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3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Ramesh Prabhakaran, R. Quamar, Danish Guhan, P. Angel Maanu, P. Sherine, W.B. Raj, Aman Mizoram University Department of Computer Engineering Mizoram India Panimalar Engineering College Department of Electrical and Communication Engineering Chennai India Panimalar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331528201

A critical component of video surveillance research and real-world applications is the detection of anomalous events. In order to improve public safety, more and more surveillance cameras are being installed in public spaces like roadways, crosswalks, banks, and shopping centers. Identification of odd occurrences, such as car accidents, crimes, or illicit activity, is a crucial duty in video surveillance. Because anomalous events are less often than normal activities, the goal of an efficient anomaly detection system is to quickly identify departures from the average and identify the abnormality's temporal span. One way to think of anomaly detection is as an early stage of video analysis that separates abnormalities from normal patterns. Using classification techniques, an anomaly can be further classified into particular activities once it has been discovered. An overview of anomaly detection with an emphasis on banking operations is given in this paper. Many every day and recurring transactions in the banking industry affect a number of stakeholders, including staff members, clients, debtors, and outside parties. Early detection of these anomalies can reduce or even eliminate any potential bad effects. In order to distinguish between normal and abnormal events, this work employs an anomaly detection technique based on machine learning. © 2024 IEEE.

关键词： Banking

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A Process Improvement Model for Software Organizations during COVID-19 Pandemic 36th

A Process Improvement Model for Software Organizations durin...

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36th International Conference on computer Applications in Industry and engineering, CAINE 2023

作者： Haneef, Hasnain Abbas, Assad Khan, Samee U. Department of Computer Science COMSATS University Islamabad Islamabad44000 Pakistan Department of Electrical and Computer Engineering Mississippi State University United States

Software Process Improvement (SPI) aims to achieve quality in software products for software organizations, as it helps to manage and improve the development processes. The success of software products highly depends on the right execution of software processes. The current pandemic (COVID-19) has highly affected the workflow of software organizations around the distributed geographical locations, resulting in difficulties in process execution which is a threat to software process improvement activity. The primary objective of this research is to provide a process improvement model for software development organizations for better management and improvement of the software development processes during the COVID-19 pandemic. Our proposed model is based on the objectives of the ‘Team Software Process’ (TSP)and ‘Personal Software Process’ (PSP) models to effectively manage the software development processes for both the teams and individuals involved in the remote development during the COVID-19 pandemic. The proposed model can also be applied in any uncertain situation other than COVID-19 to assist software organizations during remote work. © 2024, EasyChair. All rights reserved.

关键词： COVID-19

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All-optical image denoising using a diffractive visual processor

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Light(science & Applications) 2024年第3期13卷 429-445页

作者： Çağatay Işıl Tianyi Gan Fazil Onuralp Ardic Koray Mentesoglu Jagrit Digani Huseyin Karaca Hanlong Chen Jingxi Li Deniz Mengu Mona Jarrahi Kaan Akşit Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA University College London Department of Computer ScienceLondonUnited Kingdom

Image denoising,one of the essential inverse problems,targets to remove noise/artifacts from input *** general,digital image denoising algorithms,executed on computers,present latency due to several iterations implemented in,e.g.,graphics processing units(GPUs).While deep learning-enabled methods can operate non-iteratively,they also introduce latency and impose a significant computational burden,leading to increased power ***,we introduce an analog diffractive image denoiser to all-optically and non-iteratively clean various forms of noise and artifacts from input images–implemented at the speed of light propagation within a thin diffractive visual processor that axially spans<250×λ,whereλis the wavelength of *** all-optical image denoiser comprises passive transmissive layers optimized using deep learning to physically scatter the optical modes that represent various noise features,causing them to miss the output image Field-of-View(FoV)while retaining the object features of *** results show that these diffractive denoisers can efficiently remove salt and pepper noise and image rendering-related spatial artifacts from input phase or intensity images while achieving an output power efficiency of~30–40%.We experimentally demonstrated the effectiveness of this analog denoiser architecture using a 3D-printed diffractive visual processor operating at the terahertz *** to their speed,power-efficiency,and minimal computational overhead,all-optical diffractive denoisers can be transformative for various image display and projection systems,including,e.g.,holographic displays.

