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Improving the learning performance by exploiting multimedia in eXtreme apprenticeship

Multimedia Tools and Applications 2024年 1-25页

作者： Persia, Fabio D’Auria, Daniela Ge, Mouzhi Pilato, Giovanni Department of Information Engineering Computer Science and Mathematics University of L’Aquila Via Vetoio L’Aquila67100 Italy Faculty of Computer Science Free University of Bozen-Bolzano Piazza Domenicani 3 Bozen-Bolzano39100 Italy Faculty of European Campus Rottal-Inn Deggendorf Institute of Technology Dieter-Görlitz-Platz 1 Deggendorf94469 Germany Institute for High Performance Computing and Networking National Research Council of Italy Via Ugo La Malfa 153 Palermo90146 Italy

From prior studies on eXtreme Apprenticeship (XA), it can be seen that XA has emerged as an innovative and effective educational approach. The technology in computer science evolves rapidly and XA tackles the gap between University education and industry development. Additionally, distance learning by multimedia is more and more important, sometimes even becoming necessary. As a result, this paper intends to study how to integrate XA and multimedia to improve the learning performance in computer science, with particular reference to the programming courses. Since computer science is mostly driven by the new applications, XA and multimedia are considered to be effective and efficient to reduce the cognitive efforts by practical demonstration. The experimental results, based on the case study of the operating systems course at the Bachelor’s level, show that exploiting multimedia in XA can significantly improve the learning performance in terms of grade distributions, reliability, knowledge transfer and student satisfaction with respect to more traditional approaches based on frontal lectures. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Distance education

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Combined Effect of Concept Drift and Class Imbalance on Model performance During Stream Classification

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computers, Materials & Continua 2023年第4期75卷 1827-1845页

作者： Abdul Sattar Palli Jafreezal Jaafar Manzoor Ahmed Hashmani Heitor Murilo Gomes Aeshah Alsughayyir Abdul Rehman Gilal Department of Computer and Information Sciences Universiti Teknologi PETRONAS(UTP)Seri Iskandar32610Malaysia Centre for Research in Data Science UTPPerak32610Malaysia High Performance Cloud Computing Centre(HPC3) UTPPerak32610Malaysia School of Engineering and Computer Science Victoria University of WellingtonWellington6012New Zealand AI Institute University of Waikato WellingtonHamilton3240New Zealand Anti-Narcotics Force Ministry of Narcotics ControlIslamabad46000Pakistan College of Computer Science and Engineering Taibah UniversityMadinah42353Saudi Arabia

Every application in a smart city environment like the smart grid,health monitoring, security, and surveillance generates non-stationary datastreams. Due to such nature, the statistical properties of data changes overtime, leading to class imbalance and concept drift issues. Both these issuescause model performance degradation. Most of the current work has beenfocused on developing an ensemble strategy by training a new classifier on thelatest data to resolve the issue. These techniques suffer while training the newclassifier if the data is imbalanced. Also, the class imbalance ratio may changegreatly from one input stream to another, making the problem more *** existing solutions proposed for addressing the combined issue of classimbalance and concept drift are lacking in understating of correlation of oneproblem with the other. This work studies the association between conceptdrift and class imbalance ratio and then demonstrates how changes in classimbalance ratio along with concept drift affect the classifier’s *** analyzed the effect of both the issues on minority and majority classesindividually. To do this, we conducted experiments on benchmark datasetsusing state-of-the-art classifiers especially designed for data stream ***, recall, F1 score, and geometric mean were used to measure theperformance. Our findings show that when both class imbalance and conceptdrift problems occur together the performance can decrease up to 15%. Ourresults also show that the increase in the imbalance ratio can cause a 10% to15% decrease in the precision scores of both minority and majority *** study findings may help in designing intelligent and adaptive solutionsthat can cope with the challenges of non-stationary data streams like conceptdrift and class imbalance.

