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2023 International Multi-Disciplinary Conference in Emerging Research Trends, IMCERT 2023

作者： Nazir, Farrakh Khan, Muhammad U.S. Khan, Neeli Fayyaz, Ahmad Comsats University Islamabad Department of Electrical and Computer Engineering Abbottabad Pakistan Comsats University Islamabad Department of Computer Science Abbottabad Pakistan

ISBN: (纸本)9798350347708

Smartphones are now inseparable part of our reality. Several machine learning algorithms exist for detection of malwares in android applications;however, these techniques fail to rationalize specific decisions made by a 'Black Box' therefore lacking explain-Ability. To overcome this limitation, Sufficient Input Subset (SIS) technique is used along with convolutional neural network (CNN). SIS categorizes minimal subsets of features who's observed values alone be sufficient for the same verdict to be reached. The results of the proposed technique are very promising., where its detection accuracy reached more than 90% and we are able to rationalize why the Black box classified a file as malware. © 2023 IEEE.

关键词： Android (operating system)

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Surveillance of species at risk by unarmed aerial vehicles

Surveillance of species at risk by unarmed aerial vehicles

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International Conference on Artificial Intelligence, Blockchain, Computing and Security, ICABCS 2023

作者： Vijaya Chamundeeswari, V. Sujith Varshan, G. Sanjay Kumar, Y. Sudarson, A.M. Department of Computer Science and Engineering Saveetha Engineering College Chennai India

ISBN: (纸本)9781032669663

A Living being or an organism that is about to vanish from this world will come under the category of Endangered *** Explanation for their state vary from time to time but few important reasons are loss of habitat and loss of genetic variation. These organism will attain the state of endangered when their population is below 30% and it no proper source for its lack of growth. The reason for being endangered species are – Population reduction rate, Geographical range, Population size and Population restriction, Poaching. Many different species are adversely affected by poaching. Different Laws have been sanctioned in order to protect the endangered species in many countries. Forbid hunting, Restrict land development, or Create protected areas are some of the measures for their growth. Some species are even taken away from their habitat in order to ensure their existence, This is called as extensive conservation *** breeding and habitat restoration are the few examples of the above. Many efforts have been made in order to restrict the *** Cameras, Drones and DNA tracking are the some of the methods and their probablitiy of success differs with each other. These systems are static in nature whereas the solution this provides is that with the help of Drone system with high resolution image capturing system the endangered species can be monitored along with their habitat. The advantage of using this system is the range is dynamic and precision is accurate. With the help of image processing technique endangered species is segregated and monitored from the rest of the species. © 2024, CRC Press/Balkema. All rights reserved.

关键词： Antennas

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Image Captioning based on Encoder Decoder Architecture 3

Image Captioning based on Encoder Decoder Architecture

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3rd IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing, INCOS 2024

作者： Saranya, M. Veera Anusuya, V. National Engineering College Department of Computer Science and Engineering Kovilpatti India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361186

Images are essential for communicating ideas, feelings, and narratives in the era of digital media and content consumption. computers to produce textual data for an image that replaces humans. Image captioning is a fascinating fusion of computer vision (CV) and Natural Language Processing (NLP) that aims to generate text from an image. By using these technologies, images can be used as an approachable, meaningful, and descriptive form of communication. Because of its wide range of uses, image captioning has attracted a lot of attention. Strong feature representations and context-aware language generation algorithms are necessary to overcome the major challenge of bridging the semantic gap between visuals and text. In this research work, EfficientNetV2B0 is utilized in the encoder part, for extracting objects from an image. Then Long Short-Term Memory (LSTM), a type of recurrent neural network as a decoder for generating descriptions by using encoder output. The suggested approach yields superior results than the earlier research when compared to the current method on the measures of Bilingual Evaluation Understanding and Consensus Based Image Description Evaluation scores. © 2024 IEEE.

关键词： Long short-term memory

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Logistic-Based OVA-CNN Model for Alzheimer’s Disease Detection and Prediction Using MR Images 1

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4th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, ICMISC 2023

作者： John, Chinchu M. Phalgunan, Prafulla Department of Computer Science and Engineering College of Engineering Kerala Trivandrum India

