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Energy Technologies for Future Grids (ETFG), IEEE International Conference on

作者： Mohamed A. Hassan Ahmed A. Oransa Ahmed M. Elsallanty Deema R. Fekry Hatem H. Ibrahim Bishoy E. Sedhom Interdisciplinary Research Center for Renewable Energy and Power Systems (IRC-REPS) Research Institute King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Electrical Engineering Department Faculty of Engineering Damietta University Damietta Egypt Electrical Engineering Department Faculty of Engineering Mansoura University Mansoura Egypt

Recently, electric vehicles (EVs) demand has been intensely increased. Accordingly, more electrical vehicle charging stations (EVCSs) are essentially needed. The charging behavior of the EV user is affected by several issues. This paper proposes a multi-objective genetic algorithm (MOGA) optimization scheme for scheduling the charging behavior of the EV user in a smart campus. The problem is optimally formulated and designed to minimize the total traveling distance of the EV toward charging station (CS), needed fully charging time of the EV battery, total charging cost, total expected queuing time in the CS, and needed energy consumption of the EV to arrive the CS. The considered system involves 50 EVs and 3 EVCSs. Few solar cells are employed to recharge the EVs and reduce the energy loss and voltage drop. Different scenarios are provided to compare between the proposed and uncontrolled (unoptimized) schemes. The results prove the proposed technique effectiveness. The EV user's charging behavior is improved. Moreover, it is concluded that the charging cost depends on the state of charge (SoC) of the EV batteries and charging time of the EVs.

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Manta Ray Foraging Optimization Approaches on Multivariable PID Controller Tuning

Manta Ray Foraging Optimization Approaches on Multivariable ...

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Congress on Evolutionary Computation

作者： Yan Lieven Souza Luúio Luiza Scapinello Aquino Da Silva Viviana Cocco Mariani Leandro Dos Santos Coelho Electrical Engineering Graduate Program (PPGEE) Federal University of Parana (UFPR) Curitiba Brazil Department of Electrical Engineering Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Parana Brazil Department of Electrical Engineering Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) and Federal University of Parana (UFPR) Curitiba Brazil

This work presents a performance comparison between the newly developed Manta Ray Foraging Optimization (MRFO) and two different variants created for tuning a decentralized fractional order proportional-integral-derivative (FOPID) controller for a multiple-input multiple-output (MIMO) application. The application consists of a ball mill pulverizing system to pulverize coal and maximize fuel efficiency. MRFO and its applications have the task of finding the optimal controller variable values to control the system's temperature and pressure. The MRFO is a metaheuristic based on the behavior of manta rays, and although it shows efficient performance it may be improved through the use of techniques which generate new variants of the algorithm. Two techniques were used in the de-velopment of new variants: Quantum mechanics and opposition-based learning. The three different versions of MRFO were used to minimize a custom fitness function which is a combination of the integral time squared error (ITSE) and the overshoot of the system response. Simulations were carried using Simulink and Matlab softwares. For analyzing the performances, statistical measures such as minimum, maximum, best, mean, median, and standard deviation of the fitness function over 50 runs were used. Additionally, the different variants were also compared for minimizing 10 benchmark functions. The results show that the use of the previously mentioned techniques improve the performance of the original MRFO in optimizing the FOPID to control the ball mill pulverizing system.

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Enhanced thermal decomposition and combustion performance of ammonium perchlorate composite propellants using LaFeO3 catalyst

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Journal of the Taiwan Institute of Chemical Engineers 2025年

作者： Huang, Chao-Wei Wang, Tse-Hao Chen, Yi-Chu Tsai, Yu-An Huang, Chun-Fu Wang, To-Yu Wu, Chih-Yung Department of Engineering Science National Cheng Kung University Tainan Taiwan Department of Aeronautics and Astronautics National Cheng Kung University Tainan Taiwan International Degree Program on Energy in Engineering National Cheng Kung University Tainan Taiwan Institute of Space Systems Engineering National Cheng Kung University Tainan Taiwan

