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检索条件"任意字段=International Conference on Advances in Data Science and Computing Technologies, ASDC 2022"

共 6586 条记录，以下是81-90 订阅

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Color Image Encryption Using Novel 5D Piecewise Map 5

Color Image Encryption Using Novel 5D Piecewise Map

引用

5th IEEE international conference on advances in Electrical, computing, Communication and Sustainable technologies, ICAECT 2025

作者： Salunke, Bharti Salunke, Sharad Parul University Department of Computer Science & Engineering Vadodara India

ISBN: (纸本)9798350356236

This paper presents a novel color image encryption technique using a 5D piecewise chaotic map. In recent years, image encryption has become crucial for securing multimedia data in various applications, especially in communication over the internet. The proposed 5D piecewise map introduces complex chaotic behavior, ensuring higher security for color images. We extensively evaluate the performance of the encryption scheme using metrics such as correlation coefficient, information entropy, and keyspace. The results indicate that the proposed method achieves excellent security properties, and provides a substantial keyspace to prevent unauthorized access. Additionally, the comparison with recent methods demonstrates the superiority of our proposed encryption approach in terms of encryption speed, randomness, and robustness. © 2025 IEEE.

关键词： Authentication

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Emotion Recognition Using Text and Speech Through Machine Learning

Emotion Recognition Using Text and Speech Through Machine Le...

引用

international conference on advances in data science and computing technologies, asdc 2022

作者： Singla, Chaitanya Singh, Sukhdev Department of Computer Science Punjabi University Patiala Punjab India Department of Computer Science Multani Mal Modi College Patiala Punjab India

ISBN: (纸本)9789819936557

Speech recognition is an important problem that is reflected in the process of applications which work in the field of education and communication that exists in human and computer. Emotion identification from speech is a nontrivial task refers to the ambiguous meaning of emotion itself. Although it has improved several times over the years, especially with the advent of deep neural networks (DNN). There are three main reasons through which the awareness of emotion recognition becomes a challenging task: (1) human emotions are inaccessible, which means it is difficult to distinguish;(2) in general, a person’s emotions can only be experienced from time to time during prolonged speech;(3) speech data with emotional labels are often limited. The emotions extracted in this study are happy, sad, neutral and angry. The wav files and its transcriptions are taken from the publically available dataset called IEMOCAP. Taking into account both the features extracted from the speech and text, and then, both the features are fused to get one feature file that is used further for the classification of the emotions using simple machine learning models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Emotion Recognition

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An approach for real time management of global manufacturing enterprises based on Digital data Stream

An approach for real time management of global manufacturing...

引用

2022 international conference on ENTERprise Information Systems, CENTERIS 2022 - international conference on Project MANagement, ProjMAN 2022 and international conference on Health and Social Care Information Systems and technologies, HCist 2022

作者： Jain, Hemant University of Tennessee Chattanooga 615 McCallie Avenue ChattanoogaTN37403 United States

advances in sensor technology, IOTs, communication technologies, computing, data management and analytics is changing the way modern global manufacturing enterprises are managed. With appropriate design and architecture of these technologies it is possible to use digital data streams to manage these enterprises in real time. This paper focuses on issues related to the design of these systems. Specifically, we focus on developing approaches for the design of autonomous services that receive data from local devices (e.g. sensors) in real time, do some processing in real time, communicate with other services, and respond to stimuli received from other services in real time. This allows localization. © 2023 Elsevier B.V.. All rights reserved.

关键词： Information management

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Emotion Variance in Speech and Text 15

Emotion Variance in Speech and Text

引用

15th international conference on advances in computing, Control, and Telecommunication technologies, ACT 2024

作者： Peddi, Snigdha Karnati, Manikundan *** Artificial Intelligence and Data Science CBIT India *** Artificial Intelligence and Data Science CBIT India

ISBN: (纸本)9798331300579

Emotion recognition is an area of research that is gaining increasing attention and may provide some useful insights. A speech signal is used to determine the emotional state of an individual through Speech Emotion Recognition (SER). The motive of the project is to understand and interpret emotional cues in speech and text, which is an important skill for effective communication and social interaction[1]. A multiclass classification problem is formalized as our problem and two models are compared based on their performance. For speech, we extracted acoustic and spectral features from the audio signals. For text, Learning-based methods are being used to predict emotions. While keyword-based detection methods use keywords to detect emotions, learning-based methods apply various machine learning theories to a previously trained classifier in order to detect emotions such as the Multinomial Naive Bayes Classifier (MNB). The input text will be categorized according to its emotion. Overall, we compare the emotion predictions from both speech and text and visualize their coincidence using R. © Grenze Scientific Society, 2024.

