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Remote Sensing Data-Based Satellite Image Analysis in Water Quality Detection for Public Health Data Modelling

Remote Sensing in Earth Systems sciences 2024年第4期7卷 532-541页

作者： Balakrishnan, S. Preetam Raj, P Michael Somasekar, J. Kumar, Kambala Vijaya Amutha, S. Sangeetha, A. Department of Computer Science and Engineering Aarupadai Veedu Institute of Technology (AVIT) Vinayaka Mission’s Research Foundation (Deemed to be University) Chennai India Department of Computer Science and Engineering MLR Institute of Technology Telangana Dundigal Hyderabad 500043 India Department of Computer Science and Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be-University) Karnataka Bengaluru 562112 India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram AP India Department of Computer Science and Engineering School of Computing Vel Tech Rangarajan Dr. Sagunthala R & amp D Institute of Science and Technology Tamilnadu Chennai India Department of Artificial Intelligence and Data Science Kongunadu College of Engineering and Technology TamilNadu Tholurpatti India

One of the most important aspects of environmental sustainability is water quality monitoring. The ecology is impacted by poor water quality in addition to aquatic life. With the volume of data being collected from satellite systems, the issue of effectively and automatically extracting water bodies is growing more pressing. One of the most important things to do for managing and safeguarding water resources is to conduct extensive monitoring of water quality parameters, or WQPs. It is still difficult to monitor optically inactive WQPs in inland waters, such as total nitrogen (TN), ammoniacal nitrogen (AN), and total phosphorus (TP). Water quality (WQ) classification and prediction can be greatly enhanced with the use of artificial intelligence (AI). This research proposes novel method in healthcare detection by water quality analysis based on classification utilising ML model. Input is collected as healthcare dataset based on water quality as well as processed for noise removal and normalisation. The processed data features are extracted and classified utilising reinforcement Gaussian stacked layer network with variational fuzzy Markov basis neural network. In order to suggest best course of action for the water bodies, it is imperative that any study look into the spatiotemporal changes of the dominant water quality parameters (WQPs). WQP concentrations have typically been determined by extensive fieldwork. These findings could help identify and regulate non-point source pollution, offer a large-scale spatial picture of the water quality, and pinpoint vulnerable locations and times of water pollution. Experimental analysis is carried out for various water sample dataset in terms of detection accuracy, mean precision, recall, F-1 score and AUC. The proposed technique obtained 97% of detection accuracy, 95% of recall, 91% of F-1 score, 96% of AUC, and 94% of MAP. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Classification Fuzzy Markov basis Healthcare detection Machine learning model Water quality analysis

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A lightweight identity based generalized signcryption scheme for secure communication in standard model

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International Journal of Information Technology (Singapore) 2024年第2期16卷 1221-1229页

作者： Singh, Tej Kumar, Mukesh Gelmecha, Demissie Jabir Thakur, Ganesh Kumar Tyagi, Vikas Sori, Worku Jifara Department of Applied Sciences ABES Engineering College UP Ghaziabad India Institute of Applied Sciences & Humanities GLA University UP Mathura India Department of Electronics and Communication Engineering School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia Department of CSE IMS Engineering College UP Ghaziabad India Department of Computer Science School of Electrical Engineering and Computing Adama Science and Technology University Adama Ethiopia

The implementation of secure communication in the Industrial Internet of Things (IIoT) has made and it is a significant security concern. Identity-based generalized signcryption scheme is one among the cryptographic tools available that offers a secure way out to meet the security needs of IIoT. Our proposal is a lightweight scheme, an efficient identity-based generalized signcryption that works as an encryption signature, or signcryption scheme using only one algorithm in a standard model. This scheme is appropriate for storage-limited environments like wireless sensor networks and smart cards due to its lightweight nature. This means that it can be implemented in a range of IIoT applications where resources are limited, without compromising on security or efficiency. © The Author(s), under exclusive licence to Bharati Vidyapeeth's institute of computer Applications and Management 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s);author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

关键词： Bilinear Pairing Generalized signcryption Identity-based cryptography Signcryption

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A Parallel Hybrid Testing Technique for Tri-Programming Model-Based Software Systems

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computers, Materials & Continua 2023年第2期74卷 4501-4530页

作者： Huda Basloom Mohamed Dahab Abdullah Saad AL-Ghamdi Fathy Eassa Ahmed Mohammed Alghamdi Seif Haridi Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Systems Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah21493Saudi Arabia KTH Royal Institute of Technology StockholmSweden

