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Implementing Hadoop and Moodle Integrated Student Support System

Implementing Hadoop and Moodle Integrated Student Support Sy...

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international conference on Advanced Information Technologies (ICAIT)

作者： Myint Myat Aung Shin Min Htet Hein Myo Set Aung Hpone thant Sithu Htut Kyaw Zin Htet Nwe Nwe Myint thein Data Distribution Management Lab University of Information Technology Yangon Myanmar Data Distribution Management Lab Faculty of Computer Science University of Information Technology Yangon Myanmar

ISBN: (数字)9798331510046

ISBN: (纸本)9798331510053

Learning management systems (LMS) generate large amounts of real-time data which has the potential to provide valuable insights. Hadoop MapReduce is a scalable framework that is designed to handle such data. this paper presents a system architecture that integrates Hadoop MapReduce into Moodle, a popular LMS, for analyzing academic data. the implementation of the architecture allows users to generate a variety of reports from student attendance logs through a Moodle plugin which utilizes the Hadoop cluster for processing data. Users such as lecturers can then utilize these reports to identify which students do and do not engage in which courses as well as monitor their eligibility for exams. the use of Hadoop MapReduce provides high performance computing (HPC) capabilities that offer distributed parallel processing and economical scalability by means of adding commodity nodes to the cluster.

关键词： Learning management systems Scalability Systems architecture Computer architecture parallel processing Market research Real-time systems Synchronization Information technology Monitoring

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High throughput Circuit Designs of Digital to Analog Converter

High Throughput Circuit Designs of Digital to Analog Convert...

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international conference on Recent Advances in Information Technology (RAIT)

作者： M. V. D. B. Anjaneya Mohamed Asan Basiri M Department of ECE IIITDM Kurnool India

Digital to Analog Converters (DACs) have a good scope of application due to their easily implementable design structure, higher resolution, and accuracy. they are used in digital signal processing devices, digital power supplies for micro-controllers, digital potentiometers, and digital data acquisition systems. In this paper, we proposed high throughput circuit designs that perform multiple DAC operations in parallel with various resolution using the same hardware. the generated high throughput designs can be configured with the control line to perform four 2-bit, two 4-bit, and one 8-bit DAC operations. the throughput of the resistive ladder type DAC is increased by 95.70%, while that of weighted resistor type DAC is increased by 98% using the proposed hardware designs. All the proposed and existing designs are implemented with 90 nm CMOS library in Cadence Virtuoso.

关键词： Performance evaluation Resistors Power supplies Digital-analog conversion Digital signal processing throughput Hardware

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Molecular Nano Communication Networks: architectures, Protocols and Technologies

Molecular Nano Communication Networks: Architectures, Protoc...

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international conference on Multimedia, Signal processing and Communication Technologies, (IMPACT)

作者： Ash Mohammad Abbas Department of Computer Engineering Zakir Husain College of Engineering and Technology Aligarh Muslim University Aligarh India

ISBN: (纸本)9781665476485

A significant interest is created in molecular nano communication networks (MNCNs) where molecules transport information among nano transceivers. In this paper, we present a survey of state-of-the-art research related to MNCNs. We point out issues and challenges related to MNCNs. We focus on the research related to architectures, protocols and technologies for MNCNs. Also, we describe an overview of models of MNCNs pertaining to analysis of energy efficiency, capacity, design of receivers, and the effect of noise. Further, we describe schemes related to bio-nano networks.

关键词： Analytical models Protocols Biological system modeling Receivers Signal processing Energy efficiency Transceivers

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A comprehensive Analysis on Diagnosis of Pneumothorax Disease Using Convolutional Neural Network and Data Visualization for Detection

A comprehensive Analysis on Diagnosis of Pneumothorax Diseas...

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Image processing and Capsule Networks (ICIPCN), international conference on

作者： Ritika Choudhary Narinder Kaur Paurav Goel Computer Science & Engineering Chandigarh University Gharuan Mohali India

ISBN: (数字)9798350367171

ISBN: (纸本)9798350367188

this research paper explores the use of data visualization techniques to analyze a dataset related to pneumothorax, a medical condition characterized by air in the pleural cavity. the dataset consists of medical images in DICOM format, with labels indicating the presence or absence of pneumothorax. the study preprocesses the data, handles missing values, and explores key attributes such as patient demographics, imaging modalities, and view positions. Visualizations are created to illustrate the distribution of patients’ age, gender, and imaging characteristics. the occurrence of pneumothorax across different view positions is analyzed. the findings highlight the effectiveness of data visualization in gaining insights into complex medical datasets, aiding in clinical decision-making and research efforts related to pneumothorax diagnosis and treatment. the paper also provides an overview of convolutional neural network (CNN) models used in pneumothorax detection, discussing various architectures, their application in medical imaging data, and their evolution over time. the insights gained from this analysis contribute to understanding the effectiveness of CNNs in pneumothorax detection and their potential impact on clinical practice and healthcare outcomes.

