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IEEE Photonics Conference (IPC)

作者： Qian Zhang Yuan Sui Stefan Rothe Jürgen Czarske Chair of Measurement and Sensor System Technique Faculty of Electrical and Computer Engineering TU Dresden Dresden Germany School of Science Institute of Applied Physics TU Dresden

We propose a novel approach for the referenceless mode decomposition of multimode fibers. A deep neural network with the interaction of a physical model achieves decomposition of 55 modes without pre-training. This pa...

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Feature Selection with Stacked Autoencoder Based Intrusion Detection in Drones Environment

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computers, Materials & Continua 2022年第12期73卷 5441-5458页

作者： Heba G.Mohamed Saud S.Alotaibi Majdy M.Eltahir Heba Mohsen Manar Ahmed Hamza Abu Sarwar Zamani Ishfaq Yaseen Abdelwahed Motwakel Department of Electrical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharjSaudi Arabia

The Internet of Drones(IoD)offers synchronized access to organized airspace for Unmanned Aerial Vehicles(known as drones).The availability of inexpensive sensors,processors,and wireless communication makes it possible in real time *** several applications comprise IoD in real time environment,significant interest has been received by research *** IoD operates in wireless environment,it is needed to design effective intrusion detection system(IDS)to resolve security issues in the IoD *** article introduces ametaheuristics feature selection with optimal stacked autoencoder based intrusion detection(MFSOSAEID)in the IoD *** major intention of the MFSOSAE-ID technique is to identify the occurrence of intrusions in the IoD *** do so,the proposed MFSOSAE-ID technique firstly pre-processes the input data into a compatible *** addition,the presented MFSOSAEID technique designs a moth flame optimization based feature selection(MFOFS)technique to elect appropriate ***,firefly algorithm(FFA)with stacked autoencoder(SAE)model is employed for the recognition and classification of intrusions in which the SAE parameters are optimally tuned with utilize of *** performance validation of the MFSOSAE-ID model was tested utilizing benchmark dataset and the outcomes implied the promising performance of the MFSOSAE-ID model over other techniques with maximum accuracy of 99.72%.

关键词： Internet of drones unmanned aerial vehicles security intrusion detection machine learning

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Analytical Survey on the Security Framework of Cyber-Physical systems for Smart Power system Networks

Analytical Survey on the Security Framework of Cyber-Physica...

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2022 International Conference on Cyber Resilience, ICCR 2022

作者： Ali Al-Jumaili, Ahmed Hadi Muniyandi, Ravie Chandren Hasan, Mohammad Kamrul Singh, Mandeep Jit Siaw Paw, Johnny Koh Universiti Kebangsaan Malaysia Faculty of Information Science and Technology Bangi43600 Malaysia University of Fallujah Computer Centre Department Anbar00964 Iraq Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and System Engineering Selango Bangi43600 Malaysia Universiti Tenaga Nasional Department of Electronic and Communication Engineering Selango Kajang Malaysia

ISBN: (纸本)9781665461221

Cyber-Physical Power system (CPPS) is one of the most critical infrastructure systems due to deep integration between power grids and communication networks. In the power system, cascading failure is spreading more readily in CPPS, even leading to blackouts as well as there are new difficulties with the power system security simulation and faults brought by physical harm or network intrusions. The current study summarized the cross- integration of several fields such as computer and cyberspace security in terms of the robustness of Cyber-Physical systems, viewed as Interconnected and secure network systems. Therefore, the security events that significantly influenced the power system were evaluated in this study, besides the challenges and future directions of power system security simulation technologies were investigated for posing both challenges and opportunities for simulation techniques of power system security like building a new power system to accelerate the transformation of the existing energy system to a clean, low-carbon, safe, and efficient energy system which is used to assure power system stability through fusion systems that combine the cyber-physical to integrate the battery power station, power generation and renewable energy resources through the internet with the cyber system that contains Smart energy system control and attacks. © 2022 IEEE.

