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9th International Conference on science, Technology, engineering and Mathematics, ICONSTEM 2024

作者： Aancy, H. Mickle Kodgire, Shilpa Prashant Mohitha, MaddulaRatna Manimegalai, V. Vijay, G. Dhotre, Sunita Panimalar Engineering College Department of Master of Business Administration Tamil Nadu Chennai600123 India Maharashtra Institute of Technology Aurangabad Department of Electronics And Telecommunication Engineering Maharashtra India Aditya Institute of Technology And Management Department of Computer Science And Engineering Andhra Pradesh Tekkali India Sri Krishna College of Technology Department of Electrical And Electronics Engineering Tamil Nadu Coimbatore641042 India Department of English Tamil Nadu Dindigul624622 India College of Engineering Department of Computer Engineering Maharashtra Pune India

ISBN: (纸本)9798350365092

IoT detector data can be covered and authenticated using blockchain armature to avoid data duplication. It also enables secure device data transfer. IoT can handle scalability and trust challenges with blockchain, keeping data private and secure. Blockchain technology improves authentication, fraud resistance, and decentralized data security. It can polarize device authentication and communication, barring a central authority. The processing power demanded for blockchain mining and the vulnerability of present blockchains to mining monopolization are obstacles. Hyundai has patronized IoT security blockchain startups. Blockchain technology could secure IoT networks and sensitive data. Blockchain and IoT give a strong answer to linked device security issues. Blockchain's decentralized and inflexible tally can secure IoT bias and their data, according to this abstract. Blockchain technology allows secure, peer- to- peer connectivity and data sharing, guarding IoT bias from manipulation and unauthorised access. Blockchain's cryptographic algorithms guarantee data integrity, while smart contracts automate device relations to misbehave with security rules. Blockchain's practical counteraccusations in IoT security could alter how we guard our decreasingly linked world, as this exploration shows. © 2024 IEEE.

关键词： Blockchain

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The Implementation of TOGAF for Enterprise System Planning on XYZ Campus

The Implementation of TOGAF for Enterprise System Planning o...

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2023 International Conference on Networking, Electrical engineering, computer science, and Technology, IConNECT 2023

作者： Sirait, Tamsir Hasudungan Lumban Gaol, Ford Supangkat, Suhono Harso Ranti, Benny Bina Nusantara University Binus Graduate Program Computer Science Jakarta Indonesia Bina Nusantara University Computer Science Department Jakarta Indonesia Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia Universitas Indonesia Computer Science Department Jakarta Indonesia

ISBN: (纸本)9798350331172

Universities can employ information technology as one means of achieving their goals and objectives. Universities can get advantages from information technology, such as effective resource management and information management for decision-making. However, don't forget that the campus must consider what technology is appropriate to assist them achieve their goals, particularly in the current industrial era 4.0 where technology is available with many different choices. The campus requires an enterprise architecture in order to design, manage, and coordinate information technology infrastructure, applications, and processes strategically and thoroughly. The adoption of enterprise information system architecture (EA) is also intended to improve the quality of services provided to internal and external stakeholders. In this case, Enterprise Architecture can help an organization to match its information technology resources with business processes and strategies to achieve their goals. This research was conducted using TOGAF ADM, also known as the Open Group Architecture Framework Architecture Development Method. This method offers best practices for creating enterprise architecture and emphasizes several steps that include creating an architectural vision, information systems, business architecture modeling to help XYZ campus manage all their information technology. © 2023 IEEE.

关键词： Information management

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CUET-NLP@TamilNLP-ACL2022: Multi-Class Textual Emotion Detection from Social Media using Transformers 2

CUET-NLP@TamilNLP-ACL2022: Multi-Class Textual Emotion Detec...

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2nd Workshop on Speech and Language Technologies for Dravidian Languages, Proceedings of the Workshop, DravidianLangTech 2022

作者： Mustakim, Nasehatul Rabu, Rabeya Akter Mursalin, Golam Sarwar Md. Hossain, Eftekhar Sharif, Omar Hoque, Mohammed Moshiul Department of Computer Science and Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh Department of Electronics and Telecommunication Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh

ISBN: (纸本)9781955917346

Recently, emotion analysis has gained increased attention by NLP researchers due to its various applications in opinion mining, e-commerce, comprehensive search, healthcare, personalized recommendations and online education. Developing an intelligent emotion analysis model is challenging in resource-constrained languages like Tamil. Therefore a shared task is organized to identify the underlying emotion of a given comment expressed in the Tamil language. The paper presents our approach to classifying the textual emotion in Tamil into 11 classes: ambiguous, anger, anticipation, disgust, fear, joy, love, neutral, sadness, surprise and trust. We investigated various machine learning (LR, DT, MNB, SVM), deep learning (CNN, LSTM, BiLSTM) and transformer-based models (Multilingual-BERT, XLM-R). Results reveal that the XLM-R model outdoes all other models by acquiring the highest macro f1-score (0.33). © 2022 Association for Computational Linguistics.

