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An experimental platform to characterize software comprehension activities supported by visualization

An experimental platform to characterize software comprehens...

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International conference on Software Engineering - Companion, ICSE, Companion

作者： Glauco de F. Carneiro Manoel Mendonca Rodrigo Magnavita Federal University of Bahia (UFBA) Brazil Salvador University Brazil Salvador University (UNIFACS) Brazil

Software visualization has been pointed out as one of the solutions to overcome challenges that programmers face in understanding unfamiliar source code. Our work proposes an extensible multi-view software visualization infrastructure implemented as an Eclipse plug-in called SourceMiner. It allows programmers to perform tasks supported by visualization interfaces provided by the IDE. A querying view is integrated into the tool, allowing for the dynamic filtering of the modules rendered into the visualization interfaces. The whole infrastructure is conceived as an experimental platform. All actions performed by the programmer are captured in a log file. This facilitates the analysis of the IDE usage while programmers are performing specific software engineering tasks.

关键词： Programming profession Packaging Data visualization Rendering (computer graphics) Tree graphs Information filtering Information filters Information analysis Performance analysis Software engineering

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Malicious Apps May Explore a Smartphone's Vulnerability to Detect One’s Activities

Malicious Apps May Explore a Smartphone's Vulnerability to D...

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International conference on Advanced Information Networking and Applications (AINA)

作者： Xi Lu Shou-Hsuan stephen Huang Department of Computer Science University of Houston Houston USA

ISBN: (纸本)9781509060306

In order to make apps functional, mobile operating systems, such as Android, allow applications to access some system data without asking for user permission. We demonstrate that by analyzing these system data and some side channel information, it is possible to gain insight into a smartphone user's behavior, thus putting their privacy at risk. With these real-time privacy information collected, a malicious attacker may launch spear fishing attacks with much higher yield rates. In this paper, we study a combination of power consumption, network traffic, and memory usage of several commonly used activities, and demonstrated that it is possible to classify a user's smartphone activities into one of six classes. We designed several experiments to test the classification which resulted in high success rates. We also present the possibility of detecting transitions of smartphone activities.

关键词： Internet Smart phones Monitoring Music Games Power demand graphics

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FGYM: Toolkit for Benchmarking FPGA based Reinforcement Learning Algorithms

FGYM: Toolkit for Benchmarking FPGA based Reinforcement Lear...

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International conference on Field Programmable Logic and Applications

作者： Nathaniel Peura Yuan Meng Sanmukh Kuppannagari Viktor Prasanna School of Electrical and Computer Engineering University of Southern California

FPGA-based heterogeneous computing platforms are promising candidates to enable fast training of Reinforcement Learning (RL) agents. Typically, an RL agent for an environment is trained via interactions with a software that simulates the environment. While several toolkits exist to quickly deploy RL training on CPU or GPU, there lacks a similar toolkit for FPGAs. To ease the deployment process of RL using FPGAs, we demonstrate FGYM (FPGA-GYM) - a toolkit that generates an end-to-end interface between the simulation environments running on the CPU and agents running on the FPGA. FGYM supports a variety of environments and automatically generates the memory interface using PCIe. FGYM supports multiple levels of parallelism including vectorized agent-environment interactions and memory port aggregation. It also provides profiling results for users to identify the execution bottlenecks.

关键词： Training Ports (computers) graphics processing units Reinforcement learning Parallel processing Benchmark testing Software

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Computing Nash equilibria in bimatrix games: GPU-based parallel support enumeration

Computing Nash equilibria in bimatrix games: GPU-based paral...

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IEEE International conference on Performance, Computing and Communications (IPCCC)

作者： Safraz Rampersaud Lena Mashayekhy Daniel Grosu Department of Computer Science Wayne State University Detroit MI USA

Computing Nash equilibria is a very important problem in strategic analysis of markets, conflicts and resource allocation. Unfortunately, computing these equilibria even for moderately sized games is computationally expensive. To obtain faster execution times it is essential to exploit the available parallelism offered by the currently available massively parallel architectures. To address this issue, we design a GPU-based parallel support enumeration algorithm for computing Nash equilibria in bimatrix games. The algorithm is based on a new parallelization method which achieves high degrees of parallelism suitable for massively parallel GPU architectures. We perform extensive experiments to characterize the performance of the proposed algorithm. The algorithm achieves significant speedups relative to the OpenMP-based parallel implementation of the support enumeration method running on conventional multicore machines.

