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2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024

作者： Al Belushi, Yahya Yaqoob Obaid Jasmin Dennis, P. Deepa, S. Arulkumar, V. Kanchana, D. Ragini, Y.P. Military Technical College Department of Systems Engineering Oman Vi Institute of Technology Department of Electronics and Communication Engineering Tamil Nadu Chengalpattu India RMD Engineering College Department of Computer Science and Business Systems Tamil Nadu Kavarapettai India Sri Sivasubramaniya Nadar College of Engineering Kalavakkam Department of Information Technology Tamil Nadu Chennai India SRM Institute of Science and Technology Ramapuram Department of Computer Applications Tamil Nadu Chennai India SIMATS Department of Biosciences Saveetha School of Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350374100

Internet of Things (IoT) is rapidly developing technologies and the Internet of Things (IoT) is a network of physical items or effects embedded with computer software, detectors, and network connectivity. The Internet of Things also addresses the issue of centralizing physical bias management online. We are leveraging the Internet of Things (IoT) idea to construct a system that will automatically monitor all artificial processes and issue warnings or expert comments when necessary. nowadays, gas leakage is a serious concern in the house and as well as vigilance. If the gas sense is indeed low, it's because we've been too careless, intolerant, or both to look for it. If the gas position is raised, however, calamity may ensue. In this research, the crucial concept is introduced to prevent this catastrophe from occurring. In this study, we propose an alternate approach to this impending calamity and design a system with integrated sensors, controllers, and some IoT-assisted software. The suggested method, known as the Internet of Things based Industrial Safety System (IoTISS), is compared against the more established Industrial Safety System (ISS) to see how well it performs. In this system, we are monitoring the detection of gas leakages with various warning characteristics as well as other devices are used for monitoring various aspects like humidity and temperature using DHT22 sensor, MQ2 gas monitoring sensor, fire sensor and NodeMCU ESP8266 WiFi module. NodeMCU ESP8266, which doubles as a WiFi module, will receive data from all of these types of sensors. © 2024 IEEE.

关键词： Accident prevention

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Artificial Intelligence For Realtime Face Recognition Attendance Using College Classrooms and Buses

Artificial Intelligence For Realtime Face Recognition Attend...

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2024 International Conference on Electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Ahila, A. Hosanna Princye, P. Poonguzhali, A. Kavivendhan Deepa, M. Arthy, A. Saravanakumar, R. Sri Sairam College of Engineering Department of Electronics and Communication Engineering Anekal Bangalore India Francis Xavier Engineering College Department of Computer Science and Business Systems Tamil Nadu Tirunelveli India Iconix Software Solution Software Analyst Tamil Nadu Tirunelveli India

ISBN: (纸本)9798350378092

Teachers take attendance by having pupils sign in or check-in classes and transportation. Student absences often result from individual mistakes. This article examines a technology that records data from classroom photographs of every student's face. This research uses an Adaptive Boost Classifier, Random Forest (RF), and Deep Convolutional Neural networks (DCNNs). The model performs well on the DCNN model with 88 and 92% accuracy and on the ResNet50 pre-trained model with 97.21% accuracy. After detecting each student's face, they recorded their present status in an Excel document. It kept the best system implementation approach based on performance. © 2024 IEEE.

关键词： Convolutional neural networks

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TERMS: textual emotion recognition in multidimensional space

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Applied Intelligence 2023年第3期53卷 2673-2693页

作者： Ghafoor, Yusra Jinping, Shi Calderon, Fernando H. Huang, Yen-Hao Chen, Kuan-Ta Chen, Yi-Shin Social Networks and Human-Centered Computing Taiwan International Graduate Program Institute of Information Science Academia Sinica. Institute of Information Systems and Applications National Tsing Hua University Hsinchu City Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu City Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu City Taiwan

Microblogs generate a vast amount of data in which users express their emotions regarding almost all aspects of everyday life. Capturing affective content from these context-dependent and subjective texts is a challenging task. We propose an intelligent probabilistic model for textual emotion recognition in multidimensional space (TERMS) that captures the subjective emotional boundaries and contextual information embedded in a text for robust emotion recognition. It is implausible with discrete label assignment;therefore, the model employs a soft assignment by mapping varying emotional perceptions in a multidimensional space and generates them as distributions via the Gaussian mixture model (GMM). To strengthen emotion distributions, TERMS integrates a probabilistic emotion classifier that captures the contextual and linguistic information from texts. The integration of these aspects, the context-aware emotion classifier and the learned GMM parameters provide a complete coverage for accurate emotion recognition. The large-scale experimentation shows that compared to baseline and state-of-the-art models, TERMS achieved better performance in terms of distinguishability, prediction, and classification performance. In addition, TERMS provide insights on emotion classes, the annotation patterns, and the models application in different scenarios. © 2022, The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature.

关键词： Emotion Recognition

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Evaluating Optimistic Synchronization of Network Graphs in Mobile networks With MEC Support

Evaluating Optimistic Synchronization of Network Graphs in M...