关键词： Classification data streams class imbalance concept drift class imbalance ratio

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Disentangled latent factors for muti-cause treatment effect estimation 6

Disentangled latent factors for muti-cause treatment effect ...

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2024 6th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2024

作者： Zhao, Zhuoyue Wang, Haotian Xu, Liyang Wang, Qian Tang, Yuhua Department of Intelligent Data Science National University of Defense Technology Changsha410073 China Intelligent Game and Decision Lab. Academy of Military Science Beijing100071 China Institute for Quantum Information State Key Laboratory of High-Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

Existing methods estimate treatment effects from observational data and assume that covariates are all confounders. However, observed covariates may not directly represent confounding variables that influence both treatment and outcome. They always include variables that only affect the treatment or the outcome. In addition, for multi-dimensional binary treatments, disentangled methods are mainly designed for binary variables and ignore the impact of multi-cause treatment variables on the inference of latent factors. To address these two issues, based on variable decomposition and proxy inference, we propose the Disentangled Latent Factors for Multi-cause Treatment Estimation (DEMTE) algorithm. It utilizes an identifiable autoencoder to infer and disentangle latent factors based on the joint distribution of variables in observational data. DEMTE evaluates the treatment effect on the disentangled factors. Synthetic experiments and semi-synthetic experiments demonstrate the effectiveness of the inference and disentanglement techniques and our method achieves more accurate treatment effect estimation. © 2024 Institute of Physics Publishing. All rights reserved.

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Hybrid Signal Integrity Modeling and Analysis of Heterogeneous Integrated System With Neuromorphic Darwin Chip

IEEE Transactions on Signal and Power Integrity

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IEEE Transactions on Signal and Power Integrity 2024年 3卷 37-46页

作者： Chen, Quankun Ma, Hanzhi Li, Da Tao, Tuomin Tan, Shurun Liu, En-Xiao Schutt-Aine, Jose Li, Er-Ping Zhejiang University Key Laboratory of Advanced Micro/Nano Electronic Devices and Smart Systems and Applications College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang University University of Illinois at Urbana-Champaign Institute Haining314400 China A∗star Institute of High Performance Computing Singapore138632 Singapore University of Illinois at Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL61820 United States

This article introduces a comprehensive approach for designing and analyzing signal integrity in heterogeneous integrated systems that incorporate neuromorphic Darwin chips. The proposed integrated system architecture includes a neuromorphic Darwin chip, digital signal processing unit, microcontroller unit, field programmable gate arrays, and coding and decoding modules to encode and reconstruct analog spiking signals. The study evaluates the encoding module and the heterogeneous integration structure and conducts signal integrity analysis. To achieve optimal signal integrity performance, the article proposes a novel binocular eye diagram analysis technique. This innovative approach guides the encoding algorithm modification and improves the overall system performance. This research is the first to combine joint field-circuit simulation, heterogeneous integration modeling, and signal integrity analysis of the Darwin neuromorphic chip, and it is expected to serve as a valuable reference for future studies on similar systems. © 2022 IEEE.

关键词： Neural networks

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Cyberattacks against Direct Load Control of Residential Electric Water Heaters in Smart Grids

Cyberattacks against Direct Load Control of Residential Elec...

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2022 IEEE Power and Energy Society Innovative Smart Grid Technologies Conference, ISGT 2022

作者： Youssef, El-Nasser S. labeau, Fabrice Kassouf, Marthe Alarie, Stéphane McGill University Department of Electrical and Computer Engineering MontrealQC Canada Hydro-Quebec's Research Institute Data Science and High Performance Computing Unit VarennesQC Canada

ISBN: (数字)9781665437752

ISBN: (纸本)9781665437752

The invasive deployment of digital technologies in power grids increases their exposure to cyber threats. In this paper, we study a type of load-altering cyberattack that targets peak shaving programs wherein a utility directly controls the loads of domestic electric water heaters. We consider a cyberattack scenario in which an adversary gains access to the advanced metering infrastructure and sends malicious activation commands to a large number of water heaters forcing them to simultaneously switch on in the midst of a peak shaving period, thus causing a sudden, large power demand that could lead to a system-wide blackout. We develop a simulation environment to simulate the loads of a population of electric water heaters under different operating conditions as well as under this type of cyberattack. Then, we propose a cybersecurity-by-design approach to mitigate the risk of such cyberattack. The efficacy of the proposed solution is analyzed using software experiments. © 2022 IEEE.

