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1st International Conference on Electronics, Communication and Signal Processing, ICECSP 2024

作者： Geetha, R. Vijayanandh, T. Ananthi, S.N. Mercilin Raajini, X. Divya Sundar, V.S. Kumari Deepika, P. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of EEE Tamil Nadu Chennai India School of Computing Vel Tech Rangarajan Dr. Sagunthala R and D Institute of Science and Technology Department of CSE Tamil Nadu Chennai India S.A Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India St. Joseph's College of Engineering Department of Artificial Intelligence and Data Science Tamil Nadu Chennai India

ISBN: (纸本)9798350364590

As time goes on and technology gets better, various data-sharing technologies are becoming more and more integrated into many different businesses. Therefore, data exchange and security are crucial for the data's value to be realized. Nevertheless, it is challenging to verify the authenticity of a basic data sharing method in order to detect electronic data usage traces. An further difficulty is the reluctance of data suppliers to provide their data. Employing Blockchain's distributed ledger, smart contract, data trust, and traceability features. For the purpose of facilitating secure access to data, this study introduces a blockchain-based data-sharing architecture that optimizes to circumvent the security and control issues associated with traditional centralized data sharing and administration. In addition, the research evaluates the practicality and safety of the prototype. Furthermore, this paper proposes a Secured data Management Scheme (SDMS) that utilizes blockchain technology to optimize data sharing efficiency. To assess the efficacy of this model, it is cross-validated with the conventional data Privacy Handler (DPH) method. While present centralized security solutions fail to meet security requirements in an IoT setting, blockchain technology provides a decentralized solution. Through the use of a blockchain and a WiFi-enabled network model, this article seeks to offer a secure communication framework for Internet of Things (IoT) devices. According to the results, attitudes and character quirks have a role in how the intelligence community plans to use a blockchain-based data-sharing model for integrating systems. This research demonstrated the viability of using blockchain technology in an intelligence community-centric data-sharing strategy. © 2024 IEEE.

关键词： data consistency

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FPGA Implementation of XOR-MUX based Full Adder and Truncated Multiplier for Signal Processing Applications 15

FPGA Implementation of XOR-MUX based Full Adder and Truncate...

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15th International Conference on computing Communication and Networking Technologies, ICCCNT 2024

作者： Pavithara, P. Raghapriya, N.R. Dinesh, P.M. Gowtham, S. Viji, D. Kavin Kumar, K. Chandrasekaran, Gokul Department of Electronics and Communication Engineering Kongu Engineering College Perundurai Erode638060 India Department of Computer Science and Engineering Erode Sengunthar Engineering College Thuduppathi638057 India Department of Electronics and Communication Engineering Sona College of Technology Salem636005 India Department of Electrical and Electronics Engineering KSR College of Engineering Tiruchengode637215 India Department of Artificial Intelligence and Data Science Erode Sengunthar Engineering College Thuduppathi638057 India Department of Electronics and Communication Engineering Karpagam Institute of Technology Coimbatore India

ISBN: (纸本)9798350370249

There has been considerable advancement in the digital world, particularly in image processing applications, in recent years. The most important requirements are area efficiency, minimal delay, low power consumption, and fast speed. Due to the arithmetic operations of adders and multipliers, digital devices are prone to have increase in the size of logic because they take up more space in VLSI implementation. The proposed method of XOR-MUX based full adder and truncated multiplier concentrates on reducing the delay and area. Replacing normal multipliers with truncated multipliers computes n bit output instead of 2n bit outputs that is, the MSB bit of the truncated multiplier are retained whereas the LSB bits are truncated thereby preserving the information. This is suitable for certain applications of FIR filters that do not concentrate on lower bit length. In this project, the conventional full adders are replaced by XOR-MUX based full adders and are utilized in truncated multipliers which results in area reduction by 1 2 . 6 6 % and delay reduction by 11.68 % with a modest increase in power consumption. This reduction in truncated multipliers contributes towards the design of high performance FIR filters in signal processing applications. ©2024 IEEE.

关键词： FIR filters

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GRACE-C: GENERALIZED RATE AGNOSTIC CAUSAL ESTIMATION VIA CONSTRAINTS 11

GRACE-C: GENERALIZED RATE AGNOSTIC CAUSAL ESTIMATION VIA CON...