关键词： Image processing Decision making Data visualization Data models Convolutional neural networks DICOM Medical diagnostic imaging

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Comparison of the Genetic Algorithm and the Particle Swarm Optimization for Minimizing Fuel Consumption for UAVs

Comparison of the Genetic Algorithm and the Particle Swarm O...

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Innovative Research in Applied Science, Engineering and Technology (IRASET),conference on

作者： Vincent Roberge Mohammed Tarbouchi Gilles Labonté Department of Electrical and Computer Engineering Royal Military College of Canada Kingston Canada Department of Mathematics and Computer Science Royal Military College of Canada Kingston Canada

ISBN: (数字)9798331532970

ISBN: (纸本)9798331532987

this paper compares the efficiency of two metaheuristics, namely the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO), for the problem of fuel minimization for uncrewed aerial vehicles (UAVs). When flying search-and-rescue or surveillance missions, it is critical to minimize fuel consumption in order to increase the autonomy of the vehicles. the method proposed consists of using the metaheuristic to compute optimized power settings for the UAV along the trajectory. the approach involves path smoothing in 3D using circular arcs for fixed-wing UAVs. Equations of motion and Newton's equation are used to calculate fuel consumption based on power settings. the metaheuristics are used to compute optimized power settings while adhering to physical constraints. the method is parallelized on a multicore processor for faster computation and optimization in case of trajectory changes. Results show that both the GA and the PSO are efficient at minimizing fuel consumption for the UAV with the PSO being slightly superior. the proposed method can reduce fuel consumption by up to 15% and the parallel implementation is 13.8× faster than a sequential implementation on the CPU.

关键词： Smoothing methods Multicore processing Surveillance Metaheuristics Autonomous aerial vehicles Minimization Trajectory Fuels Particle swarm optimization Genetic algorithms

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You've got a Friend in ME (Mobile Edge): Blockchain processing with Cloud Node Backup 5

You've got a Friend in ME (Mobile Edge): Blockchain Processi...

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5th IEEE international conference on Blockchain (Blockchain)

作者： Karl, Zane Freedman, Hayden Showail, Ahmad Singh, Abhishek Gazzaz, Samaa Nawab, Faisal Univ Calif Irvine Donald Bren Sch Informat & Comp Sci Irvine CA 92697 USA Univ Calif Santa Cruz Baskin Sch Engn Santa Cruz CA 95064 USA Taibah Univ Dept Comp Engn Madinah Saudi Arabia

ISBN: (数字)9781665461047

ISBN: (纸本)9781665461047

the growing ubiquity of Blockchain has led to the experimental transplantation of classical web applications into the Blockchain space. Notoriously, running computationally-expensive processes on-chain is less than ideal. therefore, it is crucial to find ways to utilize the security and decentralization provided by Blockchain technology while reducing on-chain computational load. To that end, recent work has shown the benefit of Multi-stage Transaction architectures. the benefit of such systems is that they provide requested data quickly to the client while still ensuring that accurate results are eventually returned. In this paper, we describe a prototype of a multi-stage transaction system, which we call Friend in Mobile Edge (FiME), that intelligently coordinates client requests between a Blockchain and a central cloud node. We select the use case of stock price prediction and evaluate based on response time to the client as well as computational load on the various components. Our results involve an analysis of the performance of such a system in delivering timely results to the end user, as well as a discussion of the drawbacks of handling large data requests on-chain. We also include recommendations for how future systems can build on these findings.

关键词： Smart contracts Prototypes Computer architecture Blockchains Time factors Security Task analysis

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Programming Heterogeneous architectures Using Hierarchical Tasks 28th

Programming Heterogeneous Architectures Using Hierarchical T...

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28th international European conference on parallel and Distributed Computing , Euro-Par 2022

作者： Faverge, Mathieu Furmento, Nathalie Guermouche, Abdou Lucas, Gwenolé Namyst, Raymond thibault, Samuel Wacrenier, Pierre-André LaBRI/Inria/University of Bordeaux/CNRS/Bordeaux INP Bordeaux France

ISBN: (纸本)9783031312083

Task-based systems have gained popularity as they promise to exploit the computational power of complex heterogeneous systems. A common programming model is the so-called Sequential Task Flow (STF) model, which, unfortunately, has the intrinsic limitation of supporting static task graphs only. this leads to potential submission overhead and to a static task graph not necessarily adapted for execution on heterogeneous systems. A standard approach is to find a trade-off between the granularity needed by accelerator devices and the one required by CPU cores to achieve performance. To address these problems, we extend the STF model of StarPU [5] to enable tasks subgraphs at runtime. We refer to these tasks as hierarchical tasks. this approach allows for a more dynamic task graph. Combined with an automatic data manager, it allows to dynamically adapt the granularity to meet the optimal size of the targeted computing resource. We show that the model is correct and we provide an early evaluation on shared memory heterogeneous systems, using the Chameleon [1] dense linear algebra library. © 2023, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Graphics processing unit

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Carrier Phase Localization with Single Antenna: A Virtual Array Approach

Carrier Phase Localization with Single Antenna: A Virtual Ar...