Recently,researchers have shown increasing interest in combining more than one programming model into systems running on high performance computing systems(HPCs)to achieve exascale by applying parallelism at multiple *** different programming paradigms,such as Message Passing Interface(MPI),Open Multiple Processing(OpenMP),and Open Accelerators(OpenACC),can increase computation speed and improve *** the integration of multiple models,the probability of runtime errors increases,making their detection difficult,especially in the absence of testing techniques that can detect these *** studies have been conducted to identify these errors,but no technique exists for detecting errors in three-level programming *** the increasing research that integrates the three programming models,MPI,OpenMP,and OpenACC,a testing technology to detect runtime errors,such as deadlocks and race conditions,which can arise from this integration has not been ***,this paper begins with a definition and explanation of runtime errors that result fromintegrating the three programming models that compilers cannot *** the first time,this paper presents a classification of operational errors that can result from the integration of the three *** paper also proposes a parallel hybrid testing technique for detecting runtime errors in systems built in the C++programming language that uses the triple programming models MPI,OpenMP,and *** hybrid technology combines static technology and dynamic technology,given that some errors can be detected using static techniques,whereas others can be detected using dynamic *** hybrid technique can detect more errors because it combines two distinct *** proposed static technology detects a wide range of error types in less time,whereas a portion of the potential errors that may or may not occur depending on the 4502 CMC,2023,vol.74,no.2 operating environme

关键词： Software testing hybrid testing technique OpenACC OpenMP MPI tri-programming model exascale computing

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Sentiment Analysis using VADER: Unveiling Customer Sentiment and Predicting Buying Behavior in the Airline Industry 2

Sentiment Analysis using VADER: Unveiling Customer Sentiment...

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2nd IEEE International Conference for Women in Innovation, Technology and Entrepreneurship, ICWITE 2024

作者： Annamalai, R. Rasool, Shaik Atheeq Deena, S. Venkatraman, K. Soundaram, Y. Amrita Vishwa Vidyapeetham School of Computing Computer Science and Engineering Chennai India Annamalai University Department of Cse Chennai Chidambaram India St.Peter's Institute of Higher Education and Research Computer Science and Engineering India

ISBN: (纸本)9798350383287

This study focuses on leveraging sentiment analysis using VADER (Valence Aware Dictionary and Sentiment Reasoner) to analyze customer reviews and predict buying behavior in the airline industry, with a specific focus on British Airways. The study aims to enhance customer experience and provide valuable insights for the airline company. The study begins by applying web scraping techniques to collect customer reviews from the Airline Quality website. The collected unstructured data is then processed and cleaned for further analysis. VADER sentiment analysis is utilized to determine the sentiment of each customer review, classifying them as positive, negative, or neutral. This analysis provides valuable insights into customer sentiment towards British Airways, enabling the airline to identify areas of improvement and address customer concerns. Furthermore, the study involves creating a classification model to predict customer buying behavior. Various features such as flight routes, booking origins, trip types, number of passengers, and customer preferences are considered to build the model. Random Forest Classifier, XGBoost Classifier, Logistic Regression and KNN algorithms are employed to train and evaluate the models. By accurately predicting buying behavior, British Airways can tailor their services and offerings to meet customer expectations, resulting in improved customer satisfaction and increased bookings. The findings and insights from this study provide British Airways with valuable information to optimize their operations, enhance customer experience, and stay competitive in the airline industry. By understanding customer sentiment and predicting buying behavior, the airline can make data-driven decisions to attract and retain customers, ultimately leading to improved business performance and success. © 2024 IEEE.

关键词： Sentiment analysis

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Insights into research on blockchain for smart contracts: a bibliometric analysis

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Multimedia Tools and Applications 2024年 1-25页

作者： Singh, Renu Gupta, Ashlesha Mittal, Poonam Faculty of Informatics and Computing J.C. Bose University of Science and Technology YMCA Faridabad India Department of Computer Science & amp Engineering Indraprastha Institute of Information Technology IIIT New Delhi India

Over the past few years, blockchain technology has gained significant attention. This surge in popularity can be attributed to the emergence of cryptocurrencies and the development of smart contracts. Cryptocurrency is a digital currency that eliminates the problem of double spending. Cryptocurrencies like Bitcoin, Ethereum, Litecoin, Stellar, Zcash, Maker, Aave, etc. become popular and are preferred for money transfers. Smart contracts are the next popular technology on the blockchain after cryptocurrency. It can be considered a piece of code that can execute automatically when the predefined conditions are fulfilled. researchers believe that the potential of blockchain with smart contracts is only in its initial stages and that its true potential has yet to be fully discovered. Hence, an extensive bibliometric analysis is conducted to understand blockchain trends for smart contracts and to give future directions in this field. For this analysis, various steps are followed, starting with formulating the research question, defining the scope of our research, extracting and analyzing data, answering the research question, and finally, drawing a conclusion. This research paper will be fruitful for scholars and researchers, providing an extensive statistical and network analysis of extracted smart contracts publications. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Bibliometric analysis Blockchain Crypto contract Scientometrics Scopus Smart contracts VOSViewer

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Pneumonia Disease Assessment with Full Diagnostics Evaluation 2

Pneumonia Disease Assessment with Full Diagnostics Evaluatio...