ISBN: (数字)9789819994427

ISBN: (纸本)9789819994410

Alzheimer’s disease (AD) is a form of dementia that diminishes a patient’s cognition and memory. By predicting AD progression early, physicians can begin medication that may reduce the disease’s progression. AD detection and prediction have been extensively performed using convolutional neural networks (CNNs). Despite this, CNN’s use for AD detection is limited by the number of parameters and the extensive training data required. Consequently, this study proposes a logistically based OVA-CNN model for AD detection and prediction using Magnetic Resonance Images (MRI). OVA-CNN consists of the four binary CNN which classified four classes of AD and the logistic regressor predicts the time conversion of pMCI patient who converts AD. The experimental results on the Alzheimer’s Disease Neuro Imaging Initiative (ADNI) demonstrate that the proposed model achieves a high level of accuracy of 93%. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Magnetic resonance

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Design and Implementation of an AI-Enhanced Automatic Animal Food Dispenser 10

Design and Implementation of an AI-Enhanced Automatic Animal...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： Vijayalakshmi, B. Varsheni, S. Sre Ganesh, T.R. Rajalakshmi Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350353068

Animal guardians frequently face the challenge of ensuring that the animals under their care receive timely and adequate nourishment when they are away from home for some period of time. Leaving food in a bowl may result in overeating or shortage of food, and relying on friends or family members to feed the animals may not always be feasible. Additionally, pets with special dietary requirements may require precise feeding schedules and portion control. Hence, there is a growing need for automatic pet feeders to address these concerns. The objective of the project is to provide a convenient and reliable way to feed animals via Artificial Intelligence and IoT concepts, especially when their owners are not able to or available to do so. It can be programmed to dispense designated food tailored for individual animals in precise quantities without caretaker's interference and should also be able to accommodate various pet food types. The feeder must be easy to use and customizable. An automated pet feeder incorporating Internet of Things is a modern solution. It guarantees that their pets receive timely meals, even in the owner's *** systemenables remote monitoring, feeder control and food reordering facility for added convenience, making it an innovative solution for the animal's well-being. © 2024 IEEE.

关键词： Support vector machines

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Optimizing Multilayer Perceptron Classifiers for Predictive Heart Disease Diagnosis: A Hyperparameter Tuning Approach 8

Optimizing Multilayer Perceptron Classifiers for Predictive ...

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8th IEEE International Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Vadlamudi, Anvitha Talasila, Smeeth Althaph, Bollapalli Challa, Nagendra Panini Vadlamudi, Gnana Abhinay School of Computer Science and Engineering VIT-AP University Amaravati India Department of Computer Science and Engineering New York United States

ISBN: (纸本)9798331505462

Heart diseases, collectively known as cardiovascular diseases (CVDs), remain one of the foremost health challenges across the globe, taking millions of lives each year. This study evaluates the effectiveness of Multilayer Perceptron (MLP) classifiers in predicting CVDs using the Heart Disease Dataset from Kaggle. We implemented a structured approach using data pre-processing, model training with baseline MLP classifiers, and hyperparameter optimization utilizing Random and Grid Search techniques. The optimized models, particularly the MLP Classifier trained with Grid Search, outperformed the baseline, achieving up to 98.54 % accuracy and 100% precision. However, analysis of learning curves indicated the need for further model refinement to enhance generalization on unseen data. This study underscores the importance of hyperparameter tuning in developing effective MLP classifiers for CVDs prediction and suggests directions for future research, including exploring advanced optimization methods and regularization techniques. © 2024 IEEE.

关键词： Cardiology

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Influence analysis of calculated horizontally layered soil parameters on grounding parameters

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High Voltage 2023年第2期8卷 421-430页

作者： Yihua Dan Junjun Yin Jian Yang Huizhang Yang Department of Electronic Engineering Tsinghua UniversityBeijingChina School of Computer&Communication Engineering University of Science and Technology BeijingBeijingChina

Calculated parameters(soil layer resistivity,soil layer thickness,and the number of soil layers)of horizontally layered soil are usually obtained based on the measured apparent resistivity under different measurement distances,which are significant for the design,operation,and maintenance of grounding *** existing calculation methods of soil parameters are just trying to make the calculation results approach the measurement data,ignoring the relationship among measurement data,the calculated soil parameters,and grounding parameters,which would increase the workload of the *** better balance the distance range of the measurement data and the influence of the calculated horizontally layered soil on grounding parameters,this paper systematically studies the relationship among measured apparent soil resistivity,calculated horizontally layered soil parameters,and grounding *** basic theories of apparent resistivity measurement,soil parameter calculation,and grounding parameter calculation are given,the influence of soil layer thickness on the measured apparent resistivity is studied,and the influence of the calculated soil parameters on the grounding resistance of different grounding models is *** on different scales of grounding grids,the results give a corresponding reference distance range of measured apparent soil ***,this paper can help decrease the workload of soil resistivity measurement during grounding parameters analysis,which has far-reaching engineering significance.