关键词： Cybersecurity

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CEER:Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

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computer Systems science & engineering 2023年第6期45卷 2587-2602页

作者： Sayyed Mudassar Shah Tariq Hussain Babar Shah Farman Ali Khalid Zaman Kyung-Sup Kwak Institute of Computer Science&Information Technology the University of Agriculture Peshawar25000Pakistan High Performance Computing and Networking Institute National Research Council(ICAR-CNR)Naples80131Italy College of Technological Innovation Zayed UniversityDubai19282UAE Department of Software Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Inha UniversityIncheon22212Korea

Underwater acoustic sensor networks(UWASNs)aim to find varied offshore ocean monitoring and exploration *** most of these applications,the network is composed of several sensor nodes deployed at different depths in the *** nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level;these nodes need multihop communication facilitated by a suitable routing *** this research work,a Cluster-based Cooperative Energy Efficient Routing(CEER)mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH *** optimal role of clustering and cooperation provides load balancing and improves the network *** simulation results using MATlab show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol,i.e.,the average end-to-end delay of CEER was 17.39,Co-UWSN was 55.819 and LEACH was *** addition,the average total energy consumption of CEER was 9.273,Co-UWSN was 12.198,and LEACH was *** packet delivery ratio of CEER was 53.955,CO-UWSN was 42.047,and LEACH was *** stability period CEER was 130.9,CO-UWSN was 129.3,and LEACH was *** obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

关键词： Cluster head co-UWSN UWSN relay LEACH CEER

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Identification of Key Genes as Potential Drug Targets for Gastric Cancer

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Tsinghua science and Technology 2023年第4期28卷 649-664页

作者： Md.Tofazzal Hossain Md.Selim Reza Yin Peng Shengzhong Feng Yanjie Wei Center for High Performance Computing Joint Engineering Research Center for Health Big Data Intelligent Analysis TechnologyShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100049China Department of Statistics Bangabandhu Sheikh Mujibur Rahman Science and Technology UniversityGopalganj 8100Bangladesh Guangdong Provincial Key Laboratory for Genome Stability and Disease Prevention and Regional Immunity and Diseases Department of PathologyShenzhen UniversityShenzhen 518060China

Gastric cancer(GC)is one of the most common cancers and ranks the third in cancer mortality all over the *** goal of this study was to identify potential hub-genes,highlighting their functions,signaling pathways,and candidate drugs for the treatment of GC *** used publicly available next generation sequencing(NGS)data to identify differentially expressed(DE)*** top DE genes were mapped to STRING database to construct the protein-protein interaction(PPI)network and top hub genes were selected for further *** found a total of 1555 DE genes with 870 upregulated and 685 downregulated genes in *** selected the top 400(200 upregulated and 200 downregulated)genes to construct a PPI network and extracted the top 15 hub *** gene ontology(GO)term and kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analyses of the 15 hub genes exposed some important functions and signaling pathways that were significantly associated with GC *** survival analysis of the hub genes disclosed that the lower expressions of the three hub genes CDH2,COL4A1,and COL5A2 were associated with better survival of GC *** three genes might be the candidate biomarkers for the diagnosis and treatment of ***,we considered 3 key proteins(genomic biomarkers)(COL4A1,CDH2,and CO5A2)as the drug target proteins(receptors),performed their docking analysis with the 102 meta-drug agents,and found Everolimus,Docetaxel,Lanreotide,Venetoclax,Temsirolimus,and Nilotinib as the top ranked 6 candidate drugs with respect to our proposed target proteins for the treatment against GC ***,the proposed drugs might play vital role for the treatment against GC patients.