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2nd IEEE International Conference on Trends in Quantum computing and Emerging Business Technologies, TQCEBT 2024

作者： Nithin, Rayala Nagarajan, G. Sai Prathap, Thammishetti Venkat Pradeep, Srikonda Sampreeth, Itharaju School of Computing Department of Computer Science and Engineering Kalasalingam Academy of Research and Education Anand Nagar Krishnankoil Virudhnagar India

ISBN: (纸本)9798350384277

Pneumonia remains a critical global health issue, causing significant illness and mortality, especially in vulnerable populations. Early and precise diagnosis is essential for effective management and timely the intervention. This research paper introduces a novel integrated approach for the prediction and comprehensive diagnostics of pneumonia, harnessing cutting-edge advancements in medical imaging, machine learning, and clinical data analysis. The proposed framework merges three fundamental components: (1) Chest X-ray Image Analysis, (2) Clinical Data Integration, and (3) Machine Learning-Based Prediction. The chest X-ray image analysis employs state-of-the-art deep learning techniques to automatically identify and classify pneumonia-related anomalies, offering detailed insights into pulmonary conditions. Simultaneously, clinical data, encompassing patient history, demographics, and laboratory results, are integrated into the predictive model. A hybrid machine learning algorithm, combining Convolutional Neural Networks (CNN) and Gradient Boosting, is utilized to ensure robust and precise disease prediction. The research demonstrates the efficacy of this integrated approach through a thorough evaluation on a substantial dataset of pneumonia cases. Findings indicate a notable enhancement in pneumonia prediction accuracy compared to conventional diagnostic methods. Moreover, the model's interpretability is enhanced, allowing healthcare professionals to scrutinize the rationale behind each prediction, promoting trust and transparency in the decision-making process. © 2024 IEEE.

关键词： Support vector machines

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Knowledge-enriched joint-learning model for implicit emotion cause extraction

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CAAI Transactions on Intelligence Technology 2023年第1期8卷 118-128页

作者： Chenghao Wu Shumin Shi Jiaxing Hu Heyan Huang School of Computer Science and Technology Beijing Institute of TechnologyBeijingChina Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications BeijingChina

Emotion cause extraction(ECE)task that aims at extracting potential trigger events of certain emotions has attracted extensive attention ***,current work neglects the implicit emotion expressed without any explicit emotional keywords,which appears more frequently in application *** lack of explicit emotion information makes it extremely hard to extract emotion causes only with the local ***,an entire event is usually across multiple clauses,while existing work merely extracts cause events at clause level and cannot effectively capture complete cause event *** address these issues,the events are first redefined at the tuple level and a span-based tuple-level algorithm is proposed to extract events from different *** on it,a corpus for implicit emotion cause extraction that tries to extract causes of implicit emotions is *** authors propose a knowledge-enriched jointlearning model of implicit emotion recognition and implicit emotion cause extraction tasks(KJ-IECE),which leverages commonsense knowledge from ConceptNet and NRC_VAD to better capture connections between emotion and corresponding cause *** on both implicit and explicit emotion cause extraction datasets demonstrate the effectiveness of the proposed model.

关键词： emotion cause extraction external knowledge fusion implicit emotion recognition joint learning

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Static Analysis Techniques for Fixing Software Defects in MPI-Based Parallel Programs

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computers, Materials & Continua 2024年第5期79卷 3139-3173页

作者： Norah Abdullah Al-Johany Sanaa Abdullah Sharaf Fathy Elbouraey Eassa Reem Abdulaziz Alnanih Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Software Engineering and Distributed System Research Group King Abdulaziz UniversityJeddah21589Saudi Arabia

