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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Balatsouras, Christos-Panagiotis Karras, Aristeidis Karras, Christos Tsolis, Dimitrios Sioutas, Spyros Group Computer Engineering and Informatics Department Patras26504 Greece

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

On the modern era of Internet of Things (IoT) and Industry 4.0 there is a growing need for reliable wireless long range communications. LoRa is an emerging technology for effective long range communications which can be directly applied to IoT applications. Wireless sensor networks (WSNs) are by far an efficient infrastructure where sensors act as nodes and exchange information among themselves. Distributed applications such as Peer-to-Peer (P2P) networks are inextricably linked with Distributed Hash Tables (DHTs) whereabouts DHTs offer effective and speedy data indexing. A Distributed Hash Table structure known as the Chord algorithm enables the lookup operation of nodes which is a major algorithmic function of P2P networks. In the context of this paper, the inner workings of Chord protocol are highlighted along with an introduced modified version of it for WSNs. Additionally, we adapt the proposed method on LoRa networks where sensors function as nodes. The outcomes of the proposed method are encouraging as per complexity and usability and future directions of this work include the deployment of the proposed method in a large scale environment, security enhancements and distributed join, leave and lookup operations. © 2022 IEEE.

关键词： Internet of things

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Shrinking VOD Traffic via Rényi-Entropic Optimal Transport

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Performance Evaluation Review 2024年第1期52卷 75-76页

作者： Lo, Chi-Jen Marina, Mahesh K. Sastry, Nishanth Xu, Kai Fadaei, Saeed Li, Yong Department of Engineering University of Cambridge United Kingdom School of Informatics The University of Edinburgh United Kingdom School of Computer Science University of Surrey United Kingdom MIT-IBM Watson AI Lab CambridgeMA United States Department of Electronic Engineering Tsinghua University China

In response to the exponential surge in Video on Demand (VOD) traffic, numerous research endeavors have concentrated on optimizing and enhancing infrastructure efficiency. In contrast, this paper explores whether users' demand patterns can be shaped to reduce the pressure on infrastructure. Our main idea is to design a mechanism that alters the distribution of user requests to another distribution which is much more cache-efficient, but still remains 'close enough' (in terms of cost) to fulfil individual user's preference. © 2024 Owner/Author.

关键词： Video on demand

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Federated Learning Models for Intrusion Detection in Industrial IoT Networks 7

Federated Learning Models for Intrusion Detection in Industr...

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7th International Conference on Circuit Power and Computing Technologies, ICCPCT 2024

作者： Prasad, Sanjana Sharma, Ishu Rajendraprasad, Deepashree HKBK College of Engineering Department of Electronics and Communication Engineering Bangalore India Lovely Professional University Department of Computer Science and Engineering Punjab Phagwara India Boston University Department of Health Informatics BostonMA United States

ISBN: (纸本)9798350372816

The Industrial Internet of Things has emerged as an essential tool for building Industry 4.0 and Industry 5.0 where timely information can be retrieved from different scenarios. These devices are highly vulnerable to cyberattacks as heterogeneous types of devices can be used in the infrastructure that may or may not be equipped with standardized security protocols. Artificial intelligence-based methodologies can effectively identify these types of attacks on a prior basis for taking mitigation action. This method raises concerns about data privacy as building a machine learning-based method requires the sharing of network data that can reveal the actual information of industries. The proposed Federated Learning based framework handles this concern by preserving each device's critical data by utilizing the benefits of the decentralized model aggregation. This research work presents the comparison of the proposed framework on the CICIoT2023 dataset with federated averaging and federated proximal techniques for achieving a global model. The performance evaluation of these two aggregation techniques is performed based on metrics of accuracy, loss, precision and recall. The results prove that the federated proximal method achieves higher accuracy in comparison to the federated averaging method. © 2024 IEEE.

关键词： Network intrusion

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Exploiting time-series analysis to predict customers' behavioural dynamics in social networks 13

Exploiting time-series analysis to predict customers' behavi...

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13th International Conference on Information, Intelligence, Systems and Applications, IISA 2022

作者： Rompolas, Gerasimos University of Patras Computer Engineering and Informatics Department Patras Greece

ISBN: (数字)9781665463904

ISBN: (纸本)9781665463904

In the recent years, companies have focused on ways to take advantage of the rich and endless data that flow from the social media. The effective exploitation of such data has a crucial role in businesses' growth and development. Businesses in order to survive in a highly competitive market need to analyze and understand customers' needs and behaviours. This research work addresses the problem of predicting the behavioural dynamics of the customers regarding a brand name, using time-series analytics in social media. While in the existing literature many researchers have focused on studying the individual analytics, in this work we propose a more coarse-grained approach that analyses the overall behavioural dynamics in social networks. In particular, a data mining model is being presented, which exploits users' linguistic and emotional characteristics in social networks, in order to predict the future collective behavioural trends. The purpose of this work is to provide an efficient and automated tool, that will enable businesses to predict the relationships with their customers. Thus, businesses will be able to strengthen and reestablish their bonds with their customers, through appropriate social media marketing campaigns in a timely manner. © 2022 IEEE.

