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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Priyan Kishore, M.S. Chandana Sathwika, U. Malarvel, Muthukumaran Hindustan Institute Of Technology And Science Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

The proliferation of distributed networks and the increasing demand for remote collaboration and maintenance have highlighted the need for secure and controlled remote access solutions. This paper presents a novel approach to establishing remote network access through a distributed tunneling management system. The proposed methodology addresses the challenges of providing authenticated and controlled access to private networks while facilitating seamless remote collaboration and maintenance tasks. The system architecture comprises a public tunneling server responsible for hosting the tunneling service and a separate management server dedicated to handling client connections, tunnel creation, and termination. Client networks run background processes that communicate with the communication server through websocket connections, enabling tunnel establishment and termination based on authorized requests. The methodology incorporates authentication mechanisms and secure protocols to ensure the confidentiality and integrity of communication channels. The distributed nature of the architecture enhances scalability, allowing multiple client networks to leverage the tunneling service concurrently. Experimental results demonstrate the viability of the implemented protocols, showcasing efficient computation, storage, communication and practical solutions for remote access to local networks, with potential applications across various industries, including IT support, remote collaboration, and maintenance operations while ensuring the confidentiality and integrity of sensitive data. © 2024 IEEE.

关键词： Network security

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Lecter-A Large Language Model Chatbot for Cognitive Behavioral Therapy 7th

Lecter-A Large Language Model Chatbot for Cognitive Behavior...

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7th IFIP TC 12 International Conference on Computational Intelligence in Data science, ICCIDS 2024

作者： Sham Sundhar, R. Shivavardhini, T. Daphine Desona Clemency, C.A. Roobini, M.S. Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai India

ISBN: (纸本)9783031699818

Mental Illnesses such as Anxiety and Depression are fairly prevalent in modern society. Yet most people do not get diagnosed, cannot afford treatment, or there simply aren’t any readily available practitioners. In the worst-case scenario, avoiding treatment can increase the likelihood of self-harm in affected individuals, both emotionally and physically. A low-cost and easily available solution is required to provide the benefits of therapy to the masses. In this paper, we introduce "Lecter", a chatbot solution specifically targeted to providing free mental health care to individuals who cannot access an actual therapist. With the help of the superior conversational abilities of an LLM (large language model), Lecter listens to the concerns and problems that patients face and helps them introspect, and better understand their feelings using a popular therapy technique called Cognitive Behavioral Therapy (CBT). Lecter provides its services using technologies such as an LLM called Mythomax, React Js for the front end of the application, Flask for the back end, and MongoDB for authentication and storage. © IFIP International Federation for information Processing 2024.

关键词： Emotion Recognition

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Investigation of Android Malware with Machine Learning Classifiers using Enhanced PCA Algorithm

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computer Systems science & engineering 2023年第3期44卷 2147-2163页

作者： V.Joseph Raymond R.Jeberson Retna Raj Department of Computer Science and Engineering Sathyabama Institute of Science and TechnologyChennai600119TamilnaduIndia School of Computing SRM Institute of Science and TechnologyChennai603203TamilnaduIndia

Android devices are popularly available in the commercial market at different price levels for various levels of *** Android stack is more vulnerable compared to other platforms because of its open-source *** are many android malware detection techniques available to exploit the source code andfind associated components during execution *** obtain a better result we create a hybrid technique merging static and dynamic *** this paper,in thefirst part,we have proposed a technique to check for correlation between features and classify using a supervised learning approach to avoid Mul-ticollinearity problem is one of the drawbacks in the existing *** the proposed work,a novel PCA(Principal Component Analysis)based feature reduction technique is implemented with conditional dependency features by gathering the functionalities of the application which adds novelty for the given *** Android Sensitive Permission is one major key point to be considered while detecting *** select vulnerable columns based on features like sensitive permissions,application program interface calls,services requested through the kernel,and the relationship between the variables henceforth build the model using machine learning classifiers and identify whether the given application is malicious or *** goal of this paper is to check benchmarking datasets collected from various repositories like virus share,Github,and the Canadian Institute of cyber security,compare with models ensuring zero-day exploits can be monitored and detected with better accuracy rate.

