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International Conference on Telecommunications (ConTEL)

作者： Dimitris Uzunidis Gerasimos Pagiatakis Ioannis Moscholios Michael Logothetis Department of Electrical and Electronics Engineering University of West Attica Athens Greece School of Pedagogical and Technological Education ASPETE Athens Greece Department of Informatics and Telecommunications University of Peloponnese Tripolis Greece Department of Electrical and Computer Engineering University of Patras Patras Greece

This paper analyzes a course module on the five Generations of wireless and fixed networks which was presented as a part of the undergraduate course “Broadband Communications”. This course was offered at the Dept. of Electrical & Electronic engineering, School of Pedagogical & Technological Education (ASPETE), Athens, Greece. The main objective of this module is three-fold. First, to introduce the students to the fixed generations taxonomy, the definition of which is assigned to the currently formed ETSI Industry Specification Group (ISG) F5G. Secondly, to unify the students” knowledge accumulated during their previous telecom-related courses as it was totally decoupled in two parts, either wireless or optical. Finally, to discuss the state-of-the-art technology, paving the way for the students to enter as professionals the fifth-generation era. The course module covered six teaching hours at the final 1.5 week of “Broadband Communications” course. To evaluate the impact of this module, the students were asked to fill a questionnaire upon module completion.

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Towards a Theoretical Framework of Autonomous Systems Underpinned by Intelligence and Systems Sciences

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IEEE/CAA Journal of Automatica Sinica 2021年第1期8卷 52-63页

作者： Yingxu Wang Ming Hou Konstantinos NPlataniotis Sam Kwong Henry Leung Edward Tunstel Imre JRudas Ljiljana Trajkovic International Institute of Cognitive Informatics and Cognitive Computing Department of Electrical and Computer EngineeringSchulich School of Engineering and Hotchkiss Brain InstituteUniversity of CalgaryCalgary T2N 1N4Canada Toronto Research Centre Defence Research&Development CanadaToronto M3K 2C9Canada Department of Electrical&Computer Engineering University of TorontoToronto M5S3G4Canada Department of Computer Science City University of Hong KongHong KongChina Department of Electrical and Computer Engineering Schulich School of EngineeringUniversity of CalgaryCalgary T2N 1N4Canada Autonomous&Intelligent Systems Department United Technologies Research CenterCT 06108 USA University Research&Innovation Center(EKIK) Óbuda UniversityBudapest H-1034Hungary School of Engineering Science Simon Fraser UniversityBurnaby V5A 1S6Canada

Autonomous systems are an emerging AI technology functioning without human intervention underpinned by the latest advances in intelligence,cognition,computer,and systems *** paper explores the intelligent and mathematical foundations of autonomous *** focuses on structural and behavioral properties that constitute the intelligent power of autonomous *** explains how system intelligence aggregates from reflexive,imperative,adaptive intelligence to autonomous and cognitive intelligence.A hierarchical intelligence model(HIM)is introduced to elaborate the evolution of human and system intelligence as an inductive *** properties of system autonomy are formally analyzed towards a wide range of applications in computational intelligence and systems *** paradigms of autonomous systems including brain-inspired systems,cognitive robots,and autonomous knowledge learning systems are *** in autonomous systems will pave a way towards highly intelligent machines for augmenting human capabilities.

关键词： Autonomous systems(AS) cognitive systems computational intelligence engineering paradigms intelligence science intelligent mathematics

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An Authenticated Method for a Secure Changing Password

An Authenticated Method for a Secure Changing Password

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Electronic engineering, Information Technology & Education (EEITE), International Conference in

作者： Mostefa Kara Konstantinos Karampidis Laid Kenioua Manolis Karampidis Muath AlShaikh Giorgos Papadourakis Abdelkader Laouid Scientific and Technology Hub of Sidi Abdellah National Higher School of Mathematics Algiers Algeria Department of Electrical and Computer Engineering Hellenic Mediterranean University Crete Greece LIAP Laboratory El Oued University El Oued Algeria Computer Science Department College of Computing and Informatics Saudi Electronic University Riyadh Kingdom of Saudi Arabia

