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arXiv 2023年

作者： Álvarez, Josefa Díaz Risco-Martín, José L. Manuel Colmenar, J. Centro Universitario de Mérida Universidad de Extremadura Mérida06800 Spain Dpt. of Computer Architecture and Automation Complutense University of Madrid C/Prof. José García Santesmases 9 Madrid28040 Spain Dpt. of Computer Science Rey Juan Carlos University Móstoles28933 Spain

Current embedded systems are specifically designed to run multimedia applications. These applications have a big impact on both performance and energy consumption. Both metrics can be optimized selecting the best cache configuration for a target set of applications. Multi-objective optimization may help to minimize both conflicting metrics in an independent manner. In this work, we propose an optimization method that based on Multi-Objective Evolutionary Algorithms, is able to find the best cache configuration for a given set of applications. To evaluate the goodness of candidate solutions, the execution of the optimization algorithm is combined with a static profiling methodology using several well-known simulation tools. Results show that our optimization framework is able to obtain an optimized cache for Mediabench applications. Compared to a baseline cache memory, our design method reaches an average improvement of 64.43% and 91.69% in execution time and energy consumption, respectively. © 2023, CC BY-SA.

关键词： Evolutionary algorithms

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A Novel Hybrid Genetic and A-star Algorithm for UAV Path Optimization

A Novel Hybrid Genetic and A-star Algorithm for UAV Path Opt...

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Humanitarian Technology Conference (KHI-HTC), IEEE Karachi Section

作者： Danish Mehmood Asharab Ali Seerat Ali Farzana Kulsoom Hassan Nazeer Chaudhry Ammar Zeb Ul Haider Telecommunication Engineering Dpt University of Engg. & Technology Taxila Pakistan Computer Science Department Barani Institute of Technology Rawalpindi Pakistan

Unmanned aerial vehicles (UAVs) are essential in 5G/6G communication as they provide affordable and effective solutions. However, collecting data in an unfamiliar environment from various sensor nodes is challenging due to the limited energy resources of UAVs. Therefore, careful planning of the UAV’s path is vital to conserve and effectively utilize available energy resources. Our paper presents a hybrid genetic and A-star algorithm that optimizes energy consumption, making it powerful and efficient. The genetic algorithm (GA) generates numerous potential paths for a UAV to take, while the A-star algorithm identifies the most optimal route from that pool. The results show that our algorithm outperforms the state-of-the-art system while increasing the number of data nodes.

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Internet of Things under a semantic perspective with user profiles 22

Internet of Things under a semantic perspective with user pr...

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11th Euro-American Conference on Telematics and Information Systems, EATIS 2022

作者： Kourtiche, Ali Felici-Castell, S. Perez Solano, jjperezs Segura-Garcia, jsegura Soriano-Asensi, sona Navarro-Camba, E. Pinto, J. Eedis Laboratory Computer Science Department University of Sidi Bel Abbes Sidi Bel Abbes Algeria Etse - Dpt. Informàtica Universitat de València Valencia Burjassot Spain Deti - Universidade de Aveiro Aveiro Portugal

ISBN: (纸本)9781450397391

Internet of Things (IoT) is a network made up of different types of devices integrated into the Internet. For the use of IoT in cities to assist humans beings in their daily activities, it is necessary to extract and process as much information as possible and therefore, semantic web technologies are a key point. This new environment is known as the Semantic Web of Things (SWoT). The application of semantic techniques to IoT can improve interoperability, effective access to data, discovery of integration resources, reasoning and processing of knowledge extraction from data, opening up opportunities for new applications. We show an overview of the most relevant semantic technologies, focusing on SWoT and well-accepted ontologies for IoT and we stress that considering users' preferences, interests and needs are of vital importance, as a complement to the semantic information extracted. This new scenario enables the development of advanced applications and services to meet user requirements and needs, in particular for smart city applications. © 2022 ACM.

关键词： Semantic Web

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An On-chip Reconfigurable Multi-layer Perceptron and Recurrent Neural Network Processor for Speech Recognition

An On-chip Reconfigurable Multi-layer Perceptron and Recurre...

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2021 International Conference on Computing, Electronic and Electrical engineering, ICE Cube 2021

作者： Muzamal, Junaid Hussain Kwong, Anne Asghar, Muhammad Al-Khawarizmi Institute of Computer Science UET Lahore Lahore Pakistan Digital Galaxy Technologies Limited Dpt. of Research and Development Sheng Guangdong China Lahore Leads University Department of Computer Science Lahore Pakistan

ISBN: (纸本)9781665401548

Modern voice-based applications, such as speech recognition and classification, mainly exploit the neural network-based algorithms (i.e., Multilayer Perceptron, Recurrent Neural Network, LSTM), and they have established extraordinary promising results in terms of accuracy, especially in sequential data recognition. However, such algorithms involve massive Recurrent Neural Network (RNN) related computations, which are extremely difficult to manage with traditional general-purpose processors. To solve this issue, a Lookup Tables (LUT) based multiplier architecture of accelerators have merged, which comprises a collection of several hundred processing elements (PEs). By exploiting the phenomena of parallel computations, these accelerators accomplish excellent results and high throughput in general. However, already proposed architectures of PEs do not optimize the weight calculation and other parameters that impact the silicon implementation. To this end, we propose an on-chip architecture for the MLP-RNN processor to speed up the matrix multiplication while optimizing the performance, cost, and power consumption with LUT-powered multiplication. Theoretically, we observed a 75% reduction in weight and 5x improvement in power consumption in simulation on 65nm at 200MHz clock 1.2V CMOS process technology © 2021 IEEE.

