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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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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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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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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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Assessing underlying pulsatile structures with laparoscopic tools using proximal vibroacoustic sensing

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Current Directions in Biomedical engineering 2024年第1期10卷 37-40页

作者： Kaabachi, Syrine Illanes, Alfredo Esmaeili, Nazila Sühn, Thomas Spiller, Moritz Friebe, Michael Hansen, Christian Boese, Axel INKA-Innovation Laboratory for Image Guided Therapy Otto-von-Guericke University Magdeburg Germany SURAG Medical GmbH Leipzig Germany Computer Aided Medical Procedures and Augmented Reality Technical University of Munich Munich Germany AGH University of Science and Technology Department of Biocybernetics and Biomedical Engineering Krakow Poland CIBE - Center of Innovation Business Development & Entrepreneurship FOM University of Applied Sciences Essen Germany Research Campus STIMULATE Otto von Guericke University Magdeburg Germany

This work presents a novel approach for detecting underlying pulsatile structures with laparoscopic tools by using proximal vibroacoustic sensing. This new method could detect pulsations at a depth of up to 1.5 cm. The outcome of this work indicates the potential of identifying deep-seated pulsatile structures during robot-assisted laparoscopy, where haptic feedback is highly limited, to help surgeons prevent vascular damage that may lead to injuries. © 2024 by Walter de Gruyter Berlin/Boston.

关键词： Laparoscopy

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FEASIBILITY INVESTIGATION ON CLASSIFICATION OF TWO-PHASE FLOW REGIMES IN A 3×3 ROD BUNDLE CHANNEL USING ARTIFICIAL NEURAL NETWORK 30

FEASIBILITY INVESTIGATION ON CLASSIFICATION OF TWO-PHASE FLO...

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30th International Conference on Nuclear engineering, ICONE 2023

作者： Chen, Shao-Wen Ruan, Pei-Syuan Chen, Han-Yao Huang, Lung-Hung Lin, Min-Song Lee, Jin-Der Wang, Jong-Rong Institute of Nuclear Engineering and Science National Tsing Hua University Hsinchu Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu Taiwan Nuclear Science and Technology Development Center National Tsing Hua University Hsinchu Taiwan Nuclear and New Energy Education and Research Foundation Hsinchu Taiwan

ISBN: (纸本)9784888982566

In this study, two-phase flow tests have been carried out in a 3×3 rod bundle channel to investigate the feasibility on flow regime classification using artificial neural network (ANN). The rod bundle channel was constructed with nine 11.5 mm-diameter rods in a rectangular array with a pitch of 15.4 mm and enclosed by a 52×52 mm rectangular channel, and the overall height was about 5 m. The test flow conditions covered the superficial gas and liquid velocities of = 0.02-10 m/s and = 0.02-2 m/s. The transient void fraction of each test was measured and converted into probability density function (PDF) and cumulative probability distribution function (CPDF) and rearranged as the input matrices for Kohonen neural network for training and classification with the training epoch of 1500 times. While assigning 3 groups, the bubbly and cap-bubbly flows can be clearly distinguished;whereas when assigning 5 groups, the bubbly and cap-bubbly flow can be further subdivided with an additional transition region, and the cap-turbulent and churn flows can be roughly separated. This study has preliminarily demonstrated the feasibility on classification of two-phase flow regimes in the 3×3 rod bundle channel using artificial neural network technique. © 2023 by JSME.

关键词： Two phase flow

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CPU Execution Time Analysis based on RISC-V ISA Simulators: A Survey 16

CPU Execution Time Analysis based on RISC-V ISA Simulators: ...

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16th International Conference on development and Application Systems, DAS 2022

作者： Iuga, Nicolai Zagan, Ionel Gaitan, Vasile Gheorghita Stefan cel Mare University Faculty of Electrical Engineering and Computer Science Suceava Romania Integrated Center for Research Development and Innovation in Advanced Materials Suceava Romania

ISBN: (纸本)9781665481625

Multiple components affect the behavior of CPU execution tasks, mainly mutual exclusion during access to the shared resources and synchronous transmissions between tasks that require specific priorities. Referring to real-time task scheduling, the most important issues addressed are monitoring the deadline of the tasks, the probability of non-compliance with the deadline and ensuring that they are completed within the deadline imposed by the controlled system. This leads to the fact that a tasks set is feasible if the system has adequate resources to execute the tasks without losing any deadlines. To approach this challenge, this article addresses the feasibility analysis of runtime for real-time tasks to be performed in a virtual space before applying to a real embedded device. These processes take place offline, even before a system executes a set of tasks. In order to perform the feasibility analysis of the system, efforts are being made to provide virtual environments and simulators, such as the RISC-V ISA simulator and the WCET (Worst Case Execution Time) measurement, subsequently. These simulators have application-specific requirements, with their own advantages. © 2022 IEEE.

