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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Jung Uk Kim Yong Man Ro Image and Video Systems Lab School of Electrical Engineering KAIST South Korea Department of Computer Science and Engineering Kyung Hee University South Korea

Although multispectral pedestrian detection studies have shown remarkable detection performances, they are still vulnerable to adversarial attacks. We see the similarity relations between object candidates were not maintained because of the adversarial attacks, resulting in performance degradation. In this paper, we introduce a new method that can preserve the similarity relation between candidates against adversarial attacks using multispectral knowledge. First, we propose Similarity Relation Generation (SRG) module to generate the optimal similarity relation between clean candidates by referring to the two modalities (color and thermal). Second, we propose Adversarial Similarity Relation Preserving (ASRP) module to guide the similarity relation between adversarial candidates to be similar to that of the clean candidates. By maintaining the relationship between candidates, our multispectral detector can distinguish between pedestrian/background classes even in adversarial attacks. Comprehensive experimental results show that our method conspicuously improves the adversarial robustness.

关键词： Degradation Detectors Color Signal processing Robustness Acoustics Speech processing

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AnDet: ML-Based Anomaly Detection of UEs in a Multi-cell B5G Mobile Network for Improved QoS

AnDet: ML-Based Anomaly Detection of UEs in a Multi-cell B5G...

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International Conference on Computing, Networking and Communications (ICNC)

作者： Amar Sinha Anmol Agrawal Sandip Roy Venkanna Uduthalapally Debanjan Das Rajarshi Mahapatra Sachin Shetty Department of Computer Science and Engineering IIIT Naya Raipur India Department of Electronics and Communication Engineering IIIT Naya Raipur India Center for Secure & Intelligent Critical Systems Old Dominion University Virginia USA

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

The rise of 5G technology has revolutionized wireless communication, ushering in a new era of unparalleled connectivity. Approaching Beyond 5G networks, Software Defined Networks have emerged as a promising paradigm to enhance flexibility and scalability in cellular networks. However, the challenge of 5G is to ensure the network's performance based on the different Quality of Service requirements for offering interactive services. Proactive detection of anomalies can significantly improve network performance. To address this issue, we present AnDet, a robust ML-based model specifically designed for anomaly detection in SDN-enabled B5G cellular networks. Next, we deploy the proposed AnDet for anomaly detection on SDN-enabled B5G cellular networks, enhancing overall network performance and reliability. Moreover, we incorporate Explainable AI approaches into the AnDet model to ensure transparency and interpretability. Finally, we capture different performance metrics for models and deployments to evaluate the proposed solution. The extensive simulation results show that AnDet effectively identifies anomalies in SDN-enabled cellular networks operating in B5G environments, achieving an impressive 97.2% accuracy in anomaly detection.

关键词： Cellular networks Wireless communication Measurement 5G mobile communication Simulation Scalability Quality of service

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Enhancing Ship Detection on Satellite Images with Modified DeepLabV3+

Enhancing Ship Detection on Satellite Images with Modified D...

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Artificial Intelligence and Emerging Technology (Global AI Summit), International Conference on

作者： Rohit Sharma Shubham Dahatonde Srimanta Kumar Acharjya Sourabh Singh Verma Vijaypal Singh Dhaka Ramesh Singh Rawat School Of Computing & Intelligent Systems Manipal University Jaipur Jaipur India Department of Computer Science and engineering C. V Raman Global University Bhubaneswar India Dept. of computer Science and Engg Graphic Era deemed to be University Deharadun Uttrakhand India

ISBN: (数字)9798350379716

ISBN: (纸本)9798350379723

This paper presents a advance approach for ship detection in satellite imagery utilizing a modified DeepLabV3+ architecture, specifically designed to overcome the challenges inherent in such data. The proposed model features an enhanced feature extraction process and a refined atrous spatial pyramid pooling (ASPP) module, which together improve the detection of ships across various sizes and shapes. Comprehensive experiments on publicly available satellite datasets reveal that the modified DeepLabV3+ significantly outperforms existing state-of-the-art methods, achieving an accuracy of 98%. These findings demonstrate the model's robust ability to identify and localize ships in complex maritime settings, offering promising potential for improved maritime situational awareness and operational efficiency.

关键词： Training Image segmentation Accuracy Land surface Feature extraction Data models Robustness Satellite images Marine vehicles Artificial intelligence

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Learner Action Patterns in the Problem-Solving Process Related to program Code Composition Based on Tracking System Activities 7

Learner Action Patterns in the Problem-Solving Process Relat...

