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IEEE Central America and Panama Convention (CONCAPAN)

作者： Luis D. Prieto-Sibaja Luis G. Leόn-Vega Indra Leόn-Vega Jorge Castro-Godínez Stefano Cozzini Computer Engineering School Costa Rica Institute of Technology Cartago Costa Rica Math. Inf. and Geoscience Dep. University of Trieste Trieste Italy Industrial Design Engineering School Instituto Tecnolόgico de Costa Rica Cartago Costa Rica Electronics Engineering School Costa Rica Institute of Technology Cartago Costa Rica Institute of Research and Technology AREA Science Park Trieste Italy

ISBN: (数字)9798350366723

ISBN: (纸本)9798350366730

Large Language Models (LLMs) have emerged as the leading technique in Natural Language Processing due to their remarkable capabilities. These models are exceptionally complex, often utilising billions of parameters and consuming tens of gigabytes of memory unless optimised. Typically, LLMs are trained and accelerated using general-purpose Graphics Processing Units (GPUs), with a single inference potentially occupying an entire GPU. Consequently, cloud services may require hundreds of GPUs to deliver high-quality AI assistant services. This demand for extensive hardware acceleration allows exploring alternative architectures that offer improved execution time and energy *** study evaluates Field-Programmable Gate Arrays (FP-GAs), renowned for their flexibility and efficiency, to accelerate LLMs. We specifically compare the resource consumption and latency of two distinct architectures: layer and spatial accelerators. Analysing the Llama 2-7B model, we identified potential optimisation opportunities within its composition and operational graphs. Our most successful implementations demonstrate a performance improvement ranging from 1.37× to 10.98× over two AMD EPYC processors with 64 cores each. Moreover, our results indicate that, with further refinement, FPGAs have the potential to surpass GPU performance for LLM inference, showcasing their feasibility as a viable alternative for this demanding application.

关键词： Large language models High performance computing Graphics processing units computer architecture Logic gates Distance measurement Natural language processing Field programmable gate arrays Hardware acceleration Optimization

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Machine Learning Approach to Detection of Offensive Language in Online Communication in Arabic 1

Machine Learning Approach to Detection of Offensive Language...

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1st IEEE International Maghreb Meeting of the Conference on sciences and Techniques of Automatic Control and computer engineering, MI-STA 2021

作者： Alakrot, Azalden Fraifer, Muftah Nikolov, Nikola S. The College of Medical Technology Department of Information Technology Yefren Libya The College of Industrial Technologies-CIT Department of Electronic Engineering Misurata Libya University of Limerick Dep. of Computer Science and Information System Limerick Ireland

ISBN: (纸本)9781665418560

This paper presents the results of several machine learning experiments, conducted with a dataset of YouTube comments in Arabic. The experiments aim at studying the impact of various text preprocessing, feature-extraction and feature-selection techniques on the accuracy of a document classifier for detection of offensive language in online communication in Arabic. Regarding data pre-processing, our experiments focus on filtering out noisy characters and normalising inconsistencies present in casual online writing in Arabic. The combined effect of these data preprocessing techniques and a few feature-extraction and feature-selection methods is then evaluated by training document classifiers. Our results give evidence that it is possible to train a classifier for the detection of offensive language on Arabic social media with reasonable overall accuracy of 0.84, and precision, recall and F1-score of 0.89, 0.76 and 0.81, respectively. © 2021 IEEE.

关键词： Support vector machines

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Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems

arXiv

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arXiv 2021年

作者： Nikolakopoulos, Athanasios N. Ning, Xia Desrosiers, Christian Karypis, George Amazon Seattle United States Biomedical Informatics Computer Science and Engineering Dep. The Ohio State University Columbus United States Software Engineering and IT Dep. École de Technologie Supérieure Montreal Canada Computer Science & Engineering Dep. University of Minnesota Minneapolis United States

Collaborative recommendation approaches based on nearest-neighbors are still highly popular today due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations. This chapter offers a comprehensive survey of neighborhood-based methods for the item recommendation problem. It presents the main characteristics and benefits of such methods, describes key design choices for implementing a neighborhood-based recommender system, and gives practical information on how to make these choices. A broad range of methods is covered in the chapter, including traditional algorithms like k-nearest neighbors as well as advanced approaches based on matrix factorization, sparse coding and random walks. Copyright © 2021, The Authors. All rights reserved.

关键词： Recommender systems

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A Simplified Variant of Gödel's Ontological Argument

arXiv

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arXiv 2022年

作者： Benzmüller, Christoph Otto-Friedrich-Universität Bamberg AI Systems Engineering Bamberg Germany Freie Universität Berlin Dep. of Mathematics and Computer Science Berlin Germany

A simplified variant of Gödel's ontological argument is presented. The simplified argument is valid already in basic modal logics K or KT, it does not suffer from modal collapse, and it avoids the rather complex predicates of essence (Ess.) and necessary existence (NE) as used by Gödel. The variant presented has been obtained as a side result of a series of theory simplification experiments conducted in interaction with a modern proof assistant system. The starting point for these experiments was the computer encoding of Gödel's argument, and then automated reasoning techniques were systematically applied to arrive at the simplified variant presented. The presented work thus exemplifies a fruitful human-computer interaction in computational metaphysics. Whether the presented result increases or decreases the attractiveness and persuasiveness of the ontological argument is a question I would like to pass on to philosophy and theology. Copyright © 2022, The Authors. All rights reserved.