关键词： Graphics processing unit

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Results From a Large-Scale IoT-based Intervention for Energy Saving and Sustainability Awareness via Behavior Change in 25 K-12 Schools in Europe

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IEEE Internet of Things Journal 2025年第12期12卷 19308-19325页

作者： Mylonas, Georgios Amaxilatis, Dimitrios Paganelli, Federica Chatzigiannakis, Ioannis Koulouris, Pavlos Falkouskaya, Yelizaveta Markopoulos, Panos Athena Research Center Industrial Systems Institute Patras26504 Greece Comp. Tech. Institute and Press "Diophantus" 26504 Greece Spark Works Ltd GalwayH91 AHR1 Ireland Univ. of Pisa Dpt. of Computer Science Pisa56127 Italy CNIT Florence50134 Italy Sapienza University of Rome Dpt. of Computer Control and Management Engineering 00185 Italy Ellinogermaniki Agogi Athens Greece Eindhoven University of Technology AI Systems Institute Industrial Design Noord-Brabant Eindhoven5612 AE Netherlands

The unfolding climate crisis has resulted in a rising interest for increasing sustainability awareness and achieving energy savings worldwide. Several interventions within educational environments have been aimed at mobilizing younger audiences towards such goals. However, most of the interventions carried out so far are based on a subset of possible tools (e.g., IoT monitoring, gamification) and offer "all or nothing"approaches, which do not cope well with the uniqueness of schools and the need to adapt interventions to specific contexts (e.g. school size, building, curriculum, teacher involvement). We present a large-scale intervention in 25 school buildings in Europe over the course of two school years. Our intervention was based on the installation of a relatively low-cost IoT infrastructure in schools, that produced real-time energy-related data from the school buildings involved, and the application of a strategy combining, in a flexible and customizable way, educational activities, monitoring tools, gamification, and competition to motivate behavior change and achieve energy savings. Overall, 2983 students and 204 educators were directly involved to a variable degree of participation. Our results indicate a positive overall result in terms of short-term energy savings in most schools involved, with an average reduction of 20-25% in the energy that could be affected by end-users, as well as a 32.9% increase after the intervention in students self-reporting good or very good sustainability awareness. These findings suggest that such interventions can be a valuable step towards educating young students regarding sustainability and towards sustainable schools, if designed and implemented properly. © 2014 IEEE.

关键词： Behavior Change Education for Sustainable Development Energy Literacy Energy Saving Environmental Education Gamification Internet of Things K-12 Sustainability Sustainable Smart Schools

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6G-SECUREIDS: Blockchain-Enhanced Secure Knowledge Transfer for Distributed Intrusion Detection Systems in Advanced Networks

6G-SECUREIDS: Blockchain-Enhanced Secure Knowledge Transfer ...

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International Conference on Networking and Advanced Systems (ICNAS)

作者： Sabrina Sakraoui Makhlouf Derdour Ahmed Ahmim Department of Computer Science Networks and Systems Laboratory Badji Mokhtar Annaba University Annaba Algeria Department of Computer Science Networks and Systems Laboratory Oum El Bouaghi University Oum El Bouaghi Algeria Dpt. of Mathematics and Computer Science Networks and Systems Laboratory Mohamed-Cherif Messaadia University Souk Ahras Algeria

As the development of wireless networks advances towards the deployment of 6G technology, ensuring robust security measures becomes crucial. In this paper, we propose 6G-SECUREIDS, a novel intrusion detection system designed specifically for 6G wireless networks. The system leverages machine learning techniques and blockchain technology to detect and mitigate security threats, safeguard data privacy, and ensure efficient and optimized training. Our experimental results demonstrate the effectiveness and reliability of the system, with the clients achieving high accuracy scores across different model architectures. The promising results highlight the potential of 6G-SECUREIDS as a valuable security solution for future 6G networks, contributing to the overall protection and integrity of the wireless communication ecosystem.

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Software failure time series prediction with RBF, GRNN, and LSTM neural networks 26

Software failure time series prediction with RBF, GRNN, and ...

