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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Najarro, Lismer Andres Caceres Song, Iickho Dadlani, Aresh Kim, Kiseon School of Electrical Engineering and Computer Science GIST Gwangju Korea Republic of School of Electrical Engineering KAIST Daejeon Korea Republic of Chongqing University of Technology Liangjiang International College Chongqing China Nazarbayev University Department of Electrical and Computer Engineering Astana Kazakhstan

ISBN: (纸本)9781665459754

The standard differential evolution (DE) algorithm is a prominent population-based evolutionary algorithm that has shown competitive performance in addressing highly complicated problems such as target node localization in wireless sensor networks. The DE performance, however, can be compromised when the localization problem includes additional parameters, such as the transmit power and path-loss exponent in the received signal strength, to be estimated. In this paper, we propose an enhanced DE (EDE) and its variant called vEDE for addressing the deterioration of the DE when solving the localization problem. The proposed EDE and vEDE both incorporate two processes, namely random redirection and generation of midpoint individuals, to enhance their performance. In cases of high complexity, our numerical results reveal that the EDE and vEDE improve the localization accuracy to roughly 53% and 55%, respectively, as compared to the standard DE. The results also show the superiority of the vEDE as compared to the state-of-the-art algorithms based on semi-definite programming and second-order cone programming under various settings. © 2022 IEEE.

关键词： Evolutionary algorithms

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A Fast Learning-Based Unit Commitment Strategy with AC Optimal Power Flow for Large Grids with Direct Inclusion of Weather

A Fast Learning-Based Unit Commitment Strategy with AC Optim...

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IEEE Kansas Power and Energy Conference

作者： Farnaz Safdarian Joshua Peeples Dillon Richards Thomas J. Overbye Department of Electrical and Computer Engineering Texas A&M University College Station TX

ISBN: (数字)9798350372403

ISBN: (纸本)9798350372410

This paper proposes a strategy to solve a fast, learning-based and computationally feasible unit commitment (UC) with ac optimal power flow (OPF) and direct inclusion of weather measurements for large grids. Through the proposed approach, we estimate the on or off status of generators and their dispatch. One of the main challenges is that UC with ac OPF is computationally intractable for large grids over long periods. The other challenge is that the status of all units are related and not independent. We leverage multi-label machine learning classifiers to predict the status of each generator. The proposed strategy considers load and weather changes at different times of the year and the availability of the resources in addition to weather changes. The results show the UC is predicted with high classification performance metrics and feasible ac OPF results are achieved. The code for this work is publicly available at [1].

关键词： Measurement Training Radio frequency Machine learning Nearest neighbor methods Power grids Generators

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Edge computing Enabled Smart Warehouse Management System for Food Processing Industries 14

Edge Computing Enabled Smart Warehouse Management System for...

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14th International Conference on computing Communication and Networking Technologies, ICCCNT 2023

作者： Gowrishankar, V. Veena, P. Ponmurugan, P. Annapoorani, B. Vijayakumar, P. Siva Ramkumar, M. Velalar College of Engineering and Technology Department of Electronics and Communication Engineering Erode India K S R Institute for Engineering and Technology Department of Electrical and Electronics Engineering Tiruchengode India Meenakshi Academy of Higher Education and Research Department of Research Chennai600078 India Bannari Amman Institute of Technology Department of Electronics and Communication Engineering Sathyamangalam India Kongu Engineering College Department of Master of Computer Applications Tamil Nadu Perundurai638060 India Faculty of Engineering Karpagam Academy of Higher Education Department of Electrical and Electronics Engineering Coimbatore India

ISBN: (纸本)9798350335095

Food safety is a primary concern across all global platforms, and food storage is a crucial and essential part of management. This clarifies that food warehousing should be fully automated or has some management system. Good food storage plays a vital role in food security, which is affected by food waste and food loss. As a result, it is critical to identify and remove microbial contamination before it spreads to other items. To end that, we propose an edge computing-enabled intelligent warehouse system with an ESP32 microcontroller and micropython. The food commodities studied in the other papers were fish, dairy, fresh food products, crop-field cucumber, seafood, wine, and pre-packaged food. The various gas sensors are used to detect microbial growth, food decay, and shelf life. Humidity and temperature sensors are employed to monitor the warehouse environment, along with RFID technology to track food items. Multiple nodes accessible via Telegram and dashboard notifications will be put in the building to enable law enforcement collaboration. These nodes will exchange information on the building's structure. Compared to the traditional warehouse management system, the proposed edge computing-enabled IoT warehouse shelves reduce waste and contamination in fruit and vegetable chambers. Designs are experimented with different sets of fruits and vegetables. Continuous live monitoring and an alert system demonstrate the effectiveness of the proposed innovative framework compared with an existing management system. © 2023 IEEE.