关键词： Emotion Recognition

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Survey of Various Machine Learning Techniques for Analyzing IoMT-Based Remote Patient Monitoring System 1

引用

international conference on advances in data science and computing technologies, asdc 2022

作者： Johar, Sayyed Manjula, G.R. Assistant Professor Department of Artificial Intelligence and Machine Learning Jawaharlal Nehru New College of Engineering Karnataka Shivamogga India Professor Department of Computer Science and Engineering Jawaharlal Nehru New College of Engineering Karnataka Shivamogga India

ISBN: (数字)9789819936564

ISBN: (纸本)9789819936557

Internet of Medical Things (IoMT) consists of several medical devices used to capture patient health information. The recorded details are transmitted to the healthcare centers via computer networks. This transmitted information is stored in the cloud environment for making further clinical analysis. The continuous recordings of patient information help predict the patient’s chronic disease and help to initiate the respective solutions. This recorded information is processed by applying various machine learning and deep learning techniques to predict patient health conditions. Therefore, here the general discussion of IoMT and the impact of patient health monitoring systems are discussed. Along with this, various methodology’s respective pitfalls and advantages are analyzed to improve the healthcare system’s remote patient health monitoring process. The major goals of this study were to comprehend the role played by IoMT in remote patient monitoring and the effects of intelligent approaches on data analysis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep learning

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A Review on Students' Performance Prediction using Learning Analytics 15

A Review on Students' Performance Prediction using Learning ...

引用

15th international conference on advances in computing, Control, and Telecommunication technologies, ACT 2024

作者： Jyoti Kumar, Dharminder Dhingra, Sakshi Department of Computer Science and Engineering Guru Jambheshwar University of Science and Technology Haryana Hisar India

ISBN: (纸本)9798331300579

Learning Analytics is a research area that is growing rapidly. It deals with selecting, analyzing, and reporting educational data collected from various learning environments and finding relevant patterns in students' behavior. Different online learning platforms like Massive Open Online Courses (edX, Udemy, Udacity, etc.), Learning Management Systems (Moodle, Blackboard, Classroom, etc.), and Virtual Learning Environments (DEEDS, Coursera, etc.). Learning analytics can be viewed as a multidisciplinary field that includes Machine Learning (ML) Techniques, Educational data Mining (EDM), Statistics, Social Network Analysis, and Natural Language Processing. This paper comprises the study of Learning Analytics and its different techniques used in predicting students' performance. Further, it consists of an analysis of previous studies described in tabular form for better understanding. A basic learning analytics model is described which consists of the steps involved in creating any project. © Grenze Scientific Society, 2024.

关键词： Adversarial machine learning

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Integrating Cloud And Edge computing For Scalable Iot Applications 2

Integrating Cloud And Edge Computing For Scalable Iot Applic...

引用

2nd international conference on advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Nagarjuna, Pitty Sevuga Pandian, A. Sharma, Suresh Kumar Ramesh, T. Sohail, Mohammed Ali Dinesh Babu, M. Indian Institute of Science Karnataka Bengaluru India Department of Computer Science Kristu Jayanti College Karnataka Bengaluru India Dept. of Statistics Mathematics and Computer Science Sri Karan Narendra Agriculture University Jaipur Jobner India Department of CSE R.M.K Engineering College Chennai India Department of EEE Jazan University Jazan Saudi Arabia Department of Mechanical Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9798331541217

The data from the Internet of Things (IoT) is essential in the modern data-driven digital economy since it inspires many new business models supplying a wide spectrum of services both ubiquitous and intelligent. The data transmitted using edge computing technologies is investigated in this paper. Under the framework of the trust model of the research, the data exchanged between the source block and the destination block generates direct, indirect, and reciprocal trust. Although cloud computing can serve as a paradigm for safe data flow, the results of the study revealed that a trust-based approach can avoid cloud intrusion. The simulation runs on numerous test beds using the presently in use cloud technique. The results clearly illustrate that the trust-based approach is effective in protecting data moved across edge computing. © 2024 IEEE.

