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QoS aware task scheduling and congestion avoidance in fog enabled car parking systems

International Journal of Information Technology (Singapore) 2024年第8期16卷 4787-4795页

作者： Dhananjaya, M.K. Sharma, Kalpana Chaturvedi, Amit Kumar Department of Computer Science Bhagwant University Ajmer India Department of Computer Science and Application Bhagwant University Ajmer India Department of MCA Govt. Engineering College Rajasthan Ajmer India

When multiple cars compete for the same parking space, congestion arises. As it turns out, individuals waste an extensive amount of time looking for parking spaces, which increases fuel consumption and emissions. A few researchers proposed a fog-based smart car parking approach to address the drawbacks of cloud-based approaches. The researchers were unable to reach the global optimum for picking an empty parking space, and they neglected to consider quality of service (QoS) when a fog node can’t process a request. Therefore, to achieve such goals, we proposed QoS aware task scheduling and congestion avoidance in fog enabled car parking systems. This approach breaks down into three layers: the data layer, the fog layer, and the cloud layer. Data from car parking lots are gathered in the data layer using IoT devices. The relevant fog node will receive the gathered data in the fog layer. The task will be scheduled to a different suitable fog node using the multi-objective artificial flora optimization (MoAFO) algorithm. The available free parking spaces in each fog node are also estimated using the adaptive coati optimization algorithm (ACOA). The cloud server layer then stores and manages the data that the fog nodes have collected. The Java platform is used to implement the proposed methodology. The energy, time, searching time, and latency metrics are used to evaluate the effectiveness of the recommended approach. © Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Adaptive coati optimization algorithm (ACOA) Multi-objective artificial flora optimization (MoAFO) algorithm Quality of service (QoS)

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Experimental and Theoretical Assessment of a Diesel Engine Using Different Palm Oil Methyl Ester (POME) Blends at Different Compression Ratios

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Journal of The Institution of Engineers (India): Series C 2023年第5期104卷 1031-1046页

作者： Samanta, Abhishek Roy, Prokash C. Department of Automobile Engineering Ranaghat Govt. Polytechnic West Bengal Ranaghat Nadia741201 India Department of Mechanical Engineering Jadavpur University 188 Raja S.C. Mallick Rd Kolkata700032 India

In the variable compression ratio (VCR) diesel engine test setup, the palm oil methyl ester (biodiesel) was tested with diesel in varying quantities. The combustion and emission properties and the performance of diesel engines powered by biodiesel blends were examined and compared with conventional petroleum diesel. For combustion analysis, the engine’s cylinder pressure profiles, mass fraction burned, start, and end of combustion while operating on various biodiesel blends under varying loads were acquired at CR 16, 17, and 18. B5 showed a higher quality of combustion in the cylinder pressure profile at zero load than B10, and as the load increased, the cylinder pressures for both B5 and B10 were nearly equal. Furthermore, it was discovered that brake thermal efficiency rises when load increases, but brake-specific fuel consumption falls. In the load range of 0–25% at compression ratio 18, B5 requires less brake-specific fuel than B10 and diesel. Compared to B10 and diesel, B5 exhibited the highest brake thermal efficiency at high loads at a compression ratio of 17. The emission of HC and CO was reduced at higher CR for B10 and B20, but the NOx formation was higher at higher CR. © 2023, The Institution of Engineers (India).

关键词： Biodiesel

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Enhanced Approach for Facial Expression Recognition by Landmark Points in 2D and 3D Images 6th

Enhanced Approach for Facial Expression Recognition by Landm...

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6th International Conference on Smart Computing and Informatics, SCI 2024

作者： Hossain, Mohammad Alamgir Ahmad, Yasir Haseebuddin, Mohammad Khamruddin, Mohammad Masih, Raj Kumar Alam, Sk Safikul College of Engineering and Computer Science Department of Computer Science Jazan University Jazan Saudi Arabia Raja Ranjit Kishore Govt. Kishore Government Polytechnic Ramgarh India

ISBN: (纸本)9789819619801

The analysis of biometric data is essential in today’s highly connected digital environment. Image processing technology, such as the recognition of identities and facial expression identification, has gained a lot of attention from the academic and technology communities as a result of recent advancements in data collection methods using artificial intelligence and machine learning approaches. Many fields, from surveillance and safety to behavioral science and advertising, can benefit from emotion recognition from facial images. In this research, we propose a novel approach to detecting landmark points that are used as key points of interest (KPOI) on the human face. The suggested method extracts emotions from 2 and 3D images based on landmark points. We evaluated the impact of adding a feature selection approach that prioritizes minimizing redundancy and optimizing relevance on top of the feature extraction process. Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) are three popular classifiers used to uncover the labels. The outcomes validate the efficiency of the feature selection phase. The results suggest that improved performance can be achieved using landmark-based features extracted from 3D images. SVM is the best classifier, followed closely by RF. Using the CK + dataset, researchers found that combining characteristics from 2 and 3D photos yielded the best results. The proposed technique has a higher recognition rate than the current state-of-the-art standard. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Support vector machines

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9T SRAM Cell for Computation-In-Memory Architectures: Proposal & Investigation 5

9T SRAM Cell for Computation-In-Memory Architectures: Propos...