关键词： Cyber Physical system

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Improved Power Transfer Efficiency Using a Dual Transmitter Receiver Design With Integrated Decoupling Coils for IPT EV Charging

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IEEE Access 2025年 13卷 91362-91373页

作者： Bilal Alam Saad Mekhilef Marizan Mubin Kok Soon Tey Addy Wahyudie Department of Electrical Engineering Power Electronics and Renewable Energy Research Laboratory University of Malaya Kuala Lumpur Malaysia School of Engineering Swinburne University of Technology Melbourne VIC Australia Department of Computer System and Technology Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia Department of Electrical and Communication Engineering United Arab Emirates University (UAE-U) Al Ain United Arab Emirates

In high-power inductive power transfer (IPT) systems, multiple coils are used to enhance efficiency, but interactions between coils on the same side can reduce overall performance. Traditionally, decoupling coils are added to minimize these interactions, however they don’t contribute to power transfer and may even hinder system efficiency. This article introduces a new IPT system and coil structure that integrates decoupling coils, which not only improve mutual interaction between same-side coils but also actively contribute to power transfer. The coils are optimized for high mutual inductance, strong coupling coefficient, reduced self-inductance, and minimized side-by-side mutual inductance, performing well even with X-axis, Y-axis, and angular misalignments. Using 3-D Finite Element Analysis (ANSYS-Maxwell), the magnetic coupler’s performance is thoroughly evaluated, and a downsized experimental setup demonstrates the system’s feasibility. The proposed system achieves a maximum dc-dc efficiency of 94.27%, successfully delivering 1 kW across a 120-mm air gap with zero-voltage switching, presenting a significant advancement for multi-transmitter and multi-receiver systems.

关键词： Coils Receivers Transmitters Mathematical models Couplings Inductance Costs Voltage Rectifiers Integrated circuit modeling

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Reconfigurable Intelligent Surfaces and DF-relay Improved Spectral Efficiency in Cognitive Radio Networks 97

Reconfigurable Intelligent Surfaces and DF-relay Improved Sp...

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97th IEEE Vehicular Technology Conference, VTC 2023-Spring

作者： El Mettiti, Abderahmane Saber, Mohamed Chehri, Abdellah Chaibi, Hasna Badaoui, Abdel Saadane, Rachid Faculty of Sciences University Mohamed v Ehtp LRIT-GSCM Morocco SIRC/LAGeS Ehtp Laboratory Engineering System Casablanca Morocco Royal Military College Dep. Math. and Computer Science Kingston Canada Supmti Genuis Laboratory Rabat Morocco Mohammed v University Laboratory Lastimi Casablanca Morocco

ISBN: (纸本)9798350311143

Cognitive radio (CR) is considered a primary technology for spectrum usage efficiency and dynamic spectrum management. Spectrum sensing is an essential cognitive radio cycle function. Recently, reconfigurable intelligent surfaces (RIS) technology has emerged as a promising new enabler of 6G wireless communication, with the ability to control signal propagation and increase signal coverage and spectrum management. This paper investigates how integrating RISs with CR can improve spectral efficiency. First, we optimize the RIS parameters by identifying the optimal transmit powers and number of RIS antennas. Then, we compare the novel RIS technology with the traditional decode-and-forward (DF) relaying technology. Next, we investigate how adopting RIS can enhance spectral efficiency. Finally, we demonstrate how integrating the novel technology of reconfigurable intelligent surfaces with CR can significantly increase spectrum detection, the most crucial step in the cognitive radio process. Simulation studies indicate that RIS is more energy-efficient than SISO and DF-relay communications in various setups. Moreover, by boosting spectrum sensing capability in CR situations, RISs can significantly enhance the efficiency of frequency spectrum usage. © 2023 IEEE.

关键词： Cognitive radio

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Multiperspective Quality Model for Process Design 2

Multiperspective Quality Model for Process Design

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2nd International Conference on Information systems and Software Technologies, ICI2ST 2021

作者： Mosquera, Estefania Patricia Galvez Gaibor, Marco Oswaldo Santorum Escuela Politécnica Nacional Faculty of System Engineering Quito Ecuador Escuela Politécnica Nacional Department of Informatics and Computer Science Quito Ecuador

ISBN: (纸本)9780738143613

Organizational processes are constantly evolving due to different factors. To take care of this continuous transformation, these processes must be flexible enough, which implies their formalization and optimal design. To operate efficiently, the organizations must identify and manage all their processes, therefore it is important to ensure their quality. There are companies in Ecuador devoted to providing consulting services for management of processes;to that end they use methodologies, techniques, and good practices, in order to provide optimal services to meet the expectations of their customers. However, this not always *** objective of this work is to present a proposal of a model to guide the quality in the design of processes, which allows expert companies to perform a design following good practices and to evaluate the quality from syntactic, semantic, and pragmatic perspectives. © 2021 IEEE.