关键词： Zero-day exploit hybrid analysis principal component analysis supervised learning smart cities

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ImmuneChain: A Blockchain-Based Secure and Transparent Vaccine Supply Chain

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SN computer science 2025年第1期6卷 1-13页

作者： Arsheen, Sobiya Ahmad, Khaleel Department of Computer Science and Information Technology Maulana Azad National Urdu University (A Central University) Hyderabad India

Blockchain technology has the capability to handle information in a decentralized, permanent, transparent, and secure manner, which makes it unique. The data of the vaccine supply chain is maintained either manually or kept on a central server, which can be removed or tampered with. The integration of blockchain technology into the vaccine supply chain gives users a means of establishing trust. Utilizing blockchain technology to counter challenges in the global supply chain management of medicinal products is expanding quickly. Blockchain leads to secured, transparent, and traceable data over the network. This research proposes a blockchain-based vaccine supply chain to guarantee the efficiency of vaccine distribution in health centers, as well as the traceability, accuracy, and trustworthiness of immutable records. A blockchain-based supply chain acts as a safe, efficient, and transparent link in the distribution of vaccines. The proposed work connects all the stakeholders, such as the manufacturer, distributor, and health centers, using the Hyperledger Fabric blockchain platform. It also provides an interface for users to verify the authenticity of the vaccine vial and its quality. The performance of the proposed system is tested by the Hyperledger Caliper tool. The blockchain-based vaccine supply chain improves data availability and efficiency since all network participants get the responses instantly. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blockchain Hyperledger fabric Supply chain Traceability Vaccines

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Enhanced Visual Question Answering System Using DenseNet

Enhanced Visual Question Answering System Using DenseNet

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Nithish, S. Kawinbalaji, E.M. Sudalaimuthu, T. Hindustan Institute Of Technology And Science Department Of Computer Science And Engineering Chennai India

ISBN: (纸本)9798350364828

Visual Question Answering (VQA) system represents an essential usage of computer vision and natural language processing, enabling machines to understand and react to inquiries about images. This study outlines the architecture and methodologies employed in VQA system. Initially, the image undergoes feature selection and extraction using Dense Convolutional Neural Network (DenseNet) to capture its visual aspects. Simultaneously, LSTM (Long Short-Term Memory), a recurrent neural network interprets the textual question, deciphering its semantic context. The multimodal fusion of visual and textual information with the help of attention mechanism, facilitates the creation of a cohesive representation. ViLBERT (Vision-and-Language BERT), a natural language processing technique leverages this joint representation to infer and generate accurate responses to the posed questions. The complexities of VQA systems lie in managing diverse visual content, resolving ambiguities, and reasoning about relationships within images. This system demonstrates promising applications in aiding the visually impaired, enhancing human-computer interaction, and refining image-based retrieval systems, aim to enhance their accuracy, robustness, and interpretability. © 2024 IEEE.

关键词： computer vision

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Enhanced Metaheuristics-Based Clustering Scheme for Wireless Multimedia Sensor Networks

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computers, Materials & Continua 2022年第11期73卷 4179-4192页

作者： R.Uma Mageswari Sara A.Althubiti Fayadh Alenezi E.Laxmi Lydia Gyanendra Prasad Joshi Woong Cho Department of Computer Science and Engineering Vardhaman College of Engineering(Autonomous)HyderabadTelangana501218India Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySaudi Arabia Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea

