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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Kumari, Subhangi Tarlue, Ernest Diallo, Aissatou Chhabra, Megha Mishra, Gouri Shankar Goyal, Mayank Kumar School of Engineering and Technology Sharda University Department of Computer Science and Applications Greater Noida India

ISBN: (纸本)9789380544472

Indian Sign Language (ISL) is a complex and diverse language used by the deaf and hard-of-hearing community in India. ISL recognition and segmentation have been active areas of research in recent years due to the growing demand for assistive technologies for this population. In this review paper, we provide an overview of the various techniques used for ISL recognition and segmentation using machine learning and computer vision. We begin by discussing the challenges involved in ISL recognition and segmentation, such as the variations in sign language gestures, lighting conditions, and background noise. We then review the literature on various techniques used for ISL recognition. We analyze the strengths and limitations of each technique, comparing their accuracy, speed, and robustness against various factors. Finally, we present the recent advancements and future directions for ISL recognition and segmentation © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Machine learning

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Quantum Cryptography: Mathematical Modelling and Security Analysis 3

Quantum Cryptography: Mathematical Modelling and Security An...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Takalkar, Atharva Shiragapur, Bahubali School of Computer Science Engineering and Applications D y Patil International University Pune India

ISBN: (纸本)9798350302288

This paper offers a thorough investigation into quantum cryptography, a security paradigm based on the principles of quantum mechanics that provides exceptional guarantees for communication and information protection. The study covers the fundamental principles of quantum cryptography, mathematical modelling, practical applications, and future prospects. It discusses the representation of quantum states, quantum operations, and quantum measurements, emphasising their significance in mathematical modelling. The paper showcases the real-world applications of quantum cryptography in secure communication networks, financial systems, government and defence sectors, and data centres. Furthermore, it identifies emerging domains such as IoT, 5G networks, blockchain technology, and cloud computing as promising areas for implementing quantum cryptographic solutions. The paper also presents avenues for further research, including post-quantum cryptography, quantum cryptanalysis, multi-party quantum communication, and device-independent quantum cryptography. Lastly, it underscores the importance of developing robust infrastructure, establishing standards, and ensuring interoperability to facilitate widespread adoption of quantum cryptography. This comprehensive exploration of quantum cryptography contributes to the advancement of secure communication, information protection, and the future of information security in the era of quantum technology. © 2023 IEEE.

关键词： Secure communication

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Analysing weather conditions using Firebase

Analysing weather conditions using Firebase

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2023 International Conference on Green Energy, Computing and Intelligent Technology, GEn-CITy 2023

作者： Jha, Abhishek Lalan Ashraf, Azhar Verma, Sahil Kaur, Maninder Computer Science & Engineering Chandigarh University Gharuan India Department of Computer Science and Engineering Uttaranchal University Dehradun India Department of Computer Science and Applications Guru Gobind Singh College for Women Chandigarh India

ISBN: (纸本)9781839539596

Forecasting Weather to a specific time and location via the use of science and technology for its specific location from the 19th century, millions of humans have started predicting weather forecasting. This technology uses meteorology so that it predicts the weather for the future so that the response of the atmosphere can be recorded for the future purpose. Technology for predicting weather we use barometric pressure, in that which show the current weather condition and cloud cover for Sky condition this prediction model is based on the computer Based model show the records of a wide range of atmospheric will be recorded by having this technology for model prediction is pattern recognition, telecommunication model, performance knowledge, but its skill required the more in this technology for forecasting the chaotic character of the weather which is overpowered by the measurement error by this less accuracy the atmospheric dynamic model field to predicting the model which is already exist for forecasting. As a result, as the time gap between today and the predicted model for the forecast has a time gap so it leads to less accuracy, the range of forecasting prediction for selecting the most likely and accurate outcome in the model contest aid narrows free error in it. The most difficult challenge in the world is to predict the forecasting using the Meteorology virtual application for the most significant difficult Technology. In this paper, we are going to investigate data mining techniques and artificial neural networks, my research paper presents the service-oriented model that the architecture for the weather information system will be linked with the GPS system. Algorithms such as Artificial neural networks and Decision tree algorithms are going to use for prediction model for forecasting by gathering information on meteorological data collection of specific time can use for achieving accuracy therefore, this paper includes of classification of different rules f

关键词： Weather forecasting

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The Analysis of Srgb Color Space Based Density for Brain Tumor Segmentation 7th

The Analysis of Srgb Color Space Based Density for Brain Tum...