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26th International Conference on Knowledge-Based and Intelligent Information and engineering Systems, KES 2022

作者： Yakovyna, Vitaliy Shakhovska, Natalya University of Warmia and Mazury in Olsztyn Faculty of Mathematics and Computer Science ul. Oczapowskiego 2 Olsztyn10-719 Poland Lviv Polytechnic National University Artificial Intelligence Dpt. 12 S. Bandery St. Lviv79013 Ukraine

The important task of software quality assurance is failure prediction. Time series forecasting methods can be successfully used for this purpose. This paper aims to study and compare the effectiveness of software failure prediction using different types of neural networks, in particular RBF neural network and recurrent neural networks (GRNN and LSTM). The Chromium browser failure dataset was used in this study. The dataset contains information about 11, 001 bug reports for 759 consecutive days. Predictions were performed for 150-day, 500-day, and 759-day time series. Long time series of software failures cannot be approximated with satisfactory accuracy by an RBF neural network. Both GRNN and LSTM neural networks were able to predict the long software failures time series with RMSE values of 0.321 and 0.241 correspondingly. © 2022 The Authors. Published by Elsevier B.V.

关键词： Forecasting

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DECOR 2024: Where Data engineering Meets Intelligent Food and Cooking Innovation

DECOR 2024: Where Data Engineering Meets Intelligent Food an...

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International Conference on Data engineering Workshops

作者： Frederic Andres Farshad Fotouhi Gheorghita Ghinea Steve Tanimoto Digital Content and Media Sciences Research Division National Institute of Informatics Tokyo Japan Dpt of Computer Science College of Engineering Wayne State University Detroit MI USA Department of Computer Science Brunel University London London UK Paul G. Allen School of Computer Science & Engineering University of Washington Seattle WA USA

ISBN: (数字)9798350384031

ISBN: (纸本)9798350384048

This extended abstract presents the 7th International Workshop on Data engineering Meets Intelligent Food & Cooking Recipes 2024, which will be held in conjunction with the 40th IEEE International Conference on Data engineering 2024 (ICDE). The primary aim of this workshop is to provide a comprehensive overview of the latest advancements and existing challenges at the intersection of Data engineering and Intelligent Food & Cooking Recipes.

关键词： Technological innovation Conferences Data engineering

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A Generalized Tonic-Clonic Seizure Detection Method in a Bathtub using a Natural Language Verification Step 24

A Generalized Tonic-Clonic Seizure Detection Method in a Bat...

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24th Pan-Hellenic Conference on Informatics, PCI 2020

作者： Petroulaki, Olga Bicaku, Angeliki Kakarountas, Athanasios University of Thessaly Dpt. of Computer Science and Biomedical Informatics Lamia Greece

ISBN: (纸本)9781450388979

A Generalized Tonic-Clonic Seizure Detection Method in a Bathtub is proposed in this work, targeting mainly epileptic seizures. The main novelty of the presented methodology is found in the use of natural language Human-computer Interaction, in order to verify the positive detection of such seizure. The proposed system, is a low-cost and low-complexity one, that allows safe operation in an environment with limited access. It overcomes problems presented in related works in the scientific literature and offers a sufficient two-tier verification process, in order to eliminate the false positives. The preliminary results, based on simulation, showed that any incident was successfully detected. To the best of the authors knowledge this is the first time that this methodology is presented, combining smart vibration detection and natural language (NL) recognition to verify/trigger (or not) an alarm of seizure in a bathtub. © 2020 ACM.

关键词： Automation

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A sub-1V CMOS Instrumentation Amplifier for an AFE Interfacing with Sensors 5

A sub-1V CMOS Instrumentation Amplifier for an AFE Interfaci...

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5th International Young Engineers Forum in Electrical and computer engineering, YEF-ECE 2021

作者： Neves, Francisco Oliveira, João P. Oliveira, Henrique Dpt. of Electrical and Computer Engineering NOVA School of Science and Technology Caparica Portugal CTS UNINOVA Caparica Portugal Instituto de Telecomunicações Lisboa Portugal Instituto Politécnico de Beja Beja Portugal

ISBN: (纸本)9781665412643

This paper presents the design of a low-noise capacitively-coupled instrumentation amplifier with a sub-1V power supply, which is suitable for low-power sensor data acquisition systems. This amplifier is part of an Analog Front-end (AFE) which is implemented in a standard 130nm bulk CMOS technology. Beside the high-impedance input amplifier, the AFE includes a programmable switch-capacitor bandpass filter and a sigma-delta modulator. A chopper modulation technique is implemented to further reduce the flicker noise, with a positive feedback network to compensate the resulting low input impedance. The preliminary post-layout simulated results of the instrumentation amplifier achieves a total power consumption of 2.6µW, with an open loop gain of 87dB and a GBW of 584kHz and with the input reffered noise of 4.6µVrms and a NEF value of 4. The maximum CMRR of the amplifier is 101dB and the PSRR minus is greater than 66dB. For a sub 1V power supply, the input frequency range is up to 10 kHz. © 2021 IEEE.

关键词： Bandpass filters

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