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14th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2023

作者： Latke, Vaishali Narawade, Vaibhav Dept. of Computer Engineering Ramrao Adik Institute of Technology Nerul India

Dentists detect abnormalities in tooth with dental X-ray imaging techniques. Due to a wide variation in human tooth shapes, sizes, and abnormalities, processing a dental image is difficult and time-consuming task. Evaluation of dental anomalies using manual observation and inference remains to be a challenge till date. In order to make perfect analysis and formulate suitable treatment plan, automation in the field of dental picture segmentation and evaluation is crucially important. On reviewing a few approaches in the existing literature, a hybrid model has been proposed to detect Periapical lesions from an input X-ray image. Research has been segregated into three primary areas viz. Image Processing, Machine Learning and Deep Learning methodologies. The model has been tested on several X-ray images and accuracy of the same has been ascertained. Future research scope towards refinement of endodontic treatment has been proposed. © Grenze Scientific Society, 2023.

关键词： Convolutional neural networks

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Enhanced Attitude Stabilization of Quadrotors Using a Single-Axis Constraint Moment Disturbance Obserner

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IEEJ Transactions on Industry Applications 2024年第4期144卷 257-264页

作者： Ichiryu, Atsuhiro Shimada, Akira Electrical Engineering and Computer Science Graduate School of Engineering and Science Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan Dept. of Engineering and Design Shibaura Institute of Technology 3-7-5 Toyosu Koto-ku Tokyo135-8548 Japan

This study proposes a maintaining a quadrotor’s attitude system using a ‘moment disturbance observer’ aimed at enhancing stability. In recent years, quadrotors have become increasingly prevalent in sectors such as agriculture, surveying, logistics, aerial photography, infrastructure inspection, and security. However, with their growing, there have been concerns about potential physical and human harm stemming from accidents. The Ministry of Land, Infrastructure, Transport, and Tourism has reported accidents attributed to challenging maneuvering conditions that have resulted in crashes. This study aims to develop a quadrotor that can maintain a stable attitude during sudden and significant alterations in its orientation. We suggest employing a moment disturbance observer to estimate the necessary moments for stable attitude maintenance. Numerical simulation results show that the proposed method surpasses traditional PID control in terms of attitude stabilization. Furthermore, this method resulted in superior attitude stability in single-axis experiments with a mechanically constrained quadrotor compared to conventional PID control methods. © 2024 The Institute of Electrical Engineers of Japan.

关键词： Aerial photography

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An Implementation of Blockchain technology in Combination with IPFS for Crime Evidence Management System

An Implementation of Blockchain Technology in Combination wi...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Shilpa, C. Shanthakumara, A.H. Siddaganga Institute of Technology Dept. of Computer Science & Engineering Tumakuru India

ISBN: (纸本)9798350348217

Crime is an unlawful act and is punished by the authority, in order to prove crime, evidence is necessary. Evidence obtained from crime scene is crucial as it act as proof of crime, Digitalization of evidences is need of hour. During the entire process of investigation heterogenous format of data is generated and integrity of the sensitive data has to be maintained as sensitive data passes through the various levels of intermediaries forming Chain of Evidences (CoE). Evidence needs to be tramper proof and should be protected from any kind of alterations. In order to build strong system with immutability, integrity, and legitimacy features blockchain technology is more suitable. The digital evidence can be transferred in a transparent way between the parties involved without any central authority using blockchain technology. This paper focuses on how blockchain based solutions can help in building a strong secure system. The system is implemented using Ethereum platform to achieve integrity, immutability transparency as well as tampering can be identified by any one at any time. © 2023 IEEE.

关键词： Smart contract

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Questify: Your Intelligent Web Page Assistant for Quick Answers 3

Questify: Your Intelligent Web Page Assistant for Quick Answ...

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3rd International Conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Jha, Aashish Purohit, Madhavi Samanta, Gaurav Jadhav, Dipti Don Bosco Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350348347

Retaining and recalling information from web pages can often feel like a daunting task, especially when faced with the vast amount of information contained within an article. However, researchers have come up with an innovative solution to tackle this. In this study, we propose a hybrid question-answering system that uses Natural Language Processing (NLP) to logically describe the data on a web page and then react to user inquiries. The system consists of a web scraper, named entity recognition module, and classifiers to learn more about the *** process begins with a web scraper, which gets the text from a certain online page and makes sure that the required data is gathered. The system learns more about the information by identifying and classifying items like persons, locations, organizations, or other pertinent phrases. The question-answering module uses a knowledge graph to provide accurate and comprehensive answers to user queries. Using benchmark datasets, we evaluated the system's performance to confirm the efficacy of their strategy. Across several datasets, the F1 score, which is a metric for precision and recall, varied from 0.7 to 0.95. The system can serve as a useful resource for information retrieval from web sites, according to these results, which show that it is able to provide users trustworthy responses to their questions. © 2023 IEEE.

