are expressed in several languages. Secondly, the hashtags of Moroccan users may include spelling errors and abbreviations and do not contain delimiters between words, which leads to misinterpretation. In this paper, we propose a distributed approach using Apache Hadoop Framework and Natural language Processing Techniques for processing and mining Moroccan hashtags by a program we developed using open source libraries. The result is a clean corpus, which is stored in Apache Hive to allow applying analytic queries. Finally, we apply K-means algorithm to cluster all hashtags into general topics, and then plot them on the Moroccan map to specify their sources of publication by using the coordinates extracted from the tweets.

关键词： Twitter Multilingualism Analysis Hashtags Distributed Approach Apache Hadoop Framework Natural language Processing python language Apache Hive k-means Algorithm General Topics Moroccan Map

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