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3rd Novel Intelligent and Leading Emerging Sciences Conference, NILES 2021

作者： Boraey, Mohammed A. Kareem, Gamal Abdel Hameed, Hesham Abdel Salmawy, Hafez El Zagazig University Mechanical Power Engineering Department Zagazig Egypt Smart Engineering Systems Research Center Nile University Gize Egypt Mechanical Engineering Program Nile University Gize Egypt Marine units and maintenance Department PetroGulf Misr Cairo Egypt

ISBN: (纸本)9781665421577

Numerical simulation of the non-premixed combustion of methane air mixture in a gas turbine can- type swirl combustor is conducted. The study objective is to examine the effect of different design and operational parameters on the combustor performance and its emissions. The investigated parameters are the primary air flow rate, the swirl ratio between the secondary and the primary air and the fuel to the primary air swirl ratio. Several indicators are used to evaluate the combustion performance and emissions which include average exit temperature of the chamber, pattern factor, NOx and CO emission indices, combustion efficiency and the pressure drop. The results of the study demonstrate the importance of good tuning of the design and operating parameters for better performance and reduced emissions. © 2021 IEEE.

关键词： Combustors

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Multi-Object RANSAC: Efficient Plane Clustering Method in a Clutter

arXiv

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arXiv 2024年

作者： Lim, Seunghyeon Yoo, Youngjae Lee, Jun Ki Zhang, Byoung-Tak Interdisciplinary Program in Cognitive Science Seoul National University Seoul Korea Republic of Department of Computer Science and Engineering Seoul National University Seoul Korea Republic of AIIS Seoul National University Seoul Korea Republic of

In this paper, we propose a novel method for plane clustering specialized in cluttered scenes using an RGB-D camera and validate its effectiveness through robot grasping experiments. Unlike existing methods, which focus on large-scale indoor structures, our approach—Multi-Object RANSAC emphasizes cluttered environments that contain a wide range of objects with different scales. It enhances plane segmentation by generating subplanes in Deep Plane Clustering (DPC) module, which are then merged with the final planes by post-processing. DPC rearranges the point cloud by voting layers to make subplane clusters, trained in a self-supervised manner using pseudo-labels generated from RANSAC. Multi-Object RANSAC demonstrates superior plane instance segmentation performances over other recent RANSAC applications. We conducted an experiment on robot suction-based grasping, comparing our method with vision-based grasping network and RANSAC applications. The results from this real-world scenario showed its remarkable performance surpassing the baseline methods, highlighting its potential for advanced scene understanding and manipulation. Copyright © 2024, The Authors. All rights reserved.

关键词： Clutter (information theory)

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Design and Feasibility Study of Wind Powered Hydrogen Refueling Station in Saudi Arabia

Design and Feasibility Study of Wind Powered Hydrogen Refuel...

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International Symposium on Advanced Electrical and Communication Technologies (ISAECT)

作者： Kholud Munshi Raghdan Bokhari Muhammad Khalid Electrical Engineering Department King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Sustainable Energy Systems (IRC-SES) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia

ISBN: (数字)9798331529987

ISBN: (纸本)9798331529994

The transportation sector is one of the leading contributors to global carbon emissions due to its reliance on fossil fuels. Hydrogen, as a non-toxic and clean energy source, presents a promising alternative to fossil fuels. By transitioning to hydrogen-powered vehicles, we can significantly reduce carbon emissions, mitigating greenhouse gas effects and environmental pollution. If sustainable energy sources produce hydrogen and a widespread network of hydrogen refueling stations supports it, this potential becomes especially notable. This study conducted a techno-economic evaluation for a wind-powered hydrogen refueling station in NEOM, Saudi Arabia. The objective was to determine the optimal design for a wind-powered hydrogen refueling station in the city and to assess the project’s economic feasibility and its potential impact on reducing carbon emissions. We designed the station to meet the daily refueling needs of 20 hydrogen vehicles, each with a 5 kg tank capacity. The results show that the cost of producing hydrogen at this facility is approximately $3.75 per kilogram, which is competitive when compared to global hydrogen production costs. Furthermore, the hydrogen refueling station has the potential to reduce CO 2 emissions by 5904 tons and CO emissions by 19.66322 tons over its lifetime. These findings affirm the feasibility of a wind-powered hydrogen refueling station in NEOM and highlight its potential environmental benefits.

