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Sustainable Expert Systems (ICSES), International Conference on

作者： I. Mettildha Mary T. Ragunthar M. Priyadharsini H Shyam Krishnaa M K Sujit Department of Computer Science and Engineering(Cyber Security) Dr.N.G.P Institute of Technology Coimbatore Tamil Nadu India Department of Computing Technologies SRM Institute of Science and Technology Chennai Tamil Nadu India Department of Information Security School of Computer Science and Engineering (SCOPE) Vellore Institute Technology Vellore Tamil Nadu India Siemens Healthineers Bangalore Atheniac Bangalore

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Accurate identification of fish species is critical for applications in fisheries management., biodiversity monitoring., and conservation efforts. Conventional manual identification techniques take a lot of time and are prone to mistakes., particularly when working with big datasets and species that have similar physical characteristics. Automating tasks related to species identification has shown promise in recent breakthroughs in machine learning., especially in deep learning techniques like Convolutional Neural Networks (CNNs) and transfer learning. However., these systems face several challenges., including high variability in fish appearances., limited availability of labelled datasets., and the computational overhead required for real-time classification. This research study presents a fish species classification system using a transfer learning approach based on MobileNetV2. MobileNetV2., known for its efficiency and lightweight architecture., is fine-tuned on a custom fish dataset to enhance species identification accuracy while minimizing computational requirements. To increase the model's resilience and ability to generalise to new species., data augmentation approaches are used. The system is designed to deliver high classification accuracy while maintaining computational efficiency., making it suitable for deployment in real-world applications with limited resources. Experimental results demonstrate that the proposed system achieves significant improvements in accuracy compared to traditional methods., while also addressing the challenges of dataset variability and overfitting.

关键词： Accuracy Transfer learning Fish Real-time systems Computational efficiency Convolutional neural networks Object recognition Monitoring Resilience Overfitting

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Detecting Human Eye Blinks through OpenCV

Detecting Human Eye Blinks through OpenCV

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International Conference for Convergence of technology (I2CT)

作者： Kirti Wanjale Araddhana Arvind Deshmukh Jyoti Chetan Vanikar Alpana Prashant Adsul Shailesh P. Bendale Department Of Computer Engineering Vishwakarma Institute of Information Technology Symbiosis Skills and Professional University Pune Pune Maharashtra India Department of Computer Science & Information Technology (Cyber Security) Symbiosis Skill and Professional University Kiwale Pune Department of Computer Engineering Dr. D.Y. Patil College of Engineering and Innovation Affiliated to Savitribai Phule Pune University Department of Computer Engineering NBN Sinhgad School of Engineering Pune

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

Blink detection, a crucial part of facial movement analysis, is applied in a number of fields, including human-computer interaction, driver monitoring, and healthcare. However, automatic blink recognition presents unique obstacles due to variability in blink rates and ambient conditions. This work proposes a novel real-time method to robustly and accurately detect eye blinks in video sequences using OpenCV and the Modified Eye Aspect Ratio (Modified EAR) as a crucial component. The suggested methodology's automatic facial landmark detectors are initially trained on a range of real-world datasets. When it comes to adapting to shifting surroundings, such as shifts in illumination, expressions on faces, and head orientations, these detectors are incredibly versatile. Our method carefully calculates the locations of facial landmarks with every frame in the video sequence, making it possible to calculate the vertical distance between the eyelids with accuracy. This metric, which takes the form of the Modified EAR, serves as a single scalar quantity that represents the degree of eye closure or openness. Our experimentation's empirical results highlight the facial landmarks' remarkable precision in reliably assessing the dynamics of eye opening and closure. Blinks are detected by applying a threshold value to the Modified EAR, which enables the detection of blink patterns that take place within a short temporal window. Our approach not only detects blinks efficiently but also outperforms current state-of-the-art methods, as demonstrated by the results obtained from a large and thorough dataset.

关键词： Video sequences Lighting Ear Detectors Medical services Real-time systems Reliability

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A Novel Machine Learning-Based Framework for Predicting Diabetes in Healthcare

A Novel Machine Learning-Based Framework for Predicting Diab...