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5th International Conference on Devices for Integrated Circuit, DevIC 2023

作者： Gupta, Aman Kumar Joshi, Prashant Srivastava, Shobhit Panwar, Sourabh Shekhawat, Rajendra Singh Kilak, Abhishek Singh Yadav, Shivendra Joshi, Deepak Acharya, Abhishek S. V. National Institute of Technology Department of Electronics Engineering Surat India Govt. Polytechnic College Electronics and Communication Engineering Bikaner India Govt. Engineering College Electronics and Communication Engineering Bikaner India

ISBN: (纸本)9798350347265

By keeping data-intensive applications into consideration, we have investigated the robustness of digital logic circuit design for Computation In-Memory (CiM) using 9T SRAM cells at 22 nm technology nodes. PVT analysis (Process corner, Voltage, and Temperature) is also presented to check the robustness of the circuit. We have proposed a latch-based sense amplifier and voltage reference for 9T SRAM-based CiM architecture. The proposed design is good for demonstrating the logical operation with the memory. A comparison of 250 nm technology against 22 nm is also demonstrated in this work for 9T SRAM-based CiM. © 2023 IEEE.

关键词： Static random access storage

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Deep Learning-Based Road Sign Detection: The Ultimate Road Technology 1

Deep Learning-Based Road Sign Detection: The Ultimate Road T...

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1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Singh, Ajay Pal Rahi, Parvez Sahu, Bharti Basu, Nirmalya Fida, Hashmat Yadav, Vikash Chandigarh University Dept. of Computer Science & Engineering Punjab Mohali India Board of Technical Education Govt. Polytechnic College Bighapur Uttar Pradesh Unnao India

ISBN: (纸本)9798350367720

This work offers a methodical approach to detecting road signs using CNN, deep learning, and algorithms. As a one-unit regression problem, the object detection problem is defined as follows: probability classes and straight image pixels to bounding box coordinates. Many innovative ideas that are implemented to make our lives simpler and faster than they were in the past have been brought about by the rapid modernization. The Road Sign Detection Technique is one such technique. With this method, all it takes to make a forecast is a quick glance at the picture or sign. This is similar to image classification which uses Convolutional Neural Networks and makes use of AI-powered algorithms. The concept is described as the signs to be detected with the help of some rules that define the color, shape and the region where the signs are spotted. The paper describes YOLO (You Only Look Once) is a concept that is a modern approach to object detection. The object detection issue might be seen as a one-unit regression problem, with the solution representing the straight image pixels to the bounding box coordinates and class probabilities. Utilizing this method, you we can predict something just on a quick glance at the picture or sign. © 2024 IEEE.

关键词： Convolutional neural networks

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A New Proposed Data Security Model in Cloud Computing Environment

A New Proposed Data Security Model in Cloud Computing Enviro...

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2023 International Conference on computer, Electronics and Electrical engineering and their Applications, IC2E3 2023

作者： Banerjee, Pallab Prasad, Vishal Thakur, Kanika Banerjee, Probal Amity University Dept. of Computer Science Engineering Jharkhand Ranchi India Govt. Polytechnic Ranchi Dept. of Electronics and Communication Engineering Jharkhand India

ISBN: (纸本)9798350338003

Advancement in the environment of cloud computing has rapidly increases over the past years. In cloud computing protection of data utilizing centralized resources has arisen because of a growing number of businesses storing their data int the cloud helps them easily to access their data easily. The major issues faced by users nowadays, the safety and fetching of user cloud data is arisen rapidly. In this proposed algorithm, the user's data is encrypted using the advanced encryption standards algorithm, and the encrypted data is then performed with some xor operations in cypher block chaining mode using a secret key known only to the data owner to increase confidentiality and security level. If the user does not provide a secret key, the system can generate one on its own. © 2023 IEEE.

关键词： Cryptography

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Fusion Techniques in Neural Network Model for Image Captioning 4

Fusion Techniques in Neural Network Model for Image Captioni...

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4th International Conference on Information Management and Machine Intelligence, ICIMMI 2022

作者： Saxena, Varun Prakash Fredrick, Christabell Govt. Women Engineering College Rajasthan Ajmer India Computer Engineering Department Govt. Women Engineering College Ajmer Rajasthan India

ISBN: (纸本)9781450399937

Unmanned generation of the caption of any given image can be defined as image captioning. It is still one of the most important and researched topics as it is used in many tools like virtual assistants, chatbots, visual question-and-answering systems, etc. In the past, many researchers have improved the captioning quality of an image. Recurrent Neural Network using long short-term memory (LSTM) units has contributed a lot despite their disadvantages. LSTM cells are very multiplex and intrinsically progressive at different intervals of time therefore to mark the problem we have tried to solve it using a convolutional neural network considering the advantages of this network. Motivated by past research we modeled an image captioning model using a masked convolutions layer and attention mechanism. MSCOCO datasets are used as a dataset for developing a model used in captioning. © 2022 ACM.