Traditional Wireless Sensor Networks(WSNs)comprise of costeffective sensors that can send physical parameters of the target environment to an intended *** the evolution of technology,multimedia sensor nodes have become the hot research topic since it can continue gathering multimedia content and scalar from the target *** existence of multimedia sensors,integrated with effective signal processing and multimedia source coding approaches,has led to the increased application of Wireless Multimedia Sensor Network(WMSN).This sort of network has the potential to capture,transmit,and receive multimedia *** energy is a major source in WMSN,novel clustering approaches are essential to deal with adaptive topologies of WMSN and prolonged network *** this motivation,the current study develops an Enhanced Spider Monkey Optimization-based Energy-Aware Clustering Scheme(ESMO-EACS)for *** proposed ESMO-EACS model derives ESMO algorithm by incorporating the concepts of SMO algorithm and quantum *** proposed ESMO-EACS model involves the design of fitness functions using distinct input parameters for effective construction of clusters.A comprehensive experimental analysis was conducted to validate the effectiveness of the proposed ESMO-EACS technique in terms of different performance *** simulation outcome established the superiority of the proposed ESMO-EACS technique to other methods under various measures.

关键词： Wireless multimedia sensor networks clustering spider monkey optimization algorithm energy efficiency metaheuristics quantum computing

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Ensemble of Handcrafted and Deep Learning Model for Histopathological Image Classification

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computers, Materials & Continua 2022年第11期73卷 4393-4406页

作者： Vasumathi Devi Majety N.Sharmili Chinmaya Ranjan Pattanaik ELaxmi Lydia Subhi R.M.Zeebaree Sarmad Nozad Mahmood Ali S.Abosinnee Ahmed Alkhayyat Department of Computer Science Engineering Vignan’s Nirula Institute of Technology and Science for WomenGuntur522005India Department of Computer Science Engineering Gayatri Vidya Parishad College of Engineering for WomenVisakhapatnam530048India Department of Computer Science and Engineering Ajay Binay Institute of Technology CuttackOdisha750314India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Energy Department Technical College of EngineeringDuhok Polytechnic UniversityDuhokIraq Computer Technology Engineering College of Engineering TechnologyAl-Kitab UniversityIraq Computer Technical Engineering Department College of Technical EngineeringThe Islamic UniversityNajaf54001Iraq College of Technical Engineering The Islamic UniversityNajafIraq

Histopathology is the investigation of tissues to identify the symptom of *** histopathological procedure comprises gathering samples of cells/tissues,setting them on the microscopic slides,and staining *** investigation of the histopathological image is a problematic and laborious process that necessitates the expert’s *** the same time,deep learning(DL)techniques are able to derive features,extract data,and learn advanced abstract data *** this view,this paper presents an ensemble of handcrafted with deep learning enabled histopathological image classification(EHCDL-HIC)*** proposed EHCDLHIC technique initially performs Weiner filtering based noise removal *** the images get smoothened,an ensemble of deep features and local binary pattern(LBP)features are *** the classification process,the bidirectional gated recurrent unit(BGRU)model can be *** the final stage,the bacterial foraging optimization(BFO)algorithm is utilized for optimal hyperparameter tuning process which leads to improved classification performance,shows the novelty of the *** validating the enhanced execution of the proposed EHCDL-HIC method,a set of simulations is *** experimentation outcomes highlighted the betterment of the EHCDL-HIC approach over the existing techniques with maximum accuracy of 94.78%.Therefore,the EHCDL-HIC model can be applied as an effective approach for histopathological image classification.

关键词： Histopathological image classification machine learning deep learning handcrafted features bacterial foraging optimization

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Sustainable Water Futures: Enhancing Efficiency And Conservation In Madinah AL Munawara

Journal of Applied Science and Engineering

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Journal of Applied science and engineering 2024年第10期28卷 2027-2042页

作者： Syed, Toqeer Ali Naqash, Muhammad Tayyab Nawaz, Waqas Namoun, Abdallah Muhammad, Munir Azam Faculty of Computer and Information System Islamic University of Madinah Saudi Arabia Civil Engineering Department Faculty of Engineering Islamic University of Madinah Madinah42351 Saudi Arabia AI Center Faculty of Computer and Information Systems Islamic University of Madinah Madinah42351 Saudi Arabia Khwaja Fareed University of Engineering & Information Technology Faculty of Computer and Information System Punjab Rahim Yar Khan Pakistan

