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Automated Attendance Management System 5

Automated Attendance Management System

引用

5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Goyal, Pranshu Nigam, Vishwas Khan, Shahnaw A.J. Singh, Shashi Kant Galgotias College Of Engineering And Technology Dept. Of Computer Science And Engineering India

ISBN: (纸本)9798350330861

the manual process of recording and managing attendance in educational institutions and organizations is often time-consuming, prone to errors, and inefficient. To address these challenges, there is a growing need for automated attendance management systems. This research paper presents the design and implementation of an Automated Attendance Management System (AAMS) using modern technologies. The AAMS utilizes various technologies such as biometric recognition, RFID (Radio Frequency Identification), and computer vision to accurately and efficiently track attendance. The system aims to simplify the attendance recording process for both students and instructors, reduce administrative burden, and improve overall efficiency. The proposed AAMS incorporates biometric recognition techniques, such as fingerprint scanning or facial recognition, to identify and verify the identity of individuals. © 2023 IEEE.

关键词： Efficiency

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Enhancing Predictive Modeling in High Dimensional Data Using Hybrid Feature Selection 5

Enhancing Predictive Modeling in High Dimensional Data Using...

引用

5th International Conference on Electronics and Sustainable Communication Systems, ICESC 2024

作者： Ambhika, C. Gayathri, S. Anish, T.P. Sheena, B. Gracelin Nalini, M. Siva Subramanian, R. Rmd Engineering College Dept of Aiml India S.A. Engineering College Department of Computer Science and Engineering India Rmk College of Engg and Tech Dept of Cse India Sathyabama Institute of Science and Technology India S A Engineering College Dept of Cse India

ISBN: (纸本)9798350379945

Healthcare data has become invaluable for patients care enhancement as well as outcomes which have been influenced by the expanding volume and complexity of health informatics. The current research discusses the design of a hybrid feature selection(HFS) methodology which is based on a combination of filter & wrapper methods to detect the necessary variables for predictive modeling using machine learning algorithms. The study takes the data set on Parkinson's disease as a use case. The performance of KNN, Decision Trees, and Random Forest models is assessed based on this data set. Findings reveal that integration of feature selection impacts models' efficacy, where Random Forest performs best among all techniques. KNN helped to lower the total number of errors but to increase sensitivity, while the Decision Trees (DT) applied changes not only to sensitivity but to specificity also. The findings bring feature selection into the limelight making healthcare data analysis more revealing in disease prediction and personalized medicine. The application of filter and wrapper methods by providers makes the data exploring process in a high-dimensional data easier and useful in getting actionable insights for improved patient care. Additional studies on feature selection methods and network architecture evolution should be carried out in order to increase the efficiency of medical data mining and enhance predictive model accuracy. © 2024 IEEE.

关键词： Personalized medicine

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File Encryption using Noise Images as Key 3

File Encryption using Noise Images as Key

引用

3rd International Conference on Smart Data Intelligence, ICSMDI 2023

作者： Bhagya Lakshmi, A. Pradeep, R. Seshadri, K.S. Shriraam, B. Easwari Engineering College Dept. of Computer Science & Engineering TN India

ISBN: (纸本)9781665464871

Everything in today's highly connected digital world is increasingly dependent on instantaneous global data transfers. Internet efficiency facilitates our daily lives. Sharing information online presents significant security dangers and difficulties in the modern day. The use of cryptography is the means through which sensitive information can be protected from various threats. Improved cryptosystems technology is a no-brainer for securing communication networks. An improved cryptosystem is the focus of our research, and to that end we have presented a novel method of data encryption and decryption that guarantees increased efficiency over current best practises. This research work has proposed a noise image encryption and decryption scheme, wherein the noise signal is randomly selected to set the initial values for a chaotic system which also enhances the security of the system. for understanding the effectiveness of the proposed system. Experimental results confirm that the proposed chaos-based cryptosystem is efficient and suitable for information (image) transmission in a highly secured way. This study has developed a file encryption system, where encrypted file is saved to decrypt and download later. The main difference between the existing and proposed system is the implementation of file encryption system using noise images that store key values inside it. © 2023 IEEE.

关键词： Cryptography

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Real-time Event Streaming for Financial Enterprise System with Kafka 3

Real-time Event Streaming for Financial Enterprise System wi...