关键词： remove rendering holographic

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WIP: Pledging to be an Ethical Computing Professional 54

WIP: Pledging to be an Ethical Computing Professional

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Dasigi, Venu G. Estell, John K. Christensen, Ken Bowling Green State University Department of Computer Science Bowling GreenOH United States Ohio Northern University Electrical and Computer Engineering & Computer Science Department AdaOH United States University of South Florida Department of Computer Science and Engineering TampaFL United States

ISBN: (纸本)9798350351507

This innovative practice WIP paper describes the 'Pledge of the Computing Professional' (the Pledge), its need, its relationship to two major codes of ethics, and its role in inspiring computing students to act ethically and professionally. Professional ethics are the heart and soul of any profession. In developing products and services, professionals are to conduct themselves ethically, focusing on the public good. ACM has developed the Code of Ethics and Professional Conduct, and ACM and IEEE computer Society have together published the Software engineering Code of Ethics and Professional Practice. ACM considers ethics a core topic in curricular recommendations. In 2011, a team of computing professionals developed the Pledge of the Computing Professional. The purpose of the Pledge is to acknowledge the impact of computing and the attendant responsibilities and to nurture a desire to promote the public good. The Pledge has now been adopted by over 75 institutions in the US. This paper clarifies the relationship between the Pledge and the codes of ethics. It is hoped that emphasizing this connection and promoting a culture surrounding the Pledge can be instrumental in producing graduates with a well-rounded sense of ethics and professionalism, who become responsible citizens that can shape the profession's future. The Pledge may be viewed as both an introduction for the students to the profound impact and responsibilities they would have in society and a means to inspire them to reflect on its meaning as computing ethics become the center of public discourse. Future work includes making the Pledge international in scope. © 2024 IEEE.

关键词： Students

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Signal Conducting System with Effective Optimization Using Deep Learning for Schizophrenia Classification

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computer Systems science & engineering 2023年第5期45卷 1869-1886页

作者： V.Divya S.Sendil Kumar V.Gokula Krishnan Manoj Kumar School of Electrical and Electronics Engineering Sathyabama Institute of Science and TechnologyChennaiTamilnaduIndia Department of Electrical and Electronics Engineering S A Engineering CollegeChennaiTamilnaduIndia Department of Computer Science and Information Technology CVR College of EngineeringMangalpallyHyderabadTelanganaIndia School of Computer Science University of Petroleum and Energy StudiesDehradunIndia

Signal processing based research was adopted with Electroencephalogram(EEG)for predicting the abnormality and cerebral *** proposed research work is intended to provide an automatic diagnostic system to determine the EEG signal in order to classify the brain function which shows whether a person is affected with schizophrenia or *** detection and intervention are vital for better ***,the diagnosis of schizophrenia still depends on clinical observation to *** reliable biomarkers,schizophrenia is difficult to detect in its early phase and hence we have proposed this *** this work,the EEG signal series are divided into non-linear feature mining,classification and validation,and t-test integrated feature selection *** this work,19-channel EEG signals are utilized from schizophrenia class and normal ***,the datasets initially execute the splitting process based on raw 19-channel EEG into 6250 sample point’s *** this process,1142 features of normal and schizophrenia class patterns can be *** other hand,157 features from each EEG patterns are utilized based on Non-linear feature extraction process where 14 principal features can be identified in terms of considering the essential *** last,the Deep Learning(DL)technique incorporated with an effective optimization technique is adopted for classification process called a Deep Convolutional Neural Network(DCNN)with mayfly optimization *** proposed technique is implemented into the platform of MATLAB in order to obtain better results and is analyzed based on the performance analysis framework such as accuracy,Signal to Noise Ratio(SNR),Mean Square Error,Normalized Mean Square Error(NMSE)and *** comparison,the proposed technique is proved to a better technique than other existing techniques.