Water resource management worldwide faces significant challenges, including high consumption rates, scarcity, and ageing infrastructure. This paper proposes a comprehensive approach to address these issues through five key solutions. Advanced Metering Infrastructure (AMI) first facilitates real-time data collection and consumer awareness campaigns. Secondly, wastewater recycling and reuse are promoted by upgrading wastewater treatment plants and fostering public-private partnerships. Thirdly, reducing network losses is achieved through leak detection systems and regular maintenance. Fourthly, policy enhancement and regulatory frameworks are strengthened by implementing regulations for new developments and incentives for water-saving technologies. Lastly, community engagement and education initiatives are undertaken to promote sustainable water practices. This multifaceted strategy aims to improve water conservation, efficiency, and resilience of the water supply system. This paper proposes solutions that can be applied to the Madinah AL Munawara region of Saudi Arabia, an area of utmost importance, demonstrating the applicability and effectiveness of these solutions in addressing regional water management challenges. © The Author(’s).

关键词： Wastewater treatment

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Investigating Symbolic Capabilities of Large Language Models 1

Investigating Symbolic Capabilities of Large Language Models

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1st International Workshop on Logical Foundations of Neuro-Symbolic AI, LNSAI 2024

作者： Dave, Neisarg Kifer, Daniel Giles, C. Lee Mali, Ankur College of Information Sciences and Technology The Pennsylvania State University United States Department of Computer Science and Engineering The Pennsylvania State University United States Department of Computer Science and Engineering University of South Florida United States

Prompting techniques have significantly enhanced the capabilities of Large Language Models (LLMs) across various complex tasks, including reasoning, planning, and solving math word problems. However, most research has predominantly focused on language-based reasoning and word problems, often overlooking the potential of LLMs in handling symbol-based calculations and reasoning. This study aims to bridge this gap by rigorously evaluating LLMs on a series of symbolic tasks, such as addition, multiplication, modulus arithmetic, numerical precision, and symbolic counting. Our analysis encompasses eight LLMs, including four enterprise-grade and four open-source models, of which three have been pre-trained on mathematical tasks. The assessment framework is anchored in Chomsky’s Hierarchy, providing a robust measure of the computational abilities of these models. The evaluation employs minimally explained prompts alongside the zero-shot Chain of Thoughts technique, allowing models to navigate the solution process autonomously. The findings reveal a significant decline in LLMs’ performance on context-free and context-sensitive symbolic tasks as the complexity, represented by the number of symbols, increases. Notably, even the fine-tuned GPT3.5 exhibits only marginal improvements, mirroring the performance trends observed in other models. Across the board, all models demonstrated a limited generalization ability on these symbol-intensive tasks. This research underscores LLMs’ challenges with increasing symbolic complexity and highlights the need for specialized training, memory and architectural adjustments to enhance their proficiency in symbol-based reasoning tasks. © 2024 Copyright for this paper by its authors.

关键词： Open systems

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Efficient UAV Routing Strategies for Wireless Sensor Network Data Retrieval

Efficient UAV Routing Strategies for Wireless Sensor Network...

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2024 International Conference on Decision Aid sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Al-Sharhanee, Kareem Ali Malalah Najim, Ali Hamza Alheeti, Khattab M. Ali Satar, Nurhizam Safie Mohd Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University Baghdad10011 Iraq Department of Computer Technical Al-Diwaniyah Iraq College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

WSNs are applied in many disciplines where certain conditions require the ability to adapt to network sink mobility and changes in the dynamics of the area coverage. To meet these needs, it is necessary to develop integrated systems where the ''terrestrial' systems and the Unmanned Aerial Vehicles (UAVs)' collect data from sensors efficiently. Planning of UAV trajectories is another challenging issue if many WSN nodes are randomly deployed. This challenge has a big impact on the overall effectiveness of the system. This paper presents a novel approach for reducing the traveled distance of unscrewed aerial vehicles (UAVs) to improve the data collection efficiency in WSNs with poor node density. Yet the method that has been developed is aimed at increasing 'the efficiency and efficacy of data collection... with the assistance of Unmanned Aerial Vehicles (UAVs)' which means this work reveals practical application solutions. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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