Article
Energy & Fuels
Zhanzhou Wang, Lihua Cao, Heyong Si
Summary: This paper investigates the optimization of TES tank operation strategy using an improved genetic algorithm and characteristic day method, which enhances local search ability and calculation speed to ensure thermal energy supply to the maximum extent.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Computer Science, Artificial Intelligence
Bo Wang, Xuliang Yao, Yongqing Jiang, Chao Sun
Summary: The prediction of dust concentration in coal mining face is crucial for taking preventive measures and ensuring safety. The establishment of a BP neural network model has been proven to significantly improve the fitting ability and prediction accuracy.
Article
Thermodynamics
Samira Pourhedayat, Eric Hu, Lei Chen
Summary: This paper presents an improved validated semi-analytical gas turbine (GT) model that can simulate GT performance under various intake air conditions. The improved model overcomes three limitations of previous models by not assuming constant volumetric flow rate of intake air, constant output temperature of the combustion chamber (CC), and by evaluating the performance of the GT power plant directly from compressor intake air conditions. Deviations between model results and experimental data are less than 3%. Additionally, sensitivity analysis of both ambient conditions and GT characteristics is conducted as a sample application of the new model.
Article
Automation & Control Systems
Tathagata Mukherjee, Ashit Gupta, Anirudh Deodhar, Venkataramana Runkana
Summary: Continuous variations in coal quality have a significant impact on the operation of thermal power plants. This study proposes a two-stage solution for real-time soft sensing of coal type in order to improve the optimization of plant operation. By utilizing a semi-supervised cascaded clustering algorithm (SSCC) and online coal change detection algorithm, real-time classification of coal can be achieved using only live sensor data. The developed algorithms were tested and verified using synthetically generated industrial scale coal mill operation data. Real-time coal classification enables continuous optimum operation in terms of emissions, efficiency, and maintenance.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Engineering, Electrical & Electronic
Jagat Kishore Pattanaik, Mousumi Basu, Deba Prasad Dash
Summary: This article proposes an improved real-coded genetic algorithm (IRCGA) to solve reactive power dispatch problems, achieving optimal power transmission loss, improved voltage profile, and voltage stability through managing variables such as generator voltages, transformer taps, and reactive power compensators' output.
IETE JOURNAL OF RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Rahul, Bharat Choudhary
Summary: This article proposes a combined approach using NSGA III and DAG-SVM for recognition and classification of power quality disturbances. NSGA III algorithm effectively extracts features for detection, reduces the number of required features, and generates optimal solutions based on multi-objective optimization. DAG-SVM is used for training, generating multiple classifiers for improved classification accuracy and reduced computation time.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Chemistry, Analytical
Yu Gan, Hong Guo, Ziheng Zhou
Summary: This study proposes an improved algorithm based on genetic algorithm for better mapping of IP cores in 3D NoC. By introducing greedy algorithm and simulated annealing algorithm, the algorithm achieves better performance and power optimization, reducing power consumption by 42.2% in the case of a large number of cores.
Article
Engineering, Multidisciplinary
Abid Hossain Khan, Shakhawat Hossain, Mehedi Hasan, Md Shafiqul Islam, Md Mizanur Rahman, Jin-Hyuk Kim
Summary: In this work, an optimized thermodynamic model for the secondary coolant loop of a VVER-1200 reactor-based nuclear power plant is developed. The model accurately predicts the plant parameters and reveals the sensitivity of the plant efficiency to weather variation.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Energy & Fuels
Cheng Zhang, Maomao Zhang
Summary: A method using wavelet neural network and genetic algorithm for photovoltaic power generation forecast is proposed in this study, which shows improved accuracy and better performance compared to traditional methods in experimental simulations.