关键词： gastric cancer hub genes candidate genes molecular docking candidate drugs

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A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization 27

A First-Order Multi-Gradient Algorithm for Multi-Objective B...

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27th European Conference on Artificial Intelligence, ECAI 2024

作者： Ye, Feiyang Lin, Baijiong Cao, Xiaofeng Zhang, Yu Tsang, Ivor W. Department of Computer Science and Engineering Southern University of Science and Technology China Australian Artificial Intelligence Institute University of Technology Sydney Australia The Hong Kong University of Science and Technology Guangzhou China School of Artificial Intelligence Jilin University China Shanghai Artificial Intelligence Laboratory China Centre for Frontier AI Research Agency for Science Technology and Research Singapore Institute of High Performance Computing Agency for Science Technology and Research Singapore School of Computer Science and Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781643685489

In this paper, we study the Multi-Objective Bi-Level Optimization (MOBLO) problem, where the upper-level subproblem is a multi-objective optimization problem and the lower-level subproblem is for scalar optimization. Existing gradient-based MOBLO algorithms need to compute the Hessian matrix, causing the computational inefficient problem. To address this, we propose an efficient first-order multi-gradient method for MOBLO, called FORUM. Specifically, we reformulate MOBLO problems as a constrained multi-objective optimization (MOO) problem via the value-function approach. Then we propose a novel multi-gradient aggregation method to solve the challenging constrained MOO problem. Theoretically, we provide the complexity analysis to show the efficiency of the proposed method and a non-asymptotic convergence result. Empirically, extensive experiments demonstrate the effectiveness and efficiency of the proposed FORUM method in different learning problems. In particular, it achieves state-of-the-art performance on three multi-task learning benchmark datasets. © 2024 The Authors.

关键词： Optimization algorithms

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis 2

Complex Permeability Determination for EE Core Based on Flex...

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2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Jie, Huamin Zhao, Zhenyu Chang, Yongqi Wang, Changdong Jiang, Shiqi Gao, Richard Xian-Ke See, Kye Yak School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of High Performance Computing A*STAR Singapore Singapore

ISBN: (纸本)9798331509552

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz. ©2024 IEEE.

关键词： Magnetic flux

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Health Care and Management based on Block chain and Machine Learning

Health Care and Management based on Block chain and Machine ...

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2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent engineering, ICECONF 2023

作者： Bakh, Ruhi Sarkar, VeenaNair Auguskani, Jerlin Priya Lovelin Poornima, Galiveeti Shetty, Monali N. Raj, Meerjumla Govind Dr. Ambedkar Institute of Management Studies and Research India Iihmr University India Department of Nursing College Aldrab Jazan University Saudi Arabia High Performance Computing Lab School of Computer Science and Information Science Presidency University Bengaluru India Computer Science Engineering Fr. Crce India St. Martin and #39 s Engineering College Survey No. 563 Dulapally Kompally Telangana Secunderabad500100 India

ISBN: (纸本)9798350334357

With the coming of technology, we currently have an immense measure of information accessible in each field, making it conceivable to offer responses to many issues. We will utilize machine learning and block chain technology to resolve issues with healthcare information the executives in this review. With the guide of machine learning, separating just the relevant information from the data is plausible. Using prepared calculations, this is finished. The reliability of information trade turns into a test after this information has been put away. This is where block chain technology is valuable. Block chain technology's agreement guarantees that information is credible and exchanges are secure. By putting the patient at the focal point of the healthcare framework and upgrading the security and interoperability of health information, block chain technology can possibly further develop health care organization. This article fundamentally centres around settling issues with healthcare information the board using Block chain technology and including a few urgent highlights utilizing Machine Learning. The freshest technology, block chain, offers a strong and secure groundwork. With these offices, block chain has gotten some momentum in an assortment of use areas, including the food business, store network the board, energy, government support offices, and healthcare. © 2023 IEEE.

关键词： Health care

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