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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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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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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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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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An overview on IRS-enabled sensing and communications for 6G: architectures, fundamental limits, and joint beamforming designs

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science China(Information sciences) 2025年第5期68卷 170-193页

作者： Xianxin SONG Yuan FANG Feng WANG Zixiang REN Xianghao YU Ye ZHANG Fan LIU Jie XU Derrick Wing Kwan NG Rui ZHANG Shuguang CUI School of Science and Engineering (SSE) Shenzhen Future Network of Intelligence Institute (FNii-Shenzhen)and Guangdong Provincial Key Laboratory of Future Networks of Intelligence The Chinese University of Hong Kong Department of Electrical Engineering City University of Hong Kong School of Information Engineering Guangdong University of Technology Key Laboratory of Wireless-Optical Communications Chinese Academy of Sciences School of Information Science and Technology University of Science and Technology of China Computer School Beijing Information Science and Technology University National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University School of Electrical Engineering and Telecommunications University of New South Wales School of Science and Engineering Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Department of Electrical and Computer Engineering National University of Singapore

This study presents an overview on intelligent reflecting surface(IRS)-enabled sensing and communication for the forthcoming sixth-generation(6G) wireless networks, in which IRSs are strategically deployed to proactively reconfigure wireless environments to improve both sensing and communication(S&C) performance. First, we exploit a single IRS to enable wireless sensing in the base station's(BS's) non-line-of-sight(NLoS) area. In particular, we present three IRS-enabled NLoS target sensing architectures with fully-passive, semi-passive, and active IRSs, respectively. We compare their pros and cons by analyzing the fundamental sensing performance limits for target detection and parameter estimation. Next, we consider a single IRS to facilitate integrated sensing and communication(ISAC), in which the transmit signals at the BS are used for achieving both S&C functionalities, aided by the IRS through reflective beamforming. We present joint transmit signal and receiver processing designs for realizing efficient ISAC, and jointly optimize the transmit beamforming at the BS and reflective beamforming at the IRS to balance the fundamental performance tradeoff between S&C. Furthermore, we discuss multi-IRS networked ISAC, by particularly focusing on multi-IRS-enabled multi-link ISAC, multi-region ISAC, and ISAC signal routing, respectively. Finally, we highlight various promising research topics in this area to motivate future work.

关键词： integrated sensing and communication (ISAC) intelligent reflecting surface (IRS) non-line-of-sight (NLoS) sensing sensing and communication tradeoff

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Verification and Design of Robust and Safe Neural Network-enabled Autonomous Systems 59

Verification and Design of Robust and Safe Neural Network-en...

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59th Annual Allerton Conference on Communication, Control, and Computing, Allerton 2023

作者： Zhu, Qi Li, Wenchao Huang, Chao Chen, Xin Zhou, Weichao Wang, Yixuan Li, Jiajun Fu, Feisi Northwestern University Department of Electrical and Computer Engineering United States Boston University Department of Electrical and Computer Engineering United States University of Liverpool Department of Computer Science United Kingdom University of New Mexico Department of Computer Science United States

ISBN: (纸本)9798350328141

Neural networks are being applied to a wide range of tasks in autonomous systems, such as perception, prediction, planning, control, and general decision making. While they may improve system performance over traditional physical model-based methods, pressing concerns have been raised on the uncertain behaviors of neural networks under varying inputs, especially for safety-critical systems such as autonomous vehicles and robots. In this paper, we will discuss the challenges in ensuring the safety and robustness of neural network-enabled autonomous systems, and present our recent work in addressing these challenges. These include methods for certifying the robustness of neural networks, verifying the safety of neural network-controlled systems, designing these systems with safety assurance, and conducting safety-assured runtime adaptation. © 2023 IEEE.

关键词： Decision making

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Robust autonomous driving control using deep hybrid-learning network under rainy/snown conditions

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Multimedia Tools and Applications 2024年第41期83卷 89281-89295页

作者： Lee, Chao-Yang Khanum, Abida Sung, Tien-Wen Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan Department of Electrical Engineering National Cheng Kung University No.1 University Road Tainan City701 Taiwan College of Computer Science and Mathematics Fujian University of Technology No3 Xueyuan Road Fuzhou350011 China