ISBN: (数字)9798350372878

ISBN: (纸本)9798350372885

Despite their age, passwords are still widely used more than ever. In many cases, it is the solution that best fits the usage scenario. Researchers are proposing innovative designs and methods to support these scenarios. Many systems, especially sensitive ones, need to change the password. Classic systems rely on changing passwords in two stages, the first i s authentication, which usually consists of two or three rounds, and the second is creating a new password (PW), which also consists of two or three rounds. In this paper, a hidden transmission of a new random PW using the previous one is presented, we talk about an authenticated changing of PW. The verifier g enerates half of the new password and sends it to the prover, the prover authenticates the sent message using the old PW and then returns the authentication proof. After checking it, the verifier creates the second half of the PW. The proposed method combines the authentication and change PW processes into one process consisting of 3 rounds. Therefore, the proposal facilitates the process of automatic periodic change of PW between two entities (user, app, system, etc). Analysis and experiments show that our technique is robust, lightweight, and reduces many potential risks in the field.

关键词： Design methodology Education Authentication Passwords Proposals

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Mobile Vision Transformer for Surface Defect Classification from A Tiny Dataset

Mobile Vision Transformer for Surface Defect Classification ...

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International Conference on Information, Communication Technology and System (ICTS)

作者： Ghaluh Indah Permatasari Hsing-Kuo Pao Rudy Cahyadi Hario Pribadi Mohammad Iqbal Department of Computer Science and Information Engineering National Taiwan University of Science and Technology Taipei Taiwan R.O.C. Department of Informatics Engineering University of Bhayangkara Surabaya Indonesia Department of Mathematics Institut Teknologi Sepuluh Nopember Surabaya Indonesia

Surface defect classification is one pivotal step during the last product inspection before selling it to the market. Indeed, we want to serve our product to the customer in good condition. Speaking of smart manufacturing, existing studies on hot-rolled steel strip surface defect classification used deep learning models, which are very costly in terms of hardware, parameters, and dataset size. In this work, we propose a finetuned lightweight model from the Mobile Vision Transformer (MobileViT) to efficiently classify the surface defect of hot-rolled steel strips from a tiny data set. In this study, we experimented on a public benchmark dataset for surface defects of hot-rolled steel strip classification. The results showed that the proposed model can predict the defect accurately with fewer parameters and a smaller dataset than the SOTA ones.

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Fusing RGB and Thermal Imagery with Channel State Information for Abnormal Activity Detection Using Multimodal Bidirectional LSTM 1st

Fusing RGB and Thermal Imagery with Channel State Informatio...

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1st International Workshop on Cyber-Physical Security for Critical Infrastructures Protection, CPS4CIP 2020 in conjunction with the European Symposium on Research in computer Security, ESORICS 2020

作者： Bakalos, Nikolaos Voulodimos, Athanasios Doulamis, Nikolaos Doulamis, Anastasios Papasotiriou, Kassiani Bimpas, Matthaios School of Rural and Surveying Engineering National Technical University of Athens Athens15773 Greece Department of Informatics and Computer Engineering University of West Attica Athens12243 Greece Columbia University New YorkNY10027 United States

ISBN: (纸本)9783030697808

In this paper, we present a multimodal deep model for detection of abnormal activity, based on bidirectional Long Short-Term Memory neural networks (LSTM). The proposed model exploits three different input modalities: RGB imagery, thermographic imagery and Channel State Information from Wi-Fi signal reflectance to estimate human intrusion and suspicious activity. The fused multimodal information is used as input in a Bidirectional LSTM, which has the benefit of being able to capture temporal interdependencies in both past and future time instances, a significant aspect in the discussed unusual activity detection scenario. We also present a Bayesian optimization framework that fine-tunes the Bidirectional LSTM parameters in an optimal manner. The proposed framework is evaluated on real-world data from a critical water infrastructure protection and monitoring scenario and the results indicate a superior performance compared to other unimodal and multimodal approaches and classification models. © 2021, The Author(s).

关键词： Long short-term memory

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Extreme Learning Machine for Parking Slot Recognition in Smart Parking System

Extreme Learning Machine for Parking Slot Recognition in Sma...