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7th International Symposium on Intelligent Informatics, ISI 2022

作者： Gangadharappa, S. Naveena, C. Aradhya, V. N. Manjunath Department of Computer Science and Engineering SJBIT Karnataka Bengaluru India Department of Computer Applications JSS Science and Technology University Mysuru Mysore India

ISBN: (纸本)9789811980930

Medical image processing is one of the significant fields to identify the diseases as earlier to diagnose them appropriately. The brain tumor segmentation process is sub branch of a medical image processing field. The computer vision and machine learning techniques provide an effective channel for the medical practitioners for diagnosing the diseases in an effective method. This research article implements the Srgb-based density analysis for isolating the brain tumor space in MRI images. Intensity values of a given input are normalized using Srgb color space and Gaussian filter to distinguish the tumor region from the background. The adaptive threshold technique helps identify the possible tumor space in brain MRI samples. The actual brain tumor space is extracted by performing the region properties such as area and density function. Finally, the accurate tumor space is detected by applying morphological functions with eliminating possible false positives. Performance metrics including recall, precision, and F-measure are used to assess the effectiveness of the proposed approach. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Tumors

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e-Health: A Modern Approach to Healthcare Delivery 14

e-Health: A Modern Approach to Healthcare Delivery

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Maithani, Ankit Pradhan, Rahul Dit University Dehradun Department of Computer Science & Engineering Dehradun India Gla University Mathura Department of Computer Engineering & Applications Mathura India

ISBN: (纸本)9798350335095

e-Health had various attributes other than doctors, patients and medicine. Some of the components are health records, prescriptions, decision support system, online consultation videos, transcripts and telemedicine. Information technology is now integral and one of the core components of eHealth. Prescriptions generated from computer and Artificial intelligent expert systems, include diagnosis, basis of diagnosis, medicine, their side-effects and drug combination and their dosages. © 2023 IEEE.

关键词： Diagnosis

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Investigating Digital Addiction in the Context of Machine Learning Based System Design 13th

Investigating Digital Addiction in the Context of Machine Le...

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13th International Conference on Innovations in Bio-Inspired Computing and applications, IBICA 2022, and 12th World Congress on Information and Communication Technologies, WICT 2022

作者： Johar, Geetika Patel, Ravindra Department of Computer Science and Engineering UIT RGPV Bhopal India Department of Computer Applications UIT RGPV Bhopal India

ISBN: (纸本)9783031274985

In recent years popularity and availability of digital content are increased due to low-cost internet and the availability of smartphones. The suitable and appropriate use of smartphones will help us in our daily personal and professional life. On the other hand, excessive and extreme use of smartphones may invite different kinds of physical and mental disorders. In this context, we proposed to review recent literature about digital addiction. First, we collected 20 recent research articles about different kinds of addictions and the current state of research trends. Then the role of machine learning in order to deal with addiction has been studied. Further some articles are explored for locating the suitable dataset used, techniques of data collection, machine learning algorithms being applied, area of employment, feature selected, and consequences of the articles. Finally based on the collected experiences of the recent efforts we proposed a Smartphone Addiction (SA) prediction and support framework using the Machine Learning (ML) technique. Finally, the conclusion has been made and future plan has also been discussed. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Smartphones

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Vulnerability Classification for Detecting Threats in Cloud Environments Against DDoS Attacks 13

Vulnerability Classification for Detecting Threats in Cloud ...

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13th IEEE International Conference on Communication Systems and Network Technologies, CSNT 2024

作者： Jyothi, V. Esther Chowdary, N. Sampreeth Velagapudi Ramakrishna Siddhartha Engineering College Department of Computer Applications Vijayawada India P.V.P. Siddhartha Institute of Technology Department of Computer Science and Engineering Vijayawada India

ISBN: (纸本)9798350305463

In order to secure data, infrastructure, and services from potential attacks, cloud security is a wide issue that includes any combination of policies, technologies, and procedures. The cloud has substantially different security needs than traditional settings. Because of its dynamic nature and low client infrastructure ownership, the cloud has decreased traditional security architecture. Internet connectivity and distant servers are used in cloud computing to manage data and applications. It provides users with on-demand software, bandwidth, and dynamic virtualized resources through the internet and ensures that its adapters will share in various financial advantages. The utilization of hardware, software licenses, and system maintenance is decreased for the benefit of the customers. The protocol known as SOAP or Simple Object Access Protocol, it enables communication between various web-based services. Extensible Mark-up Language (XML) and Hyper Text Transport Protocol (HTTP) are both used to develop SOAP communications. A cloud web service that uses HTTP and XML might be bringing down by the new type of Distributed Denial of Service (DDoS) attacks. HTTP and XML Denial of Service (DoS) attacks provide a serious security risk to cloud computing. The Hypertext Extensible-Denial of Service (HX-DoS) attack, which causes the cloud service provider's communication channel to get blocked and go down, is made up of purposefully transmitted HTTP and XML messages. Differentiating between suitable and improper communications is necessary to solve the issue of HX-DoS attacks against cloud web services. To decide and place the packets on the side of the victim, the reconstruct and drop technique is utilized. Detection rate, accuracy, and precision were the performance parameters used to evaluated the model's performance. © 2024 IEEE.