关键词： Human computer interaction

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Fabrication and Studies of Dielectric Properties of Nanocomposites Materials Based on Polyurethane

SSRN

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SSRN 2023年

作者： Hardoň, Štefaň Kúdelčík, Jozef Baran, Anton Hornak, Jaroslav Trnka, Pavel Tamus, Adam Zoltan Koltunowicz, Tomasz Norbert Kozáková, Alena Dérer, Tomáš Department of Physics Faculty of Electrical Engineering and Information Technology University of Žilina Žilina010 26 Slovakia Dep. of Physics Fac. of Electrical Engineering and Informatics Technical University of Košice Park Komenského 2 Košice042 00 Slovakia Dep. of Technologies and Measurement Fac. of Electrical Engineering University of West Bohemia at Pilsen Plzeň301 00 Czech Republic Dep. of Electric Power Engineering Fac. of Electrical Engineering and Informatics Budapest University of Technology of Economics Egry J. Street 18. BudapestH-1111 Hungary Dep. of Electrical Devices and High Voltage Technology Fac. of Electrical Engineering and Computer Science Lublin University of Technology Lublin Poland VUKI a.s. Electroinsulating Resins and Varnishes Bratislava Slovakia

This paper addresses the influence of nanoparticles (NPs) on the dielectric properties of polyurethane. In this research, we only investigated the effect of Al2O3, MgO and ZnO NPs for concentrations up to 2% wt and in the temperature range from 25 to 120 °C. During the preparation of nanocomposites, polymer chains bind to NPs, which then limits their mobility. This effect results in a decrease in real permittivity and the course of polarization mechanisms. We observed an increase in permittivity over the entire temperature range only for a 2% MgO concentration. The decrease in the mobility of polymer chains was confirmed by dynamic-mechanical analysis. This method also results in an increase in the glass transition temperature dep.nding on the type and concentration of NPs. The presence of NPs and the limited mobility of the polymer chains results in a shift of the low-frequency local maximum to lower frequencies © 2023, The Authors. All rights reserved.

关键词： Aluminum oxide

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Roadblocks to Attracting Students to Software Testing Careers: Comparisons of Replicated Studies

arXiv

引用

arXiv 2022年

作者： Souza, Rodrigo E.C. de Souza Santos, Ronnie E. Capretz, Luiz Fernando de Sousa, Marlon A.S. de Magalhães, Cleyton V.C. Agile Testing Program CESAR School Pernambuco Recife Brazil Faculty of Computer Science Dalhousie University HalifaxNS Canada Dep. of Electrical & Computer Engineering Western University LondonON Canada

Context. Recently, a family of studies highlighted the unpopularity of software testing careers among undergraduate students in software engineering and computer science courses. The original study and its replications explored the perception of students in universities in four countries (Canada, China, India, and Malaysia), and indicated that most students do not consider a career in software testing as an option after graduation. This scenario represents a problem for the software industry since the lack of skilled testing professionals might decrease the quality of software products and increase the number of unsuccessful projects. Goal. The present study aims to replicate, in Brazil, the studies conducted in the other four countries to establish comparisons and support the development of strategies to improve the visibility and importance of software testing among undergraduate students across the globe. Method. We followed the same protocol in the original study to collect data using a questionnaire and analyzed the answers using descriptive statistics and qualitative data analysis. Results. Our findings indicate similarities among the results obtained in Brazil in comparison to those obtained from other countries. We observed that students are not motivated to follow a testing career in the software industry based on a belief that testing activities lack challenges and opportunities for continuous learning. Conclusions. In summary, students seem to be interested in learning more about software testing. However, the lack of discussions about the theme in software development courses, as well as the limited offer of courses focused on software quality at the university level reduce the visibility of this area, which causes a decrease in the interest in this career. © 2022, CC BY.

关键词： Software testing

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Blockchain-based scalable authentication for IoT: Poster abstract 20

Blockchain-based scalable authentication for IoT: Poster abs...

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18th ACM Conference on Embedded Networked Sensor Systems, SenSys 2020

作者： Mukhandi, Munkenyi Andrade, Eduardo Damião, Francisco Granjal, Jorge Vilela, João P. Cisuc Dep. of Informatics Engineering University of Coimbra Portugal Pdmfc Lisbon Portugal CRACS/INESCTEC Cisuc Dep. of Computer Science Faculty of Sciences University of Porto Portugal

ISBN: (纸本)9781450375900

Device identity management and authentication are one of the critical and primary security challenges in IoT. In order to decrease the IoT attack surface and provide protection from security threats such as introduction of fake IoT nodes and identity theft, IoT requires scalable device identity management systems and resilient device authentication mechanisms. Existing mechanisms for device identity management and device authentication were not designed for huge number of devices and therefore are not suitable for IoT environments. This work presents results of a blockchain-based identity management approach with consensus authentication, as a scalable solution for IoT device authentication management. Our identity management approach relies on having a blockchain secure tamper proof registry and lightweight consensus-based identity authentication. © 2020 Owner/Author.

