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2023 IEEE International Conference on Industrial Technology, ICIT 2023

作者： Bregu, Ornela Zamzami, Nuha Bouguila, Nizar Concordia Institute for Information Systems Engineering Concordia University Montreal Canada College of Computer Science and Engineering University of Jeddah Department of Computer Science and Ai Jeddah Saudi Arabia

ISBN: (纸本)9798350336504

In this paper, we have applied a density-based regression technique to predict the age of a human brain based on Magnetic Resonance Images. We propose four different multivariate discrete distributions to accommodate different mean-covariance and correlation structures, given the challenging nature of medical datasets. Then, we use a novel Minorization-Maximization framework to address the issue of high dimensional optimization. Finally, to handle the time and memory requirements of processing large amounts of high-resolution images, we have adopted a real-time framework, where the learning behavior is gradually improved as new data become available. © 2023 IEEE.

关键词： Forecasting

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"There is a Damn Hello on the Social Media!" Insights into Public Risk Communication in the Digital Age 18th

"There is a Damn Hello on the Social Media!" Insights into P...

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18th IFIP WG 11.12 International Symposium on Human Aspects of Information Security and Assurance, HAISA 2024

作者： Große, Christine Division of Computer Science Electrical and Space Engineering Department of Digital Services and Systems Luleå University of Technology Luleå971 87 Sweden

ISBN: (纸本)9783031725586

The ability to handle threats, such as disinformation, manipulation of public opinion, and disruption of critical supplies, is becoming increasingly important, thus, necessitating, among other strategies, efforts to establish a proper risk communication to the public. This paper addresses the need for more empirical research in this area to contribute to the development of an in-depth understanding of public risk communication that includes information-related threats and cyber issues. The study involves officials of three public organizations entrusted with safety and security in society: the police, the rescue service, and the county administrative board of a county in the middle of Sweden. The results detail the recognition of risks to be communicated, the organization of the communication process, the messages that these actors seek to bring forth, and to whom as well as challenges of public risk communication in the digital era. The findings indicate that information-related and cyber risks are increasingly essential to consider as an additional layer of public communication. Two implications emerged as particularly important: (1) all communication about risks and crises must consider the systemic risk of mis- and disinformation, and (2) tailored communication about the risks interrelated with disinformation should use human-centered, dialogue-based, and moderated approaches. Further research can focus on associated challenges, considering the distribution of responsibilities, inter-organizational information sharing and cooperation, and the possibly stochastic effects on critical (information) infrastructures and, ultimately, societal values. © IFIP International Federation for Information Processing 2025.

关键词： Stochastic systems

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Intelligent Fire Detection and Alert System with Sensing Capabilities Powered by Artificial Intelligence 3

Intelligent Fire Detection and Alert System with Sensing Cap...

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3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Yasir Abdullah, R. Hariharan, V.C. Nithin, K.M. Swetha, V. Vijayaalayan, A. Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Coimbatore India

ISBN: (纸本)9798350322842

Artificial Intelligence (AI) has become a popular tool to perform video surveillance in order to detect and identify humans, vehicles, objects, and events. By analyzing audio and images via computer software programs, AI model can identify people's faces and other emerging technologies that are commonly used in security monitoring systems. The main purpose of this study is to explore the different areas, where Artificial Intelligence (AI) can be used to detect and prevent fires. © 2023 IEEE.

关键词： Face recognition

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MayGAN:Mayfly Optimization with Generative Adversarial Network-Based Deep Learning Method to Classify Leukemia Form Blood Smear Images

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computer systems science & engineering 2023年第8期46卷 2039-2058页

作者： Neenavath Veeraiah Youseef Alotaibi Ahmad F.Subahi Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P.521180India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

Leukemia,often called blood cancer,is a disease that primarily affects white blood cells(WBCs),which harms a person’s tissues and *** condition may be fatal when if it is not diagnosed and recognized at an early *** physical technique and lab procedures for Leukaemia identification are considered *** is crucial to use a quick and unexpected way to identify different forms of *** screening of the morphologies of immature cells is essential for reducing the severity of the disease and reducing the number of people who require *** deep-learning(DL)model-based segmentation and categorization techniques have already been introduced,although they still have certain *** order to enhance feature extraction and classification in such a practical way,Mayfly optimization with Generative Adversarial Network(MayGAN)is introduced in this ***,Generative Adversarial System(GAS)is integrated with Principal Component Analysis(PCA)in the feature-extracted model to classify the type of blood cancer in the *** semantic technique and morphological procedures using geometric features are used to segment the cells that makeup *** lymphocytic Leukaemia(ALL),acute myelogenous Leukaemia(AML),chronic lymphocytic Leukaemia(CLL),chronic myelogenous Leukaemia(CML),and aberrant White Blood Cancers(WBCs)are all successfully classified by the proposed MayGAN *** proposed MayGAN identifies the abnormal activity in the WBC,considering the geometric *** with the state-of-the-art methods,the proposed MayGAN achieves 99.8%accuracy,98.5%precision,99.7%recall,97.4%F1-score,and 98.5%Dice similarity coefficient(DSC).