关键词： Benchmarking

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Forecasting Consumer Price Index (CPI) Using Deep Learning and Hybrid Ensemble Technique 2

Forecasting Consumer Price Index (CPI) Using Deep Learning a...

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2nd IEEE International Conference on Advances in Computing, Communication and Applied Informatics, ACCAI 2023

作者： Mohammed Adnan, A. Prince Immanuel, J. Roobini, M.S. Sathyabama Insititute of Science and Technology Dept of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350315905

In today's day and age, economic crises are all over the world due to high inflation. Inflation is a rise in price of the goods and services produced in a country. As a result of rising prices, a given amount of money can now buy fewer goods and services. The general public's cost of living is affected by this loss of purchasing power, which ultimately slows economic growth. Thus, it has a negative impact on the purchasing power of the people. Various sorts of baskets of commodities are generated and tracked as price indices to calculate inflation or deflation, depending on the chosen set of goods and services used. One type of price index proposed in this project is Consumer Price Index (CPI), which looks at the weighted average of costs for a variety of products and services like transportation, food, and healthcare. This paper proposes different deep learning time series models such as LSTM, BiLSTM and hybrid ensemble learning to forecast the Indian consumer price index (CPI). These two single RNN models (LSTMs and BiLSTMs) are compared with the hybrid ensemble learning model to see which gives better forecasting results for the consumer price index. © 2023 IEEE.

关键词： Long short-term memory

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Institutional Accreditation Data Analysis And Decision-Making System 3

Institutional Accreditation Data Analysis And Decision-Makin...

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3rd International Conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Dsouza, Chris Gupta, Rhea Pradhan, Sarah Shaikh, Phiroj Don Bosco Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350348347

This paper highlights the implementation of the National Accreditation System's fifth criteria and its application to ensure quality assurance standards are met by the University. The authors provide an overview of recent advancements in the Institute's Special Faculty Administrative Region and examine how they relate to neighbouring institutes' engineering practices. The paper concludes with the author's observations on the interplay between different institutes in India with regard to accreditation criteria. Specifically, the paper delves into the contents of Self-Assessment Reports, the process of developing them, challenges encountered during their creation, as well as the advantages and features of the Accreditation Data Management © 2023 IEEE.

关键词： Accreditation

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Exploring emerging spreaders through GCN-based link prediction and a novel centrality method 17

Exploring emerging spreaders through GCN-based link predicti...

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17th International Conference on COMmunication Systems and NETworkS, COMSNETS 2025

作者： Nandi, Suman Maji, Giridhar Dutta, Animesh National Institute of Technology Dept. of Computer Science and Engineering West Bengal Durgapur India Asansol Polytechnic Dept. of Electrical Engineering West Bengal India

ISBN: (纸本)9798331531195

Exploring influential spreaders and predicting missing links in complex networks is essential for understanding and effectively controlling network dynamics. This paper presents a Graph Convolutional Network (GCN)-based link prediction method to estimate the probability of future link formation. We incorporate node features that capture local and global topological connectivity structures and feed these into the GCN model, where convolutional layers aggregate neighboring information and transform node features. This approach enables the model to capture structural patterns by integrating local and global information from neighboring nodes. In the final layer, the GCN model computes a prediction score representing the likelihood of an edge's existence, using insights gained during training. Finally, considering the predicted links, we update the network structure and introduce a novel centrality method called Emerging Spreader Centrality (ESC) to identify emerging spreaders within this augmented network. We conduct two separate experiments to evaluate the performance of the GCN-based link prediction and the ESC method, comparing their effectiveness with various state-of-the-art methods. Results demonstrate that our approach not only effectively predicts future links but also identifies emerging spreaders in the augmented networks. © 2025 IEEE.

