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检索条件"任意字段=International Conference on Inventive Computing and Informatics"

共 197 条记录，以下是21-30 订阅

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Enhancing Access Control: A Biometric Approach with Facial Recognition and Near-Field Communication Integration

Enhancing Access Control: A Biometric Approach with Facial R...

引用

international conference on inventive computing and informatics (ICICI)

作者： Rahulkrishnan Ravindran Sabarinath Udayakumar Yellanki Revanth Kalakunnath Namitha Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

This study presents a human identity authentication framework that integrates facial recognition and biometric scanning, enhancing security and speeding up individual identification. The system also includes careful observation of people entering and leaving a designated area, keeping detailed logs in a MongoDB back-end. This strategic integration allows for effective tracking and retrieval of vital information about movement patterns within the monitored area. TensorFlow models, which use Convolutional Neural Networks(CNN), are the core of the identification process, contributing to unmatched accuracy in person recognition. This study provides a comprehensive investigation of the cooperative combination of bio-metrics, facial recognition, CNN, and backend database management for identity verification, raising the bar for their effectiveness, security, and user-friendliness in today’s technological environments. The CNN based algorithm was opted for making facial recognition a much more accurate and easier process.

关键词： Privacy Ethics Accuracy Law Face recognition Biological system modeling Computational modeling

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Defending the Digital World: A Comprehensive Guide Against SQL Injection Threats

Defending the Digital World: A Comprehensive Guide Against S...

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international conference on inventive computing and informatics (ICICI)

作者： Gaurav Kailash Borana Neeraj Harikesh Vishwakarma Shakil Tamboli Pooja Sharma Moresh M. Mukhedkar Nitin A. Dawande Department of Information Technology School of Engineering and Technology D. Y. Patil University Pune Maharashtra India Department of AI & DS School of Engineering and Technology D. Y. Patil University Pune Maharashtra India Department of Computer Engineering School of Engineering and Technology D. Y. Patil University Pune Maharashtra India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

An SQL injection attack is one type of cyberattack targeting web application databases to gain data or modify the structure of data, such as insert, delete, or update. Every sector that utilizes the website as a mode of business uses various techniques to avoid cyber-attacks, but attacks still occur day by day, and it is challenging to use this powerful tool to minimize attacks. Technology is multiplying quickly and new attacks are invented, so we should update and think ahead on how to make the system powerful before a chance attack occurs. There must be a minimum probability of hackers hacking the system This research work briefly discuss on SQL attacks in various phase what is SQL injection, how it happens, mechanisms and effects, and how to protect your data through various prevention and detection mechanisms.

关键词： Filtering Databases Computer hacking Prevention and mitigation Honey pot (computing) Machine learning SQL injection

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Multi Cancer Prediction using Deep Learning and CNN Algorithm

Multi Cancer Prediction using Deep Learning and CNN Algorith...

引用

international conference on inventive computing and informatics (ICICI)

作者： Siddharth Patel Zayd Hassan S. Iniyan Usha Desai Department of Computer Science and Engineering SRM Institute of Science and Technology Kaatankulathur Chennai Tamilnadu India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kaatankulathur Chennai Tamilnadu India S. E. A. College of Engineering & Technology Bengaluru

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

Deep learning approach is used to predict the chance of acquiring several types of malignancies, including breast, brain, lung, colon, oral, kidney, and cervical cancer. To find patterns and risk factors linked to each kind of cancer, deep learning algorithms, such as convolutional neural networks and recurrent neural networks, are trained on enormous databases of patient data, including genetic markers, lifestyle variables, and medical history. Deep learning algorithms can accurately forecast an individual’s risk of acquiring cervical, lung, colon, oral, kidney, breast, or brain cancer by evaluating these intricate datasets. Results indicate varied performance across cancer types, with cervical, breast, lung, and colon cancer models exhibiting high accuracy (>98%) and lower validation losses, suggesting strong generalization capabilities. Conversely, kidney and oral cancer models displayed signs of overfitting, emphasizing the challenges of model generalization. These findings highlights the DL’s potential in enhancing cancer detection, early diagnosis, and personalized treatment planning.

关键词： Deep learning Prevention and mitigation Lung Breast Prediction algorithms Brain modeling History

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Transforming Healthcare: Unified Medical Identification and AI-Enabled Treatment Advancements

Transforming Healthcare: Unified Medical Identification and ...

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international conference on inventive computing and informatics (ICICI)

作者： Abhinand Arun Aswin Babu K V Goutham Rajesh Parthasaradhi H Bindhya Bhadran Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

In the dynamic realm of healthcare, accurate disease prediction stands as a cornerstone for proactive management and personalized care. Through the introduction of Unified Medical Identification (UMI), users can easily connect to their medical records anywhere at any time. With advanced features like rural language support via video-based disease prediction integrated with the Large Language Model, the system generates a broader bracket of users. An ensembled machine learning model is used for general disease prediction. Integrating the CatBoost Classifier with the LangChain framework, the model accurately detects chronic diseases keeping UMI as the central source of the user’s medical data. Furthermore, an AI chatbot aids in the enhancement of user engagement offering targeted treatment options and suitable lifestyle recommendations resulting in better health outcomes. With a remarkable 92.8% accuracy in general disease prediction and a whopping 95.8% accuracy in chronic disease prediction, this revolutionary tool not only reforms the healthcare delivery mode but also guarantees that it is well accepted and widely available across dissimilar communities.