关键词： Design

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Development of a Dempster-Shafer Model for Diagnosing Mental Health Disorders on Social Media

Development of a Dempster-Shafer Model for Diagnosing Mental...

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International Seminar on Research of Information Technology and Intelligent systems (ISRITI)

作者： Ayahri Hadi Nasyuha Ananda Hadi Ilyas Widyastuti Andriyani Aloysius Agus Subagyo Dept. of Information System Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Dept. of Information System Faculty Of Engineering And Computer Science Universitas Dharmawangsa Medan Indonesia Dept. of Master of Information Technology Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia Dept. of Accounting Information System Faculty of Information Technology Universitas Teknologi Digital Indonesia Yogyakarta Indonesia

ISBN: (数字)9798331519643

ISBN: (纸本)9798331519650

The rapid proliferation of social media has been paralleled by an increase in mental health concerns, often reflected in users' online behaviors and text posts. Traditional methods for diagnosing mental health disorders do not effectively leverage this vast amount of data, nor do they address the ambiguities and uncertainties inherent in natural language processing of social media content. A novel diagnostic model based on the Dempster-Shafer evidence theory is developed specifically for analyzing social media text. The model aims to enhance the precision of mental health disorder diagnoses by incorporating probabilistic reasoning and handling uncertainty in the data more effectively than traditional binary classification methods. It integrates linguistic cues, sentiment analysis, and behavioral indicators extracted from user posts to assess the likelihood of various mental health conditions. We collected a dataset comprising social media posts tagged with mental health keywords, verified by clinical annotations. The Dempster-Shafer model was trained with features derived from text analytics, including sentiment scores, thematic elements, and engagement metrics. The model’s performance was evaluated against standard classification models through metrics such as accuracy, sensitivity, and specificity. The Dempster-Shafer model demonstrated superior capability in handling the uncertainty and imprecision of social media data, showing an improvement in diagnostic accuracy by 15% over traditional models. The findings suggest that applying Dempster-Shafer theory in mental health diagnostics can effectively utilize the nuanced and sparse data available on social media, offering a promising tool for early identification and intervention in mental health issues.

关键词： Measurement Seminars Analytical models Sentiment analysis Accuracy Social networking (online) Mental health Sensitivity and specificity Data models Standards

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A Development of Object Detection system based on Deep Learning Approach to Support the Laparoscope Manipulating Robot (LMR)

A Development of Object Detection System based on Deep Learn...

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2022 International Electrical engineering Congress, iEECON 2022

作者： Sonsilphong, Suphachoke Sonsilphong, Amornthep Hormdee, Daranee Khampitak, Kovit Khon Kaen University Data Science Health Informatics Program Academic Affairs Faculty of Medicine Khon Kaen Thailand Rajamangala University of Technology Isan Department of Electrical Engineering Khon Kean Thailand Khon Kaen University Embedded System RD Group Department of Computer Engineering Faculty of Engineering Khon Kean Thailand Khon Kean University Faculty of Medicine Department of Obstetrics and Gynecology Khon Kean Thailand

ISBN: (纸本)9781665402064

This paper presents the development of an object detection system based on the deep learning approach of computer vision to support the laparoscopic surgical robotic position control system. The system comprises two main phases, the training phase, and the real-time operating phase. In the training phase, a modified YOLOv4 algorithm is proposed to be adopted within the Darknet framework for training the weights of detection models. The best detection model is then selected to be assigned to the object detector in the real-time operating phase. The validation result of the detection model across the experiment datasets is 90% accuracy on average during the training phase. To validate the viability of real-time object detection, the proposed system was implemented in two test-cases of gynecologic surgery with the soft-body cadavers. © 2022 IEEE.