关键词： Deep learning optimization algorithm signal conducting system schizophrenia convolutional neural network mayfly optimization algorithm

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Switching Control for Identification Deception in Cyber-Physical Systems 63

Switching Control for Identification Deception in Cyber-Phys...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Mavridis, Christos Kanellopoulos, Aris Sandberg, Henrik Johansson, Karl Henrik Kth Royal Institute of Technology Division of Decision and Control School of Electrical Engineering and Computer Science Stockholm Sweden

ISBN: (纸本)9798350316339

We investigate the problem of deceiving a malicious agent employing an identification method to estimate the closed-loop dynamics of a cyber-physical system. In particular, we propose a moving target defense mechanism that utilizes stochastic switching between linear closed-loop dynamics to drive a linear system identification process of a potential adversary to sub-optimal solutions with non-vanishing error. We provide a statistical analysis of the induced identification error and show that it is not possible for any linear system identification method to reconstruct the average dynamics of a stochastic switched linear system. Finally, we utilize the theory of Markov jump linear systems to guarantee asymptotic stability of the switching system, and formulate the switching control problem as an optimization problem that guarantees stability while taking into account the trade-off between security and switching effort. Simulation results showcase the efficacy of the proposed approach in inducing identification error for the adversary using minimal switching. © 2024 IEEE.

关键词： Markov processes

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Design of an Optical Wireless Communication Link Using Mid Wave Infrared Laser Source & Comparison with Short Wave Infrared Laser Sources in Different Atmospheric Anomalies: An Analytical Study

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Nonlinear Optics Quantum Optics 2024年第1-2期60卷 85-111页

作者： Mukherjee, Shibabrata Paul, Sujoy Mazumdar, Saswati Electrical Engineering Department Jadavpur University West Bengal Kolkata700032 India Centre for Distributed Computing Computer Science Engineering Department Jadavpur University West Bengal Kolkata700032 India

Optical Wireless Communication (OWC), sometimes referred to as Free Space Optics (FSO), is the backbone of leading-edge communication systems that offer high performance and fast speed. The main pitfall of this system is that the optical signal is hindered by the different atmospheric anomalies. As a result, the system performance has been distorted and degraded. Among the different atmospheric anomalies like fog, rain, snow, etc., fog is the main enemy of this system. Using the properly chosen optics at the transmitter and receiver sides and wavelength, the system performance may be increased in diverse weather conditions. In this article, four wavelengths like two Mid Wave Infrared (MWIR) (3400 nm, 4100 nm) and two Short Wave Infrared (SWIR) (1550 nm & 2000 nm), 27 dBm optical peak power, the OOK modulation technique, 10 MHz modulation bandwidth, 10-7 BER, 2 km optical wireless link distance have been considered. From the theoretical simulation results, it has been initiated that MWIR optical sources (like 4100 nm and 3400 nm) contribute 72.22 dB, and 71.27 dB link margin at adverse atmospheric anomalies respectively, whereas SWIR Optical sources like 1550 nm & 2000 nm furnish 67.70 dB, 68.50 dB link margin respectively for 2 km link distance. The 4100 nm wavelength Laser source performs better in different atmospheric anomalies and provides a better pointing error angle in clear, as well as adverse weather conditions, compared to other wavelengths. © 2024 Old City Publishing, Inc.

关键词： Space optics

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Reflect-and-Amplify: a Novel SWIPT Technique through Hybrid Active/Passive RIS

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IEEE Internet of Things Journal 2025年第12期12卷 22073-22089页

作者： Ata, Yalcin Zedini, Emna Vegni, Anna Maria Alouini, Mohamed-Slim Ostim Technical University Ostim Department of Electrical and Electronics Engineering Yenimahalle Ankara06374 Turkey University of Michigan-Flint College of Innovation and Technology FlintMI United States Roma Tre University Department of Industrial Electronics and Mechanical Engineering Rome Italy Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia

This paper presents a novel technique for the simultaneous wireless information and power transfer (SWIPT) toward low-power devices, by means of Reconfigurable Intelligent Surfaces (RISs). Our approach is based on a Reflect-and-Amplify protocol meaning that, based on the RIS beam-steering functionality and assuming different reflection coefficients for the RIS elements, it allows to reflect and amplify the impinging wireless signal from the transmitter toward the receiver, which will be able to both collect energy and download data. Specifically, by considering a hybrid RIS comprised of both passive and active elements, the proposed SWIPT approach is defined Active/Passive Switching (APS). The reflection of the wireless beam toward the receiver is accomplished by means of passive RIS elements, while an amplification of the wireless signal is provided through active RIS elements. Such amplification allows the receiver to convert the incoming wave power into a DC voltage, but also causes an increase of power consumption due to active elements. To assess the performance of the proposed SWIPT approach, we derive the closed-form expression of the joint data transmission and energy harvesting outage probability (OP) in case of both a single and multiple users. We compare the proposed technique to other SWIPT approaches from the literature, such as the power splitting and the time switching, under power fairness conditions. Our results validate the benefits of using hybrid RISs for SWIPT systems, as compared to other existing approaches showing reduced performance, also in case of asymptotic analysis for high power and high number of RIS elements. © 2014 IEEE.