关键词： Accuracy Computational modeling Prevention and mitigation Medical services Machine learning Transforms Chatbots

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Malpractice Detection in Examination Hall using Deep Learning

Malpractice Detection in Examination Hall using Deep Learnin...

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international conference on inventive computing and informatics (ICICI)

作者： Aruna S K Madhumitha A Selvanayaki Kolandapalayam Shanmugam Senthil Kumar Thangavel Maiga Chang Department of Computer Science and Engineering School of Engineering and Technology Bangalore CHRIST University India Department of Mathematics and Computer Science Ashland University Ohia USA Department of Computer Science and Engineering Amrita School of Computing Coimbatore Amrita Vishwa Vidyapeetham India School of Computing Information and Systems Athabasca University Canada

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

Various institutions administer tests at designated examination locations, chosen third-party and approved centers, and have established standards for installing CCTV cameras and conducting frisking under the supervision of designated personnel. Some institutions are using online proctoring, which enables students to take exams from any location. In all of the aforementioned scenarios, human monitoring is conducted, and maintaining a high level of vigilance may be challenging due to administrative oversight or intentional allowance of malpractice for personal gain. The malpractice detection may be attributed to acts like as plagiarism, unauthorized sharing of papers, and non-verbal communication. The study is conducted by capturing the dataset in the classroom of Christ University. The proposed approach is based on the YOLO framework. The movies are processed in real time to identify hand rotation, paper extraction, and classify the motion. The accuracy for the Head_right class is significantly higher than that of the Head_left class. The system is implemented using the programming language Python and has the potential for future expansion to provide real-time monitoring.

关键词： YOLO Accuracy Plagiarism Real-time systems Classification algorithms Object recognition Monitoring

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Integrating Emotion Detection with Sentiment Analysis for Enhanced Text Interpretation

Integrating Emotion Detection with Sentiment Analysis for En...

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international conference on inventive computing and informatics (ICICI)

作者： Arpan Ghosh Naimish Pandey C. AshokKumar Department of Computing Technologies School of Computing College of Engineering and Technology SRM Institute of Science and Technology Chennai India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

The analysis of public sentiment on various social media platforms has become more important.. However, conventional sentiment analysis often struggle to capture intricate emotional nuances present in textual data.. This study proposes an innovative approach by integrating emotion detection with sentiment analysis to improve the interpretation of text.. A novel algorithm "BERT-DeepEmo" is proposed, combining the strong contextual modeling capabilities of Bidirectional Encoder Representations from Transformers (BERT) with a deep learning-based emotion recognition model (DeepEmo). Simulation analyses were performed to evaluate the effectiveness of the proposed algorithm compared to established approaches like BiLSTM-ECNN and RoBERTa-EDTA. Evaluation metrics including accuracy, precision, and mean absolute error were employed for comparison purposes. The results confirmed that BERT-DeepEmo enhances the overall quality of sentiment analysis while considering the emotional nuances in text. These findings highlight the proposed approach's potential to offer a more holistic and effective sentiment analysis framework, thereby facilitating informed decision-making and deeper insights across various applications. Future research work may explore into further integration with alternate process of emotional data, such as speech or visual inputs, to broaden the framework's applicability and efficacy.

关键词： Sentiment analysis Emotion recognition Adaptation models Visualization Accuracy Social networking (online) Bidirectional control

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Enhanced Feature Extraction for Image Dehazing: A Comparative Study between Deep Learning Architectures and FFA-NET

Enhanced Feature Extraction for Image Dehazing: A Comparativ...

引用

international conference on inventive computing and informatics (ICICI)

作者： Sarthak Chaudhary Samridh Gupta S. Iniyan Department of Computer Science and Engineering SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Chennai Tamil Nadu India

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

The problem of poor visibility in foggy images has spurred various image de-hazing strategies. As the need for high-quality images grows, especially for autonomous systems, this research aims to leverage different Deep Learning (DL) architectures to draw out key details from images , localizing this retrieved data to mitigate the impact of haze. The work explores using DL methods, particularly contrasting the regression and classification models of Convolutional Neural Networks (CNN), to remove haze from foggy images. This work sets the stage for further developments in image processing, particularly in conditions with poor visibility. It opens opportunities for improving image quality in various applications, such as autonomous driving and outdoor robotics, where clarity of vision is crucial. The final stage of the proposed model involves three specific pre-processing methods: contextual regularization, air light estimation and boundary constraint for optimal results. The next stage sets out to determine the best DL model for producing clear images from de-hazed ones.