关键词： Blockchain

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Enhanced SNR Based Admission Control Algorithm for Vehicular Ad-Hoc Network 23

Enhanced SNR Based Admission Control Algorithm for Vehicular...

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Proceedings of the 7th International Conference on Future Networks and Distributed Systems

作者： Aws Zuhair Sameen Mohammed Hasan Alwan Mayssam Saad Kadhum Yousif I Hammadi Mokhalad Abdulameer Kadhim Alsaeedi Ahmed Aziz Mohammed Saleh Ali Muthanna Department of Medical Instrumentation Engineering Techniques Al-Farahidi University Iraq Department of Communications Engineering University of Diyala Iraq Dep. of Medical Instruments Engineering Techniques Bilad Alrafidain University College Iraq Department of computer science Benha university Egypt and International Business Management Department Tashkent State University of Economics Uzbekistan Institute of Computer Technologies and Information Security Southern Federal University Russia

ISBN: (纸本)9798400709036

Vehicular Ad-hoc Network (VANET) becomes a fundamental subcategory of mobile ad-hoc networks that provides vehicles to communicate with each other and with roadside infrastructure smartly. Various VANET performance challenges are considered in terms of Quality of Service (QoS) due to vehicle speed and transmission rates. Different problems cause performance degradation as performance anomaly where high rates of vehicles have to meet the speed of the low rates vehicle while transmitting data. In this paper, a QoS-aware Signal to Noise Ratio (SNR) admission control mechanism (QASAC) is proposed to handle the performance anomaly problem while maintaining the QoS levels for different traffic types. QASAC has been compared against the latest SNR based admission control mechanism. QASAC has enhanced the performance of data delivery up to 23% in terms of data dropping rates for high priority traffic.

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An actor-critic algorithm with policy gradients to solve the job shop scheduling problem using deep double recurrent agents

arXiv

引用

arXiv 2021年

作者： Monaci, Marta Agasucci, Valerio Grani, Giorgio Sapienza University of Rome Dep. of Computer Science Control and Management Engineering Rome Italy Sapienza University of Rome Dep. of Statistics Rome Italy

In this work, we present a method that applies Deep Reinforcement Learning, an approximate dynamic programming procedure using deep neural networks, to the job shop scheduling problem (JSSP). The aim is to show that a greedy-like heuristic trained on a subset of problems, can effectively generalize to some extent to unseen instances, and be competitive compared to other methods. We model the JSSP as a Markov Decision Process and we exploit the efficacy of reinforcement learning to solve the problem. We adopt an actor-critic scheme based on policy gradients, specifically the Proximal Policy Gradient method, where the action taken by the agent is influenced by policy considerations on the state-value function. The procedures take into account the challenging nature of JSSP, where the state and the action space change for every instance and after each decision. To tackle this variability, we introduced a novel model based on two incident Long-Short Term Memory networks, followed by an encoding model, different in structure for both the actor and the critic. Experiments show the algorithm reaches good solutions in a short time, proving that is possible to generate new greedy heuristics just from learning-based methodologies. We compared our algorithms against several established heuristics, an adaptive method, a commercial solver based on branch and cut, and another approach based on Deep Reinforcement Learning, proving the validity of the proposed method in terms of time and makespan. The model can generalize, to some extent, to larger problems originating from a different *** Codes 90-08 © 2021, CC BY.

关键词： Reinforcement learning

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Improving Obstacle Avoidance Strategies in Autonomous Navigation of a Sailboat

Improving Obstacle Avoidance Strategies in Autonomous Naviga...

引用

On-Line Conference (ONCON), Industrial electronics Society Annual

作者： Pedro Paiva Luís Gomes Dep. Electrical and Computer Engineering NOVA School of Science and Technology — FCT-NOVA NOVA University Lisbon Caparica Portugal School of Science and Technology Center of Technology and Systems (UNINOVA-CTS) and Associated Lab of Intelligent Systems (LASI) NOVA University Lisbon Caparica Portugal

This work explores the different mechanisms involved in creating a behavioural system for route planning and collision avoidance, taking into account the constraints imposed by the navigational characteristics of the sailboat. The implementation of these mechanisms is accompanied by an introduction to fundamental concepts, including Artificial Potential Fields, Histograms of Vector Fields, Navigation in the No-Go Zone, Differentiation of the Nature of Obstacles resulting in Different Operations, and the Constitution of Different Areas of Actuation. Finally, multiple simulations are conducted in a virtual environment to verify the resilience of the proposed navigation strategy.

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