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11th International Conference on Learning Representations, ICLR 2023

作者： Abavisani, Mohammadsajad Danks, David Plis, Sergey M. Department of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Halicioglu Data Science Institute Department of Philosophy University of California San Diego San DiegoCA92093 United States TReNDS Center Department of Computer Science Georgia State University AtlantaGA30302 United States

Graphical structures estimated by causal learning algorithms from time series data can provide misleading causal information if the causal timescale of the generating process fails to match the measurement timescale of the data. Existing algorithms provide limited resources to respond to this challenge, and so researchers must either use models that they know are likely misleading, or else forego causal learning entirely. Existing methods face up-to-four distinct shortfalls, as they might a) require that the difference between causal and measurement timescales is known;b) only handle very small number of random variables when the timescale difference is unknown;c) only apply to pairs of variables;or d) be unable to find a solution given statistical noise in the data. This paper addresses these challenges. Our approach combines constraint programming with both theoretical insights into the problem structure and prior information about admissible causal interactions to achieve multiple orders of magnitude in speed-up. The resulting system maintains theoretical guarantees while scaling to significantly larger sets of random variables (> 100) without knowledge of timescale differences. This method is also robust to edge misidentification and can use parametric connection strengths, while optionally finding the optimal solution among many possible ones. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Random variables

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On the Effectiveness of Function-Level Vulnerability Detectors for Inter-Procedural Vulnerabilities 24

On the Effectiveness of Function-Level Vulnerability Detecto...

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44th ACM/IEEE International Conference on Software engineering, ICSE 2024

作者： Li, Zhen Wang, Ning Zou, Deqing Li, Yating Zhang, Ruqian Xu, Shouhuai Zhang, Chao Jin, Hai Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Cluster and Grid Computing Lab National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hong Kong Jin YinHu Laboratory Wuhan China School of Cyber Science and Engineering Huazhong University of Science and Technology Wuhan China University of Colorado Colorado Springs Department of Computer Science Colorado Springs Colorado United States Institute for Network Sciences and Cyberspace Tsinghua University Beijing China School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798400702174

Software vulnerabilities are a major cyber threat and it is important to detect them. One important approach to detecting vulnerabilities is to use deep learning while treating a program function as a whole, known as function-level vulnerability detectors. However, the limitation of this approach is not understood. In this paper, we investigate its limitation in detecting one class of vulnerabilities known as inter-procedural vulnerabilities, where the to-be-patched statements and the vulnerability-triggering statements belong to different functions. For this purpose, we create the first Inter -Procedural Vulnerability dataset (InterPVD) based on C/C++ open-source software, and we propose a tool dubbed VulTrigger for identifying vulnerability-triggering statements across functions. Experimental results show that VulTrigger can effectively identify vulnerability-triggering statements and inter-procedural vulnerabilities. Our findings include: (i) inter-procedural vulnerabilities are prevalent with an average of 2.8 inter-procedural layers;and (ii) function-level vulner-ability detectors are much less effective in detecting to-be-patched functions of inter-procedural vulnerabilities than detecting their counterparts of intra-procedural vulnerabilities. © 2024 ACM.

关键词： Open source software

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Revolutionizing Medical Diagnostics with Transparent AI-Driven Decision Support Systems 4

Revolutionizing Medical Diagnostics with Transparent AI-Driv...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Annamalai, M. Mittal, Tanusha Sunkara, Krishna Chaitanya Pandey, Himani Jadhav, Girish Nemane, Vivek Vinsys It Services India Limited Pune India Graphic Era Deemed to be University Department of Computer Science & Engineering Dehradun India Oracle Cloud Engineering Data Center NC United States Baroda University Department of Environmental Science Vadodara India Parul institute of Engineering and Technology Parul University Faculty of Engineering and Technology Department of Electrical Engineering Post Limda India Faculty of Law Pune India

ISBN: (纸本)9798350352931

This study introduces an innovative AI-Driven Decision Support System (DSS) for revolutionizing healthcare diagnostics, emphasizing the use of Explainable AI (XAI) to enhance transparency and trust in medical decision-making. The proposed system integrates machine learning and deep learning algorithms to analyze and interpret complex medical data, providing clinicians with clear, understandable insights that support diagnostic accuracy and patient outcomes. The system was evaluated on a dataset of 25,000 patient records across multiple diagnostic domains, including cardiology, oncology, and radiology. Key performance metrics showed a significant improvement in diagnostic precision and explain ability. The model achieved an accuracy of 94.8% in diagnosing cardiac conditions, with an explanation accuracy of 92.1%, measured by how well the XAI techniques correlated with expert evaluations. For oncology cases, the system demonstrated an 87.5% reduction in false positives, while maintaining an overall accuracy of 93.2%. In terms of clinician trust, surveys indicated a 35% increase in confidence when using the XAI-based system compared to traditional black-box models. Additionally, the time to generate diagnostic explanations was reduced by 40%, improving clinical workflow and decision-making efficiency. These results underscore the transformative potential of integrating XAI into healthcare decision support systems, providing not only accurate predictions but also interpretable insights that enhance trust and usability in medical diagnostics. © 2024 IEEE.

关键词： Oncology

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On-site Testing and Preventive Maintenance for a Fire Automation System Employing PSO, FA and ANN Algorithms 1

On-site Testing and Preventive Maintenance for a Fire Automa...

