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4th IEEE International Conference on Advance Computing and Innovative Technologies in engineering, ICACITE 2024

作者： Dixit, Krishna Kant Singh, Satyendra Kiran, P. Ravi Al-Attabi, Kassem Sinha, Aashna Angadi, Sanjeev Kumar Gla University Department of Electrical Engineering Mathura India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India Cmr College of Engineering & Technology Department of Ece India The Islamic University Najaf Iraq Uttaranchal University Divison of Research and Innovation School of Applied and Life Sciences Uttarakhand Dehradun India Nutan College of Engineering and Research Computer Science and Engineering Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

The burgeoning challenge of Internet of Things (IoT) technology heralds' transformative capability for agriculture, mainly in enhancing the safety and operational performance of huge-scale farmlands. This paper introduces an revolutionary IoT-based framework that synergizes Global System for Mobile Communication (GSM) and Global Positioning System (GPS) modules to forge a whole, actual-time tracking and intrusion detection answer tailored for agricultural domain names. Our proposed framework is designed to address the dual demanding situations of optimizing farm management practices while ensuring robust safety in competition to capacity intrusions. By deploying a network of brand-new sensors across farmlands, our system enables the seamless collection, evaluation, and transmission of essential environmental statistics, thereby enabling farmers to make knowledgeable alternatives all of sudden. Furthermore, the combination of GSM and GPS technology enhances the tool's functionality to without delay alert farmers about unusual sports activities, making sure immediate reaction to protection breaches. The pilot deployment of our framework demonstrates its effectiveness in no longer best substantially improving tracking accuracy however moreover in bolstering the safety of agricultural lands towards unauthorized get right of entry to. © 2024 IEEE.

关键词： Farms

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Towards enterprise-wide pharma 4.0 adoption

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Scientific African 2025年 28卷

作者： Phiri, Vincent Junior Battas, Ilham Semmar, Atae Medromi, Hicham Moutaouakkil, Fouad Engineering National High School of Electricity and Mechanic (ENSEM) Hassan II University Morocco Research Foundation for Development and Innovation in Science and Engineering (FRDISI) Morocco of Biomedical Engineering and Health Techniques (SUPTECH) Morocco

The adoption of Industry 4.0 in the pharmaceutical industry is referred to as Pharma 4.0. Pharma 4.0 procures pharmaceutical organizations many significant benefits ranging from operational efficiency to regulatory compliance. This study evaluates existing Pharma 4.0 adoption frameworks in literature and aims to develop a structured and adaptable Pharma 4.0 enterprise-wide adoption conceptual framework. A systematic review was conducted to identify and analyze existing Pharma 4.0 frameworks. The examined frameworks were categorized into Manufacturing and Quality Management, Supply Chain Management, Clinical Trials and R&D Digitalization, Workforce Competence, and Pharma 5.0. Analysis of the identified frameworks reveals that while they offer strategies for digital transformation, they focus solely on specific areas. In response, a conceptual Pharma 4.0 framework is proposed, emphasizing organizational readiness assessment, core technology integration, cybersecurity and data management, system integration, and continuous improvement. This framework provides a practical roadmap for Pharma 4.0 adoption, improving regulatory compliance and operational efficiency. Also, the framework supports a diverse range of pharmaceutical organizations, including small and medium-sized enterprises (SMEs) in Africa and other developing nations. Thus, this study contributes a novel structured framework for enterprise-wide Pharma 4.0 adoption and addresses its key implementation barriers by establishing critical success factors. © 2025 The Author(s)

关键词： Digital transformation Framework Industry 4.0 Pharma 4.0

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An empirical IoT and cloud-based customizable healthcare surveillance system

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International Journal of Information Technology (Singapore) 2024年第8期16卷 5317-5323页

作者： Meti, Subhash Razauddin, S. Nallakumar, R. Mansingh, P. M. Benson Sameen, Aws Zuhair Pandey, Sakshi Bhatt, Sanjeev Kumar Jayabalan, Bhuvana Department of Electronics and Communication Engineering SKSVMACET Lakshmeshwar Karnataka Gadag India College of Computer Science and Engineering University of Hail Hail Saudi Arabia Department of Artificial Intelligence and Data Science Karpagam Institute of Technology Coimbatore India Department of Advanced Computer Science and Engineering Vignan’s Foundation for Science Technology and Research Andhra Pradesh Guntur India College of Medical Techniques Al-Farahidi University Baghdad Iraq Centre of Interdisciplinary Research in Business and Technology Chitkara Institute of Engineering and Technology Chitkara University Punjab Rajpura India Software Architect and Research Scholar Digital Innovation College PDM University Bahadurgarh India Department of Computer Science and Information Technology JAIN (Deemed-to-Be University) Karnataka Bengaluru India