关键词： Denial-of-service attack

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Knowledge-enriched joint-learning model for implicit emotion cause extraction

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CAAI Transactions on Intelligence Technology 2023年第1期8卷 118-128页

作者： Chenghao Wu Shumin Shi Jiaxing Hu Heyan Huang School of Computer Science and Technology Beijing Institute of TechnologyBeijingChina Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications BeijingChina

Emotion cause extraction(ECE)task that aims at extracting potential trigger events of certain emotions has attracted extensive attention ***,current work neglects the implicit emotion expressed without any explicit emotional keywords,which appears more frequently in application *** lack of explicit emotion information makes it extremely hard to extract emotion causes only with the local ***,an entire event is usually across multiple clauses,while existing work merely extracts cause events at clause level and cannot effectively capture complete cause event *** address these issues,the events are first redefined at the tuple level and a span-based tuple-level algorithm is proposed to extract events from different *** on it,a corpus for implicit emotion cause extraction that tries to extract causes of implicit emotions is *** authors propose a knowledge-enriched jointlearning model of implicit emotion recognition and implicit emotion cause extraction tasks(KJ-IECE),which leverages commonsense knowledge from ConceptNet and NRC_VAD to better capture connections between emotion and corresponding cause *** on both implicit and explicit emotion cause extraction datasets demonstrate the effectiveness of the proposed model.

关键词： emotion cause extraction external knowledge fusion implicit emotion recognition joint learning

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Enhancing Heart Disease Prediction Through VGG16 and CapsNet 5

Enhancing Heart Disease Prediction Through VGG16 and CapsNet

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5th International Conference on IoT Based Control Networks and Intelligent Systems, ICICNIS 2024

作者： Hemalatha, S. Kavitha, T. Sivabalaselvamani, D. Naveena, N. Haripriya, M. Kongu Engineering College Department of Computer Applications Erode Perundurai India Presidency University School of Information Science Bengaluru India

ISBN: (纸本)9798331518097

This research investigates the application of deep learning algorithms, specifically Capsule Networks and Convolutional Neural Networks (CNNs) based on VGG16, for the early prediction of cardiac issues. By analyzing a diverse dataset of health-related information, we aim to improve the accuracy of binary classification in predicting the presence or absence of heart disease. The study compares the performance of CapsNets and VGG16 CNNs, with VGG16 demonstrating superior accuracy at 99.8% and CapsNets achieving 98% precision. This research contributes to the advancement of predictive analytics in healthcare, enabling more accurate and timely diagnosis of cardiac conditions and paving the way for improved patient outcomes. © 2024 IEEE.

关键词： Convolutional neural networks

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Assessing the Effectiveness of Predictive Maintenance for Internet of Things (IoT) Networks Using Reinforcement Learning 3

Assessing the Effectiveness of Predictive Maintenance for In...

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3rd International Conference on Technological Advancements in Computational sciences, ICTACS 2023

作者： Sharma, Aparna Rastogi, Divya Manwal, Manika Tyagi, Ayushi Sharma, Prashant Kumar Computer Science and Applications Sharda University UP Greater Noida India Computer Science & Engineering Graphic Era Hill University Uttarakhand Dehradun India Computer Science & Engineering Raj Kumar Goel Institute of Technology UP Ghaziabad India Computer Applications Hindustan Institute of Management & Computer Studies UP Mathura India

ISBN: (纸本)9798350342338

Reinforcement getting to know (RL) has emerged as a famous method to predict considerable occasions inside the Net of Things (IoT) networks. RL is a form of artificial intelligence that models conduct from praise and punishment alerts for a given venture or aim. It has been efficaciously used to expect numerous events in dynamic systems and Internet of Things (IoT) networks. Predictive maintenance (PM) aims to stumble on and diagnose screw-ups in IoT structures before they occur. PM aims to expect events and situations in IoT devices to avoid unplanned stoppages or steeply-priced maintenance. Using RL for predictive protection helps with the upkeep of IoT networks by providing a proactive technique. The RL set of rules can study styles from the information accumulated in actual time from the IoT network, after which a prediction algorithm can discover ability screw-ups and endorse preventive preservation tactics. RL can also regulate its mastering process over time based on remarks from the IoT network. The RL approach toward PM provides tremendous benefits over conventional renovation strategies because of its self-getting-to-know and predictive skills. Extensive proof suggests that reinforcement mastering enhances the effectiveness of predictive preservation for IoT networks. RL gives many blessings along with personalized preventive renovation pointers and lowering the value of maintenance, amongst others. As a result, increasingly, groups are adopting reinforcement studying for predictive upkeep to take advantage of its cost financial savings and proactive technique. © 2023 IEEE.

关键词： artificial intelligence dynamic systems IoT predictive maintenance Reinforcement learning

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