引用

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

作者： Sanjana, N. Raj, Sinchana Vishalakshi Prabhu, H. Sandhya, S. Rv College of Engineering Dept. of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350302288

Real-time event streaming refers to the continuous and immediate processing and analysis of events as they occur in real time. Presently, Apache Kafka is a very popular and preferred framework for real-time data streaming. Data stream pipelines to serve enormous data for large organizations are built between systems in Kafka for real-time streaming. Kafka provides a distributed, scalable, and fault-tolerant platform for capturing, storing, and processing streams of events. It provisions seamless integration with different systems and applications, enabling real-time data analysis and processing. Thus, event streaming with Kafka is a modern approach to processing and analyzing large volumes of data in real-time. Event streaming with Kafka has a wide range of applications in varied industries such as finance, e-commerce, and more. It has the potential to transform the way businesses operate by enabling faster decision-making, improved operational efficiency, and better customer experiences. With financial enterprise application as our main goal, we focus on how Kafka could be a better-suited alternative to enhance event streaming. © 2023 IEEE.

关键词： Decision making

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Optimizing Customer Segmentation: A Comparative Analysis of Clustering Algorithms Using Evaluation Metrics 8

Optimizing Customer Segmentation: A Comparative Analysis of ...

引用

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

作者： Sakina, Noor Arun, Ajith P. Pavithra, R. Vishalakshi Prabhu, H. Gupta, Praveen Kumar Rv College of Engineering Dept. of Computer Science and Engineering Bengaluru India Rv College of Engineering Dept. of Chemical Engineering Bengaluru India Rv College of Engineering Dept. of Electronics and Communication Engineering Bengaluru India Rv College of Engineering Dept. of Biotechnology Bengaluru India

ISBN: (纸本)9798331505462

Customer segmentation is the route to data-driven decisions within organizations serving a wide variety of customer needs. This research explores customer segmentation with the utilization of K-means, hierarchical clustering, fuzzy C-means, along with DBSCAN to behavioural and demographic data. These algorithms are measured against each other using their silhouette score, Davies-Bouldin index, and cluster cohesion value. These results highlight that clustering can reveal meaningful patterns in customer data for improving personalized marketing strategies, customer retention, and profitability. © 2024 IEEE.

关键词： Sales

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CryptoProctor In Elevating Online Exams through Blockchain Technology 1

CryptoProctor In Elevating Online Exams through Blockchain T...

引用

1st IEEE International Conference on Computing and Data science, ICCDS 2024

作者： Ramani, R. Gangadhar, S. Balaganesh, A. Ganganathan, M. P.S. R Engineering College Dept of Computer Science and Engineering Tamil Nadu Sivakasi India

ISBN: (纸本)9798350365337

Rise of digital technologies, the safety and reliability of online tests have been emerged as a critical concerned. To enhance the trust worthiness and reliability of online tested services, "Crypto Proctor"stands out as an innovative solution that employs blockchain technology. This abstract provides an overview of the project's key components and may have an impact on online education as a whole. Traditional online assessment platforms often have challenges with authenticating users, ensured data accuracy and combating concern-cheat. Blockchain technology enhances the safety of online exams with a distributed and immutable ledger called "Crypto Proctor.". This work's overarching objective is to provide the groundwork for an unbreakable testing environment. By utilizing blockchain technology, "Crypto Proctor"aimed to enhance the credibility and safety of online exams. Distributed and guaranteed immutability is the platform's primary goal in prevented fraudulent behavior, protected user identities, and preserved the integrity of examination data. The "Crypto Proctor"solution incorporates blockchain protocols for the following purposes: a) Questioned delivery b) answered submission c) User identity verification. Smart contracts which are automated and confirm certain aspects of the inspection process as well as ensure that all records are securely and publicly record on the blockchain. An auditable and immutable recorded of every test session is intended to produce by the used methodologies. When it has tested in online platforms, Crypto Proctor is a huge leap forward. This initiative leverages blockchain technology to be addressed prevalent issues of data security and cheated, establishing a sensed of confidence and reliability in the online assessment procedure. As the educational system adapts to digital transformation, "Crypto Proctor"served as a beacon, showed how blockchain technology may fortify the foundations of online learning process and evaluations. © 202

关键词： Blockchain

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Enhancing Supply Chain Management Efficiency through 4PL Integration: Leveraging Recent Technological Advancement 5

Enhancing Supply Chain Management Efficiency through 4PL Int...

引用

5th IEEE International Conference for Emerging Technology, INCET 2024

作者： Beevi, L. Sherin Joe Prathap, P.M. Dani, W. Vinil Shweatha, B.M. Department of Computer Science and Engineering R.M.D. Engineering College Kavaraipettai India Department of Computer Science and Engineering R.M.D. Engineering College Kavaraipettai India Department of EEE St. Peter's College of Engineering & Technology Avadi India Dept. of Computer Science and Engg. R.M.D. Engineering College Kavaraipettai India

ISBN: (纸本)9798350361155

This research study looks at how Fourth Party Logistics (4PL) and supply chain management (SCM) work together to improve operational efficiency and effectiveness. It looks into the integration of recent technological advances to improve 4PL capabilities within SCM systems. The paper investigates the role of new technologies such as IoT, AI, and blockchain in revolutionizing existing supply chain paradigms through a comprehensive literature review and case study analysis. Insights are presented into the obstacles, opportunities, and solutions for successfully integrating 4PLs through technology. Finally, this study contributes to a better understanding of how organizations can use technology to alter supply chain operations and gain a competitive advantage in today's changing business climate. © 2024 IEEE.