关键词： Food storage

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Mandatory Automated Safety Kernel (MASK): Face Mask Recognition Using Deep Learning computer Vision 2

Mandatory Automated Safety Kernel (MASK): Face Mask Recognit...

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2nd International Conference on Artificial Intelligence and Smart Energy, ICAIS 2022

作者： Dinesh, G. Singh, Amarjeet Shinz, Nehar Sravanya, Mogalluru Venkata Agrawal, Gaurangi Srm Institute of Science and Technology School of Computing Department of Computational Intelligence Kattankulathur Chennai India New Horizon College of Engineering Department of Computer Science Engineering Bangalore India

ISBN: (纸本)9781665400527

This paper involves utilizing modules to create an efficient and accurate machine learning face mask detection model that can give an accuracy close to 100 percent and a value loss of less than 5%. This paper sees up to the fact that it is the local clusters that need to take care of themselves and this is what will eventually help the society on the larger scale as a whole and aims to aid the concerning authorities in keeping their crowd wearing masks at their respective premises. This is done by programming a system that can recognize the visuals from a camera at the entrance of such premises flagging offenders who do not wear a face mask and notifying authorities as it happens. This can be implemented in private organizations like educational institutions or company offices making it possible to combine it with a facial recognition model thereby notifying the offenders themselves via their cell phones by fetching their information from database resources that would be already existing in the case of these private organizations. © 2022 IEEE.

关键词： Face recognition

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Digital Signature Techniques for IoT Privacy and Trust Management

Digital Signature Techniques for IoT Privacy and Trust Manag...

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Emerging Technologies for Dependable Internet of Things (ICETI), International Conference on

作者： Qais Abd Al-Salam Mohammed Mohammed Joudah Zaiter Hamid Mohammed Farhan Department of Computer and Communication Engineering Electrical Engineering Technical College Middle Technical University Baghdad Iraq

ISBN: (数字)9798331533557

ISBN: (纸本)9798331533564

In this article, a live solution for data acquisition from sensors and its representation on a web interface is discussed with the help of a Raspberry Pi in which MQTT is used for communication the Flask as the framework. Particularly emphasized is the improvement of the efficiency and the time needed for generating Digital signature using the ECDSA algorithm which is traditionally slow and requires much resources to be applied for real time IoT applications. For this, the authors try the approach of parallel processing on the Raspberry Pi which becomes many times shorter in generation of the signatures without any loss of the data integrity. It involves input data including temperature, humidity, motion, distance, and light intensity, processes them and then sends the input data over a secure MQTT connection. They also showed that the FCMP algorithm incurs less computation time, and the speed attained is almost constant and stable when parallel processing is incorporated in the generation of some of the ECDSA algorithm’s signatures. As presented in the experimental results, the processing time is reduced in comparison with sequential processing, which emphasizes the possibility of parallelization. Altogether we can state that the usage of Raspberry Pi and Flask as the core of the system along with MQTT as a communication protocol provides the necessary level of security and reliability for monitoring the sensor data in the IoT system. They show that parallel processing can indeed help enhance the cryptographic operations making this approach beneficial for performance optimization across multiple IoT applications.