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2025 International Conference on Intelligent Control, Computing and Communications, IC3 2025

作者： Oliver, A. Sheryl Gupta, Kimmi Singh, Jagendra Agnihotri, Atul Kumar Vasavi, M. Kaur, Gaganjot Srm Institute of Science and Technology Department of Computational Intelligence Chennai India School of Computer Science Engineering & Technology Bennett University Greater Noida India School of Engineering and Technology Chhatrapati Shahu Ji Maharaj University Electronics and Communication Engineering Kanpur India Cvr College of Engineering Department of Et -Cyber Security Hyderabad India Raj Kumar Goel Institute of Technology Department of Computer Science Ghaziabad India

ISBN: (纸本)9798331527495

The rise in diabetes is considered the greatest global health issue;thus, the call for early and accurate predictions of the disease is a dire need in the health sector. The detection of the disease in its initial stages would allow patients to undergo timely interventions and appropriate treatments. A novel approach for the prediction of stages and severity of diabetes by utilizing various models within a machine learning framework, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Decision tree learning (DT), and Random Forest (RF) is proposed in this paper. The training data would involve the history of medical conditions, age, BMI, insulin, skin thickness, glucose level, the number of pregnancies, and existence or non-existence of diabetes. The models were trained on 70% of the data and tested on the remaining 30%. The results show that SVM outperforms all other models, achieving an accuracy of 96.5%, followed by ANN with 94.5%, DT with 90.2 %, and RF with 86.7%. These results indicate that SVM, followed by ANN, is the most effective model for predicting diabetes stages. The accuracy and reduction of data loss have been constant improvements with epochs 30 to 360;therefore, models can be used in real-time applications in the clinical area. Thus, this research concludes that machine learning models, such as SVM, may be helpful in predicting and diagnosing early cases of diabetes;thus, these models could be helpful in making good decisions on healthcare and improving the patient's health. © 2025 IEEE.

关键词： Diseases

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Analysis of Detection and Recognition of Human Face Using Support Vector Machine 1st

Analysis of Detection and Recognition of Human Face Using Su...

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1st International Conference on Artificial Intelligence of Things, ICAIoT 2023

作者： Hannan, Shaikh Abdul Pushparaj Ashfaque, Mohammed Waseem Lamba, Anil Kumar, Anil Computer Science and Information Technology AlBaha University AlBaha Saudi Arabia Electronics and Communication Engineering National Institute of Technical Teachers Training and Research Chandigarh India Computer Science and I.T. Dr. B.A.M. University Aurangabad India Cyber Security Technology Risk and Resilience Oversight American Express New York United States Government Millennium Polytechnic Himachal Pradesh Chamba India

ISBN: (纸本)9783031487804

Recently, Support Vector Machines (SVMs) have been suggested as an additional technique for design identification. In this study, a face detection framework with demeanor recognition utilizing Support Vector Machines (SVMs) with a double tree identification process is used to tackle the face recognition issue. It plays a crucial role in applications including face delineation data set management, human PC interaction, and video examination. Through two steps, the face recognition with appearance appraisal framework accomplishes look recognition. The captured image is initially processed to identify the face, and then the perceived appearance. The first two stages of the framework handle facial recognition and face trimming using picture handling, while the third stage handles converting the altered image’s colors from RGB to grayscale and applying the appropriate smoothing channel. We employ a simple method to create our own SVM classifier with a Gaussian component that can recognize eyes in grayscale photos as the first step towards a part-based face identifier. The architecture of an iterative bootstrapping method is discussed in detail, and we show how choosing boundary values will usually result in the best outcomes. The findings of our study are in line with earlier studies, and the challenges encountered are typical for anybody developing an article identification system. Large support vector SVM classifiers are sluggish, and accuracy is highly reliant on the caliber and diversity of training data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Support vector machines

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An Improved iBAT-COOP Protocol for Cooperative Diversity in FANETs

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computers, Materials & Continua 2021年第5期67卷 2527-2546页

作者： Shahzad Hameed Qurratul-Ain Minhas Sheeraz Ahmed Shabana Habib Mohammad Kamrul Hasan Muhammad Islam Sheroz Khan Quaid-i-Azam University IslamabadPakistan Iqra National University PeshawarPakistan Network and Communication Technology Lab Center for Cyber SecurityUKMBangiMalaysia Department of Information Technology College of ComputerQassim UniversityBuraydahSaudi Arabia Department of Electrical Engineering Onaizah College of Engineering&Information TechnologyAl-QassimSaudi Arabia