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IEEE International Conference on Cloud Networking (CLOUDNET)

作者： Matthias Frei Reinhard German Anatoli Djanatliev Fraunhofer Institute for Integrated Circuits IIS Erlangen Germany Dept. of Computer Science Computer Networks and Communication Systems University of Erlangen-Nürnberg Germany

Future networks with well-developed Multi-Access Edge Computing (MEC) resources, where network nodes and distributed service instances can form a dense topology, face the challenge of distributing service data among many nodes. In particular, frequent data changes require an efficient update mechanism. System flexibility and user mobility, e.g, cellular hand-overs, or unpredictable service deployment or node changes, pose additional challenges. In this paper, a method is proposed and evaluated, how network graph-structured data can be distributed and synchronized between many nodes. The design considers especially the challenges of mobile networks with dynamic changes. At the example of a MEC scenario, the method is evaluated using a system-level simulation environment with fifth generation (5G) cellular communication, mobile as well as locally bound nodes, and dynamic service deployment changes. Network and computing resources are represented and shared using a graph. To gain deeper insight into the performance of our model, the time and bandwidth resources required to replicate graph updates to all clients in the 5G network are evaluated. Hereby, the impact of different background network traffic, of information-dependent graph update frequencies, and of the connectivity type can be shown. Finally, by implementing a practical example, the maintenance overhead for synchronizing the graph data to have a local information source is compared to the time required when querying remote information sources.

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Taking Class Imbalance Into Account in Open Set Recognition Evaluation

arXiv

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arXiv 2024年

作者： Komorniczak, Joanna Ksieniewicz, Pawel Department of Systems and Computer Networks Wroclaw University of Science and Technology Wyb. Wyspianskiego 27 Wroclaw50370 Poland

In recent years Deep Neural Network-based systems are not only increasing in popularity but also receive growing user trust. However, due to the closed-world assumption of such systems, they cannot recognize samples from unknown classes and often induce an incorrect label with high confidence. Presented work looks at the evaluation of methods for Open Set Recognition, focusing on the impact of class imbalance, especially in the dichotomy between known and unknown samples. As an outcome of problem analysis, we present a set of guidelines for evaluation of methods in this field. © 2024, CC BY-NC-SA.

关键词： Deep neural networks

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LoRaWAN and Biosensor-Assisted Smart City Framework to Mitigate the Effects of Lung Diseases

LoRaWAN and Biosensor-Assisted Smart City Framework to Mitig...

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2024 IEEE International Conference on Modeling, Simulation and Intelligent Computing, MoSICom 2024

作者： Abubeker, K.M. Roberts, Michaelraj Kingston Prajitha, C. Rinesh, S. Shafeena Karim, A. Jeevanandham, S. Department of Electronics and Communication Engineering Kerala India Sri Eshwar College of Engineering Centre for Advances in Signal Processing and Wireless Sensor Networks Department of Electronics and Communication Engineering Coimbatore India Karpagam Academy of Higher Education Centre for Interdisciplinary Research Department of Electronics and Communication Engineering Coimbatore India V.S.B College of Engineering Technical Campus Department of Computer Science and Engineering Coimbatore India Sri Ramakrishna Engineering College Department of Information Technology Coimbatore India

ISBN: (纸本)9798331533311

Urbanization and industrialization in cities present substantial obstacles to air quality, resulting in detrimental effects on public health, including respiratory health. This research introduces an Internet of Things (IoT) framework for a smart city environment using LoRaWAN and sensor networks. The framework utilizes the ESP32 LoRaWAN module to provide real-time monitoring of essential air quality metrics, such as carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, and humidity. Integrating biosensors enhances accuracy by identifying distinct biological indicators linked to respiratory well-being. The proposed work aims to use the framework in an urban setting within a global context, demonstrating its capacity to reduce the effects of lung disorders. The ESP32 LoRaWAN module enables effective communication within the sensor network up to 20 kilometers, guaranteeing a robust and adaptable solution for smart city applications. The developed framework provides a scalable and novel method for developing healthier and more sustainable cities, decreasing respiratory disorders as urban settings develop. © 2024 IEEE.

关键词： Lung cancer

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Energy-Efficient communication Protocols for IoT Devices 9

Energy-Efficient Communication Protocols for IoT Devices

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

作者： Rahamathunnisa, U. Vivekanand, Chettiyar Vani Chithras, T. Sreedevi, E. Kiran, Venneti Rajendiran, M. School of Computer Science Engineering And Information Systems Vellore Institute of Technology Tamil Nadu Vellore632014 India Rmk College of Engineering And Technology Department of Electronics And Communication Engineering Tamil Nadu Thiruvallur India Veltech Rangarajan Dr.Sagunthala R&d Institute of Science And Technology Department of Electrical And Electronics Engineering Chennai Tamil Nadu Avadi600062 India KoneruLakshmaiah Education Foundation Department of Computer Science And Engineering Andhra Pradesh Vaddeswaram India Andhra Pradesh Surampalem India Panimalar Engineering College Department of Computer Science And Engineering Tamil Nadu Chennai600123 India