关键词： Image quality Deep learning Atmospheric modeling Neural networks Estimation Feature extraction Convolutional neural networks

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IoT-based Precision Agriculture Monitoring System: Enhancing Agricultural Efficiency

IoT-based Precision Agriculture Monitoring System: Enhancing...

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international conference on inventive computing and informatics (ICICI)

作者： Tahmina Akter Tanjim Mahmud Rishita Chakma Nippon Datta Mohammad Shahadat Hossain Karl Andersson Dept. of CSE Port City International University Chittagong Bangladesh Department of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Dept. of CSE Rangamati Science and Technology University Rangamati Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Dept. of CSE University of Chittagong Chittagong Bangladesh Cybersecurity Laboratory Luleå University of Technology Luleå Sweden

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

This research study introduces an IoT-based Agricultural Monitoring System designed to enhance precision farming practices. Employing Arduino microcontrollers and a network of sensors including water level, soil moisture, temperature, and pH, the system enables real-time monitoring of agricultural parameters. Integration with GSM and WiFi modules facilitates data communication and remote-control capabilities. Additionally, solar power integration enhances sustainability. The collected data is uploaded to a cloud platform for analysis, providing farmers with actionable insights for informed decision-making. The study aims to optimize resource utilization, improve crop yield, and promote sustainable agriculture practices.

关键词： Temperature sensors Precision agriculture Soil moisture Sensor systems Real-time systems Sensors Resource management

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Optimizing Garbage Collection Scheduling and Reporting with Truck Location Tracking Towards an Efficient Waste Management System 24

Optimizing Garbage Collection Scheduling and Reporting with ...

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24th international Arab conference on Information Technology, ACIT 2023

作者： Salac, Djoanna Marie V. Salac, Renz Mervin A. Samonte, Benjie R. College of Informatics and Computing Sciences Batangas State University The National Engineering University Arasof Nasugbu Campus Batangas Philippines

ISBN: (纸本)9798350384307

The annual global waste output hits a substantial 2.12 billion tons, posing a significant challenge for effective management. In the Philippines, the daily accrual of household waste stands at an imposing 35,580 tons, necessitating inventive solutions. This study introduces a sophisticated automated waste management system tailored for Nasugbu, Batangas, utilizing the Agile process model. Employing an iterative approach encompassing brainstorming, design, development, quality assurance, and deployment, the system optimizes garbage collection schedules and enhances user experience. The core objective of the study is to streamline garbage collection and enable real-time garbage truck tracking in the locality. The research delves into the challenges faced by Nasugbu's current waste management system, proposing an automated solution to revolutionize the process. Specific evaluation results substantiate high satisfaction levels among residents, barangay staff, and IT experts. Residents benefit from an intuitive interface offering features such as scheduling, waste calendar management, garbage truck tracking, and proactive SMS notifications. The system not only meets but surpasses expectations, bringing tangible improvements to the waste collection process. © 2023 IEEE.

关键词： agile development automated system garbage collection waste collection optimization waste management

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IoT in Action: Design and Implementation of a Tank Water Monitoring System

IoT in Action: Design and Implementation of a Tank Water Mon...

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international conference on inventive computing and informatics (ICICI)

作者： Tahmina Akter Tanjim Mahmud Rishita Chakma Nippon Datta Mohammad Shahadat Hossain Karl Andersson Dept. of Computer Science and Engineering Port City International University Chittagong Bangladesh Dept. of Computer Science and Engineering Rangamati Science and Technology University Rangamati Bangladesh Dept. of Computer Science and Engineering Chittagong University of Engineering & Technology Chittagong Bangladesh Dept. of Computer Science and Engineering University of Chittagong Chittagong Bangladesh Cybersecurity Laboratory Luleå University of Technology Luleå Sweden

ISBN: (数字)9798350373295

ISBN: (纸本)9798350373301

Water management in residential areas often faces challenges such as unpredictable shortages and damaging overflows due to inadequate monitoring of tank water levels. This study presents the design and implementation of an Internet of Things (IoT)-based tank water monitoring system aimed at providing a reliable and efficient solution to these issues. Utilizing advanced sensor technology, the system accurately monitors water levels, volume, and quality within storage tanks. It incorporates dual sensors that enhance reliability: one sensor manages the water level, initiating pump activation when levels fall below a critical threshold, while the second sensor prevents overflows by deactivating the pump once the water level reaches a pre-set maximum. The system is designed to be user-friendly, offering real-time water level data and control via an Android application or web dashboard. This allows for remote operation of the motor pump, ensuring that water availability is consistent and secure, while also safeguarding against overflows and subsequent water wastage. The implementation of this IoT system demonstrates significant potential for enhancing water resource management in residential settings, promoting both sustainability and ease of use.

关键词： Reliability engineering Motors Real-time systems Water monitoring Internet of Things Sustainable development informatics

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