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A Tensor Low-Rank Approximation for Value Functions in Multi-Task Reinforcement Learning 58

A Tensor Low-Rank Approximation for Value Functions in Multi...

引用

58th Asilomar Conference on Signals, systems and computers, ACSSC 2024

作者： Rozada, Sergio Paternain, Santiago Bazerque, Juan Andrés Marques, Antonio G. King Juan Carlos University Dept. of Signal Theory and Communications Madrid Spain Rensselaer Polytechnic Institute Dept. of Electrical Computer and Systems Engineering TroyNY United States University of Pittsburgh Dept. of Electrical and Computer Engineering PittsburghPA United States

ISBN: (纸本)9798350354058

In pursuit of reinforcement learning systems that could train in physical environments, we investigate multi-task approaches as a means to alleviate the need for massive data acquisition. In a tabular scenario where the Q-functions are collected across tasks, we model our learning problem as optimizing a higher order tensor structure. Recognizing that close-related tasks may require similar actions, our proposed method imposes a low-rank condition on this aggregated Q-tensor. The rationale behind this approach to multi-task learning is that the low-rank structure enforces the notion of similarity, without the need to explicitly prescribe which tasks are similar, but inferring this information from a reduced amount of data simultaneously with the stochastic optimization of the Q-tensor. The efficiency of our low-rank tensor approach to multi-task learning is demonstrated in two numerical experiments, first in a benchmark environment formed by a collection of inverted pendulums, and then into a practical scenario involving multiple wireless communication devices. © 2024 IEEE.

关键词： Multi-task learning

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FedStar Caching: Decision Center Assisted Federated Cooperative Edge Caching 4

FedStar Caching: Decision Center Assisted Federated Cooperat...

引用

4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： Gharib, Sirvan Kesargheh, Mohammad Mansour Seyedmohammadi, S. Jamal Hajiakhondi, Zohreh Abouei, Jamshid Plataniotis, Konstantinos N. Yazd University Dept. Of Electrical Engineering Yazd Iran Concordia University Inst. Of Information Systems Engineering Montreal Canada Concordia University Dept. Of Electrical Engineering Montreal Canada University Of Toronto Dept. Of Electrical And Computer Engineering Toronto Canada

ISBN: (纸本)9798350315790

With the explosion of data, Wireless Edge Caching (WEC) has become a promising approach for locally accessing cached contents. Due to the limited storage capacity of local caching devices and the varying preferences of humans for content, it is necessary to predict popular contents. In this article, we will address two distinct objectives: 1) Popularity prediction of the content that should be cached at the edge to effectively utilize edge device memory. 2) Edge devices collaboration for efficient content delivery. Accordingly, we propose an FL-based Star Cooperative Caching (FedStar Caching), utilizing a Star network topology for realizing an efficient cooperation among Femto-cell Access Points (FAPs) using a Decision Center (DC) to enhance power efficiency and delay performance. Considering human sensitivity to privacy, collecting users' data on a central server is not desirable, therefore, we leverage Federated Learning (FL) to alleviate this challenge. Simulation results demonstrate that the proposed method outperforms alternatives in terms of cache efficiency, as well as delay and power consumption. © 2024 IEEE.

关键词： Stars

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The Early Detection of Dementia Disease Using Machine Learning Approach

The Early Detection of Dementia Disease Using Machine Learni...

引用

2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Kabir, Md. Shariar Khanom, Jakia Bhuiyan, Md. Atik Tumpa, Zerin Nasrin Rabby, S.K. Fazlee Bilgaiyan, Saurabh Daffodil International University Dept. of Computer Science and Engineering Dhaka Bangladesh Daffodil International University Dept. of Software Engineering Dhaka Bangladesh Kalinga Institute of Industrial Technology School of Computer Engineering Bhubaneswar India

ISBN: (纸本)9798350348217

Early dementia detection is a crucial but challenging task in Bangladesh. Often, dementia is not recognized until it is too late to receive effective care. This results in part from a lack of knowledge about the illness and its signs and symptoms. Recent improvements in machine learning algorithms, however, may change this. In a recent study, we developed a model that can identify early dementia in Bangladesh using machine learning algorithms. This research paper proposed an efficient machine learning-based approach for early detection of dementia disease A dataset of 199 people with dementia and 175 healthy controls was used to develop the model. In 96% of the cases, the algorithm correctly identified dementia. This is a significant accomplishment that could revolutionize Bangladesh's dementia detection process. For patients to get the care they require, early dementia detection is essential. This study offers a proof-of-concept for the use of machine learning in dementia early detection & The results of this study suggest that machine learning models can be used as a powerful tool for early detection of dementia. © 2023 IEEE.

关键词： Machine learning

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Assessment of Backup Generator Connection Barriers to Australian Medium Voltage Networks

Assessment of Backup Generator Connection Barriers to Austra...