关键词： Electric potential Costs Electricity Hydrogen Urban areas Transportation Carbon dioxide Fossil fuels Stakeholders Sustainable development

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Breakdown of effective-medium theory by a photonic spin Hall effect

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Science China(Physics,Mechanics & Astronomy) 2023年第11期66卷 145-154页

作者： Shuaijie Yuan Xinxing Zhou Yu Chen Yuhan Zhong Lijuan Sheng Hao Hu Hongsheng Chen Ido Kaminer Xiao Lin Key Laboratory of Low-Dimensional Quantum Structures and Quantum Control of Ministry of Education Synergetic Innovation Center for Quantum Effects and ApplicationsSchool of Physics and ElectronicsHunan Normal UniversityChangsha410081China International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology Engineering Technology Research Center for 2D Material Information Function Devices and Systems of Guangdong ProvinceInstitute of Microscale OptoelectronicsShenzhen UniversityShenzhen518060China Interdisciplinary Center for Quantum Information State Key Laboratory of Extreme Photonics and InstrumentationZJU-Hangzhou Global Scientific and Technological Innovation CenterZhejiang UniversityHangzhou310027China International Joint Innovation Center Electromagnetics Academy at Zhejiang UniversityZhejiang UniversityHaining314400China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore639798Singapore Key Laboratory of Radar Imaging and Microwave Photonics Ministry of EducationCollege of Electronic and Information EngineeringNanjing University of Aeronautics and AstronauticsNanjing211106China Key Laboratory of Advanced Micro/Nano Electronic Devices&Smart Systems of Zhejiang Jinhua Institute of Zhejiang UniversityZhejiang UniversityJinhua321099China Shaoxing Institute of Zhejiang University Zhejiang UniversityShaoxing312000China Department of Electrical Engineering Technion-Israel Institute of TechnologyHaifa32000Israel

Effective-medium theory pertains to the theoretical modelling of homogenization,which aims to replace an inhomogeneous structure of subwavelength-scale constituents with a homogeneous effective *** effective-medium theory is fundamental to various realms,including electromagnetics and material science,since it can largely decrease the complexity in the exploration of light-matter interactions by providing simple acceptable ***,the effective-medium theory is thought to be applicable to any all-dielectric system with deep-subwavelength constituents,under the condition that the effective medium does not have a critical angle,at which the total internal reflection *** we reveal a fundamental breakdown of the effective-medium theory that can be applied in very general conditions:showing it for deep-subwavelength all-dielectric multilayers even without a critical *** finding relies on an exotic photonic spin Hall effect,which is shown to be ultrasensitive to the stacking order of deep-subwavelength dielectric layers,since the spin-orbit interaction of light is dependent on slight phase accumulations during the wave *** results indicate that the photonic spin Hall effect could provide a promising and powerful tool for measuring structural defects for all-dielectric systems even in the extreme nanometer scale.

关键词： photonic spin Hall effect effective-medium theory spin-orbit interaction of light

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Distilling BlackBox to Interpretable models for Efficient Transfer Learning

arXiv

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arXiv 2023年

作者： Ghosh, Shantanu Yu, Ke Batmanghelich, Kayhan Department of Electrical and Computer Engineering Boston University BostonMA United States Intelligent Systems Program University of Pittsburgh PittsburghPA United States

Building generalizable AI models is one of the primary challenges in the healthcare domain. While radiologists rely on generalizable descriptive rules of abnormality, Neural Network (NN) models suffer even with a slight shift in input distribution (e.g., scanner type). Fine-tuning a model to transfer knowledge from one domain to another requires a significant amount of labeled data in the target domain. In this paper, we develop an interpretable model that can be efficiently fine-tuned to an unseen target domain with minimal computational cost. We assume the interpretable component of NN to be approximately domain-invariant. However, interpretable models typically underperform compared to their Blackbox (BB) variants. We start with a BB in the source domain and distill it into a mixture of shallow interpretable models using human-understandable concepts. As each interpretable model covers a subset of data, a mixture of interpretable models achieves comparable performance as BB. Further, we use the pseudo-labeling technique from semi-supervised learning (SSL) to learn the concept classifier in the target domain, followed by fine-tuning the interpretable models in the target domain. We evaluate our model using a real-life large-scale chest-X-ray (CXR) classification dataset. The code is available at: https://github. com/batmanlab/MICCAI-2023-Route-interpret-repeat-CXRs. © 2023, CC BY.