关键词： Cloud platforms

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Hybrid Visual Verification 14

Hybrid Visual Verification

引用

14th international conference on Cloud computing, data science and Engineering, Confluence 2024

作者： Bushra, S.Nikkath Syed Ismail, A. Sasigresa, P. Edwin Singh, C. Srm Institute of Scienece and Technology Department of Computing Technologies Chengalpattu Kattankulathur India Srm Institute of Scienece and Technology Department of Data Science and Business Systems Chengalpattu Kattankulathur India Veltech University Department: Computer Science and Engineering India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department: Computer Science and Engineering India

ISBN: (纸本)9798350344837

data security is becoming increasingly important as cloud computing advances. data security is the fundamental problem of all distributed computing systems. Cloud computing enables access to distributed applications and services belonging to various organizations spread across different locations. Cloud computing raises security concerns, because it shares data with distributed users via network in an open terrain. In this system, some of the most important security services like image-based security are handled by the cloud computing system. The proposed scheme takes care of several attacks like botnets, malware and guessing attacks. This scheme is contrasted withseveral established schemesand a new form of authentication is used for the purpose of storing files in a secure manner. © 2024 IEEE.

关键词： Authentication

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A Comparative Analysis Multiple Disease Prediction using Machine Learning Models 15

A Comparative Analysis Multiple Disease Prediction using Mac...

引用

15th international conference on advances in computing, Control, and Telecommunication technologies, ACT 2024

作者： Swathi, Ch. Cheripelli, Ramesh Dept of CSE G Narayanamma Institute of Technology and Science Telanagana Hyderabad India Vidya Jyothi Institute of Technology Dept of IT Telanagana Hyderabad India

ISBN: (纸本)9798331300579

The diagnosis of diseases at an earlier stage is critically important to the overall improvement of healthcare outcomes because it paves the way for timely interventions and more effective treatment choices. The development of the Smart Health Prediction System as a subfield of medical science has paved the way for reliable disease prediction by utilizing data mining strategies. This was previously impossible. However, the currently available systems have a number of drawbacks, including a slow generation rate for analysis reports, low operational efficiency, high operational costs, and poor accuracy. In this context, the model that is being suggested tries to properly forecast the overall health condition of individuals by leveraging measurable parameters such as TH11, Spo2, pulse rate, and MQ2 parameters. Specifically, the goal of this work is to improve overall health outcomes. © Grenze Scientific Society, 2024.

关键词： Prediction models

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Forest Fire Prediction and Detection using NodeMCU with IoT 15

Forest Fire Prediction and Detection using NodeMCU with IoT

引用

15th international conference on advances in computing, Control, and Telecommunication technologies, ACT 2024

作者： Shashikala, S.V. Gowda, Sinchana S. Shafiyamariyam Samanvitha, R. Suhas, R. Department of Computer Science BGS Institute of Technology Mandya India

ISBN: (纸本)9798331300579

The rising threat of forest fires demands efficient and timely detection and prevention *** project presentsasolutionleveragingtheNodeMCU, an open-source IoT platform, to create a forest fire detection and prevention *** proposed system integrates various sensors to monitor environmental factors such as temperature, humidity, and smoke levels *** from these sensors and transmit it wirelessly using IoT protocols to a centralized *** data collected is analysedinRealtimetodetectabnormalchangesthatmay indicate the onset of a ***, this system employs machine learning algorithms for predictive analysis, aiming to forecast potential fire outbreaks based on historical data *** fire detection, thesystem triggers alerts to designated authorities, enabling swift response measures to contain and prevent fire *** project aims to provide ascalable, and productive arrangement for forest fire detectionand prevention, leveraging the capabilities of IoT and NodeMCU technology to safeguard vast forested regions. © Grenze Scientific Society, 2024.

关键词： Environmental monitoring

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