Background: Advancements in solid composite propellant technology hold significant promise for enhancing thrust capabilities, thereby improving booster performance in terms of payload capacity and trajectory precision. Consequently, the selection of a combustion catalyst is of paramount importance. Methods: LaFeO3 was proposed as a potential combustion catalyst. The characteristics of the catalyst were examined through Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDS), X-ray Diffraction (XRD), and Thermogravimetric Analysis (TGA). Concurrently, composite propellant specimens were prepared, and the enhancement of their performance attributable to the incorporation of LaFeO3 on the combustion velocity of the fuel was assessed. The efficacy of LaFeO3 was systematically compared against traditional iron oxide combustion catalysts. Significant findings: The outcomes underscore that introducing LaFeO3 as an additive effectively reduces the instantaneous activation energy of NH4ClO4 at the temperature corresponding to the peak decomposition rate. The results of the measured activation energy indicated that when LaFeO3 was mixed with an oxidant at a concentration of 1 %, the activation energy decreased by approximately 5.88 %. Consequently, this positively impacts the burning rate of the composite solid fuel. Significantly, the promotion of burning velocity by LaFeO3 surpasses that of classic Fe2O3, establishing the former's superiority. Notably, LaFeO3's distinct advantage lies in its capacity to achieve specific performance enhancements with a relatively lower catalyst dosage. © 2025

关键词： Composite propellants

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Future Glycemic Events Prediction Model Based On Artificial Neural Network

Future Glycemic Events Prediction Model Based On Artificial ...

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2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies, 3ICT 2022

作者： Syafrudin, Muhammad Alfian, Ganjar Fitriyani, Norma Latif Hadibarata, Tony Rhee, Jongtae Anshari, Muhammad Sejong University Department of Artificial Intelligence Seoul Korea Republic of Universitas Gadjah Mada Department of Electrical Engineering and Informatics Vocational College Yogyakarta Indonesia Sejong University Department of Data Science Seoul Korea Republic of Curtin University Environmental Engineering Program Miri Malaysia Dongguk University Department of Industrial and Systems Engineering Seoul Korea Republic of Universiti Brunei Darussalam School of Business and Economics Brunei

ISBN: (数字)9781665451932

ISBN: (纸本)9781665451932

Predicting future glycemic events such as hypoglycemia, hyperglycemia, and normal for type 1 diabetes (T1D) remains a significant and challenging issue. In this study, an artificial neural network (ANN)-based model is proposed to predict the future glycemic events of T1D patients. We utilized five T1D patient datasets to build the models and predict future glycemic events with a prediction horizon (PH) of 30 and 60 minutes ahead of time. We applied the data preprocessing method based on the sliding window approach by sliding the blood glucose time-series data from the past 60 minutes (the last 12 data points) as input and using the next 30 and 60 minutes (the next 6 and 12-th data points) as output. All the numeric blood glucose output data are then transformed into a multi-class classification label, such as hypoglycemia, hyperglycemia, and normal. Our proposed model is then used to learn and create the prediction model from the preprocessed blood glucose dataset. Four performance metrics such as accuracy, precision, recall, and f-1 score were utilized to measure the performance of the classification models used in this study, such as Naïve Bayes (NB), Decision Tree (DT), Support Vector Machine (SVM), and K-Nearest Neighbour (KNN). The results showed that our proposed ANN-based model performed better at predicting future glycemic events than other models, with an average accuracy, precision, recall, and f-1 score of 88.649%, 76.661%, 71.731%, 72.609%, and 83.364%, 60.437%, 61.345%, 60.62% for the PH of 30 and 60 minutes, respectively. As a result, knowing this future glycemic event sooner can help patients avoid potentially dangerous conditions and can eventually be used to improve diabetes management. © 2022 IEEE.

关键词： Decision trees

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Text2Scene: Text-driven Indoor Scene Stylization with Part-aware Details

arXiv

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arXiv 2023年

作者： Hwang, Inwoo Kim, Hyeonwoo Kim, Young Min Department of Electrical and Computer Engineering Seoul National University Korea Republic of Interdisciplinary Program in Artificial Intelligence and INMC Seoul National University Korea Republic of

We propose Text2Scene, a method to automatically create realistic textures for virtual scenes composed of multiple objects. Guided by a reference image and text descriptions, our pipeline adds detailed texture on labeled 3D geometries in the room such that the generated colors respect the hierarchical structure or semantic parts that are often composed of similar materials. Instead of applying flat stylization on the entire scene at a single step, we obtain weak semantic cues from geometric segmentation, which are further clarified by assigning initial colors to segmented parts. Then we add texture details for individual objects such that their projections on image space exhibit feature embedding aligned with the embedding of the input. The decomposition makes the entire pipeline tractable to a moderate amount of computation resources and memory. As our framework utilizes the existing resources of image and text embedding, it does not require dedicated datasets with high-quality textures designed by skillful artists. To the best of our knowledge, it is the first practical and scalable approach that can create detailed and realistic textures of the desired style that maintain structural context for scenes with multiple objects. © 2023, CC BY.