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2023 IEEE International Conference on Energy Technologies for Future Grids, ETFG 2023

作者： Gu, Mingchen Wanninayaka, Chathuranga Ahmed, Moudud Hasan, Kazi N. Meegahapola, Lasantha Jalili, Mahdi Wilkinson, Richardt McGrath, Brendan Yu, Xinghuo Razzaghi, Reza Rmit University School of Engineering Australia Monash University Dept. of Electrical and Computer Systems Engineering Australia

ISBN: (纸本)9781665471640

Demand response (DR) programs can benefit electricity consumers, distribution network service providers (DNSPs), system operators and the energy market. However, the complexity and characteristics associated with loads connected to customer premises, utilisation of backup generators for DR and the baseline calculation process still require considerable research to optimise and further unlock the capabilities of DR programs. This paper analyses the barriers to using backup generators in medium voltage (MV) networks in DR programs. Two representative Australian MV networks (e.g., Urban-NSW1 network, Urban-VIC network) are analysed in DIgSILENT PowerFactory under different scenarios, such as variation in locations, power export limits, and dynamic export limits of backup generators. The study has found that a backup generator located at the end of the network can achieve better performance in supporting the network voltage. Moreover, the voltage limit and thermal limit of the power network mainly constrain the export limits of backup generators. Furthermore, a backup generator with a dynamic export limit can export 1 to 5 times more energy than the static export limit. © 2023 IEEE.

关键词： Backup generators demand response (DR) dynamic export limit medium voltage (MV) thermal limit

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Mobile Gateways for LoRa End-Devices: Support Connectivity on the Move 29

Mobile Gateways for LoRa End-Devices: Support Connectivity o...

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29th IEEE International Workshop on computer Aided Modeling and Design of Communication Links and Networks, CAMAD 2024

作者： Moysiadis, Vasileios Skoutas, Dimitrios N. Skianis, Charalabos Lagkas, Thomas Argyriou, Vasileios Sarigiannidis, Panagiotis University of the Aegean Dept. of Information and Communication Systems Engineering Samos83200 Greece International Hellenic University Dept. of Computer Science Greece University of Western Macedonia Dept. of Electrical and Computer Engineering Kozani Greece Kingston University Dept. of Networks and Digital Media Kingston upon Thames United Kingdom

ISBN: (纸本)9798350377644

This paper proposes a method enabling mobile LoRa gateways to support mobile end devices. The approach utilizes trilateration and similar approaches based on RSSI to estimate the position of end devices and specify the movement of the gateways to maintain contact. The evaluation of the proposed method tests various parameters such as speed and number of end devices, and it shows that it is able to retain contact even with speeds up to 12 mps. Moreover, the evaluation shows that the ADR-MIN algorithm performs better in this scenario than the default ADR. © 2024 IEEE.

关键词： Gateways (computer networks)

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Comparing Actual Measurement and PVsyst Simulation Results for Energy Generation of Microgrid-Connected PV systems 13

Comparing Actual Measurement and PVsyst Simulation Results f...

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13th Smart Grid Conference, SGC 2023

作者： Nazififard, Mohammad Hashemi-Dezaki, Hamed Nazififard, Kia School of Mechanical Engineering Dept. of Energy Systems Engineering Kashan Iran Dept. of Electrical and Computer Engineering Kashan Iran Independent Researcher Tehran Iran

ISBN: (纸本)9798350396065

This paper evaluates the uncertainty in energy generation of a 12 kWp microgrid (MG)-connected solar photovoltaic (PV) system located at the University of Kashan campus. The study compares long-term recorded measurements and PVsyst simulations for energy generation of PV systems over the course of a year. It is focused on specific yield and the deviation between the measured net energy generated by the PV facility and the calculated useful produced energy by PVsyst software. The results indicate a significant difference between the output power and the simulation results from PVsyst during colder months. However, in warmer months, the disparity between recorded measurements and simulated results is less than 10%. The largest deviation occurs in November, where the difference exceeds 35%. Generally, PVsyst software estimates the energy output from the PV system with an uncertainty of less than 10%. These findings contribute to understanding the variability in PV power generation and developing effective energy management strategies. Such strategies are crucial for ensuring a reliable power supply within an MG. © 2023 IEEE.

关键词： Solar power generation

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Investigating Online Searching Behavior Based on Google Trends in MENA Region Before and After COVID-19 53

Investigating Online Searching Behavior Based on Google Tren...