关键词： Leukemia blood smear images optimization classification neural networks

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Survey of Online Exam Proctoring Model to Detect Cheating Behavior based on Face Recognition 8

Survey of Online Exam Proctoring Model to Detect Cheating Be...

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8th International Conference on systems and Informatics, ICSAI 2022

作者： Rabiha, Sucianna Ghadati Kartowisastro, Iman Herwidiana Setiawan, Reina Budiharto, Widodo Bina Nusantara University Binus Graduate Program - Computer Science. Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Computer Science Department Binus Graduate Program - Computer Science Computer Engineering Department Jakarta11480 Indonesia Bina Nusantara University School of Computer Science Computer Science Department Binus Graduate Program - Computer Science Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9781665474481

Exams are an important component of any educational program, including online education. In any test, there is a possibility of cheating, so its detection and prevention is important. This study aims to conduct an in-depth study of the online exam monitoring model approach based on facial recognition used to detect cheating. Based on the inclusion and exclusion criteria designed, 13 selected studies were obtained. From these studies, we conducted further analysis regarding the Face Detection Method, Face Recognition Method, Initial Feature, Behavior Analysis and Evaluation Metrics used in each study so as to provide answers to research questions. the most frequently used Face detection method was Viola-Jones with a presentation of 20%, then CNN and MTCNN with a total presentation of 21%. The most widely used face recognition method in selected studies is CNN and metrics Accuracy is one of the most frequently used evaluations with a percentage of 33%. While the features that are usually used to detect cheating during online exams include facial motion and head pose which occupies the first position. The second is eye movement, then multiple faces gaze estimation and facial expression is in third place. Other features that also play a role in analyzing cheating behavior are mouth detection, facial vector, landmark location, gesture and posture. © 2022 IEEE.

关键词： Face recognition

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Assessing the Effects of Blackhole Attacks on MANET Reliability and Security

Assessing the Effects of Blackhole Attacks on MANET Reliabil...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Fadhil, Saif Aamer Najim, Ali Hamza Ali Alheeti, Khattab M. Mohd Satar, Nurhizam Safie Abdallah Hashim, Aisha Hassan Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq Department of Computer Technical Engineering Baghdad10011 Iraq College of Computer and Information Technology Computer Networking Systems Department University of Anbar Anbar Iraq Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

Mobile Ad Hoc Networks (MANETs) are characterized by some important attributes, including infrastructure, mobile, and dynamic nature, which makes them have vast applications in different areas of computer networks. The black hole attack falls among the strongly criticized security threats within the framework of the MANETs. This deceptive behavior captures data packets from a source destined for the malicious node and then declines them when they are received. This paper comprehensively reviews prior studies done to analyze and mitigate black hole attacks in MANETs. Besides this, we will conduct a comparative analysis of the research above projects. The present paper extends prior work by actually performing the black hole assault simulations in a MANETs environment. This is done with the aid of the NS2 simulator and the Ad Hoc On-Demands Distance Vector (AODV) routing protocol. In this study, the black hole attack is analyzed and the consequences of the attack are assessed in terms of the system performance and security. We analyze crucial parameters like end-to-end latency, PDR, packet drop, and throughput to evaluate the consequences of this assault. From our results derived from the analysis of our simulations, we aim to present substantial points to do with the impacts of blackhole attacks on MANETs. In this way, our goal is to participate in the perpetually evolving efforts aimed at enhancing the security and reliability of such dynamic networks. © 2024 IEEE.

关键词： Mobile ad hoc networks

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Algorithms for the Collaborative Delivery Problem with Monitored Constraints 19th

Algorithms for the Collaborative Delivery Problem with Mo...

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19th International Conference and Workshops on Algorithms and Computation, WALCOM 2025

作者： Blank, Lotte Huynh, Kien C. Luo, Kelin Naredla, Anurag Murty Institute of Computer Science University of Bonn Bonn Germany Communications and Transport Systems ITN Linköping University Linköping Sweden Department of Computer Science and Engineering University at Buffalo GetzvilleNY United States

ISBN: (纸本)9789819628445

We provide efficient algorithms to solve package delivery problems in which a sequence of drones work together to ‘optimally’ deliver a package from a source s to a target t. The package may be transferred from one drone to another only on a given line on which secure package transfers are ensured (we refer to this as monitored constraints). We allow the source and target to lie outside of this line. The drones have different starting locations, speeds, and rates of fuel consumption. Two notions of optimality are studied—fuel-efficient delivery (minimize total fuel consumption in a successful delivery), and fastest delivery (minimize total time for delivery). © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Drones