关键词： Sentiment analysis

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CUET-NLP@DravidianLangTech-ACL2022: Exploiting Textual Features to Classify Sentiment of Multimodal Movie Reviews 2

CUET-NLP@DravidianLangTech-ACL2022: Exploiting Textual Featu...

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2nd Workshop on Speech and Language Technologies for Dravidian Languages, Proceedings of the Workshop, DravidianLangTech 2022

作者： Mustakim, Nasehatul Jannat, Nusratul Hasan, Md. Maruf Hossain, Eftekhar Sharif, Omar Hoque, Mohammed Moshiul Department of Computer Science and Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh Department of Electronics and Telecommunication Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh

ISBN: (纸本)9781955917346

With the proliferation of internet usage, a massive growth of consumer-generated content on social media has been witnessed in recent years that provide people's opinions on diverse issues. Through social media, users can convey their emotions and thoughts in distinctive forms such as text, image, audio, video, and emoji, which leads to the advancement of the multimodality of the content users on social networking sites. This paper presents a technique for classifying multimodal sentiment using the text modality into five categories: highly positive, positive, neutral, negative, and highly negative. A shared task was organized to develop models that can identify the sentiments expressed by the videos of movie reviewers in both Malayalam and Tamil languages. This work applied several machine learning (LR, DT, MNB, SVM) and deep learning (BiLSTM, CNN+BiLSTM) techniques to accomplish the task. Results demonstrate that the proposed model with the decision tree (DT) outperformed the other methods and won the competition by acquiring the highest macro f1-score of 0.24. © 2022 Association for Computational Linguistics.

关键词： Decision trees

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Hybrid Encryption Based on Fernet and Rivest Shamir Adleman (RSA)

Hybrid Encryption Based on Fernet and Rivest Shamir Adleman ...

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2023 International Seminar on Application for Technology of Information and Communication, iSemantic 2023

作者： Hisbullah, Muhammad Dafi Sari, Christy Atika Rachmawanto, Eko Hari Handoko, Lekso Budi Umam, Chaerul Isinkaye, Folasade University of Dian Nuswantoro Study Program in Informatics Engineering Semarang Indonesia Ekiti State University Department of Computer Science Ekiti Nigeria

ISBN: (纸本)9798350339215

RSA is an asymmetric encryption algorithm that uses two different keys, a public key to encrypt the plain text and a private key to decrypt the cipher text. Fernet is a symmetric encryption algorithm that uses a single key to encrypt and decrypt information. This study uses Fernet and RSA which is the combination of symmetric and asymmetric encryption called hybrid encryption. In addition, the cipher text will be hidden inside an image using Stepic. Hybrid Encryption uses asymmetric encryption to encrypt the symmetric encryption secret key, it will secure the symmetric encryption. The result of this study is the lowest error that we got as the MSE is 0.00% and is inversely proportional with the Peak Signal to Noise Ratio (PSNR) and Avalanche (AVA) with 79.00% and 42.34% in order. Inversely proportional to the length of the text that is hidden in the image, the longest text that is hidden, the more changes that we get in the image with the highest Unified Average Changing Intensity (UACI) and Number of Pixels Change Rate (NPCR) with the biggest image size with 46.48% for UACI and 99.86% for the NPCR. © 2023 IEEE.

关键词： Signal to noise ratio

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Encoder-Decoder Based LSTM Model to Advance User QoE in 360-Degree Video

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computers, Materials & Continua 2022年第5期71卷 2617-2631页

作者： Muhammad Usman Younus Rabia Shafi Ammar Rafiq Muhammad Rizwan Anjum Sharjeel Afridi Abdul Aleem Jamali Zulfiqar Ali Arain Ecole Doctorale Mathematiques InformatiqueTelecommunicationde ToulouseUniversity Paul SabatierToulouse31330France School of Electronics and Information Northwestern Polytechnical UniversityXi’an710129China Department of Computer Science NFC Institute of Engineering and Fertilizer ResearchFaisalabad38000Pakistan Department of Electronic Engineering The Islamia University of BahawalpurBahawalpur63100Pakistan Department of Electrical Engineering Sukkur IBA UniversitySukkur65200Pakistan Department of Electronic Engineering Quaid-e-Awam University of EngineeringScience and Technology(QUEST)Nawabshah67450Pakistan Department of Telecommunication Engineering MUETJamshoro76060Pakistan