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International Conference on Electrical, Telecommunication and computer engineering (ELTICOM)

作者： Romi Fadillah Rahmat Sharfina Faza Ilham Syahputra Pauzi Ibrahim Nainggolan Riza Sulaiman Mohd Amiruddin Abd Rahman Department of Information Technology Universitas Sumatera Utara Medan Indonesia Department of Computer Engineering and Informatics Politeknik Negeri Medan Medan Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Institute of IR 4.0 Universiti Kebangsaan Malaysia Bangi Malaysia Faculty of Science Universiti Putra Malaysia Selangor Malaysia

ISBN: (数字)9798331531249

ISBN: (纸本)9798331531256

In the modern era, technology has become an integral part of human life, particularly in image processing. This advanced technology is now applied to parking areas to identify vacant parking spaces. The application is designed to detect empty parking slots in real time using image data captured by a camera as input. The system then automatically scans for available parking spaces, displaying the results on the interface with green indicators for empty slots and red for occupied ones. The process involves several key stages, such as image pre-processing, image segmentation, and object detection. The system employs the Extreme Learning Machine (ELM) method to enhance its object detection capabilities. This system achieves a high accuracy rate of 94%under well-lit conditions. This novel technology optimizes parking management, providing an effective and dependable method to monitor parking availability in real time.

关键词： Accuracy Thresholding (Imaging) Translation Extreme learning machines Target recognition System performance Lighting Object detection Real-time systems Automobiles

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Fall Detection System for Elderly (FDS-E) using Low-cost Camera Based on LSTM and OpenPose

Fall Detection System for Elderly (FDS-E) using Low-cost Cam...

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IEEE Instrumentation and Measurement Technology Conference

作者： Herti Miawarni Tri Arief Sardjono Eko Setijadi Wijayanti Mauridhi Hery Purnomo Dept. of Electrical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Electrical Engineering Dept. of Biomedical Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember Surabaya Indonesia Dept. of Architecture Faculty of Engineering Universitas Diponegoro Semarang Indonesia Dept. of Electrical Engineering Dept. of Computer Engineering Faculty of Intelligent Electrical and Informatics Technology (F-Electics) Institut Teknologi Sepuluh Nopember University Center of Excellence on Artificial Intelligence for Healthcare and Society (UCE AIHeS) Surabaya Indonesia

Recently, many countries have been dealing with an increasing amount of elderly who are living alone. Unfortunately, fall incidents in the elderly tend to happen, and without proper dependable care would lead to fatal injuries. The elderly must be closely monitored under constant observation. Accidental falls are a leading cause of injury, mortality, and mobility limitations in the elderly. The expenses of national healthcare systems are also significantly impacted by accidental falls. These findings highlight the importance of investing heavily in the study and advancement of fall detection and intervention technologies. It is essential to recognize them early and provide fast assistance by developing technologies that can simultaneously improve the standard and the safety of the elderly's living environment. In this paper, we present a computer vision algorithm for falling incident detection using a low-cost camera and deep learning model. Ultimately, this algorithm can be used for the cases of elderly, in which falling risk is high and fatal. Furthermore, one self-developed dataset was used to validate the suggested approach experimentally. We used an OpenPose-based feature using a low-cost camera input and then classified each event or activity as either fall or non-fall. Classification tasks are carried out by Long Short-Term Memory (LSTM) with multiple validation metrics. The LSTM in this work is also optimized using Bayesian method. Finally, our approach to recognize falls has accuracy of 99.5%, which is distinct from other past works.

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The Complexity of Temporal Vertex Cover in Small-Degree Graphs

arXiv

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arXiv 2022年

作者： Hamm, Thekla Klobas, Nina Mertzios, George B. Spirakis, Paul G. Algorithms and Complexity Group TU Wien Vienna Austria Department of Computer Science Durham University United Kingdom Department of Computer Science University of Liverpool United Kingdom Computer Engineering & Informatics Department University of Patras Greece

Temporal graphs naturally model graphs whose underlying topology changes over time. Recently, the problems Temporal Vertex Cover (or TVC) and Sliding-Window Temporal Vertex Cover (or ∆-TVC for time-windows of a fixed-length ∆) have been established as natural extensions of the classic problem Vertex Cover on static graphs with connections to areas such as surveillance in sensor networks. In this paper, we initiate a systematic study of the complexity of TVC and ∆-TVC on sparse graphs. Our main result shows that for every ∆ ≥ 2, ∆-TVC is NP-hard even when the underlying topology is described by a path or a cycle. This resolves an open problem from literature and shows a surprising contrast between ∆-TVC and TVC for which we provide a polynomial-time algorithm in the same setting. To circumvent this hardness, we present some fixed-parameter and approximation algorithms. Copyright © 2022, The Authors. All rights reserved.