关键词： soil parameters apparent

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Effect of Signal Conditioning and Evoked-Potential Based Representation on Stability and Distinctiveness of EEG Brain Signatures 12

Effect of Signal Conditioning and Evoked-Potential Based Rep...

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12th International Symposium on Digital Forensics and Security, ISDFS 2024

作者： Oztemel, Muhammed Esad Soysal, Omer Muhammet Louisiana State University Division of Electrical and Computer Engineering United States Southeastern Louisiana University Computer Science United States

ISBN: (纸本)9798350330366

Biometric patterns have been used for authentication purposes for more than decades. Although traditional biometric measurements including fingerprints, facial recognition, and sound recognition are often used for authentication purposes, there is ongoing concern about the risks associated with their repeatability and susceptibility to theft. The utilization of electroencephalography (EEG) has promising potential thanks to the distinctive patterns extracted from brain signals. The main goal of this study is to explore the effectiveness of signal conditioning and evoked potentials on uniqueness and permanence of individuals' EEG signals for authentication purpose. We utilized the Laplacian of Gaussian as a signal conditioning operator. In addition, three signifying functions were explored in obtaining evoked potential time-domain representation from an individual EEG signal. Different stimuli protocols were employed for comparison. A time-series and a statistical technique were utilized for uniqueness and permanence analysis. © 2024 IEEE.

关键词： Authentication

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An Evolution of Hybrid Bagging Technique in Chemoinformatic and Drug Discovery 2

An Evolution of Hybrid Bagging Technique in Chemoinformatic ...

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2nd International Conference on Data science and Information System, ICDSIS 2024

作者： Aluvala, Srinivas Kalshetty, Jagadevi N. Husain, Saif O. Kaur, Jagroop Thind, Harpreet Kaur Sr University School Of Computer Science And Engineering Telangana Warangal India Nitte Meenakshi Institute Of Technology Department Of Computer Science And Engineering Bengaluru India The Islamic University College Of Technical Engineering Department Of Computers Techniques Engineering Najaf Iraq Punjabi University Department Of Computer Science And Engineering Patiala India Dayananda Sagar College Of Engineering Department Of Computer Science And Engineering Bengaluru India

ISBN: (纸本)9798350381665

The drug deals with every living organism on the earth, for classification of drugs based on their action is an important element in drug development. This research paper presents a machine learning model that predicts the action of a drug, utilizing a large drug network. The model integrates J-48 algorithm and random forest algorithm, and form the hybrid bagging technique with the neural network model demonstrating. The model uses the struck2vec data feature, which derived from the large network. Then the data features and dataset are trained on the hybrid bagging technique for drug classification according to the drug properties. The study's findings highlight the important of machine learning models in drug classification which offers a valuable tool for researchers and pharmaceutical companies in the drug development process. The output includes the top classes of drugs, the prediction of action and aiding in new drugs discovery with higher accuracy of 95.83% which is superior over other learning models. © 2024 IEEE.

关键词： Classification (of information)

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Analysis on Success Factors for Improved User Search Through Comprehensive Locality Information

Analysis on Success Factors for Improved User Search Through...

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

作者： Charan, Chamala Giri Swaraj, Kondawar Gopichand, Devarakonda Reddy, H. Venkateswara Hariharan, Shanmugasundaram Kukreja, Vinay Vardhaman College Of Engineering Department Of Computer Science And Engineering Hyderabad India

ISBN: (纸本)9798350364828

An customized user-friendly website providing comprehensive information on hostels for students attending colleges far from their hometowns. The website focuses on crucial details such as room availability, infrastructure, fees, and images, streamlining the search for affordable and quality hostels near respective colleges. The platform features an intuitive interface with robust search and filter options, enabling users to find hostels based on location and amenities. A unique aspect is the inclusion of detailed owner information, facilitating direct communication between students and hostel owners for better decision-making. Development involves meticulous planning, a user-friendly frontend, and a secure backend. The website incorporates a review and rating system for community engagement, and a map integration feature to visually display hostel proximity to colleges, aiding accessibility assessments. Development involves meticulous planning, a user-friendly frontend, and a secure backend. The website incorporates a review and rating system for community engagement, and a map integration feature to visually display hostel proximity to colleges, aiding accessibility assessments. In conclusion, this website addresses a critical need through leveraging technology. This leads to analysis of results which was more promising and contributes to streamlined and informed decision-making process for students, enhancing their overall college experience. © 2024 IEEE.

关键词： Websites

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