关键词： Inductive power transmission

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Efficient Bit-Plane Based Medical Image Cryptosystem Using Novel and Robust Sine-Cosine Chaotic Map

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computers, Materials & Continua 2025年第4期83卷 917-933页

作者： Zeric Tabekoueng Njitacke Louai A.Maghrabi Musheer Ahmad Turki Althaqafi Department of Electrical and Electronic Engineering College of Technology(COT)University of BueaBueaP.O.Box 63Cameroon Department of Software Engineering College of EngineeringUniversity of Business and TechnologyJeddah22246Saudi Arabia Department of Computer Engineering Jamia Millia IslamiaNew Delhi110025India Department of Computer Science School of EngineeringComputing and DesignDar Al-Hekma UniversityJeddah22246Saudi Arabia

This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine *** map demonstrates remarkable chaotic dynamics over a wide range of *** employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map,which allows us to select optimal parameter configurations for the encryption *** findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors,an essential characteristic for effective *** encryption technique is based on bit-plane decomposition,wherein a plain image is divided into distinct bit *** planes are organized into two matrices:one containing the most significant bit planes and the other housing the least significant *** subsequent phases of chaotic confusion and diffusion utilize these matrices to enhance *** auxiliary matrix is then generated,comprising the combined bit planes that yield the final encrypted *** results demonstrate that our proposed technique achieves a commendable level of security for safeguarding sensitive patient information in medical *** a result,image quality is evaluated using the Structural Similarity Index(SSIM),yielding values close to zero for encrypted images and approaching one for decrypted ***,the entropy values of the encrypted images are near 8,with a Number of Pixel Change Rate(NPCR)and Unified Average Change Intensity(UACI)exceeding 99.50%and 33%,***,quantitative assessments of occlusion attacks,along with comparisons to leading algorithms,validate the integrity and efficacy of our medical image encryption approach.

关键词： Image cryptosystem robust chaos sine-cosine map nonlinear analysis tools medical images

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News Modeling and Retrieving Information: Data-Driven Approach

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Intelligent Automation & Soft Computing 2023年第11期38卷 109-123页

作者： Elias Hossain Abdullah Alshahrani Wahidur Rahman Electrical&Computer Engineering North South UniversityDhaka1229Bangladesh Department of Computer Science and Artificial Intelligence College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia Department of Computer Science and Engineering Uttara UniversityDhaka1230Bangladesh

This paper aims to develop Machine Learning algorithms to classify electronic articles related to this phenomenon by retrieving information and topic *** Methodology of this study is categorized into three phases:the Text Classiﬁcation Approach(TCA),the Proposed Algorithms Interpretation(PAI),andﬁnally,Information Retrieval Approach(IRA).The TCA reﬂects the text preprocessing pipeline called a clean *** Global Vec-tors for Word Representation(Glove)pre-trained model,FastText,Term Frequency-Inverse Document Fre-quency(TF-IDF),and Bag-of-Words(BOW)for extracting the features have been interpreted in this *** PAI manifests the Bidirectional Long Short-Term Memory(Bi-LSTM)and Convolutional Neural Network(CNN)to classify the COVID-19 ***,the IRA explains the mathematical interpretation of Latent Dirich-let Allocation(LDA),obtained for modelling the topic of Information Retrieval(IR).In this study,99%accuracy was obtained by performing K-fold cross-validation on Bi-LSTM with Glove.A comparative analysis between Deep Learning and Machine Learning based on feature extraction and computational complexity exploration has been performed in this ***,some text analyses and the most inﬂuential aspects of each document have been explored in this *** have utilized Bidirectional Encoder Representations from Trans-formers(BERT)as a Deep Learning mechanism in our model training,but the result has not been uncovered ***,the proposed system can be adjustable in the real-time news classiﬁcation of COVID-19.

关键词： COVID-19 news retrieving data-driven machine learning BERT topic modelling

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