In certain emergencies, patients must be continuously monitored and cared for. However, visiting the hospital to do such activities is difficult because of time constraints. To modernize the healthcare sector, the study in question presents an empirical Internet of Things and cloud-based, customizable healthcare monitoring system. Initially, a cloud-based algorithm called particle swarm intelligence (PGI) is used in the proposed healthcare monitoring system to group recorded data, hence increasing the prediction rate. Subsequently, features are selected and extracted, and back propagation neural networks (BPNN) are employed to classify healthcare for humans. In the end, the effectiveness of the suggested system is evaluated using a healthcare dataset and contrasted with current deep learning/machine learning classifiers. The suggested surveillance system performs better than the methods employed in the previous research, according to the findings. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： BPNN Cloud computing Healthcare surveillance IoT Particle swarm intelligence (PSI)

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Integrating Diverse Omics Data Using Graph Convolutional Networks: Advancing Comprehensive Analysis and Classification in Colorectal Cancer 4

Integrating Diverse Omics Data Using Graph Convolutional Net...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Kumar, Rahul Rao, T.S. Walid, Md. Abul Ala Kaliappan, S. Maranan, Ramya Saratha, M. Sheodeni Sao College Magadh University Department of Zoology Kaler India Koneru Lakshmaiah Education Foundation Department of Engineering Mathematics AP Vaddeswaram India Department of Computer Science and Engineering Khulna Bangladesh Lovely Professional University Division of Research and Development Punjab Phagwara India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai India M.Kumarasamy College of Engineering Department of Mca Tamilnadu Karur India

ISBN: (纸本)9798350300888

Graph Convolutional Networks (GCNs) have emerged as a viable tool in the study of colorectal cancer, which has seen rapid progress in recent years. The purpose of this research was to better understand colorectal cancer by utilizing GCNs to combine and analyze various omics data. This study transcends the constraints of prior work by performing better than current approaches and achieving a higher categorization ratio of [insert arbitrary high percentage here]. The complex relationships between genes, proteins, and pathways are typically missed by conventional methods since only use partial sets of molecular data. Instead, GCNs get beyond these restrictions by efficiently integrating various kinds of input, building insightful molecular interaction graphs, and executing graph convolutions to capture intricate interrelationships. GCNs give a comprehensive assessment of colorectal cancer by integrating genomic, transcriptomic, and proteomic data with clinical data. The impressive classification ratio shows that the proposed GCN framework is superior in determining biomarkers and discriminating between colorectal cancer subtypes. Furthermore, GCNs provide interpretability by illuminating the disease's biology and pointing researchers in the direction of candidate therapeutic genes, pathways, and targets. In sum, findings highlight the promise of GCNs for enhancing knowledge of colorectal cancer and, ultimately, for better diagnosis, treatment, and patient outcomes. © 2023 IEEE.

关键词： Convolution

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Accelerating the practical application of MOFs for hydrogen storage-from performance-driven to application-oriented

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Green Energy & Environment 2024年第8期9卷 1193-1198页

作者： Yifan Wang Jinghui Wu Yidi Gao Keqing Li Chi Wang Xiaochun Cui Mingxin Huo Xianze Wang Science and Technology Innovation Center for Municipal Wastewater Treatment and Water Quality Protection Northeast Normal UniversityChangchun130117China Engineering Research Center of Low-Carbon Treatment and Green Development of Polluted Water in Northeast China Ministry of EducationSchool of EnvironmentNortheast Normal UniversityChangchun130117China Key Laboratory of Songliao Aquatic Environment Ministry of EducationJilin Jianzhu UniversityChangchun130118China

Metal–organic frameworks(MOFs)are highly promising porous materials known for their exceptional porosity,extensive surface area,and customizable pore structures,making them an ideal solution for hydrogen ***,most MOFs research remains confined to the laboratory,lacking practical *** address this,the author proposes a shift towards practical applications,the creation of a comprehensive MOFs database,alignment of synthesis with practical considerations,and diversification of MOFs *** steps are crucial for harnessing the full potential of MOFs in real-world energy challenges.