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7th International Conference on Informatics and Computing, ICIC 2022

作者： Syahidi, Aulia Akhrian Supianto, Ahmad Afif Hirashima, Tsukasa Watanobe, Yutaka Politeknik Negeri Banjarmasin Smart City Information System Applied Undergraduate Program Banjarmasin City Indonesia Research Center for Data and Information Sciences Bandung City Indonesia Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama Learning Engineering Laboratory Higashihiroshima Japan University of Aizu Division of Information Systems Department of Computer Science and Engineering Fukushima AizuWakamatsu Japan

ISBN: (纸本)9798350345711

Learning activities are an indicator of the learner's desire to learn during the learning process. The pattern of learner action is related to learning activities. In this case, in extracting the learning process, it is necessary to collect a lot of data through analysis of the learning process. The purpose of this study is to recommend and report the performance of an activity tracking system equipped with visual artifacts as an educational data mining approach to analyze action patterns when learners complete the arrangement of program code lines in each programming problem. In this study, data were taken from activity recordings when learners used interactive learning media for a basic programming subject called TOLSYASUPI-EduMed which had problem-solving learning models embedded in their interactions. Learning Analytics is used as a method of this research and data relationships from learner actions during the learning process using the 'if-then' rule. Log data is used for recording and detecting activities carried out by learners. We confirm that the results of the study are based on the findings of the data relationship that if the lines of program code are too long (more than five lines) then almost all learners experience a bottleneck condition. The completion time of each question and the number of iterations in completing the program code lines for each question have also been recorded and have a pattern of connection between the data. The information that has been obtained is then forwarded to teachers or stakeholders as key information to make appropriate feedback to learners based on the results as a means of analyzing and evaluating the programming learning process. © 2022 IEEE.

关键词： Data mining

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On the Generalization of Machine-Learning-aided QoT Estimation in Optical Networks 32

On the Generalization of Machine-Learning-aided QoT Estimati...

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32nd Wireless and Optical Communications Conference, WOCC 2023

作者： Gao, Hanyu Zhang, Liang Zhang, Bin Chen, Xiaoliang Li, Zhaohui School of Electronics and Information Technology Sun Yat-sen University Guangdong Provincial Key Labratory of Optoelectronic Information Processing Chips and Systems Guangzhou China Southern Marine Science and Engineering Guangdong Laboratory Zhuhai China George Mason University Department of Electrical and Computer Engineering FairfaxVA22030 United States

ISBN: (纸本)9798350337150

This paper presents a composable machine learning method for generalizing the quality-of-transmission (QoT) metric estimation in optical networks. The composable machine learning approach characterizes this metric for lightpaths of arbitrary lengths by compositions of launch, propagation and readout modules. Results verify the feasibility of the design and show its successful application in facilitating autonomous lightpath provisioning. © 2023 IEEE.

关键词： Fiber optic networks

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Diabetic Retinopathy Imaging: Network Exudate Detection to Classify Abnormalities

Diabetic Retinopathy Imaging: Network Exudate Detection to C...

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Intelligent Computing and Control for engineering and Business systems (ICCEBS)

作者： A. Chinnasamy P. Selvakumari Department of Data Science and Business Systems school of computing SRMIST kattankulathur campus Chennai Department of Computer Science and Engineering Chennai Institute of Technology Chennai Anna University

The DR becomes increasingly common, there is a need to automatically extract and classify disease severity. Due to diabetes problems, about 2% of people with this disease become completely blind, and DR complications make him 10% visually impaired if he has diabetes for 15 years. Furthermore, it plays an important role in the progression of blindness in middle-aged and older adults. If the disease is not recognized as soon as possible, patients can experience a severe stage of irreversible blindness. The shortage of ophthalmologists is a serious problem for the growing number of diabetic patients. Hard exudates must be found to screen and assist in disease monitoring and diagnosis. Therefore, Lloyd's clustering technique was used in this work.

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Identifying Flakiness in Quantum programs

Identifying Flakiness in Quantum Programs

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International Symposium on Empirical Software engineering and Measurement, ESEM

作者： Lei Zhang Mahsa Radnejad Andriy Miranskyy Department of Information Systems University of Maryland Baltimore County Baltimore USA Department of Computer Engineering Isfahan Branch Islamic Azad University Isfahan Iran Department of Computer Science Toronto Metropolitan University Toronto Canada

In recent years, software engineers have explored ways to assist quantum software programmers. Our goal in this paper is to continue this exploration and see if quantum software programmers deal with some problems plaguing classical programs. Specifically, we examine whether intermittently failing tests, i.e., flaky tests, affect quantum software development. To explore flakiness, we conduct a preliminary analysis of 14 quantum software repositories. Then, we identify flaky tests and categorize their causes and methods of fixing them. We find flaky tests in 12 out of 14 quantum software repositories. In these 12 repositories, the lower boundary of the percentage of issues related to flaky tests ranges between 0.26% and 1.85% per repository. We identify 46 distinct flaky test reports with 8 groups of causes and 7 common solutions. Further, we notice that quantum programmers are not using some of the recent flaky test countermeasures developed by software engineers. This work may interest practitioners, as it provides useful insight into the resolution of flaky tests in quantum programs. Researchers may also find the paper helpful as it offers quantitative data on flaky tests in quantum software and points to new research opportunities.