Article
Engineering, Electrical & Electronic
Yang Wang, Hanlu Yang, Xiaorong Xie, Xiaomei Yang, Guanrun Chen
Summary: In recent years, subsynchronous control interaction (SSCI) has become a frequent problem in renewable-connected power systems. This paper proposes a simple and effective method that utilizes intrinsic time-scale decomposition (ITD) to improve the accuracy and robustness of ITD for SSCI monitoring. The method incorporates the least-squares method and achieves a good balance between dynamic performance and estimation accuracy. Comprehensive comparative studies using synthetic signals, EMTP simulations, and field-recorded SSCI data demonstrate the usefulness of the method, and real-time simulation tests show its feasibility for real-time monitoring.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Ning Wang, Jia-Yang Li
Summary: This study proposes a thermal monitoring and temperature prediction method based on infrared thermocouples. A nine-channel whole-machine thermal monitoring system is designed to collect real-time temperature data. The improved linear regression algorithm can accurately predict the thermal characteristics of the CPU based on historical thermal distribution data and real-time temperature data. The experimental results show that the proposed method can accurately monitor temperature data and has a high coincidence with the actual values.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2022)
Article
Green & Sustainable Science & Technology
Bo Zhao, Xiaoxv Wang, Yongshao Xu, Bingzheng Liu, Shengxian Cao, Qi Zhao
Summary: This study aims to address fouling issues associated with air-cooled condensers in thermal power plants, with Ni-P coatings showing the best performance by reducing fouling resistance by 83.3%. These coatings have potential applications in thermal power plants to reduce CO2 emissions.
CLEAN TECHNOLOGIES AND ENVIRONMENTAL POLICY
(2021)
Article
Polymer Science
Yuyin Zhang, Ningjie Deng, Shiding Zhang, Pingping Liu, Changjing Chen, Ziheng Cui, Biqiang Chen, Tianwei Tan
Summary: In this study, a genetic algorithm with variable mutation probability was used to screen key molecular descriptors for predicting substitution factor. The improved genetic algorithm significantly enhanced the prediction accuracy. The selected descriptors mainly focused on describing the branching of the molecule, which is consistent with the importance of branching chains in the plasticization process.
Article
Engineering, Civil
Sumit Kumar, Neha Aswal, Subhamoy Sen
Summary: The rapid growth of urbanization worldwide requires reliable infrastructure and efficient support structures like utility bridges and tunnels. However, the design of such structures is often overlooked, resulting in inconsistent standards and specifications. Tensegrity structures, with their lightweight, sturdy, and deployable properties, offer a promising approach for utility bridge design. This study develops a form-finding approach using a Genetic Algorithm to design tensegrity modules that comply with tensegrity properties and meet structural and constructional requirements.
Article
Automation & Control Systems
Dehao Wu, Donghua Zhou, Maoyin Chen, Jifeng Zhu, Fei Yan, Shuiming Zheng, Entao Guo
Summary: This article discusses the importance of operation safety and efficiency in power plants, and introduces the concept of KPI-related nonstationary process monitoring to detect anomalies and assess their impact. The Output-relevant Common Trend Analysis (OCTA) method is proposed to model the relationship between input and output variables in thermal power plants, showing superior monitoring performance in detecting anomalies and determining their impact on thermal efficiency.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Engineering, Electrical & Electronic
S. Raghavendra, Dharmesh Dhabliya, Dipannita Mondal, Batyrkhan Omarov, Krishnan Sakthidasan Sankaran, Anishkumar Dhablia, Sushovan Chaudhury, Mohammad Shabaz
Summary: The Internet of Things (IoT) is a smart network that connects everything to the internet. Machine learning algorithms can help IoT devices learn and counter the growing network threats. This article presents a method for classifying intrusion data sets using feature selection and machine learning, with KNN and PCA showing better performance.
IET COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Sheng-li Xu, Tang Yeyao, Mohammad Shabaz
Summary: During the COVID-19 outbreak, information technology played a critical role in promoting global education. Online teaching had a positive impact on students' learning processes by providing rich learning resources and improving teachers' teaching techniques. The Fuzzy Analytical Hierarchy Process (Fuzzy AHP) method proved to be an efficient tool for selecting teaching approaches.
Article
Computer Science, Artificial Intelligence
Wei Jiang, Mengqi Li, Mohammad Shabaz, Ashutosh Sharma, Mohd Anul Haq
Summary: A voice signal change detection method based on convolutional neural networks is proposed in this study. By changing tones in voice libraries and recording voices at different levels, a classifier with an average accuracy of over 97% is determined. The experimental results demonstrate that the detection algorithm is effective and has good generalization ability.
ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
(2023)
Article
Computer Science, Cybernetics
Ashima Kukkar, Dinesh Gupta, Shehab Mohamed Beram, Mukesh Soni, Nikhil Kumar Singh, Ashutosh Sharma, Rahul Neware, Mohammad Shabaz, Ali Rizwan
Summary: Diabetic retinopathy (DR) is a major cause of blindness in middle-aged people, and an Internet of Medical Things (IoMT) enabled computer-aided diagnostic (CAD) system can provide remote monitoring and diagnosis. This study aims to classify and diagnose DR using the IoMT-enabled CAD system to prevent blindness. A novel DR classification (DRC) system is designed by combining deep learning models with optimization algorithms.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Computer Science, Information Systems
Ankur Gupta, Rajesh Gupta, Dhairya Jadav, Sudeep Tanwar, Neeraj Kumar, Mohammad Shabaz
Summary: Implementation of blockchain is gaining popularity in real-world applications, which requires integrating real-world data or third-party services to execute smart contracts. Decentralized Oracle Networks (DONs) enable the communication between on-chain code and off-chain infrastructure, but also expose the blockchain to security risks. Designing a Zero Trust Architecture and using Proxy Smart Contracts (PSC) can provide end-to-end security and prevent improper smart contract execution.
COMPUTER COMMUNICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
Pradyumna Kumar Tripathy, Mohammad Shabaz, Abdelhamid Zaidi, Ismail Keshta, Uttam Sharma, Mukesh Soni, Anurag Vijay Agrawal, Renato R. Maaliw III, D. P. Sharma
Summary: This paper presents an algorithm called Formal Rule Conflict Detection (FRCD) to improve Industrial Internet of Things (IIOT), device flexibility, and lower maintenance costs. The procedure of FRCD is explained thoroughly. Experimental results comparing FRCD with three existing standard IIIOT rule conflict detection techniques, namely SPIDER, UTEA, and IRIS, show that FRCD outperforms them.
COMPUTERS & ELECTRICAL ENGINEERING
(2023)
Article
Multidisciplinary Sciences
Praveen Kumar Kollu, Manoj L. Bangare, P. Venkata Hari Prasad, Pushpa M. Bangare, Kantilal Pitambar Rane, Jose Luis Arias-Gonzales, Sachin Lalar, Mohammad Shabaz
Summary: Food instability is associated with various health issues, and the use of IoT and machine learning can improve the predictability and precision of agriculture production. This article presents a precision agriculture fertilizer recommendation system based on IoT and multilinear regression, achieving an accuracy of 99.3%.
SN APPLIED SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Mukesh Soni, Mohammad Shabaz, Renato R. Maaliw, Ismail Keshta, Rasool Altaee, Sanju Das
Summary: The healthcare industry is adopting low-cost solutions that utilize non-invasive sleep monitoring system to improve patient care and provide healthcare decision-makers with real-time intelligence. The system records breathing and apnea using a pressure-sensitive sensor belt, transmits the data wirelessly to a mobile device, and can display real-time waveforms and upload data to a cloud platform. The system utilizes a piezoresistive sensor for accurate measurements.
INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS
(2023)
Article
Computer Science, Cybernetics
Mukesh Soni, Nikhil Kumar Singh, Pranjit Das, Mohammad Shabaz, Piyush Kumar Shukla, Partha Sarkar, Shweta Singh, Ismail Keshta, Ali Rizwan
Summary: Traditional classification algorithms have difficulty correctly categorizing hypertensive retinopathy (HR) lesions due to their lack of obvious characteristics. To address this issue, a regional IoT-enabled federated learning-based HR categorization approach (IoT-FHR) is proposed, incorporating global and local attributes. The local feature arterial and venous nicking (AVN) classification model is fused with the overall IoT-FHR classification model to enhance its effectiveness. An intersection detection algorithm is suggested for the AVN classification. Experimental results demonstrate that the suggested model outperforms the currently used methods when compared to a single-stage classification model.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Yasir Shah, Yumin Liu, Faiza Shah, Fadia Shah, Muhammad Islam Satti, Evans Asenso, Mohammad Shabaz, Azeem Irshad
Summary: This article examines the effects of the COVID-19 pandemic and gold prices on the stock market, focusing on the relationship between COVID-19 cases and stock market prices, as well as the impact on various commodity elements. The study utilizes financial models, machine learning algorithms, and a financial Gaussian mixture model for data analysis and comparison. The findings highlight the correlation between the virus, trading outcomes, and the importance of Karachi Stock Exchange-100 index data in preventing market crashes.