关键词： Textures

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Torsional Performance of Vat-Photopolymerized Tough Resins: Influences of Gauge Length and Uv Post-Curing

SSRN

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SSRN 2024年

作者： Sadaghian, Hamed Khalilzadehtabrizi, Sahand Khodadoost, Saeed Yeon, Jung Heum School of Architecture Building and Civil Engineering Loughborough University LoughboroughLE11 3TU United Kingdom Department of Civil and Environmental Engineering Centre for Infrastructure Systems Engineering University of Surrey Guilford United Kingdom Department of Civil Engineering University of Tabriz Tabriz Iran Civil Engineering Program Ingram School of Engineering Texas State University San MarcosTX78666 United States

A myriad of materials, ranging from soft sensors to bone substitutes, undergo torsional loading throughout their operational lifespan, often produced using additive manufacturing (AM) technology due to its broad applicability. Understanding the torsional behavior of these AM components is paramount prior to their utilization. However, research concerning the torsional behavior of solid additively-manufactured resin polymers remains limited. To bridge this gap, 48 torsion specimens were fabricated using vat photopolymerization (VPP) with AnyCubic UV Tough Resin. These specimens varied in gage lengths (20, 40, 60, and 80 mm) and were subjected to five UV post-curing durations (0, 15, 30, 60, 90, and 120 minutes). Monotonic torsion was applied until failure at a rate of 0.1 revolutions per minute, revealing ductile failure patterns across specimens. Longer post-curing times correlated with increased torsional capacities and shear moduli, although conclusions regarding energy absorption per unit volume remained inconclusive. Additionally, a normalized trilinear model was proposed to characterize the behavior of additively-manufactured resin polymers under monotonic torsion, facilitating numerical simulation of material responses in finite element software. © 2024, The Authors. All rights reserved.

关键词： Torsional stress

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IoT human needs inside compact house

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Journal of Open Innovation: Technology, Market, and Complexity 2023年第1期9卷 1-9页

作者： Azis, Baskoro Ong, Ardvin Kester S. Prasetyo, Yogi Tri Persada, Satria Fadil Young, Michael N. Sari, Yanuarita Kusuma Permata Nadlifatin, Reny Interior Design Department School of Design Bina Nusantara University Jakarta 11480 Indonesia School of Industrial Engineering and Engineering Management Mapua University Manila 658 Muralla St. Intramuros Manila 1002 Philippines Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta 11480 Indonesia Communication Science Department Faculty of Digital Communication and Hotel & Tourism Bina Nusantara University Jakarta 11480 Indonesia Department of Information Systems Institut Teknologi Sepuluh November Kampus ITS Sukolilo Surabaya 60111 Indonesia

Indonesia is entering Industry 4.0, but is still not using supportive technology, especially in residential areas. A compact house is one of the dwellings built on limited modern land, providing flexible use of space according to the activities carried out by residents. The current version of this type of residence, namely smart homes, is still far from what is expected. There is a need for the modern use of IoT in every room, which can adapt to the activities of residents to make it easier for residents to move. A grounded theory and descriptive approach was used to find the continuity of modern Industry 4.0 and IoT technology in smart homes with the compact house concept to find the novelty of design standards. The findings are in the form of lighting that can be adjusted via IoT to reduce the crime rates in abandoned homes or in homes that are not active because the residents are traveling. © 2023 The Authors

关键词： Activity Compact house IoT Light Smart home

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Analyzing the Behavioral Aspects of Implementing Green IT in an Academic Environment 8

Analyzing the Behavioral Aspects of Implementing Green IT in...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Syamsuar, Dedy Triando, Fero Ulfa, Maria Antoni, Darius Mailangkay, Adele Witarsyah, Deden School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Universitas Bina Darma Postgradute Department Palembang Indonesia Universitas Bina Darma Information System Study Program Computer Science Faculty Palembang Indonesia Universitas Indo Global Mandiri Faculty of Computer Science Palembang Indonesia School of Industrial Engineering Telkom University Bandung Indonesia