关键词： Long short-term memory

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Achieving Seamless Semantic Interoperability and Enhancing Text Embedding in Healthcare IoT: A Deep Learning Approach with Survey

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SN computer Science 2024年第1期5卷 99页

作者： Purushothaman, Sony Shanmugam, G. Siva Nagarajan, Sureshkumar School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore India Department of Computer Science Govt. Model Engineering College Kerala Kochi India Department of Computer Science and Engineering School of Computing Kalasalingam Academy of Research and Education Tamil Nadu Krishnakovil India

Achieving semantic interoperability in healthcare is one of the significant challenges in the rapidly expanding healthcare sector. On the other hand, IoT in healthcare can provide patient-centric treatment mechanisms to help resolve these issues. When several healthcare organizations are generating heterogeneous medical information, semantic interoperability becomes essential to develop better treatment plans and better medical research. In this article, we discuss the applications of healthcare IoT, a comparative study of existing solution paradigms for achieving semantic interoperability and its enabling technologies. The comprehensive analysis of semantic interoperability has versatile dimensions to meet this, and it establishes deep learning-based directions. In continuing the background work, we proposed a new deep learning model called MedRelBERT with six embeddings to remove linguistic ambiguities in medical documents. The survey also examines the bibliographic evaluation of Web of Science articles discussing semantic interoperability solutions. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Deep learning Internet of medical things Privacy Semantic interoperability

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Design Analysis of Graphene Based Half Wave Dipole Antenna for Future Wireless Applications 1

Design Analysis of Graphene Based Half Wave Dipole Antenna f...

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1st IEEE International Conference on Contemporary Computing and Communications, InC4 2023

作者： Raj, Rajesh Kumar Sharma, Virendra Kumar Choudhary, Harji Joshi, Prashant Ajmer & Bhagwant University Ajmer Department of Electronics and Communication Engineering Govt.Engineering College Ajmer India Bhagwant University Ajmer Vice Chancellor Ajmer India Govt.Engineering College Ajmer Department of Computer Science & Engineering Ajmer India Govt. Polytechnic College Department of Electronics and Communication Engineering Bikaner India

ISBN: (纸本)9798350335774

In this communication, we show the comparisons among different conductors (patch) material properties for microstrip antenna then simulate a Graphene based half wave dipole antenna with two different substrate layers. The dipole antenna is designed for THz frequency ranges according to desired applications. The simulated results like return loss, directivity ampersand gain for the antenna at dissimilar values of chemical potential, length of dipole of Graphene. © 2023 IEEE.

关键词： Chemical potential

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Leveraging IoT and Digital Twins to Monitor Crop Growth and Health in Agriculture 10

Leveraging IoT and Digital Twins to Monitor Crop Growth and ...

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10th International Conference on Advanced Computing and Communication Systems, ICACCS 2024

作者： Benny, Brijit Shirley, C.P. Berin Jeba Jingle, I. Vidhya, K. Elakkiya, E. Karunya Institute of Technology and Sciences Department of Computer Science and Engineering Coimbatore India Govt. Arts College for Women Tamil Nadu Sivaganga India

ISBN: (数字)9798350384369

ISBN: (纸本)9798350384369

Digital twins and Internet of Things (IoT) technology have revolutionized modern farming by enabling creative techniques of monitoring and controlling crop growth and well-being. This article investigates the potential applications of Internet of Things (IoT) sensors and digital twin models for agriculture to provide farmers with analytical projections, assistance in making decisions, and continuous surveillance. Digital twin models are simulated representations of the real agricultural ecosystem that use data from multiple sources to correctly represent the dynamic interplay among crop nutritional status and conditions in the environment. The Internet of Things (IoT) and the use of digital twins have revolutionized the modern agricultural sector by enabling the monitoring and management of farms in order to regulate crop health and growth. The current research looks into the use of IoT sensors and digital twin technologies in agriculture. Farmers can obtain comprehensive data on agricultural growth conditions by utilizing Internet of Things (IoT) sensors. Sensors such as these collect data on solar exposure, pH, temperature, humidity, and moisture levels in the soil. Digital twin designs, computational depictions of the real agriculture atmosphere, are being developed using this information sources to replicate the dynamic interaction involving the physiology of crops and external factors. © 2024 IEEE.

关键词： Temperature sensors Temperature measurement Biological system modeling Crops Real-time systems Data models Digital twins Sensors Internet of Things Farming

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