Flying ad hoc networks(FANETs)present a challenging environment due to the dynamic and highly mobile nature of the *** network topology and uncertain node mobility structure of FANETs do not aim to consider only one path *** different techniques are adopted to address the issues arising in FANETs,from game theory to clustering to channel estimation and other statistical *** approaches mostly employ traditional concepts for problem *** of the novel approaches that provide simpler solutions to more complex problems is to use biologically inspired *** Nature-inspired schemes address cooperation and alliance which can be used to ensure connectivity among network *** such species that resembles the dynamicity of FANETs are *** this paper,the biologically inspired metaheuristic technique of the BAT Algorithm is proposed to present a routing protocol called iBATCOOP(Improved BAT Algorithm using Cooperation technique).We opt for the design implementation of the natural posture of bats to handle the necessary flying ***,we envision the concept of cooperative diversity using multiple relays and present an iBAT-COOP routing protocol for *** paper employs cooperation for an optimal route selection and reflects on distance,Signal to Noise Ratio(SNR),and link conditions to an efficient level to deal with FANET’s *** way of simulations,the performance of iBAT-COOP protocol outperforms BAT-FANET protocol and reduces packet loss ratio,end-to-end delay,and transmission loss by 81%,21%,and 82%***,the average link duration is improved by 25%compared to the BAT-FANET protocol.

关键词： Routing protocols UAVs FANETs iBATCOOP BATCOOP

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A Community Detection Approach for Academic Social Network: The Case of the Cross-Strait Academic Conference Network 3

A Community Detection Approach for Academic Social Network: ...

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3rd International Conference on Electronics, Communications and Information technology, CECIT 2022

作者： Zhang, Xinxin Xu, Li Gao, Min Fan, Jianxi Sun, Hung-Min Fujian Normal University College of Computer and Cyber Security Fujian Provincial Key Laboratory of Network Security and Cryptology Fuzhou China Fudan University The School of Computer Science Shanghai China Soochow University The School of Computer Science and Technology Suzhou China National Tsing Hua University The Department of Computer Science Hsinchu Taiwan

ISBN: (纸本)9798350331974

With the fast development of information networks, academic social network analysis has attracted significant attention, we regard these researchers sharing common interests as a research community. The community has been widely used as the underlying structure of social networks. To utilize network information as much as possible, we capture the structural characteristics and attribute features to detect communities in the cross-strait academic conference network. In this paper, we first consider 2-hop neighbors with the Pareto principle to filtrate the central seed nodes in networks. Then we propose a new seed shrinkage strategy to get the initial communities and define the similarity according to the structure and attributes of social networks to merge the communities. Finally, we define a new indicator named inner average distance (IAD) to measure the aggregation density for each community. A case study of the cross-strait academic social network was developed to test the applicability of the proposed model, the experiment analysis suggests that our method can be more accurate to identify communities in most situations, which contributes to controlling the information spreading in networks. © 2022 IEEE.

关键词： Pareto principle

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Hybrid Models for Recognizing Indonesian Textual Entailment 7

Hybrid Models for Recognizing Indonesian Textual Entailment

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7th International Conference on Informatics and Computational Sciences, ICICoS 2024

作者： Ahmadian, Hendri Abidin, Taufik Fuadi Riza, Hammam Muchtar, Kahlil Universitas Syiah Kuala Graduate School of Mathematics and Applied Sciences Banda Aceh Indonesia Universitas Syiah Kuala Faculty of Mathematics and Natural Sciences Department of Informatics Banda Aceh Indonesia National Research and Innovation Agency Research Center for Artificial Intelligence and Cyber Security Jakarta Indonesia Universitas Syiah Kuala Faculty of Engineering Department of Electrical and Computer Engineering Banda Aceh Indonesia

ISBN: (纸本)9798350375886

A paragraph raises pertinent issues about linguistic disparities in understanding the semantic relationships between sentences within the natural language processing domain (NLP) Addressing this challenge necessitates the development of robust NLP models, with a specific emphasis on text entailment. This research endeavors to enhance the performance of Indonesian NLP benchmarks in text entailment by harnessing a variant of the Bidirectional Encoder Representations from Transformer (BERT) model tailored explicitly for the Indonesian language, known as IndoBERT. The approach in this study adopts a hybrid methodology, amalgamating the IndoBERT layer modification model by summing the last four hidden layers with neural networks. The performance evaluation of the hybrid models, combining the IndoBERT layer modification model with the Bidirectional Gated Recurrent Unit (BiGRU) model and the IndoBERT layer modification model with the Bidirectional Long Short-Term Memory (BiLSTM) model, yields the F1-scores of 0.87 and 0.84, respectively. © 2024 IEEE.