The development of multimedia content has resulted in a massiveincrease in network traffic for video streaming. It demands such types ofsolutions that can be addressed to obtain the user’s Quality-of-Experience(QoE). 360-degree videos have already taken up the user’s behavior by ***, the users only focus on the part of 360-degree videos, known as aviewport. Despite the immense hype, 360-degree videos convey a loathsomeside effect about viewport prediction, making viewers feel uncomfortablebecause user viewport needs to be pre-fetched in advance. Ideally, we canminimize the bandwidth consumption if we know what the user motionin advance. Looking into the problem definition, we propose an EncoderDecoder based Long-Short Term Memory (LSTM) model to more accuratelycapture the non-linear relationship between past and future viewport positions. This model takes the transforming data instead of taking the direct inputto predict the future user movement. Then, this prediction model is combinedwith a rate adaptation approach that assigns the bitrates to various tiles for360-degree video frames under a given network capacity. Hence, our proposedwork aims to facilitate improved system performance when QoE parametersare jointly optimized. Some experiments were carried out and compared withexisting work to prove the performance of the proposed model. Last but notleast, the experiments implementation of our proposed work provides highuser’s QoE than its competitors.

关键词： Encoder-decoder based lSTM 360-degree video streaming LSTM QoE viewport prediction

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COMBATANT@TamilNLP-ACL2022: Fine-grained Categorization of Abusive Comments using Logistic Regression 2

COMBATANT@TamilNLP-ACL2022: Fine-grained Categorization of A...

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2nd Workshop on Speech and Language Technologies for Dravidian Languages, Proceedings of the Workshop, DravidianLangTech 2022

作者： Hossain, Alamgir Bishal, Mahathir Mohammad Hossain, Eftekhar Sharif, Omar Hoque, Mohammed Moshiul Department of Computer Science and Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh Department of Electronics and Telecommunication Engineering Chittagong University of Engineering & Technology Chattogram4349 Bangladesh

ISBN: (纸本)9781955917346

With the widespread usage of social media and effortless internet access, millions of posts and comments are generated every minute. Unfortunately, with this substantial rise, the usage of abusive language has increased significantly in these mediums. This proliferation leads to many hazards such as cyber-bullying, vulgarity, online harassment and abuse. Therefore, it becomes a crucial issue to detect and mitigate the usage of abusive language. This work presents our system developed as part of the shared task to detect the abusive language in Tamil. We employed three machine learning (LR, DT, SVM), two deep learning (CNN+BiLSTM, CNN+BiLSTM with FastText) and a transformer-based model (Indic-BERT). The experimental results show that Logistic regression (LR) and CNN+BiLSTM models outperformed the others. Both Logistic Regression (LR) and CNN+BiLSTM with FastText achieved the weighted F1-score of 0.39. However, LR obtained a higher recall value (0.44) than CNN+BiLSTM (0.36). This leads us to stand the 2nd rank in the shared task competition. © 2022 Association for Computational Linguistics.

关键词： Deep learning

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GAMe-BiLSTM: a novel modified metaheuristic deep learning technique for non-ST-segment elevation myocardial infarction classification

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International Journal of Information Technology (Singapore) 2025年第2期17卷 1063-1078页

作者： Patil, Sachin Sambhaji Mohite-Patil, Tanajirao Bapuso Kalipindi, Murali Sarvani, Chalamalasetty Ramesh Babu, P. Maheshwari, Shikha Department of Electronics and Communication Engineering School of Engineering and Sciences MIT-ADT University Loni Kalbhor Maharashtra Pune India Department of Electronics and Telecommunication Engineering D. Y. Patil College of Engineering and Technology Maharashtra Kasaba Bawada Kolhapur India Department of Artificial Intelligence and Machine Learning Vijaya Institute of Technology for Women (Affiliated to JNTUK) Andhra Pradesh Enikepadu India Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Department of Computer Science College of Engineering and Technology Wollega University Oromia Region Nekemte Ethiopia Centre for Distance & amp Online Education Manipal University Rajasthan Jaipur India