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Rubini, B. Kalaiarasi, G. Vasuki, S. Pradeep Kumar, S. Murugan, Suganiya Arul Stephen, C. Vels Institute of Science Technology and Advanced Studies Department of Electrical and Electronics Engineering Pallavaram Chennai India Vignan Foundation for Science Technology and Research Deemed to Be University Department of Advanced Computer Science and Engineering Andhrapradesh Guntur India M. Kumarasamy College of Engineering Department of Electronics and Communication Engineering Tamilnadu Karur India Srm Institute of Science and Technology Department of Computing Technologies Kaattankulathur Chennai India Vels Institute of Science Technology and Advanced Studies Department of Electronics and Communication Engineering Pallavaram Chennai India

ISBN: (纸本)9798350359756

engineering elements influencing in commercial and government buildings fire safety rendition buildings have been deliberated. For both new and existing buildings, all variables such as structure of building, damage due to fire from prevention compartments, Time of incidents evacuation routes should be control leverage on people's evacuation routes, controlled, and additional standard fire protection equipment are imposed. This page outlines the classes of diesel fire pumps, batteries, and pumping systems, besides the elements prompting fire rendition. Onsite diesel generator pump must be connected to a hydrant and the water pumping pressure range must be customized to 8 bar using a pressure gauge. The substantive intent of this concert is to reinforce firefighter safety. Only experienced technicians and training professionals in fire guard are responsible for this part. To simulate the battery tightness position, an extra-critical condition has been considered. Owing to the position of the fire safety properties and battery reaction in buildings, the Firefly and Particle Swarm optimization algorithms have been exerted on the iterations with objective values used for analysis in the iterative process using Matlab 2021 software. Two well-known algorithms are compared to see which provides the best results. The ANN serves as a tool for analyzing and optimizing the pump's rendition in maintaining an adequate water supply for fire emergencies. © 2023 IEEE.

关键词： Fires

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Physics-aware cross-domain fusion aids learning-driven computer-generated holography

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Photonics Research 2024年第12期12卷 2747-2756页

作者： GANZHANGQIN YUAN MI ZHOU FEI LIU MU KU CHEN KUI JIANG YIFAN PENG ZIHAN GENG Institute of Data and Information Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518071China School of Optoelectronic Engineering Xidian UniversityXi’an 710071China Department of Electrical Engineering City University of Hong KongHong Kong SARChina School of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China Department of Electrical and Electronic Engineering The University of Hong KongHong Kong SARChina Department of Computer Science The University of Hong KongHong Kong SARChina

The rapid advancement of computer-generated holography has bridged deep learning with traditional optical principles in recent ***,a critical challenge in this evolution is the efficient and accurate conversion from the amplitude to phase domain for high-quality phase-only hologram(POH)*** computational models often struggle to address the inherent complexities of optical phenomena,compromising the conversion *** this study,we present the cross-domain fusion network(CDFN),an architecture designed to tackle the complexities involved in POH *** CDFN employs a multi-stage(MS)mechanism to progressively learn the translation from amplitude to phase domain,complemented by the deep supervision(DS)strategy of middle features to enhance task-relevant feature learning from the initial ***,we propose an infinite phase mapper(IPM),a phase-mapping function that circumvents the limitations of conventional activation functions and encapsulates the physical essence of *** simulations,our proposed method successfully reconstructs high-quality 2K color images from the DIV2K dataset,achieving an average PSNR of 31.68 dB and SSIM of ***,we realize high-quality color image reconstruction in optical *** experimental results highlight the computational intelligence and optical fidelity achieved by our proposed physics-aware cross-domain fusion.

关键词： computer cross holography

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Type II Fuzzy Logic Based Cluster Head Selection for Wireless Sensor Network

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computers, Materials & Continua 2022年第1期70卷 801-816页

作者： J.Jean Justus M.Thirunavukkarasan K.Dhayalini G.Visalaxi Adel Khelifi Mohamed Elhoseny Department of Computer Science&Engineering St.Joseph’s College of EngineeringChennai600119India School of Computing Science and Engineering Galgotias UniversityUttar Pradesh203201India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science&Engineering Bharath Institute of Higher Education and ResearchChennai600073India Department of Computer Science and Information Technology Abu Dhabi UniversityAbu Dhabi59911United Arab Emirates College of Computer Information Technology American University in the EmiratesDubaiUnited Arab Emirates Faculty of Computers and Information Mansoura UniversityEgypt