关键词： Prediction models

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Smart Posture Analyzer for Exercise 6

Smart Posture Analyzer for Exercise

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6th IEEE International Conference on Advances in Science and technology, ICAST 2023

作者： Dhaigude, Siddharth Panigrahi, Hrishikesh Godse, Sahil Shaikh, Phiroj Dept. of Computer Engineering Don Bosco Institure of Technology Mumbai India

ISBN: (纸本)9798350359817

Going to the gym on your own is, of course, possible, but a personal trainer can really help you increase your endurance. In this day and age, many people rely on YouTube tutorial videos to figure out what works best for them. However, if done unsupervised or incorrectly, it can be ineffective and potentially dangerous. During exercise, sudden movements and poor posture can result in temporary or permanent disability. So, we devised this smart exercise posture analyzer concept. By alerting the user and providing alternative actions, the system warns the user about poor posture. This would allow the user to focus on the exercise rather than the mobile screen. The idea is to track the body posture of the user while they are doing exercise and recommend changes simultaneously. The system will also keep track of reps the user is doing. The proposed system does not consider more than 3 exercises. Algorithms based on machine learning are used to predict and guide users when performing specific workouts. © 2023 IEEE.

关键词： Long short-term memory

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Systematic Approach to Analyze The Avast IOT-23 Challenge Dataset For Malware Detection Using Machine Learning 18

Systematic Approach to Analyze The Avast IOT-23 Challenge Da...

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18th IEEE International Conference on Emerging Technologies, ICET 2023

作者： Jahangir, Muhammad Talha Wakeel, Muhammad Asif, Humza Ateeq, Ahsan Mns University of Engineering and Technology Dept. of Computer Science Multan Pakistan

ISBN: (纸本)9798350328172

The integration of the Internet of Things (IoT) becomes more ingrained in our lives, it has gained significant importance for manufacturing companies. By enabling real time monitoring of machine status, evaluating product quality, and observing environmental conditions within factories. IoT empowers managers to make well considered decisions that reduce risks and alleviate losses. However, the growing reliance on IoT devices and services has also given rise to concerns about security and safety due to possible anomalies within IoT networks. Swiftly identifying and resolving these anomalies are crucial to prevent potential harm or losses. The proposed method introduces an innovative approach that leverages machine learning and deep learning techniques for the rapid classification of malicious software attacks on IoT networks. The central goal of this research is to conduct a thorough examination of the Avast IoT-23 dataset with the aim of pinpointing the most effective algorithm in terms of performance and efficiency. In this proposed methodology, the Decision Tree (DT) algorithm stands out as the most efficient and effective choice due to its high accuracy and low time complexity cost. © 2023 IEEE.

关键词： Internet of things

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Optimized Crop Prediction and Monitoring Using Ensemble Machine Learning Algorithms 2

Optimized Crop Prediction and Monitoring Using Ensemble Mach...

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2nd IEEE International Conference on Networks, Multimedia and Information technology, NMITCON 2024

作者： Kavitha, H.S. Usha, S.M. Sheela, S.N. Anu, H. Sharmila, N. Mallikarjunaswamy, S. Basavaraju, N.M. Ravi, P. Pavithra, G.S. Jss Academy of Technical Eduction Dept of Electronics and Communication Engineering Bengaluru India Jss Science and Technology University Dept of Electronics and Electrical Engineering Mysuru India Dept of Computer Science and Engineering Mysuru India Jss Academy of Technical Eduction Dept of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350372892

This paper addresses the urgent need for enhanced agricultural practices by pinpointing the significant limitations of existing crop prediction and monitoring systems. Traditional methods, often characterized by low accuracy and high resource consumption, severely limit effective farming decision-making and sustainability. In response to these challenges. A proposed method is introducing the Optimized Crop Prediction and Monitoring Model (OCPMM), a groundbreaking approach that harnesses the power of advanced Machine Learning Algorithms (MLAs) to elevate accuracy and efficiency in crop management. The OCPMM distinguishes itself through innovative features such as real-time data analysis and predictive analytics, establishing a new benchmark for precision agriculture. Our comparative analysis reveals that the OCPMM markedly surpasses conventional methods, such as the Standard Crop Yield Estimation Technique (SCYET), across key metrics, including prediction accuracy, resource utilization, and time efficiency. These enhancements are instrumental in optimizing crop yields, minimizing waste, and advancing sustainable agricultural practices. By rigorously addressing the deficiencies of traditional systems and highlighting the superiority of the OCPMM with empirical evidence, this study illuminates the transformative potential of machine learning technologies in agriculture. It presents a scalable, reliable, and efficient framework poised to revolutionize agricultural practices, paving the way for a future where farming decisions are informed by precision and foresight. © 2024 IEEE.

关键词： Adversarial machine learning

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