关键词： Games graphics processing units Instruction sets Nash equilibrium Algorithm design and analysis Equations Parallel processing

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Test-Time Adversarial Detection and Robustness for Localizing Humans Using Ultra Wide Band Channel Impulse Responses

Test-Time Adversarial Detection and Robustness for Localizin...

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European Signal Processing conference (EUSIPCO)

作者： Abhiram Kolli Muhammad Jehanzeb Mirza Horst Possegger Horst Bischof Institute of Computer Graphics and Vision Graz University of Technology Austria

Keyless entry systems in cars are adopting neural networks for localizing its operators. Using test-time adversarial defences equip such systems with the ability to defend against adversarial attacks without prior training on adversarial samples. We propose a test-time adversarial example detector which detects the input adversarial example through quantifying the localized intermediate responses of a pretrained neural network and confidence scores of an auxiliary softmax layer. Furthermore, in order to make the network robust, we extenuate the non-relevant features by non-iterative input sample clipping. Using our approach, mean performance over 15 levels of adversarial perturbations is increased by 53.3% for the fast gradient sign method and 60.9% for both the basic iterative method and the projected gradient method when compared to adversarial training.

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Remote IoT teaching across the North-Atlantic

Remote IoT teaching across the North-Atlantic

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EAEEIE Annual conference,

作者： Saemundur E Thorsteinsson Helgi Thorbergsson Kristinn Andersen Ian F. Akyildiz Electrical and Computer Engineering University of Iceland Reykjavik Iceland

The ability to offer courses over the Internet between remote teacher(s) and students enhances curricula and can improve quality in university work regarding both teaching and research. This is particularly true for small universities that struggle to offer comprehensive curricula due to lack of professors and students. In the spring semester of 2021, the University of Iceland offered a course on the Internet of Things taught by a professor emeritus in Atlanta, Georgia, assisted by a local professor. The lectures were given on Zoom and all assignments and exams were given over the Internet. In this paper, this course’s framework will be described, how it was implemented and what was accomplished. The authors will also share their thoughts on the future of this kind of university work that has to some extent developed due to the Covid situation.

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Reflecting on development processes in the video game industry

Reflecting on development processes in the video game indust...

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International conference on Software Engineering - Companion, ICSE, Companion

作者： Andrew Brownsword Electronic Arts Inc. USA

Summary form only given. In the past thirty years consumer video game hardware has progressed from simple 8-bit processors, some dedicated display logic and a few kilobytes of memory to high clock rate multi-core processors coupled with a programmable graphics unit, large memories, high capacity optical and fixed drives, network interfaces, high definition audio/video output, and sophisticated user input devices. With this tremendous increase in capability has come a corresponding increase in the sophistication of video games, broadening their market appeal from a niche into a business that rivals Hollywood. The need to create products of this complexity has driven project team sizes from a couple of hackers in a basement to multi-disciplinary teams often numbering well over a hundred. Allowing project teams of this size to function effectively and deliver products on a manageable schedule has driven the evolution of software and content authoring practices and processes within the games industry. This evolution has drawn on experiences, concepts and tools from the software development industry at large, integrating them into the unique environment of video game development. This talk will provide an overview of some of these processes and best practices, as well as the key challenges in the creation of hit titles such as Skate and Need For Speed.

关键词： Games Toy industry computer industry Hardware Auditory displays Logic devices Clocks Multicore processing Optical coupling graphics

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Simulation and architecture improvements of atomic operations on GPU scratchpad memory

Simulation and architecture improvements of atomic operation...