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international conference on Computer and Communications (ICCC)

作者： Jinghui Han Xiaohui Chen Li Chen Huarui Yin Department of Electronic Engineering & Information Science University of Science and Technology of China Hefei Anhui China

ISBN: (数字)9798331507077

ISBN: (纸本)9798331507084

With the release of 3GPP Release 18, Carrier Phase Positioning (CPP) has emerged as a pivotal technology in 5G positioning. However, the current CPP algorithms typically require the coordination of multiple base stations or antennas for effective localization, which limits their applicability in scenarios where only single-antenna devices are available. To adress this problem, we integrate carrier phase positioning with virtual array technology to propose a novel method that enables accurate localization using single-antenna terminals. Unlike traditional multi-antenna localization approaches, our method eliminates the need for time synchronization and spatial resolution, offering greater flexibility and adaptability across various scenarios. Additionally, we conducted real-world experiments using software-defined radio equipment, and the results confirmed the algorithm's feasibility.

关键词： Phased arrays Location awareness Accuracy Array signal processing Signal processing algorithms parallel processing Autonomous aerial vehicles Synchronization Spatial resolution Software radio

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A Study on the Effectiveness of Deep Learning architectures in Style Transfer: A Comparative Analysis of CNN, VGG16, and VGG19 5

A Study on the Effectiveness of Deep Learning Architectures ...

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5th international conference on Big-data Service and Intelligent Computation, BDSIC 2023

作者： Wang, Zhixiang Xie, Mengtong Lin, Yi Wu, Tong The Glasgow Academy University of Electronic Science and Technology of China Chengdu610097 China University of Nottingham Nottingham CityNG7 2QL United Kingdom Guangdong Technion-Israel Institute of Technology Shantou515000 China School of Engineering The Pennsylvania State University Erie16563 United States

ISBN: (纸本)9798400708923

this study explores the performance differences among different deep learning models, including VGG19, VGG16, and a basic CNN, in the context of image style transfer. Style transfer is an image processing technique aimed at transferring the artistic style of one image onto the content of another. Our research motivation stems from the potential applications of style transfer across various domains and the opportunities for enhancing model performance. through a series of experiments, we assess the performance of these models in terms of the visual quality of generated images, style preservation, feature extraction, and training efficiency. the results demonstrate significant variations in performance across diverse and complex conditions, especially in tasks involving advanced features. VGG19 and VGG16 exhibit exceptional performance, accurately capturing and conveying high-level features, resulting in the generation of synthesized images with artistic value. However, for tasks emphasizing speed and resource efficiency, the basic CNN also exhibits notable advantages. Lastly, we discuss the limitations of the study and provide suggestions for future work to further optimize model performance. In conclusion, the choice of an appropriate deep learning model should be determined by the nature and requirements of the task. this research provides valuable insights into the applications of different models in the field of image style transfer. © 2023 ACM.

关键词： Feature extraction

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Optimizing Massively parallel Winograd Convolution on ARM Processor 21

Optimizing Massively Parallel Winograd Convolution on ARM Pr...

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50th international conference on parallel processing (ICPP)

作者： Li, Dongsheng Huang, Dan Chen, Zhiguang Lu, Yutong Sun Yat Sen Univ Guangzhou Peoples R China

ISBN: (纸本)9781450390682

Convolution Neural Network (CNN) has gained a great success in deep learning applications and been accelerated by dedicated convolutional algorithms. Winograd-based algorithm can greatly reduce the number of arithmetic operations required in convolution. However, our experiments show that existing implementations in deep learning libraries cannot achieve expected parallel performance on ARM manycore CPUs with last-level cache (LLC). Compared to multicore processor, ARM manycore CPUs have more cores, more NUMA nodes and the parallel performance is more easily restricted by memory bandwidth, cache contention, NUMA configuration and etc. In this paper, we propose an optimized implementation for single-precision Winograd-based algorithm on ARM manycore CPUs. Our algorithm adjusts the data layout according to the input shape and is optimized for the characteristics of ARM processor, thus reducing the matrix transformation overhead and achieving high arithmetic intensity. We redesign the parallel algorithm for Winograd-based convolution to achieve a more efficient implementation for manycore CPUs. the experimental results with 32 cores showthat for modern ConvNets, our implementation achieves speedups ranging from 3x to 5x over the state-of-the-art Winogradbased convolution on ARM processor. Even conducted on a set of convolutional benchmarks executing on a 128-core system with 4 NUMA nodes, the results show that our implementation can also achieve better performance than existing implementations on ARM processor.

关键词： convolution winograd parallelization NUMA

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