Outdated approaches encounter challenges in discerning subtle electrocardiographic changes in real-time associated with Non-ST-Segment Elevation Myocardial Infarction (NSTEMI), leading to suboptimal outcomes, characterized by low accuracy, prolonged processing times, and slow convergence speeds. To address these issues, the introduced framework integrates a Graph Attention Meerkat based-Bidirectional Long Short Term Memory (GAMe-BiLSTM) to overcome interpretability limitations in traditional approaches, providing insights into critical clinical variables for more informed NSTEMI classification. GAMe-BiLSTM adapts to missing values, further enhancing model robustness. The effectiveness of the newly introduced NSTEMI classification approach is substantiated through an ablation experiment, where variations in loss functions, learning rates, and optimizers are systematically explored. This experimentation confirmed the superiority of the proposed classification method. This research underscores the integral role played by real-time electrocardiographic signal image data in enhancing the accuracy (99.99%) and efficacy of the introduced methodology, thereby contributing significantly to the advancement of NSTEMI classification techniques in the realm of cardiovascular research and diagnosis. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Cardiovascular diagnostics Deep learning Electro cardio gram GAMe-BiLSTM Myocardial infarction

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An Efficient Inter-Cluster Wireless Sensor Network Communication by using Priority Queues and Reliability Models

An Efficient Inter-Cluster Wireless Sensor Network Communica...

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2023 IEEE International Conference on Integrated Circuits and Communication Systems, ICICACS 2023

作者： Devi, Renuka Patel, Suresh Shivaprasad Yadav, S.G. Shivakanth, Gandla Divya, G. H. K. E. Society's S. L. N. College of Engineering Department of Computer Science & Engineering Raichur India Ramaiah Institute of Technology Department of Electronics and Telecommunication Engineering Bangalore India K L University Vadeeshwaram Department of Computer Science & Engineering Vijayawada India Nitte Meenakshi Institute of Technology Department of Electronics and Communication Engineering Bengaluru India

ISBN: (纸本)9798350398465

Even though Electromagnetic and Radio Interference, Reliability, Cyber Security, and Resource Depletion are still concerns with Wireless Sensor Networks (WSNs), even though WSNs have become increasingly widespread and are used in a wide variety of contexts. It is possible to detect and transmit a wide variety of data using a wide variety of sensors, including electric sensors, magnetic field sensors, infrared sensors, laser sensors, navigation sensors, and many others. The requirement for increased spatial and temporal precision in all applications has led to a decrease in the price of sensors as well as a reduction in their size and weight, respectively. Loss of packets and interference are extremely common in the real world because of the complexity and noise present in that environment. These sensors are extremely important for sensing and reporting data on a regular basis, in response to specific inquiries, or based on events that have occurred. In this investigation, the information that has been gathered by the leader nodes needs to be transmitted to the target node in the most effective manner possible through multiple hops. With the assistance of a number of different leader nodes located in their own distinct clusters, the data is moved to its ultimate location. Utilizing the appropriate strategy of data acknowledgments and queue thresholds is required in order to both ensure the data's integrity and reduce the amount of unneeded management overhead. Congestion limitations that are determined by wait levels contribute to helping assure dependability. © 2023 IEEE.

关键词： Radio interference

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Design of An IoT based Smart Plant Monitoring System 10

Design of An IoT based Smart Plant Monitoring System

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10th International Conference on Emerging Trends in engineering and Technology - Signal and Information Processing, ICETET-SIP-22 2022

作者： Rane, Apeksha Vidhale, Bhushan Kale, Priyanka Hemant Khekare, Ganesh G H Raisoni College of Engineering Electronics and Telecommunication Department Nagpur India G H Raisoni Institute of Engineering and Technology Electronics and Telecommunication Department Nagpur India Parul Institute of Technology Computer Science and Engineering Department Gujarat India

ISBN: (纸本)9781665467414

In IoT plant monitoring system we can monitor and control with the help of IoT concepts. The gasses produced by the plant in Day time and nighttime will be monitored on IoT cloud. And according to the moisture of the soil the water pump supply to the plant will be controlled. If moisture is seen below the certain threshold value, then the pump will get turned on and when moisture reaches above the threshold level then the water pump will be turned off by the controller in the system. The Temperature and humidity will be sensed by smart sensors digitally. The hazardous gas will be sensed by the other sensor at that place. The controller which is integrated in the system will send all the monitored parameter and different gasses data on IoT Cloud with the help of Wi-Fi and IoT system. Other circuitry is used to control the relay and to provide power supply to the system. On the IoT cloud the data will be received on the google firebase Real-time database. From that it will be transferred to the AWS server and all the data will be visualized by different gauges and past data will be plotted. © 2022 IEEE.

关键词： Temperature sensors Temperature measurement Cloud computing Gases Moisture Crops Humidity

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