关键词： Simulators

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Hydrodynamic Performance of a New Box-type Floating Breakwater with a Protruding Bottom Plate

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Journal of Marine Environmental engineering 2025年第1期12卷 49-67页

作者： Lv, Jiao Fan, Ning Niu, Guoxu Pan, Wei Ma, Tianchi Song, Laifu Zhao, Xizeng College of Civil Engineering and Architecture Wenzhou University Wenzhou325035 China Wenzhou Academy of Agricultural Sciences Wenzhou325006 China Southern Zhejiang Key Laboratory of Crop Breeding Wenzhou325006 China Key Laboratory of Engineering and Technology for Soft Soil Foundation and Tideland Reclamation of Zhejiang Province Wenzhou325035 China Zhejiang International Science and Technology Cooperation Base of Ultra-soft Soil Engineering and Smart Monitoring Wenzhou325035 China Beijing Langrun Innovation Technology Company Limited Beijing100080 China Zhejiang Engineering Research Center of Disaster Prevention and Mitigation for Coastal Soft Soil Foundation Wenzhou325035 China Ocean College Zhejiang University Zhoushan316021 China

Floating breakwaters can effectively resist wave impacts and maintain a relatively calm water environment. To solve the problem of insufficient wave attenuation performance of traditional box-type floating breakwaters with increasing wave periods, a new box-type floating breakwater (NFB) with a protruding bottom plate was proposed in this study. Based on the computational fluid dynamics (CFD) approach, a series of numerical simulations of the interaction between regular waves and floating breakwaters were carried out. The evolution of the vortices and the wave dissipation mechanism of the NFB were investigated. The effect of the change in the dimension of the protruding bottom plate of the NFB on the hydrodynamic performance was analysed, and a reasonable length of the protruding bottom plate was recommended. Finally, the hydrodynamic performance of the proposed approach was compared with that of the traditional box-type floating breakwaters under identical breakwater draft and width conditions. The results showed that the transmission coefficient of the NFB is improved by approximately 20% on average, and the reflection coefficient, maximum horizontal wave forces and negative maximum vertical wave forces are significantly reduced, indicating that the NFB has good application prospects. © 2025 Old City Publishing, Inc.

关键词： Floating breakwaters

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A Convolutional Neural Network-Weighted Cellular Automaton Model for the Fast Prediction of Urban Pluvial Flooding Processes

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International Journal of Disaster Risk science 2024年第5期15卷 754-768页

作者： Jiarui Yang Kai Liu Ming Wang Gang Zhao Wei Wu Qingrui Yue School of National Safety and Emergency Management Beijing Normal UniversityBeijing 100875China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC‑FEMD) Nanjing University of Information Science and TechnologyNanjing 210044China Department of Transdisciplinary Science and Engineering Tokyo Institute of TechnologyTokyo 226‑8501Japan National Disaster Reduction Center of China Ministry of Emergency ManagementBeijing 100124China Research Institute of Urbanization and Urban Safety University of Science and Technology BeijingBeijing 100083China National Science and Technology Institute of Urban Safety Development Shenzhen 518046China

Deep learning models demonstrate impressive performance in rapidly predicting urban floods,but there are still limitations in enhancing physical connectivity and *** study proposed an innovative modeling approach that integrates convolutional neural networks with weighted cellular automaton(CNN-WCA)to achieve the precise and rapid prediction of urban pluvial flooding processes and enhance the physical connectivity and reliability of modeling *** study began by generating a rainfall-inundation dataset using WCA and LISFLOOD-FP,and the CNN-WCA model was trained using outputs from LISFLOOD-FP and ***,the pre-trained model was applied to simulate the flood caused by the 20 July 2021 rainstorm in Zhengzhou *** predicted inundation spatial distribution and depth by CNN-WCA closely aligned with those of LISFLOOD-FP,with the mean absolute error concentrated within 5 mm,and the prediction time of CNN-WCA was only 0.8%that of *** CNN-WCA model displays a strong capacity for accurately predicting changes in inundation depths within the study area and at susceptible points for urban flooding,with the Nash-Sutcliffe e fficiency values of most flood-prone points exceeding ***,the physical connectivity of the inundation distribution predicted by CNN-WCA is better than that of the distribution obtained with a *** CNN-WCA model with additional physical constraints exhibits a reduction of around 34%in instances of physical discontinuity compared to *** results prove that the CNN model with multiple physical constraints has signifi cant potential to rapidly and accurately simulate urban flooding processes and improve the reliability of prediction.

关键词： Convolutional neural networks Physical continuity Rapid prediction Urban pluvial flooding processes Weighted cellular automata

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