ISBN: (纸本)9798350365092

The development and optimisation of energy-efficient communication protocols that are specifically adapted for Internet of Things (IoT) devices is the focus of this research. The proliferation of interoperable bias has given rise to the converse girding energy consumption, which has come a consummate concern in the contemporary period. The primary end of this bid is to probe innovative approaches and protocols with the capacity to reduce the energy consumption of Internet of Effects(IoT) connections. As a result, the bias will retain the capability to attain an extended functional lifetime while coincidently producing a lowered environmental footmark. The presented protocols aim to achieve a result that balances the utilisation of energy coffers with the conservation of dependable communication. A thorough examination of the presently employed protocols, coupled with the perpetration of sophisticated optimisation ways, will be the styles employed to achieve this thing. Theprovides a significant donation to the development and prosecution of communication protocols that effectively address the unique energy constraints encountered by Internet of effects(10T)- connected ecosystems. This contributes to the enhancement of effectiveness and sustainability in the world of networked bias, which is expanding at an accelerated rate. © 2024 IEEE.

关键词： Energy efficiency

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An Implementation of Naming Rule Checking Function and Its Applications to Java Programming Codes

An Implementation of Naming Rule Checking Function and Its A...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Wai, Khaing Hsu Funabiki, Nobuo Mentari, Mustika Aung, Soe Thandar Kyaw, Htoo Htoo Sandi Yamaguchi, Shingo Kao, Wen-Chung Graduate School of Science and Engineering Akita University Akita Japan Department of Information and Communication Systems Okayama University Okayama Japan Department of Computer and Information Science Tokyo University of Agriculture and Technology Tokyo Japan Graduate School of Sciences and Technology for Innovation Yamaguchi University Japan Department of Electrical Engineering National Taiwan Normal University Taipei Taiwan

ISBN: (纸本)9798331521165

Currently, a lot of universities are offering Java programming courses for teaching the first-step object-oriented programming language. For novice students, to master writing readable codes using proper names for variables, classes, and methods is crucial in Java programming, to improve understandability and maintainability. In this paper, we consider four naming rules to write a readable code and implement the naming rule checking function to check whether the given code follows them. For evaluations, we applied the proposal to 2, 908 source codes submitted in Java programming courses from students in Okayama University, Japan, Malang State Polytechnic, Indonesia, and Yamaguchi University, Japan. The results confirm the effectiveness of the proposal. © 2025 IEEE.

关键词： Java programming language

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Mining Railway Grievances on Twitter for Efficient E-Governance in India

Mining Railway Grievances on Twitter for Efficient E-Governa...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Agarwal, Swati Kumar, Ashrut Ganguly, Rijul Bits Pilani K K Birla Goa Campus Computational Linguistics and Social Networks Lab Department of Computer Science and Information Systems Goa India

ISBN: (纸本)9781665480451

Recently, Twitter has been used as a citizen-engaging platform by Indian Railway Ministry (IRM) for collecting civic issues. However, due to the manual inspection model, a large percentage of complaints are left unaddressed affecting the credibility of the citizen-sourcing mediums. The existing solutions are for English reports and unable to capture the diverse range of code-mixed languages used in the complaints. In this paper, we developed a multilingual cased version of BERT (mBERT) for automated identification of monolingual and multilingual (aka code- mixed) complaints. The proposed mBERT is a transformers- based model pre-trained on multilingual Wikipedia corpus. In addition to the grievances classification, we also employ a BERT multi-label classifier for labelling the tweets with the issues reported in the complaints. The proposed solution approach obtains an accuracy of 82% with the binary classifier and overall accuracy of 95% with the multi-label model. Additionally, a critical analysis is presented on the classified reports and a location-based analysis to visualise the velocity and veracity of complaints across India. © 2022 IEEE.

关键词： Classification (of information)

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Self-excitation of Terahertz Plasmons in Graphene FETs Enabled by Transit-time Negative Dynamic Conductance 2

Self-excitation of Terahertz Plasmons in Graphene FETs Enabl...

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2nd International Conference for Advancement in Technology, ICONAT 2023

作者： Ryzhii, Maxim Ryzhii, Victor Otsuji, Taiichi Mitin, Vladimir Shur, Michael S. University of Aizu Department of Computer Science and Engineering Aizu-Wakamatsu Japan Research Institute of Electrical Communication Tohoku University Sendai Japan University at Buffalo Department of Electrical Engineering SUNY BuffaloNY United States Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering TroyNY United States

ISBN: (纸本)9781665475174

The interband Zener-Klein interband tunneling in the field-effect transistors (FETs) with the graphene channels consisting of the reverse-biased p-i-n junctions enables the negative dynamic conductance associated with the electrons and hole propagation delays. This can lead to the self-excitation of plasmons in the gated p- and n-regions. For the submicrometer gate lengths, the frequency of these plasmons is in the terahertz (THz) range. The plasmon self-excitation in this regime can be used for the generation of THz radiation. © 2023 IEEE.

关键词： Plasmons

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