ISBN: (纸本)9798350326093

Environmental awareness has recently emerged as one of the most crucial topics. As a result, various groups advocate for these technologies and research ways to promote their usage in various contexts. This study examines the factors influencing the intention and use of green technology among academics. This study integrates Price Value (PV) and Consideration of future consequence (CFC) to Theory Planned Behavior (TPB) as a theoretical basis. Two hundred five valid replies were gathered and processed through statistical analysis. The results of this study partly support the developed hypotheses. Four hypotheses developed from TPB have presented significant relationships. However, PV and CFC were not. The findings indicate that individuals in this study did not consider CFC or PV of green IT products as critical factors in their decision-making process. Findings also suggest that for implementation success, competent parties must consider the campaign to increase individual awareness and provide financial support regarding environmental policy. © 2023 IEEE.

关键词： Decision making

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Effect of Environment Temperature and Relative Humidity on Thermal Emissivity: Study Case of Mango Fruit

Effect of Environment Temperature and Relative Humidity on T...

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International Symposium on Intelligent systems and Informatics (SISY)

作者： Panmanas Sirisomboon Jiraporn Sripinyowanich Jongyingcharoen Apiwat Junto Thitima Phanomsophon Cheewanun Dachoupakan Sirisomboon Panan Rerngsamran Dharma Raj Pokhrel Sneha Sharma Jetsada Posom Pimpen Pornchaloempong Anupun Terdwongwarakul Prabhas Chongstitvatana Department of Agricultural Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Agricultural Engineering School of Engineering and Innovation Rajamangala University of Technology Tawan-Ok Chon Buri Thailand Office of Administrative Interdisciplinary Program on Agricultural Technology School of Agricultural Technology King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Microbiology Faculty of Science Chulalongkorn University Bangkok Thailand Department of Infrastructure Engineering University of Melbourne Victoria Australia Department of Agricultural Engineering Faculty of Engineering Khon Kaen University Khon Kaen Thailand Department of Food Engineering School of Engineering King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Department of Agricultural Engineering Faculty of Engineering at Kanpangsan Kasetsart University Thailand Department of Computer Engineering Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798350385601

ISBN: (纸本)9798350385618

This research was to study the effect of the environment condition during image captured including temperature and relative humidity in the packaging house of the mango exporting factory and in the orchard on the emissivity of mango fruit. The result showed that in the controlled environment of the packaging house in factory, the emissivity was increased (the mango emitted more energy) when the surface temperature was lower and the emissivity of mango is 0.71-0.84 and in the uncontrolled environment of open-air packaging yard in the mango orchard, the different transpiration rates of mango effected mainly by ambient temperature and relative humidity make the morning condition emissivity of 0.44-0.66 and the afternoon condition of 0.72-0.98. There was the effect of the different measured positions on the fruits where the physiology was different and the fluctuated environment in the latter condition made the wide range of emissivity of mangoes. This indicated the shortcoming of thermal imaging of horticultural product if the correct emissivity varied and difficult to set in the thermal camera setting, hence the inaccurate thermogram to be obtained.

关键词： Temperature measurement Transpiration Temperature Humidity Packaging Position measurement Cameras Production facilities Physiology Temperature control

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Uncertainty Quantification Using Subsampling for Assembly-Free Estimates of Genomic Distance and Phylogenetic Relationships 26th

Uncertainty Quantification Using Subsampling for Assembly-F...

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26th International Conference on Research in Computational Molecular Biology, RECOMB 2022

作者： Rachtman, Eleonora Sarmashghi, Shahab Bafna, Vineet Mirarab, Siavash Bioinformatics and Systems Biology Graduate Program UC San Diego La JollaCA United States Department of Electrical and Computer Engineering UC San Diego La JollaCA United States Department of Computer Science and Engineering UC San Diego La JollaCA United States

Computing the distance between two genomes, often without using alignments or even access to assembled sequences, is fundamental to many downstream analyses. © 2022, The Author(s), under exclusive license to Spri... 详细信息

ISBN: (纸本)9783031047480

关键词： Uncertainty analysis

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