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Materials property prediction using feature selection based machine learning technique

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Materials Today: Proceedings 2022年 69卷 710-715页

作者： Valli Priyadharshini, K. Vijay, A. Swaminathan, K. Avudaiappan, T. Banupriya, V. Department of Computer Science and Engineering K.Ramakrishnan College of Technology Trichy India Department of Information Technology M.Kumarasamy College of Engineering Karur India Department of Computer Science and Engineering K.Ramakrishnan College of Engineering Trichy India Department of Computer Science and Business Systems M.Kumarasamy College of Engineering Karur India

An essential role in increasing quality and reducing environmental damage and public safety is played by material performance prediction in materials research. There is still a long way to go before traditional regression analysis models in materials science can accurately capture non-linearities in data, time-consuming predictions, and enormous amounts of data. Because the more features you have, the less accurate your classification will be, hence you need a feature selection method to improve your results. This necessitates the use of modern computer science methods to analyse materials data. Machine learning (ML) has arose in fresh years as a powerful tool for establishing correlations between data and is finding application in the field of materials science due to its generalizability, noise tolerance, and error tolerance. Different materials servicing varied settings can be predicted for their various properties using machine learning techniques based on feature selection. In this research, feature selection-based ML techniques are demonstrated. Comparisons with various computing and input-ranking approaches demonstrate the importance of the suggested model in materials-related challenges. © 2023

关键词： Forecasting

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Sector-Based Incremental Clustering and Scalable Deletion for Real-Time Big Data Streaming Application 2nd

Sector-Based Incremental Clustering and Scalable Deletion fo...

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2nd International Conference on Deep sciences for Computing and Communications, IconDeepCom 2023

作者： Ananthi, M. Mangayarkarasi, T. Department of Computer Science and Business Systems Sri Sairam Engineering College Chennai India Department of Instrumentation and Control Engineering Sri Sairam Engineering College Chennai India

ISBN: (纸本)9783031689079

Massive streaming data is the most current technology for storing and manipulating large quantities of data. Processing the substantial amount of streaming data is still a challenging issue. The speed and throughput can be improved while extracting this huge amount of data by using a dynamic query processing technique. The sector-based incremental clustering indexing and scalable deletion approach is used in this paper to improve the system performance. Stream processing can be more effective and flexible by applying dynamic query processing technique. Incremental clustering using sector-based method and scalable deletion which removes unwanted, spurious data is proposed in this work in order to process incoming streaming data effectively. Incremental clustering is one of the clustering methods used for processing dynamic information. It is not necessary to plan the entire dataset ahead of time in this method which is suitable for live streaming data, because it processes one instance at a time. So, less space and time is used. Various queries with different types of datasets executed using sector based incremental clustering and scalable deletion methods. The proposed system achieves the highest results for more than 90% accuracy with less space and more speed when the execution time and data retrieval are empirically increased compared with conventional approaches. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Data streams

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Histogram-Based Decision Support System for Extraction and Classification of Leukemia in Blood Smear Images

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computer systems science & engineering 2023年第8期46卷 1879-1900页

作者： Neenavath Veeraiah Youseef Alotaibi Ahmad FSubahi Department of Electronics and Communications DVR&DHS MIC Engineering CollegeKanchikacharlaA.P.521180India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al-Qura UniversityMakkah21421Saudi Arabia

An abnormality that develops in white blood cells is called *** diagnosis of leukemia is made possible by microscopic investigation of the smear in the *** training is necessary to complete the morphological examination of the blood smear for leukemia *** paper proposes a Histogram Threshold Segmentation Classifier(HTsC)for a decision support *** proposed HTsC is evaluated based on the color and brightness variation in the dataset of blood smear *** operations are used to crop the nucleus based on automated *** Blood Cell(WBC)segmentation is calculated using the active contour model to determine the contrast between image regions using the color transfer *** entropy-adaptive mask generation,WBCs accurately detect the circularity region for identification of the *** proposed HTsC addressed the cytoplasm region based on variations in size and shape concerning addition and rotation *** in WBC imaging characteristics depends on the cytoplasmic and nuclear *** computation of the variation between image features in the cytoplasm and nuclei regions of the WBCs is used to classify blood smear *** classification of the blood smear is performed with conventional machine-learning techniques integrated with the features of the deep-learning regression *** designed HTsC classifier comprises the binary classifier with the classification of the lymphocytes,monocytes,neutrophils,eosinophils,and abnormalities in the *** proposed HTsC identifies the abnormal activity in the WBC,considering the color and shape *** exhibits a higher classification accuracy value of 99.6%when combined with the other *** comparative analysis expressed that the proposed HTsC model exhibits an overall accuracy value of 98%,which is approximately 3%–12%higher than the conventional technique.

关键词： White blood cells leukemia segmentation histogram blood smear

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