SCIENTIFIC AFRICAN
(2023)
Article
Multidisciplinary Sciences
Arun Sofia, Arun Malik, Mohammad Shabaz, Evans Asenso
Summary: Covid-19 has negatively impacted people worldwide in various ways, including health, employment, mental health, education, social isolation, economic inequality, and access to healthcare. Depression has emerged as a common illness that can lead to early death and other health conditions. Early detection and intervention are crucial in preventing the severity of depression and its associated risks. A survey using the Hamilton tool and input from psychiatrists was conducted, and machine learning techniques such as Decision Tree, KNN, and Naive Bayes were employed for analysis. The study concludes that KNN yielded better results in terms of accuracy, while decision tree performed better in detecting depression promptly. The suggestion is made to replace conventional methods of detecting depression with a machine learning-based model that involves asking people encouraging questions and obtaining regular feedback.
SCIENTIFIC AFRICAN
(2023)
Review
Mathematical & Computational Biology
Sushovan Chaudhury, Kartik Sau, Muhammad Attique Khan, Mohammad Shabaz
Summary: Histology is one of the most effective approaches for identifying breast cancer, which involves meticulous inspection of tissues under a microscope. The type of cancer cells and their malignant or benign nature can be determined by analyzing the type of tissue in the test. This study aims to automate the classification of breast cancer histology samples using a transfer learning technique that combines Gradient Color Activation Mapping, image coloring, and discriminative fine-tuning based on the Squeeze Net architecture.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2023)
Article
Computer Science, Artificial Intelligence
Surbhi Gupta, Mohammad Shabaz, Ankur Gupta, Abdullah Alqahtani, Shtwai Alsubai, Isaac Ofori
Summary: This study provides a comprehensive review and analysis of research on Internet of Medical Things (IoMT), focusing on its progress, research issues, trends, and future aspects. The study proposes Personal HealthCare of Things (PHoT) as a novel approach to bring personalization to healthcare systems and provide customized health services. Multiple studies were selected, classified, and compared to evaluate the need for enhancing PHoT systems. The study also discusses the proposed PHoT architecture and aims to address various research inquiries.
CAAI TRANSACTIONS ON INTELLIGENCE TECHNOLOGY
(2023)
Article
Engineering, Mechanical
Lili Zhang, Chuanbao Zhang, Peng Wang, Mohammad Shabaz, M. G. Skanda, C. Vijayalakshmi, Kakarla Hari Kishore
Summary: A three-dimensional simulation model was built to achieve the practical use of electromechanical program control by optimizing an automatic electromechanical control system based on PLC technology and using fuzzy control PID adjustment algorithm. The system has a higher control and management efficiency, which is 30% greater than that of the conventional system. The continuous operation efficiency enhancement of mechatronic manufacturing system can significantly lower investment costs and boost the financial gains of industrial organizations.
NONLINEAR ENGINEERING - MODELING AND APPLICATION
(2023)
Article
Automation & Control Systems
Altaf Hussain, Samee Ullah Khan, Noman Khan, Mohammad Shabaz, Sung Wook Baik
Summary: The integration of artificial intelligence (AI) into human activity recognition (HAR) in smart surveillance systems has the potential to revolutionize behavior monitoring, improving security and surveillance measures. A proposed AI-based behavior biometrics framework is introduced, utilizing a dynamic attention fusion unit (DAFU) and temporal-spatial fusion (TSF) network to effectively recognize human activity in surveillance systems.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