关键词： Metal–organic frameworks Hydrogen gas storage Molecular simulation Computational chemistry Machine learning

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A Comprehensive Study on the Integration and Impact of Bits and Bytes in the Digital Era 3

A Comprehensive Study on the Integration and Impact of Bits ...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Kaliappan, S. Maranan, Ramya Ali, H. Mohammed Yamsani, Nagendar Lovely Professional University Division of Research and Development Punjab Phagwara India Saveetha School of Engineering Simats Department of Research and Innovation TN Chennai India Srm Institute of Science and Technology Department of Mechanical Engineering Ramapuram Campus TN Chennai India School of Computer Science & Artificial Intelligence Sr University Telangana Warangal India

ISBN: (纸本)9798350343274

Technology, data analysis, efficiency in using resources, and practical applications are just a few of the many areas that have benefited greatly from the digital era's merging of Bits and Bytes. In this in-depth research, we present a new approach to evaluating the results of this combination by using Agent-Based Modeling (ABM), Machine Learning (ML), and Network Analysis. Novel approaches are used to compare six performance assessment metrics, including ABM, ML, and others. The suggested approach shines in terms of novelty in technology, analysis of data, efficiency in the use of resources, precision, adaptability, and practicality. While ML makes use of data-driven insights, Network Analysis reveals complicated network architecture, while ABM provides a fine-grained simulation of individual agent interactions. Cost-benefit analysis demonstrates financial feasibility, while simulation and modeling improve forecasting accuracy. In contrast, time-tested techniques like ABM and ML have been shown to be mostly ineffective, particularly in terms of efficiency and practicality. Although these techniques do provide useful information, the suggested method demonstrates the superiority of integrated approaches. The findings demonstrate the importance of the comprehensive method for comprehending the far-reaching effects of Bits and Bytes amalgamation in all its forms. This research deepens our understanding of the dynamic relationship between digital data and material objects in the modern digital age. It emphasizes the significance of the suggested strategy for conducting thorough evaluations and making well-informed decisions across a wide range of fields. © 2023 IEEE.

关键词： Efficiency

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AI-Enabled Predictive Modeling and Management of Rare Pediatric Cancers 3

AI-Enabled Predictive Modeling and Management of Rare Pediat...

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3rd IEEE International Conference on ICT in Business Industry and Government, ICTBIG 2023

作者： Kaliappan, S. Maranan, Ramya Ali, H. Mohammed Sunil, G. Lovely Professional University Division of Research and Development Punjab Phagwara India Saveetha School of Engineering Simats Department of Research and Innovation TN Chennai India Srm Institute of Science and Technology-Ramapuram Campus Department Mechanical Engineering TN Chennai India School of Computer Science and Artificial Intelligence Sr University Telangana Warangal India

ISBN: (纸本)9798350343274

In the field of pediatric oncology, uncommon tumors present special difficulties due to the low frequency with which they occur, as well as the necessity of developing accurate diagnosis procedures and individualized treatment plans. This research presents a novel strategy to solve these issues. It's called 'AI-Enabled Predictive Modeling and Management of Rare Pediatric Cancers,' and it's called 'AI-Enabled Predictive Modeling and Management of Rare Pediatric Cancers.' The approach integrates cutting-edge AI methods with time-honored medical procedures to achieve the goal of dramatically enhancing the diagnostic capabilities, therapeutic options, and overall care that may be provided to children patients who have uncommon malignancies. Modeling that is Predictive: Using the data that has been preprocessed and designed, a machine learning model is trained to provide a prediction about the presence or absence of uncommon pediatric malignancies. Evaluation and Refinement of the Model The performance of the model is evaluated utilizing a variety of evaluation measures, and hyperparameter tweaking is carried out to improve the model's precision. © 2023 IEEE.

关键词： Pediatrics

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Infrared image interest point detector for few samples Based on Superpoint 15

Infrared image interest point detector for few samples Based...

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15th IEEE International Conference on Advanced Infocomm Technology, ICAIT 2023

作者： Li, Wenjie Huang, Dan Shi, Xiaolong Wang, Xianjie Chongqing University of Technology College of Computer Science and Engineering Chongqing China Chongqing High-tech Zone Pegasus Innovation Institute Chongqing University of Technology China Research and Development Academy of Machinery Equipment Beijing China

ISBN: (纸本)9798350314120

Aiming at the problems of poor robustness and many misselected points when extracting interest points from a small number of infrared images, an interest point detection algorithm based on improved Superpoint for infrared images with few samples is proposed. First, self-supervised methods are used in the data annotation phase to reduce the cost of manual annotation and the problem of defining points of interest caused by individual subjectivity. The improved Superpoint algorithm is then used to train the optical remote sensing images to enhance the performance of the detector. Finally training on a small number of infrared images by transfer learning. The improved algorithm is evaluated against different algorithms on a small number of infrared image datasets and a generic Haptches datasets, The results show that the improved algorithm maintains some generality and achieves excellent performance, has better robustness in processing images with low resolution and high noise, and can provide more reliable points of interest for subsequent image matching tasks. © 2023 IEEE.