关键词： Temperature sensors Temperature distribution Protocols Humidity Sensor systems Real-time systems Sensors Internet of Things Monitoring Digital signatures

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A multi-objective grey wolf optimizer for energy planning problem in smart home using renewable energy systems

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Sustainable Operations and computers 2024年第1期5卷 88-101页

作者： Makhadmeh, Sharif Naser Al-Betar, Mohammed Azmi Al-Obeidat, Feras Alomari, Osama Ahmad Abasi, Ammar Kamal Tubishat, Mohammad Elgamal, Zenab Alomoush, Waleed Department of Data Science and Artificial Intelligence University of Petra Amman11196 Jordan College of Engineering and Information Technology Ajman University Ajman United Arab Emirates Department of Information Technology Al-Huson University College Al-Balqa Applied University P.O. Box 50 Al-Huson Irbid Jordan Department of Computer Science and Information Technology College of Engineering Abu Dhabi University Abu Dhabi United Arab Emirates College of Technological Innovation Zayed University Abu Dhabi United Arab Emirates School of Computing Skyline University College Sharjah United Arab Emirates School of Information Technology Skyline University College Sharjah P.O. Box 1797 United Arab Emirates Abu Dhabi United Arab Emirates

This paper presents the energy planning problem (EPP) as an optimization problem to find the optimal schedules to minimize energy consumption costs and demand and enhance users’ comfort levels. The grey wolf optimizer (GWO), One of the most powerful optimization methods, is adjusted and adapted to address EPP optimally and achieve its objectives efficiently. The GWO is adapted due to its high performance in addressing NP-complex hard problems like the EPP, where it contains efficient and dynamic parameters that enhance its exploration and exploitation capabilities, particularly for large search spaces. In addition, new energy and real-world resources based on solar renewable energy systems (RESs) are combined with the proposed GWO to enhance its performance and ensure the optimisation of EPP objectives. Furthermore, EPP is presented as a multi-objective planning problem to optimize all objectives simultaneously. To efficiently investigate the proposed method performance, the results obtained by the GWO with the RESs are compared in three stages: comparison with original methods without RESs, comparison with methods using RESs, and comparison with state-of-the-art. The obtained results proved the robust performance of the proposed method in handling EPP and optimizing its objectives. © 2024 The Author(s)

关键词： Multiobjective optimization

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Integration of ML Layer with GBC based Classifier for Better Recognition of Voice in Mobile 4

Integration of ML Layer with GBC based Classifier for Better...

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4th IEEE International Conference on Advance computing and Innovative Technologies in engineering, ICACITE 2024

作者： Aelgani, Vivekanand Kumar, Gaurav Al-Fatlawy, Ramy Riad Kumar, Yogendra Sharma, Deepti Angadi, Sanjeevkumar Cmr College of Engineering & Technology Department of Cse India Chitkara University Chitkara Centre for Research and Development Himachal Pradesh 174103 India The Islamic University Najaf Iraq Gla University Department of Electrical Engineering Mathura India Uttaranchal University Uttaranchal Institute of Management Department of Management Dehradun248007 India Nutan College of Engineering and Research Computer Science and Engineering Talegaon Dabhade Maharashtra Pune India

ISBN: (纸本)9798350360165

People can express their feelings through words and sentences in different languages during a speech. Spoken language frequently contains feelings including surprise, fear, indifference, contempt, fury, grief, and happiness. This essay explores the topic of identifying these feelings in speech. We performed an investigation to identify and categorize emotions present in speech by utilising machine learning methods, such as random forest, additional trees, gradient boosting, decision tree, and light gradient boosting classifiers. We were able to acquire informative findings by using the previously specified classifiers along with datasets. © 2024 IEEE.

关键词： Emotion Recognition

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Optimizing User Data Privacy and Confidentiality in Cloud Storage Systems Through Advanced Obfuscrypt Encryption Methods for Enhanced Security and Efficient Data Protection

Optimizing User Data Privacy and Confidentiality in Cloud St...

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2024 IEEE International Conference on Recent Advances in Science and engineering Technology, ICRASET 2024

作者： Ramesh, P.S. Sudha, I. Jagannathan, J. Pandiarajan, Rajkumar Ponmalar, A. Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Tamilnadu Chennai India Saveetha Institute of Medical and Technical Sciences Simats University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Department of Software and Systems Engineering Katpadi Vellore India Kalasalingam Academy Of Research and Education School of Computing Department of Information and Technology Krishnankoil Virudhunagar India R.M.K. Engineering College Tamilnadu Chennai India