关键词： Supply chain management

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Comparative Study on Extractive Summarization Using Sentence Ranking Algorithm and Text Ranking Algorithm

Comparative Study on Extractive Summarization Using Sentence...

引用

2023 International Conference on Power, Instrumentation, Control and Computing, PICC 2023

作者： Majeed, Mansoora Kala, M.T. Government Engineering College Dept. of Computer Science and Engineering Thrissur India

ISBN: (纸本)9798350334463

It is possible to create an accurate and succinct summary using a method called automatic text summarising. Before creating the necessary summary sentences, the machine learning algorithms may be trained to understand documents and recognise the portions that transmit crucial facts and information. Abstractive text summa- rization and Extractive text summarization are its two methods. An extractive text summarization refers to the process of removing significant text from a text document or source manuscript. Deep learning techniques are used to train an abstractive text summarizer, which then generates new phrases and keywords based on the content of the original text. The process of acquiring and assimilation of the knowledge from numerous sources takes time. Automatic text summary is used to speed up the process of finding and consuming pertinent information. An extractive text summarising technique chooses crucial phrases, sentences, and other parts of the original text and concatenates them into a compressed form. The extractive text summarization produces grammatically correct sentences. The project is to develop a model that demonstrates extractive text summarization using sentence ranking and text rank algorithm. It shows that the text rank algorithm does a remarkable performance to extractive text summarization. Using a sentence ranking algorithm, extractive summaries are created that rate sentences according to their weights. In order to create a high-quality summary of the input document and store the summary as audio, the input document's highly scored sentences are extracted. A non-supervised, extractive text summarising method is called TextRank. While calculating the value of words and phrases in a document, the TextRank algorithm looks at how they relate to one another. According on how important the words are in each phrase, it then assigns a score to each one. The summary is formed using the algorithm's choice of the most crucial phrases. © 2023 IE

关键词： Deep learning

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Suicidal Ideation Prediction Using Machine Learning

Suicidal Ideation Prediction Using Machine Learning

引用

2023 International Conference on Circuit Power and Computing Technologies, ICCPCT 2023

作者： Benny, Anson Aarsha, V.S. Subair, Ameen Anu Nair, A. Thomas, Shiney Amal Jyothi College of Engineering Dept of Computer Science & Engineering Kanjirappally India

ISBN: (纸本)9798350333244

Suicide has become a leading factor in death globally. The rate of suicides is sharply increasing with every passing year. It is important to note that suicidal ideation is a complex issue that cannot be solely attributed to a single factor or mental disorder. According to reports, the primary components that go into suicide ideation are depression, anxiety, high levels of stress, unsatisfactory relationships, sleep disturbances, and physical or mental impairments. Therefore, it is essential to consider a holistic approach that considers multiple factors when predicting suicidal ideation. Our proposed work uses machine learning techniques to foresee suicide ideation utilizing a sizable example of review information. After collecting the data using a labelled dataset, we preprocessed and trained it on various machine learning models such as Random Forest (RF), Logistic Regression (LR), Support Vector Machines (SVM), and Decision Tree (DT). The results showed that among the calculated models LR gives the best result with 76% accuracy, followed by SVM (75%), MLP (74%), RF (74%), DT (74%). The proposed framework is vital to the clinical business and thus the well-being of our society. © 2023 IEEE.

关键词： Decision trees

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VAR: An Efficient Silent Video to Speech System with Subtitle Generation using Visual Audio Recall 5

VAR: An Efficient Silent Video to Speech System with Subtitl...

引用

5th International Conference on Inventive Research in Computing Applications, ICIRCA 2023

作者： Shanmugam, Diya Dhandapani Syed, Safiya Fathima Dinesh, Sahana Chitrakala, S. College of Engineering Guindy Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350321425

In this paper, a method to generate speech from a muted video is proposed. Recent advances in computer vision and deep learning have allowed the development of lip-reading technology that can recognize and interpret lip movements in videos. However, one of the main challenges in visual-to-speech synthesis is distinguishing between homophenes, or sets of words that look identical on a person's lips but contain different sounds. To address this challenge, the proposed model utilizes a speech generation framework that uses an external memory called Visual Audio Recall (VA-Recall) to generate speech from silent video. The VA-Recall system allows the system to effectively synthesize speech from a speaker by recalling the most relevant auditory information that matches the visual input context. The proposed method further generates subtitles for the reconstructed audio. Overall, this process allows for a more natural and contextually appropriate speech synthesis system. © 2023 IEEE.

关键词： Speech synthesis

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