关键词： Approximation algorithms

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Analysis of the Best Employee Selection Decision Support System Using Analytical Hierarchy Process (AHP) 1

Analysis of the Best Employee Selection Decision Support Sys...

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1st International Conference on Innovation and Application of Science and Technology, ICIASTECH 2019

作者： Lia Hananto, April Priyatna, Bayu Fauzi, Ahmad Yuniar Rahman, Aviv Pangestika, Yulia Tukino Faculty of Computing Universiti Teknologi Malaysia Skudai Johor Malaysia Faculty of Technology and Computer Science Universitas Buana Perjuangan Karawang Indonesia Department of Informatics Engineering Universitas Widyagama Malang Indonesia Faculty of Postgraduate Management Computer Indonesia of University Indonesia

The award is given by the company to the best employees always to provide the best performance for companies that carry out duties and obligations in the company. How to give rewards to employees not only for how long they have been working at the company but about the results achieved. The gift can be in the form of salary or inventory from the company. So employees have great loyalty to the company. Decision making to determine the company can do the best employee by assessing the performance that has been done by employees at a specific time. Performance evaluation of Hon Chuan Company is influenced by several criteria, namely discipline, innovation, and responsibility. The support system for the best employee selection method uses the Analytical Hierarchy Process (AHP) method. The decision-making system is carried out to assess choices based on predetermined criteria. AHP method is applied to choose the best prospective employees. The calculation of the AHP method gives the results of the order of importance of criteria, namely discipline level (0.5584), responsibility (0.3196), and innovation (0.1220) and the best employee selection results obtained by Hendra (0.189), Vienna (0.189), Yin (0.145), Paul (0.109), Kandi (0.108), Kusworo (0.101), Bayu (0.088), and Ade Muhidin (0.072). © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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Goal-Aware RSS for Complex Scenarios via Program Logic

Goal-Aware RSS for Complex Scenarios via Program Logic

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IEEE Symposium on Intelligent Vehicle

作者： Ichiro Hasuo Clovis Eberhart James Haydon Jérémy Dubut Rose Bohrer Tsutomu Kobayashi Sasinee Pruekprasert Xiao-Yi Zhang Erik André Pallas Akihisa Yamada Kohei Suenaga Fuyuki Ishikawa Kenji Kamijo Yoshiyuki Shinya Takamasa Suetomi National Institute of Informatics (NII) Tokyo Japan SOKENDAI (The Graduate University for Advanced Studies) Japan Japanese-French Laboratory for Informatics (IRL 3527) Tokyo Japan Dept. Computer Science Worcester Polytechnic Institute Worcester MA USA Inst. Software & Systems Engineering University of Augsburg Augsburg Germany Cyber Physical Security Research Center AIST Tokyo Japan Graduate School of Informatics Kyoto University Kyoto Japan Mazda Motor Corporation Fuchu Japan

ISBN: (数字)9798350348811

ISBN: (纸本)9798350348828

We introduce a goal-aware extension of responsibility-sensitive safety (RSS), a recent methodology for rule-based safety guarantee for automated driving systems (ADS). Making RSS rules guarantee goal achievement—in addition to collision avoidance as in the original RSS—requires complex planning over long sequences of manoeuvres. To deal with the complexity, we introduce a compositional reasoning framework based on program logic, in which one can systematically develop RSS rules for smaller subscenarios and combine them to obtain RSS rules for bigger scenarios. As the basis of the framework, we introduce a program logic dFHL that accommodates continuous dynamics and safety conditions. Our framework presents a dFHL-based workflow for deriving goal-aware RSS rules; we discuss its software support, too. We conducted experimental evaluation using RSS rules in a safety architecture. Its results show that goal-aware RSS is indeed effective in realising both collision avoidance and goal achievement.

关键词： Intelligent vehicles computer architecture Software Cognition Safety Planning Complexity theory

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