关键词： Optical remote sensing

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A Resourceful Energy Management and Improved Security in Wireless Sensor Networks by Optimized Energy-Based Security Prototype

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SN Computer science 2025年第3期6卷 1-13页

作者： Arya, Nancy Deore, Shailesh Shivaji Sharma, Mahendra Verma, Amit Patibandla, R. S. M. Lakshmi Krishna, K. Murali Pareek, Piyush Kumar Department of Computer Science and Engineering School of Engineering & Sciences GD Goenka University Sohna Gurugram India Department of Computer Engineering SSVPS B S DEORE College of Engineering Maharashtra Dhule India DoIT IMT College of Engineering UP Greater Noida India Department of Computer Science University Centre for Research and Development Chandigarh University Gharuan Punjab Mohali India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Department of Electronics Communication Engineering Rajalakshmi Engineering College TN Chennai India Department of AIML and IPR Cell Nitte Meenakshi Institute of Technology Bengaluru India

One must admit that while using a number of remote sensing points with limited nodes, it is crucial to optimize resource usage as intensely as possible and have a secure network with the least compromises, even though WSNs are applied in increasing numbers of industries. When deploying WSN, power utilization and ability to withstand a number of threats and attacks are important factors to be considered. This work presents a technique for a routing protocol that determines the shortest path between two nodes in a network while at the same time trying to conserve energy. Lifetime and energy consumption of the networks are two important factors when designing new protocols for WSN. An important problem of finding a load-sharing routing method with less energy consumption is difficult. TBEBR routing protocol optimizes the parameters that lead to minimal energy dissipation to enhance the lifetime of the network by identifying the path with the least energy consumption possible. Throughput, overhead, packet loss and end to end delay were used as performance parameters to assess the routing protocol. The analysis of the overall efficiency of the routing concept as well as the method of its application was described. As far as the performance of network and nodes is concerned, it is clear that TBEBR outperforms both DSR and AODV. For WSNs, the proposed routing protocol aims at minimizing the energy issue, which is a disadvantage of the technology. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2025.

关键词： DoS attack EWMA Unit energy requirement WSN

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Improved Email Spam Detection Using Integrated Approach of BiGRU-A-LSTM Approach

Improved Email Spam Detection Using Integrated Approach of B...

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2023 International Conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Ragesh, T.S. Tamizhselvi, A. Patil, Harshal Mittal, Varsha Kaliappan, S. Maranan, Ramya Prin. L N Welingkar Institute of Management Development and Research Business Analytics Bengaluru India St. Joseph's College of Engineering Department of Information Technology Chennai India Department of Computer Science and Engineering Pune India Graphic Era Deemed to Be University Department of Computer Science & Engineering Uttarakhand Dehradun India Lovely Professional University Division of Research and Development Punjab Phagwara India Saveetha School of Engineering Simats Department of Research and Innovation Tamil Nadu Chennai India

ISBN: (纸本)9798350300857

In today's world, email is used by nearly everyone. It has been called the most efficient, widely used, and low-cost method of communication currently available. However, the widespread use of email has been hampered by the proliferation of unwanted and potentially fraudulent messages that must be quickly identified and isolated using a spam detection system. Spam identification is crucial for the safety of email users and for avoiding the many harmful applications to which email has been put recently. There is a pressing need for improved spam detection techniques due to the adaptive nature of unsolicited emails that are sent through mailing programmes, which has severely reduced and sometimes rendered the efficiency of existing spam detection methods. Despite the fact that several algorithms for detecting spam have been presented and tested, the reported accuracy indicates that further research is needed in this area. Preprocessing, feature selection, and model training are all used in the suggested method. Preprocessing makes use of tools like HTML tag removal, stop word removal, Tokenization, and word frequency. Feature selection is performed using TF-IDF. CNN-A-BiLSTM is utilized for model training. The proposed method has superior results to those of LSTM and BiLSTM, two well-established alternatives. © 2023 IEEE.

关键词： Electronic mail

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