ISBN: (纸本)9798350388602

With a steady increase in the adoption of cloud storage systems, the client's data are at risk of being leaked. There are several methods of encrypting data which are quite useful but they lack some of the features of today's sophisticated threats. The methodology used in this research propose an encryption framework known as Obfuscrypt to improve the issues of data privacy as well as confidentiality of data stored in cloud storage systems. Obfuscrypt uses conventional encryption strategies incorporated with obfuscation and post-quantum cryptographic algorithms to provide a complex security plan immune to classic and quantum approaches. Some of the proposed other innovations include the decentralised key management with multi-factor authentication and RBAC-ABE as the fine-grained access control techniques. These features make it possible for only the authorized personnel to be in a position to be in a position of decrypting and retrieving the stored data thereby minimizing the possibility of the data being accessed by unauthorized people. The work also considers the issue of performance efficiency of the cloud storage systems. Similar to other symmetric encryption programs, Obfuscrypt uses light encryption algorithms and brings in to play the hardware acceleration so that it may infuse lesser computational overhead in the process of encryption and decryption. As can be clearly seen from the results, the actual work proves that the proposed framework not only offers a higher level of security but does not affect the system performance to a great extent. Also, the study addresses the post-quantum cryptographic algorithm for making the system resistant to an attack that can be posed by quantum computing systems. With the help of these improved algorithms, Obfuscrypt guarantees the permanent data security in the world of constantly emerging cyber threats. © 2024 IEEE.

关键词： Data obfuscation

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On the Optimal Placement of Electric Vehicle Charging Stations

On the Optimal Placement of Electric Vehicle Charging Statio...

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2023 IEEE International Conference on Technology Management, Operations and Decisions, ICTMOD 2023

作者： Tiu, Johnny Ramharack, Shankar Hosein, Patrick The University of the West Indies Department of Mechanical and Manufacturing Engineering St. Augustine Trinidad and Tobago The University of the West Indies Department of Electrical and Computer Engineering St. Augustine Trinidad and Tobago The University of the West Indies Department of Computing and Information Technology St. Augustine Trinidad and Tobago

ISBN: (纸本)9798350313352

Increasing the adoption of Electric Vehicles (EV) is an integral part of many strategies to address climate change and air pollution. However, Electric Vehicle adoption rates are inhibited by several factors which reduces the confidence of potential buyers of electric vehicles, namely range anxiety and limited charging infrastructure. The latter concern can be addressed by carefully planning the placement of Electric Vehicle charging stations to sustainably meet long-term demand. We outline a methodology to optimally allocate Electric Vehicle Charging stations using a novel approach to demand estimation, by first transforming demand using a weighted neighbourhood average and applying a regularised regression. Using this approach the first two authors placed second in the Academic category of an International Shell competition which was created to obtain solutions to this problem. They were also provided with a grant to further study this approach and to develop a deployment strategy. © 2023 IEEE.

关键词： Electric vehicles

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Processing of food assisted by solar based equipment

Processing of food assisted by solar based equipment

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2024 International Conference on Sustainable computing and Integrated Communication in Changing Landscape of AI, ICSCAI 2024

作者： Nainwal, Ankita Bansode, Avinash Al-Fatlawy, Ramy Riad Badhoutiya, Arti Shrivastava, Anurag Singh, Navdeep Kumar, Rohit Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Basic Engineering Indira College of Engineering and Management Pune India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical Engineering GLA University Mathura India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Tamilnadu Chennai India Lovely Professional University Phagwara India School of Management Gautam Budha University Greater Noida India

ISBN: (纸本)9798350355338

The present research involved a theoretical examination of food processing, global patterns of cooking and solar-powered cooking techniques. Direct absorption, air heating, and a combination of direct and indirect drying by sun radiation are used as solar-powered food processing techniques. This method is one of the most often used processing technologies and is also one of the most easily available. In the traditional solar drying process, items are left in the sun. Depending on the type of food or substance, different temperatures and timeframes are used for solar drying and cooking. The efficiency of food processing and cooking systems is determined by the amount of solar energy that reaches the system and design criteria. The temperature of the heated air and surrounding environment determines how long drying and cooking will take. The performance of dryers and cooker boxes is significantly influenced by the temperature ranges, food's mass, and its constituent ingredients. © 2024 IEEE.

关键词： Solar dryers

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