关键词： Data mining

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Analyzing the impact and application of Augmented Reality in Education: The case of students with special educational needs 26

Analyzing the impact and application of Augmented Reality in...

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26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Kapetanaki, Andrianthi Krouska, Akrivi Troussas, Christos Sgouropoulou, Cleo Department of Informatics and Computer Engineering University of West Attica Greece

ISBN: (纸本)9781450398541

This study presents a systematic review of the literature which analyzes the impact and application of Augmented Reality (AR) technology in the tutoring of students with special educational needs. In recent years, Information and Communication Technology (ICT) promotes learning in a pluralistic and multisensory environment that favors students with special educational needs. Augmented Reality is an emerging technology which has been widely used in the field of education, but only few studies are related to special education. This paper investigates the research in AR educational systems addressed to students with special educational needs. In total, 26 studies between 2014 and 2022 were selected and analyzed. Specifically, this systematic review examines the advantages and limitations of AR use in Special Education, the AR platforms and tools used in learning scenarios and the different types of students with special educational needs. © 2022 ACM.

关键词： Students

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Intelligent Modeling Method to Optimal Predictive Model for Metal Powder Injection Molding Gears Using Fuzzy-Logic-Based Multi Objective Design

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International Journal of Fuzzy Systems 2023年第6期25卷 2338-2355页

作者： Huang, Wei-Tai Kung, Chien-Yu Chou, Jyh-Horng Department of Mechanical Engineering National Pingtung University of Science and Technology Pingtung Taiwan Department of Mechanical and Computer-Aided Engineering Feng Chia University Taichung407 Taiwan Department of Healthcare Administration and Medical Informatics Kaohsiung Medical University Kaohsiung807 Taiwan

This study will use intelligent modeling to optimize the metal powder injection molding gear process. The robust process combined with fuzzy theory would be used to find process parameters for optimizing process single and multiple quality characteristics. And establish a reverse transfer neural network and adaptive neuro-fuzzy system prediction model. The model hyperparameter structure will be optimized during the modeling process to improve accuracy. The industry can use it to reduce process uncertainty, cost, and extremely a process innovation. The experimental results are single-objective optimization. After optimizing the parameters, the process target displacement, volume shrinkage rate, and powder concentration, compared with the manufacturer's original process, the improvements are increased by 5.79%, 5.66%, and 1.57%. Optimizing multiple quality characteristics has risen by 5.37%, 5.66%, and 0.31%. In the prediction model building part, after the optimization experiment of hyperparameter setting, the accuracy of the backward pass neural network model can reach 96.99%;the accuracy of the adaptive neuro-fuzzy system model can reach 97.45%. © 2023, The Author(s) under exclusive licence to Taiwan Fuzzy Systems Association.

关键词： Injection molding

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Deploying YOLOV10 for Affordable Real-Time Handgun Detection 22

Deploying YOLOV10 for Affordable Real-Time Handgun Detection

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22nd IEEE International Symposium on Intelligent Systems and informatics, SISY 2024

作者： Zigulic, Nikola Glucina, Matko Frank, Domagoj Lorencin, Ivan Sverko, Zoran Matika, Dario University of Rijeka Faculty of Engineering Rijeka Croatia Istrian University of Applied Sciences Department of Engineering Pula Croatia University North Department of Computer Science and Informatics Koprivnica Croatia Juraj Dobrila University of Pula Faculty of Informatics Pula Croatia University North Department of Electrical engineering Varaždin Croatia