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53rd IEEE ASEE Frontiers in Education International Conference, FIE 2023

作者： Belkacem, Abdelkader Nasreddine Jamil, Nuraini Alrabaee, Saed College of It Uae University Dept. of Computer and Network Engineering Al Ain United Arab Emirates College of It Uae University Dept. of Computer Science and Software Engineering Al Ain United Arab Emirates College of It Uae University Dept. of Information Systems and Security Al Ain United Arab Emirates

ISBN: (纸本)9798350336429

The outbreak of the coronavirus disease (COVID-19) has had a profound impact on education worldwide. The rise of remote learning is one of the most significant changes in this regard, as many schools and universities were forced to close down by regional health authorities. This has also caused people to become more conservative in trade-offs between healthcare and education. Google Trends is the most common tool for analyzing online search behaviors. It is a free resource that provides information on the trends and changes in users' online interests over time based on certain terms and subjects. The online search queries on Google can be used to assess users' behaviors concerning online learning to forecast their choices regarding online education. This paper examines the frequency of users' web searches for online communication tools, courses, and learning terms. We statistically compared users in the Middle East and North Africa regions by using the volumes of searches recorded on Google Trends from January 2016 to August 2022. Moreover, we used machine learning techniques to identify differences among the keywords used. The findings statistically show that COVID-19 has led to an increase in the extent of students' attention to and interest in online learning. © 2023 IEEE.

关键词： COVID-19 Google Trends MENA Online learning Remote learning Web Behavior

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Establishing a Correlation of Clinical Characteristics with the Level of Tumor Mutation Burden in Urothelial Bladder Carcinoma

Establishing a Correlation of Clinical Characteristics with ...

引用

2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Alshomali, Lujain Khorma, Rania Al-Refai, Abdullah Alkhateeb, Abedalrhman Princess Sumaya University for Technology Software Engineering Dept. Amman Jordan Lakehead University Computer Science Dept. Thunder Bay Canada

ISBN: (纸本)9798350337488

Bladder cancer is a complex disease and one of the most lethal types of cancer. Recently, some malignancies, including bladder carcinomas, have shown better results with immunotherapy using immune checkpoint inhibitors. Tumor mutational burden (TMB) is a potential biomarker for predicting tumor behavior and immunotherapy response as an outcome. Publicly available clinical data from the bladder cancer of TCGA project is used to analyze correlations of clinical variables with an increased tumor mutation burden (TMB) number compared with those with a lower number of mutations. The threshold for the high mutation burden in the analysis was set at 10 mutations (Mut) per Megabase (Mb). The Chi-Square test (χ2) was used to compare categorical data. The Chi-Square 'Best first' method was used to find a correlation between clinical variables and TMB, then compared with the p-value of significance (p © 2023 IEEE.

关键词： biomarkers Chi-Square clinical characteristics Tumor mutational burden urothelial bladder carcinoma

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Union Bound for Generalized Duplication Channels with DTW Decoding

Union Bound for Generalized Duplication Channels with DTW De...

引用

2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Vidal, Adrian Wijekoon, V.B. Viterbo, Emanuele Monash University Dept. Electrical & Computer Systems Engineering ClaytonVIC3800 Australia

ISBN: (纸本)9781665475549

In this paper, we calculate a union bound for dynamic time warping (DTW)-based decoding of piecewise constant signals corrupted by additive noise and time stretching due to sample duplications, as observed in raw measurement signals obtained from nanopore sequencers. We consider both finitely- and infinitely-supported duplications with geometric-like characteristic, which include discrete uniform distributions as a special case. First, we provide explicit algorithms that calculate the union bound in O(ak2) time for the infinite-support case and in O(ß2k2) for the finite-support case, where k is the codeword length, a is the minimum duplication, and ß is the maximum duplication. Next, we show that a multi-read union bound exhibits a thresholding effect, where the error probability can be made arbitrarily close to zero by aggregating DTW distances from sufficiently many independent reads. Finally, we validate the calculated bounds relative to simulation results. © 2023 IEEE.

关键词： Additive noise

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Sinhala Sign Language Learning System for Hearing Impaired Community 4

Sinhala Sign Language Learning System for Hearing Impaired C...

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4th International Informatics and software engineering Conference, IISEC 2023

作者： Idushan, K.A.S. Dilshan, P.G.T. Jayasundera, P.S. Madhushan, K.L.B. Krishara, Jenny Wijendra, Dinuka Sri Lanka Institute of Information Technology Dept. of Computer Science and Software Engineering Malabe Sri Lanka

ISBN: (纸本)9798350318036

This research aims to develop a comprehensive system for Sinhala Sign Language (SSL) that includes a learning system, dynamic sign detection, audio/video to sign conversion, and vocal training. SSL plays a crucial role in facilitating communication for individuals who are deaf or hard of hearing in Sri Lanka. The learning system provides a platform for learning SSL and includes a text-To-sign language interpreter. The dynamic sign detection system uses computer vision techniques to identify and interpret dynamic signs accurately. The audio/video to sign conversion system bridges the gap between spoken language and SSL by converting auditory information into visual representations. The vocal training system focuses on enhancing the vocal skills of cochlear implanted children. This research contributes to the development of effective communication and language skills for SSL users. © 2023 IEEE.

关键词： Learning systems

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