The Message Passing Interface (MPI) is a widely accepted standard for parallel computing on distributed ***, MPI implementations can contain defects that impact the reliability and performance of parallelapplications. Detecting and correcting these defects is crucial, yet there is a lack of published models specificallydesigned for correctingMPI defects. To address this, we propose a model for detecting and correcting MPI defects(DC_MPI), which aims to detect and correct defects in various types of MPI communication, including blockingpoint-to-point (BPTP), nonblocking point-to-point (NBPTP), and collective communication (CC). The defectsaddressed by the DC_MPI model include illegal MPI calls, deadlocks (DL), race conditions (RC), and messagemismatches (MM). To assess the effectiveness of the DC_MPI model, we performed experiments on a datasetconsisting of 40 MPI codes. The results indicate that the model achieved a detection rate of 37 out of 40 codes,resulting in an overall detection accuracy of 92.5%. Additionally, the execution duration of the DC_MPI modelranged from 0.81 to 1.36 s. These findings show that the DC_MPI model is useful in detecting and correctingdefects in MPI implementations, thereby enhancing the reliability and performance of parallel applications. TheDC_MPImodel fills an important research gap and provides a valuable tool for improving the quality ofMPI-basedparallel computing systems.

关键词： High-performance computing parallel computing software engineering software defect message passing interface deadlock

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Intense Triad Defender for End-User Security in Cyber Physical System 2

Intense Triad Defender for End-User Security in Cyber Physic...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Sheryl Sharon, G. Maranco, M. Nidhya, R. Sivakumar, M. Coimbatore Institute of Technology Department of Computer Science and Engineering Coimbatore641014 India SRM Institute of Science and Technology School of Computing Faculty of Engineering and Technology Department of Networking and Communications Kattankulathur603203 India Madanapalle Institute of Technology and Science Department of Computer Science and Engineering Andhra Pradesh Madanapalle India

ISBN: (数字)9798350365269

ISBN: (纸本)9798350365269

The rapid advancement of technology has undoubtedly brought comfort to humanity, but it also necessitates robust authentication measures to ensure security in the ever-expanding e-world. This research aims to address the critical aspects of security, focusing on end-user authentication. The proposed solution incorporates multiple factors, including location-based authentication, text-based authentication with enhanced encryption standards, and facial recognition authentication. Location-based authentication serves to restrict access geographically, mitigating the risk of impersonation by enforcing strict geographic limits on facility access. Strong text passwords, utilizing a unique algorithm with a classic salt method, add an extra layer of complexity for potential attackers, making it challenging to compromise user credentials. The incorporation of facial recognition technology acts as a deterrent against non-human entities attempting unauthorized access. Leveraging deep learning and API servers ensures precision and scalability in the model, enhancing its effectiveness in real-world scenarios. These multi-factor authentication techniques collectively contribute to a secure, reliable, and forward-looking solution to address the evolving landscape of digital security threats. In adhering to the age-old adage "prevention is better than cure,"the research emphasizes the importance of proactive measures to safeguard against potential security breaches. © 2024 IEEE.

关键词： Network security

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A Design and Challenges in Energy Optimizing CR-Wireless Sensor Networks

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Recent Advances in computer science and Communications 2023年第5期16卷 82-92页

作者： Reddy, Pundru Chandra Shaker Sucharitha, Yadala School of Computing and Information Technology REVA University Karnataka Bengaluru India Department of Computer Science and Engineering CMR Institute of Technology TS Hyderabad India

Background: The progress of the Cognitive Radio-Wireless Sensor Network is being influenced by advancements in wireless sensor networks (WSNs), which significantly have unique features of cognitive radio technology (CR-WSN). Enhancing the network lifespan of any network requires better utilization of the available spectrum as well as the selection of a good routing mechanism for transmitting informational data to the base station from the sensor node without data conflict. Aims: Cognitive radio methods play a significant part in achieving this, and when paired with WSNs, the above-mentioned objectives can be met to a large extent. Methods: A unique energy-saving Distance-Based Multi-hop Clustering and Routing (DBMCR) methodology in association with spectrum allocation is proposed as a heterogeneous CR-WSN model. The supplied heterogeneous CR-wireless sensor networks are separated into areas and assigned a different spectrum depending on the distance. Information is sent over a multi-hop connection after dynamic clustering using distance computation. Results: The findings show that the suggested method achieves higher stability and ensures the energy-optimizing CR-WSN. The enhanced scalability can be seen in the First Node Death (FND). Additionally, the improved throughput helps to preserve the residual energy of the network which helps to address the issue of load balancing across nodes. Conclusion: Thus, the result acquired from the above findings shows that the proposed heterogeneous model achieves the enhanced network lifetime and ensures the energy optimizing CR-WSN. © 2023 Bentham science Publishers.

关键词： Cognitive radio

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