ISBN: (纸本)9798350385601

The development of artificial intelligence is one of the most significant technological innovations that contributes to humanity with its characteristics and facilitates, secures, and improves everyday life. However the challenge arises when the programmer-engineer learns the algorithm of artificial intelligence to perform the proposed task, that is, the challenge lies in the issue of available hardware resources. Artificial intelligence algorithms perform many human-impossible tasks, such as detection and counting, i.e. calculating the interrelationships of individual objects, segmentation of tumors and other malignant diseases, i.e. tissues, classification of specific states of classes of a scene, and many other similar technologies. This research paper examines the possibility of implementing the You Only Look Once algorithm of the tenth generation on certain devices such as an affordable Raspberry Pi, and will discuss the advantages and disadvantages of changes in detection parameters, i.e. inferences to the applied model. In addition, a mock-up of the device will be shown, which will serve to provide timely information about criminals and suspicious persons who possess firearms in different situations, such as normal weather conditions in a populated place or in shops where petty robberies are frequent. The testing will be done using recorded videos in real-time scenarios. Finally, real-time inference or detection in real-time will be tested and the actions that Raspberry will perform will be simulated. The results indicate that the optimal model achieved a precision of 0.938, recall of 9.863, mAP50 of 0.91, and mAP50-95 of 0.739. This was achieved using an image size of 640, IOU threshold of 0.7, confidence threshold of 0.6, and training for 600 iterations with the Stochastic Gradient Descent optimizer, without augmentations, and employing the ONNX inference format. © 2024 IEEE.

关键词： Stochastic systems

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Optimization techniques for the energy efficiency of wireless networks 26

Optimization techniques for the energy efficiency of wireles...

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26th Pan-Hellenic Conference on informatics, PCI 2022

作者： Konstantinos, Mavrommatis University of West Attica Department of Informatics and Computer Engineering Greece

ISBN: (纸本)9781450398541

This paper aims to study the energy efficiency optimization techniques applied to the design and architecture of wireless cellular networks to achieve the reduction of gas emissions in the environment and the improvement of the energy efficiency of mobile networks. The urgent need to reduce energy consumption and protect the environment have now oriented research into new techniques for optimizing the energy efficiency of wireless networks and are a key factor in their design and implementation © 2022 ACM.

关键词： Wireless networks

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An Explainable Artificial Intelligence model in the assessment of Brain MRI Lesions in Multiple Sclerosis using Amplitude Modulation - Frequency Modulation multi-scale feature sets 24

An Explainable Artificial Intelligence model in the assessme...

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24th International Conference on Digital Signal Processing, DSP 2023

作者： Nicolaou, Andria Kakas, Antonis Pattichis, Constantinos S. Pattichis, Marios S. Fotso, Kevin Loizou, Christos P. Pantzaris, Marios Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering and Computer Engineering University of New Mexico United States Department of Electrical Engineering and Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Cyprus Institute of Neurology and Genetics Nicosia Cyprus

ISBN: (纸本)9798350339598

The objective of this study was to implement an explainable artificial intelligence (AI) model with embedded rules to assess Multiple Sclerosis (MS) disease evolution based on brain Magnetic Resonance Imaging (MRI) multi-scale lesion evaluation. Amplitude Modulation-Frequency Modulation (AM-FM) features were extracted from manually segmented brain MS lesions obtained using MRI and were labeled with the Expanded Disability Status Scale (EDSS). Machine learning models were used to classify the MS subjects with a benign course of the disease and subjects with advanced accumulating disability. Rules were extracted from the selected model with high accuracy and then were modified to perform argumentation-based reasoning. It is demonstrated that the proposed explainable AI modeling can distinguish MS subjects and give meaningful information to track the progression of the disease. Future research will examine more subjects and add new feature sets and models. © 2023 IEEE.

关键词： Frequency modulation

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An Improved Structure for Academic Information Services through AI Chatbots

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Journal of engineering Science and Technology Review 2023年第5期16卷 164-173页

作者： Ula, Mutammimul Hardi, Richki Hipiny, Irwandi Department of Information Systems Faculty of Engineering Universitas Malikussaleh Aceh Indonesia Department of informatics Universitas Mulia Balikpapan Indonesia Faculty of Computer Science and Information Technology Universiti Malaysia Sarawak Sarawak Malaysia

Academic information service is the most critical factor that must be considered in a university. Service quality is an important indicator affecting all academics’ satisfaction and loyalty. Improvement of information services on campus has been a lot of research focusing on academics. Meanwhile, the software aspect has received less attention. Researchers have previously discussed information service frameworks but have not accommodated future needs. Software that must be considered can quickly respond to the user, one of which is a chatbot. Chatbots can be used to solve problems related to question-and-answer services, especially for academic institutions that do not have specific resources to handle this work. With chatbots, redundant user questions can be handled automatically. Chatbots are increasingly being offered as an alternative source of customer service. For a user to use a chatbot for this purpose, the user must trust the chatbot to provide the necessary support. To overcome this knowledge gap, a framework can integrate software, stakeholders, and academics in higher education. Therefore it is necessary to conduct new research to help answer future needs. © 2023 School of Science, IHU. All rights reserved.

关键词： Information services

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