关键词： Laparoscopy

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FlexiFed: Personalized Federated Learning for Edge Clients with Heterogeneous Model Architectures 23

FlexiFed: Personalized Federated Learning for Edge Clients w...

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2023 World Wide Web Conference, WWW 2023

作者： Wang, Kaibin He, Qiang Chen, Feifei Chen, Chunyang Huang, Faliang Jin, Hai Yang, Yun School of Computer Science and Technology Huazhong University of Science and Technology China Department of Computing Technologies Swinburne University of Technology Australia School of Information Technology Deakin University Australia Faculty of Information Technology Monash University Australia Guangxi Key Lab of Human-machine Interaction and Intelligent Decision Nanning Normal University China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)9781450394161

Mobile and Web-of-Things (WoT) devices at the network edge account for more than half of the world's web traffic, making a great data source for various machine learning (ML) applications, particularly federated learning (FL) which offers a promising solution to privacy-preserving ML feeding on these data. FL allows edge mobile and WoT devices to train a shared global ML model under the orchestration of a central parameter server. In the real world, due to resource heterogeneity, these edge devices often train different versions of models (e.g., VGG-16 and VGG-19) or different ML models (e.g., VGG and ResNet) for the same ML task (e.g., computer vision and speech recognition). Existing FL schemes have assumed that participating edge devices share a common model architecture, and thus cannot facilitate FL across edge devices with heterogeneous ML model architectures. We explored this architecture heterogeneity challenge and found that FL can and should accommodate these edge devices to improve model accuracy and accelerate model training. This paper presents our findings and FlexiFed, a novel scheme for FL across edge devices with heterogeneous model architectures, and three model aggregation strategies for accommodating architecture heterogeneity under FlexiFed. Experiments with four widely-used ML models on four public datasets demonstrate 1) the usefulness of FlexiFed;and 2) that compared with the state-of-the-art FL scheme, FlexiFed improves model accuracy by 2.6%-9.7% and accelerates model convergence by 1.24 × -4.04 ×. © 2023 ACM.

关键词： Speech recognition

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Food Horticultural Supply Chain Performance Efficiency using Hybrid Model: SCOR-system Dynamic Simulation

Food Horticultural Supply Chain Performance Efficiency using...

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2022 International Seminar on Application for Technology of Information and Communication, iSemantic 2022

作者： Yusianto, Rindra Casnan, Casnan Sudibyo, Usman Suprihatin, Marimin Hardjomidjojo, Hartrisari Dian Nuswantoro University Faculty of Engineering Department of Industrial Engineering Central Java Semarang53192 Indonesia STKIP Muhammadiyah Kuningan Department of Mathematics Education West Java Kuningan45552 Indonesia Dian Nuswantoro University Faculty of Computer Science Department of Information System Central Java Semarang53192 Indonesia Faculty of Agricultural Engineering and Technology Department of Agro-Industrial Technology West Java Bogor16002 Indonesia

ISBN: (数字)9781665488396

ISBN: (纸本)9781665488396

Today's highly competitive and dynamic business environment has forced horticultural food commodity farmers to implement better supply chain management (SCM) strategies. An essential aspect of SCM is how farmers and collectors can detect changes in supply chain (SC) behavior;these changes affect the efficiency of SC performance. This study aims to improve food horticultural SC performance efficiency. We propose a hybrid method using the supply chain operation reference (SCOR) and system dynamics simulation. To illustrate the methodology, we use a case study of the potato agroindustry in Wonosobo District, Central Java, Indonesia. The results show that the SC performance measurement consists of six perspectives, namely Plan, Source, Make, Deliver, Return, and Enable, with 23 KPIs. The SC value in January-March 2022 is 71.01%, meaning that the average measurement results are in a suitable category. The best scenario we propose is Scenario I, which is a reduction in indirect performance labor costs of IDR 600,000 in three months and an increase in efficiency of 11.08%. For further research, researchers can use this method to increase efficiency in the food processing industry made from food horticultural commodities. © 2022 IEEE.

关键词： Supply chain management

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