Wireless Sensor Network(WSN)forms an essential part of *** is embedded in the target environment to observe the physical parameters based on the type of *** nodes inWSN are constrained by different features such as memory,bandwidth,energy,and its processing *** WSN,data transmission process consumes the maximum amount of energy than sensing and processing of the ***,diverse clustering and data aggregation techniques are designed to achieve excellent energy efficiency in *** this view,the current research article presents a novel Type II Fuzzy Logic-based Cluster Head selection with Low Complexity data Aggregation(T2FLCH-LCDA)technique for *** presented model involves a two-stage process such as clustering and data ***,three input parameters such as residual energy,distance to Base Station(BS),and node centrality are used in T2FLCH technique for CH selection and cluster ***,the LCDA technique which follows Dictionary Based Encoding(DBE)process is used to perform the data aggregation at ***,the aggregated data is transmitted to the BS where it achieves energy *** experimental validation of the T2FLCH-LCDAtechnique was executed under three different scenarios based on the position of *** experimental results revealed that the T2FLCH-LCDA technique achieved maximum energy efficiency,lifetime,Compression Ratio(CR),and power saving than the compared methods.

关键词： Clustering data aggregation energy consumption cluster head selection wireless sensor networks

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A computer-aided diagnosis system for breast pathology: a deep learning approach with model interpretability from pathological perspective

A computer-aided diagnosis system for breast pathology: a de...

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作者： Hsu, Wei-Wen Wu, Yongfang Chen, Chung-Hao Hao, Chang Hou, Yu-Ling Gao, Xiang Shao, Yun Zhang, Xueli He, Tao Tai, Yanhong Department of Computer Science and Information Technology National Taitung University Taitung Taiwan Department of Pathology The Fifth Medical Center of Chinese PLA General Hospital Beijing China Department of Electrical and Computer Engineering Old Dominion University NorfolkVA United States Institute of Big Data Technology Bright Oceans Corporation Beijing China

In this study, a computer-aided diagnosis (CAD) system for whole-slide images (WSIs) with breast cancer was proposed to achieve lesion detection and classification. Different from the previously proposed works that performed segmentation directly and applied the segmentation metrics for performance evaluation, here we computed the accuracy in patch-level, region-level, and slide-level to access our proposed framework to meet the clinical requirements, instead of simply regarding it as an AI segmentation task. To achieve that for WSIs, lesion detection was conducted at high magnification (× 40) first for region proposal by patching using the modified AlexNet model;and then, several patches were sampled from the detected regions at lower magnification (× 10) to observe cells’ patterns for lesion classification by the model of ResNet50. With such fashion, the deep features being distinguishing in lesion classification from the convolutional neural networks (CNN) were further analyzed in this work to provide comprehensive interpretability for the proposed CAD system based on pathological knowledge. For our experiments, a total of 186 slides of WSIs were collected and classified into three categories: Non-Carcinoma, Ductal Carcinoma in Situ (DCIS), and Invasive Ductal Carcinoma (IDC). The slide-level accuracy rate for the three-category classification reached 90.8% (99/109) through a fivefold cross-validation and achieved 94.8% (73/77) on the testing set. In addition, the learned features reflect the clinical insights in lesion classification for explainable AI, which enhanced the reliability and validity of our proposed system. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.

关键词： computer aided diagnosis

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A Review and Bibliometric Analysis of the Current Studies for the 6G Networks

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computer Modeling in engineering & sciences 2024年第9期140卷 2165-2206页

作者： Qusay M.Salih Md.Arafatur Rahman Ahmad Firdaus Mohammed Rajih Jassim Hasan Kahtan Jasni Mohamad Zain Ahmed Hussein Ali Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah(UMPSA)PekanPahang26600Malaysia Department of Medical Equipment Technology Engineering Al Salam University CollegeBaghdadIraq School of Mathematics and Computer Science University of WolverhamptonWolverhampton01902UK Department of Production Engineering and Metallurgy University of TechnologyBaghdadIraq Cardiff School of Technologies Cardiff Metropolitan UniversityCardiffCF52YBUK Institute for Big Data Analytics and Artificial Intelligence(IBDAAI) Kompleks Al-KhawarizmiUniversiti Teknologi MARAShah AlamSelangor40450Malaysia Department Computer Science Al-Salam University CollegeBaghdadIraq

The race to develop the next generation of wireless networks,known as Sixth Generation(6G)wireless,which will be operational in 2030,has already *** realize its full potential over the next decade,6G will undoubtedly necessitate additional improvements that integrate existing solutions with cutting-edge ***,the studies about 6G are mainly limited and scattered,whereas no bibliometric study covers the 6G ***,this study aims to review,examine,and summarize existing studies and research activities in *** study has examined the Scopus database through a bibliometric analysis of more than 1,000 papers published between 2017 and ***,we applied the bibliometric analysis methods by including(1)document type,(2)subject area,(3)author,and(4)country of *** study’s results reflect the research 6G community’s trends,highlight important research challenges,and elucidate potential directions for future research in this interesting area.

关键词： 6G bibliometric wireless networks review

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