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SPD Miscoordination in PV systems Due to Lightning Strikes

SPD Miscoordination in PV Systems Due to Lightning Strikes

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International Conference on Applied and Theoretical Electricity (ICATE)

作者： Osmel Pérez Baluja Bernardo Yaser León Avila Carlos A. García Vázquez Daniel Tudor Cotfas Petru Adrian Cotfas Orlys E. Torres Breffe Department of Electronics and Computers Faculty of Electrical Engineering and Computer Science Transilvania University of Braşov Brasov Romania Department of Electric Power Systems Faculty of Electrical Engineering Technological University of Havana Havana Cuba

ISBN: (数字)9798350388107

ISBN: (纸本)9798350388114

This study deals with the coordination of surge protection devices (SPD) in photovoltaic systems (PV). A PV farm model was developed in MATLAB Simulink with all the main components, solar panels, converter, grounding system, power transformer, cables in the DC and AC branches with their capacitances, and surge protection device throughout the installation. It was found that when lightning strikes the grounding system or in the vicinity of the PV installation, the coordination among SPD types 1, 2, and 3 is lost. Miscoordination can cause damage to several elements of the PV system, mainly the inverters. Finally, solutions were proposed to avoid SPD miscoordination during lightning strikes.

关键词： Grounding Software packages Lightning Surge protection Stars Switches Inverters Power transformers Solar panels Fault current limiters

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Total Harmonics Distortion Prediction at the Point of Common Coupling of industrial load with the grid using Artificial Neural Network

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Energy and AI 2023年第4期14卷 294-303页

作者： Emenike Ugwuagbo Adeola Balogun Biplob Ray Adnan Anwar Chikodili Ugwuishiwu Centre for Space Transport and Propulsion (CSTP)Epe1 LASU Epe driveLagos106101Nigeria Department of Electrical&Electronics Engineering University of LagosAkoka101017LagosNigeria Centre for Intelligent Systems(CIS) School of Engineering and TechnologyCQ UniversityNorman Gardens4701RockhamptonAustralia Strategic Centre for Cyber Security Research Institute(CSRI) School of Information TechnologyDeakin UniversityGeelong3216MelbourneAustralia Department of Computer Science University of NigeriaNsukka410001EnuguNigeria

Power quality challenges have generated a lot of disputes between utilities,customers,network operators,and equipment manufacturers around the world as regards the share of responsibility for power quality solutions,this results in different levels of financial and technical losses for both the network operators and the *** of the major consequences of the operation of heavy-duty factories globally is the corruption of power quality at the point of common coupling(PCC).In order to quantify the harmonics contribution at the PCC by industrial consumers,this paper presents three-phase total harmonics distortion of current(THDi)prediction model at the *** proposed artificial neural network(ANN)models use a multilayer perceptron neural network(MLPN)to predict three-phase total harmonic *** input parameter used in the models is easily measured with basic power *** model was trained with input parameters captured at 33 kV and 132 kV voltage levels using power quality meters at five(5)different steel manufacturing ***(8)different models were designed,trained,validated,and tested with different combinations of input parameters,number of hidden layers,and number of neurons in the hidden *** results show that the model with two hidden layers which uses four major power parameters(Current,apparent power,reactive and active power)as input parameters in the training model had the best performance with a 95.5%coefficient of correlation between the measured THDi and the predicted THDi.

关键词： Total harmonics distortion(THD) Power quality(PQ) Artificial neural network(ANN)

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Retinal Image Analysis for Early Deduction of Diabetic Retinopathy

Retinal Image Analysis for Early Deduction of Diabetic Retin...

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International Conference on Advanced Computing and Communication systems (ICACCS)

作者： A. Chinnasamy P. Selvakumari Department of Data Science and Business Systems School of Computing SRMIST Chennai India Department of Computer Science and Engineering Chennai Institute of Technology Anna University Chennai India

The prevalence of DR is steadily rising, which necessitates the automatic disease severity extraction and classification. About 2% of those with this illness are entirely blind because of the diabetic mellitus problem and 10% get vision impairment after 15 years of diabetes as a result of the DR complication. It is also a significant contributor to blindness in both middle aged and older age groups. The patient may develop to severe stages of irreversible blindness if the condition is not detected early. The growing number of diabetic patients face a major issue due to a lack of ophthalmologists. It is suggested that an automated DR screening system be created to aid the ophthalmologist in making decisions. One of the primary symptoms of the DR is hard exudates. The detection of hard exudates is crucial for screening purposes and aids in disease monitoring and diagnosis. Thus, utilising Lloyd’s clustering technique, this work offered a unique techniques to segment the exudates and irregularities in DR were found.

关键词： Support vector machines Image segmentation Visual impairment Blindness Blood vessels Retina Time measurement

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