The study introduces a groundbreaking two-stage deep hybrid learning architecture, Robust Autonomous Driving Control (RADC), designed to address the formidable challenge of ensuring safe and efficient autonomous driving in adverse weather conditions, including heavy rain and snow, in complex scenarios. In the first stage, our proposal utilizes an encoder as a variational autoencoder (VAE) model. This encoder leverages the VAE to extract feature information from the perceptual data surrounding the environment. Moving on to the second stage, we build a decoder as an Inception-Bidirectional Long Short-Term Memory (IBL) model. This decoder combines the VAE latent features obtained in stage one with additional control vehicle information tasks, including steering, speed, etc. Our approach involves predicting driving behavior along a predetermined route, allowing autonomous vehicles to stay centered on the road, simulating diverse driving scenarios, and achieving significant reductions in route-following time. This framework utilizes deep hybrid learning methods and harnesses Nvidia GPU capabilities to evaluate the effectiveness of InceptionNet, ResNet-50, MobileNet, DenseNet, and VGG16 convolutional neural networks. It enhances vehicle route following with improved metrics such as reduced inference time, heightened accuracy, and minimized lane changes in training. The RADC demonstrates exceptional performance, notably achieving a mean square error of 0.0464, 0.0346, and a 6-millisecond inference time in challenging weather like hard rain and snow. The proposed model is validated through comprehensive experiments in the Airsim environment, showcasing notable interpretability, generalization, and robustness capabilities. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Decision making

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Enhancing Cybersecurity: A Pipeline Approach for Efficient Machine Learning Intrusion Detection 14

Enhancing Cybersecurity: A Pipeline Approach for Efficient M...

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14th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023

作者： Berei, Ethan Oun, Ahmed Khan, M. Ajmal Ohio Northern University Department of Electrical & Computer Engineering and Computer Science OH United States

ISBN: (纸本)9798350304138

The escalating commonness of severe cyberattacks on a global scale has advanced the critical need for integrating machine learning into cybersecurity practices. Seven models, trained on a reduced feature inSDN dataset, aim to detect malicious SDN traffic. Testing involves diverse traffic types generated with Pyshark and CICFlowMeter. The study achieves its goals by creating effective intrusion detection models, developing new test datasets, implementing the pipeline, and validating it through testing in the real-time practical network in the cybersecurity lab. The use of double-feature selection is pivotal. Overall, this research accelerates the deployment of supervised machine learning in intrusion detection, strengthening cybersecurity against evolving threats. © 2023 IEEE.

关键词： Pipelines

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Boosting efficiency and stability of 2D alternating cation perovskite solar cells via rational surface-modification: Marked passivation efficacy of anion

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Journal of Energy Chemistry 2023年第9期84卷 354-362页

作者： Hualin Zheng Xuefeng Peng Tingxi Chen Ting Zhang Shihao Yuan Lei Wang Feng Qian Jiang Huang Xiaodong Liu Zhi David Chen Yanning Zhang Shibin Li State Key Laboratory of Electronic Thin Films and Integrated Devices and School of Optoelectronic Science and EngineeringUniversity of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Institute of Fundamental and Frontier Sciences University of Electronic Science and Technology of China(UESTC)Chengdu 610054SichuanChina Department of Electrical&Computer Engineering and Center for Nanoscale Science&EngineeringUniversity of KentuckyLexingtonKY 40506USA Institute of Electronic and Information Engineering of UESTC in Guangdong Dongguan 523808GuangdongChina

Two-dimensional(2D) alternating cation(ACI) perovskite surface defects,especially dominant iodine vacancies(V_Ⅰ) and undercoordinated Pb^(2+),limit the performance of perovskite solar cells(PVSCs).To address the issue,1-butyl-3-methylimidazolium trifluoro-methane-sulfonate(BMIMOTF) and its iodide counterpart(BMIMI) are utilized to modify the perovskite surface *** find that BMIMI can change the perovskite surface,whereas BMIMOTF shows a nondestructive and more effective defect passivation,giving significantly reduced defect density and suppressed charge-carrier nonradiative *** mainly attributes to the marked passivation efficacy of OTF-anion on V_Ⅰ and undercoordinated Pb^(2+),rather than BMIMI^(+) *** from the rational surface-modification of BMMIMOTF,the films exhibit an optimized energy level alignment,enhanced hydrophobicity and suppressed ion ***,the BMIMOTF-modified devices achieve an impressive efficiency of 21.38% with a record open-circuit voltage of 1.195 V,which is among the best efficiencies reported for 2D PVSCs,and display greatly enhanced humidity and thermal stability.

关键词： 2D ACI perovskite solar cells Charge-carrier nonradiative recombination Surface defects passivation Energy level alignment Ionic migration Stability

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