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IEEE International conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： Gert-Jan van den Braak Juan Gómez-Luna Henk Corporaal José María González-Linares Nicolás Guil Department of Electrical Engineering Eindhoven University of Technology The Netherlands Universidad de Cordoba Cordoba AndalucÃa ES Department of Computer Architecture University of Málaga Spain

GPUs are increasingly used as compute accelerators. With a large number of cores executing an even larger number of threads, significant speed-ups can be attained for parallel workloads. Applications that rely on atomic operations, such as histogram and Hough transform, suffer from serialization of threads in case they update the same memory location. Previous work shows that reducing this serialization with software techniques can increase performance by an order of magnitude. We observe, however, that some serialization remains and still slows down these applications. Therefore, this paper proposes to use a hash function in both the addressing of the banks and the locks of the scratchpad memory. To measure the effects of these changes, we first implement a detailed model of atomic operations on scratchpad memory in GPGPU-Sim, and verify its correctness. Second, we test our proposed hardware changes. They result in a speed-up up to 4.9× and 1.8× on implementations utilizing the aforementioned software techniques for histogram and Hough transform applications respectively, with minimum hardware costs.

关键词： Instruction sets graphics processing units computer architecture Atomic measurements Hardware Histograms Logic gates

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Real-Time Automatic License Plate Recognition through Deep Multi-Task Networks

Real-Time Automatic License Plate Recognition through Deep M...

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Brazilian Symposium on computer graphics and Image Processing (SIBGRAPI)

作者： Gabriel Resende Gonçalves Matheus Alves Diniz Rayson Laroca David Menotti William Robson Schwartz Department of Computer Science Universidade Federal de Minas Gerais Brazil Laboratory of Vision Robotics and Imaging Universidade Federal do Paraná Brazil

With the increasing number of cameras available in the cities, video traffic analysis can provide useful insights for the transportation segment. One of such analysis is the Automatic License Plate Recognition (ALPR). Previous approaches divided this task into several cascaded subtasks, i.e., vehicle location, license plate detection, character segmentation and optical character recognition. However, since each task has its own accuracy, the error propagation between each subtask is detrimental to the final accuracy. Therefore, focusing on the reduction of error propagation, we propose a technique that is able to perform ALPR using only two deep networks, the first performs license plate detection (LPD) and the second performs license plate recognition (LPR). The latter does not execute explicit character segmentation, which reduces significantly the error propagation. As these deep networks need a large number of samples to converge, we develop new data augmentation techniques that allow them to reach their full potential as well as a new dataset to train and evaluate ALPR approaches. According to experimental results, our approach is able to achieve state-of-the-art results in the SSIG-SegPlate dataset, reaching improvements up to 1.4 percentage point when compared to the best baseline. Furthermore, the approach is also able to perform in real time even in scenarios where many plates are present at the same frame, reaching significantly higher frame rates when compared with previously proposed approaches.

关键词： Licenses Detectors Task analysis Character recognition Proposals Image segmentation Real-time systems

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Analysis of the Influence of Color Normalization in the Classification of Non-Hodgkin Lymphoma Images

Analysis of the Influence of Color Normalization in the Clas...

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Brazilian Symposium on computer graphics and Image Processing (SIBGRAPI)

作者： Matheus G. Ribeiro Leandro A. Neves Guilherme F. Roberto Thaína A. A. Tosta Alessandro S. Martins Marcelo Z. do Nascimento Department of Computer Science and Statistics (DCCE) São Paulo State University (UNESP) São Paulo Brazil Universidade Federal de Uberlandia Uberlandia MG BR Center of Mathematics Computing and Cognition Federal University of ABC Santo André Uberlândia Brazil Federal Institute of Triangulo Mineiro (IFTM) Ituiutaba Minas Gerais Brazil Faculty of Computation (FACOM) Federal University of Uberlândia (UFU) Uberlândia Minas Gerais Brazil

In this work, a method is proposed to analyze the influence of color normalization in the classification lymphoma images. The approach combines multidimensional fractal techniques, curvelet transforms and Haralick features. The method considered a feature selection technique and different classification approaches to evaluate the combinations, such as decision tree, random forest, support vector machine, naive bayes and k-star. The classifications were analyzed considering three common lymphoma classes: mantle cell lymphoma, follicular lymphoma and chronic lymphocytic leukemia. The best result was achieved for the extraction from input images, features obtained mostly from lacunarity and percolation from curvelet sub-images, using random forest classifier. The tests were considered with 10-fold cross-validation and the result was a rate of AUC=0.963. The color normalization was not able to provide relevant classification rates. The obtained performance with the analysis over different types of features, classifiers and color normalization influence are important contributions to the identification of the lymphoma cancer.

关键词： Feature extraction Image color analysis Fractals Transforms Cancer Probabilistic logic Support vector machines

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