关键词： Semantics

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Generalized Simultaneous Perturbation-Based Gradient Search With Reduced Estimator Bias

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IEEE Transactions on Automatic Control 2025年

作者： Pachalyl, Soumen Bhatnagarz, Shalabh Prashanth, L.A. TCS Research Department of Computer Science and Engineering Indian Institute of Technology Madras Chennai India Indian Institute of Science Department of Computer Science and Automation The Robert Bosch Centre for Cyber Physical Systems Bangalore India Indian Institute of Technology Madras Department of Computer Science and Engineering Chennai India

We present a family of generalized simultaneous perturbation-based gradient search (GSPGS) estimators that use noisy function measurements. The number of function measurements required by each estimator is guided by the desired level of accuracy. We first present in detail unbalanced generalized simultaneous perturbation stochastic approximation (GSPSA) estimators and later present the balanced versions (B-GSPSA) of these. We extend this idea further and present the generalized smoothed functional (GSF) and generalized random directions stochastic approximation (GRDSA) estimators, respectively, as well as their balanced variants. We show that estimators within any specified class requiring more number of function measurements result in lower estimator bias. We present a detailed analysis of both the asymptotic and non-asymptotic convergence of the resulting stochastic approximation schemes. We further present a series of experimental results with the various GSPGS estimators on the Rastrigin and quadratic function objectives. Our experiments are seen to validate our theoretical findings. © 1963-2012 IEEE.

关键词： Stochastic systems

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A Proposed Approach for Risk Planning and Management

A Proposed Approach for Risk Planning and Management

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Information technology (ACIT)

作者： Mohammed N. Al Refai Yazan Al-Smadi Adai Al-Momani Zeyad M. Jamhawi Ahmed Ali Otoom Issa Atoum Ahid Yaseen Jafar Ababneh Mohammad Kanan Software Engineering Dep. Zarqa University Zarqa Jordan Department of Computer Science Zarqa University Zarqa Jordan Department of Computer Science Applied Science Private University Amman Jordan Department of Cyber Security Applied Science Private University Amman Jordan Software Engineering Department Faculty of Information Technology Philadelphia University Jordan Department of Cyber Security Zarqa University Zarqa Jordan Dep. of Industry Engineering University of Business and Technelogy Jeddah Saudi Arabia

ISBN: (数字)9798331540012

ISBN: (纸本)9798331540029

Project Risk management is the process of identifying, evaluating, avoiding, or reducing risks. Where there is no software project without risks existence are natural in the context of project planning and management. This study focuses on proposing an enhanced risk management approach where testing phases were added to make the risk management process more effective by proposing solutions to many mistakes and challenges that occur through dealing with risks. The proposed approach focuses on dealing with risks that cannot be easily defined, more accurate risk evaluation, planning, and managing risk coordinated with a contingency plan.

关键词： Technological innovation Accuracy Contingency management Process control Software Planning Risk management Information technology Testing

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Reliability of Multipath Networks with Optimization of the Location of Inter-Path Communication Nodes

Reliability of Multipath Networks with Optimization of the L...

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2023 International Russian Smart Industry Conference, SmartIndustryCon 2023

作者： Bogatyrev, Vladimir A. Tu Le, Anh Abramova, Evgenia A. Saint-Petersburg State University of Aerospace Instrumentation Department Information Systems Security Saint Petersburg Russia University ITMO Faculty of Software Engineering and Computer Technology Saint Peterburg Russia

ISBN: (纸本)9781665464291

The article explores the possibility of improving the reliability of a network with multipath routing. A feature of the proposed study is the analysis of the influence of the placement of switching nodes that switch path segments on the probability of network connectivity with servers of the same type and heterogeneous in functionality. The purpose of the article is to increase the reliability of the network, taking into account the influence of the placement of communication nodes that implement the switching of route segments during reconfiguration, on the connectivity of the network with servers that are homogeneous and heterogeneous in functionality. The research involves the construction of a structural reliability model that takes into account the possibility of failures of both communication nodes and the links between them. The reliability model is built taking into account the availability of request sources with full and non-full access connections to the set of network paths. © 2023 IEEE.

关键词： Reliability

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