关键词： Large dataset

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A novel framework for human leukocyte antigen (HLA) genotyping using probe capture-based targeted next-generation sequencing and computational analysis

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Computational and Structural Biotechnology Journal 2024年 23卷 1562-1571页

作者： Lai, Sheng-Kai Luo, Allen Chilun Chiu, I-Hsuan Chuang, Hui-Wen Chou, Ting-Hsuan Hung, Tsung-Kai Hsu, Jacob Shujui Chen, Chien-Yu Yang, Wei-Shiung Yang, Ya-Chien Chen, Pei-Lung Genome and Systems Biology Degree Program Academia Sinica and National Taiwan University Taipei Taiwan Department of Medical Genetics National Taiwan University Hospital Taipei Taiwan Graduate Institute of Medical Genomics and Proteomics College of Medicine National Taiwan University Taipei Taiwan Department of Biomechatronics Engineering National Taiwan University Taipei Taiwan Graduate Institute of Clinical Medicine College of Medicine National Taiwan University Taipei Taiwan Division of Endocrinology and Metabolism Department of Internal Medicine National Taiwan University Hospital Taipei Taiwan Department of Clinical Laboratory Sciences and Medical Biotechnology College of Medicine National Taiwan University Taipei Taiwan Department of Laboratory Medicine National Taiwan University Hospital Taipei Taiwan

Human leukocyte antigen (HLA) genes play pivotal roles in numerous immunological applications. Given the immense number of polymorphisms, achieving accurate high-throughput HLA typing remains challenging. This study aimed to harness the human pan-genome reference consortium (HPRC) resources as a potential benchmark for HLA reference materials. We meticulously annotated specific four field-resolution alleles for 11 HLA genes (HLA-A, -B, -C, -DPA1, -DPB1, -DQA1, -DQB1, -DRB1, -DRB3, -DRB4 and -DRB5) from 44 high-quality HPRC personal genome assemblies. For sequencing, we crafted HLA-specific probes and conducted capture-based targeted sequencing of the genomic DNA of the HPRC cohort, ensuring focused and comprehensive coverage of the HLA region of interest. We used publicly available short-read whole-genome sequencing (WGS) data from identical samples to offer a comparative perspective. To decipher the vast amount of sequencing data, we employed seven distinct software tools: OptiType, HLA-VBseq, HISAT genotype, SpecHLA, T1K, QzType, and DRAGEN. Each tool offers unique capabilities and algorithms for HLA genotyping, allowing comprehensive analysis and validation of the results. We then compared these results with benchmarks derived from personal genome assemblies. Our findings present a comprehensive four-field-resolution HLA allele annotation for 44 HPRC samples. Significantly, our innovative targeted next-generation sequencing (NGS) approach for HLA genes showed superior accuracy compared with conventional short-read WGS. An integrated analysis involving QzType, T1K, and DRAGEN was developed, achieving 100% accuracy for all 11 HLA genes. In conclusion, our study highlighted the combination of targeted short-read sequencing and astute computational analysis as a robust approach for HLA genotyping. Furthermore, the HPRC cohort has emerged as a valuable assembly-based reference in this realm. © 2024 The Authors

关键词： Probes

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Speed Control of Wind Turbines System using Evolutionary Algorithm based Cascaded Controller

Speed Control of Wind Turbines System using Evolutionary Alg...

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International Conference on Control, Automation and Diagnosis (ICCAD)

作者： Ghali Ahmad Muhammad Majid Gulzar Adnan Shakoor Salman Habib Hasnain Ahmad Department of Control & Instrumentation Engineering King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Sustainability Energy Systems (IRC-SES) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Biosystems and Machines (IRC-BMRC) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Interdisciplinary Research Center for Smart Mobility and Logistics (IRC-SML) King Fahd University of Petroleum & Minerals Dhahran Saudi Arabia Department of Electrical Engineering Pakistan Institute of Engineering and Applied Sciences (PIEAS) Islamabad Pakistan

ISBN: (数字)9798350361025

ISBN: (纸本)9798350361032

In the last decades, wind turbine systems have emerged as one of the sources of electricity, and they are further considered to be part of the renewable energy sources that produce energy with zero carbon emissions. Due to the high demand for electrical energy and the reduction of greenhouse gas emissions, wind turbines have gained massive consideration in previous and current decades. Harvesting that energy from the wind to utilize by the system and producing electrical energy faced many challenges due to different factors, including the non-proper control system of the plant. In this regard, the paper presents control strategies of wind turbine systems using evolutionary algorithm-based cascaded controllers to tackle these issues. The control techniques used in this work are PSO-PID, SMC-PID and GA-PID. The paper described the principles of each control and optimization technique and their application in wind turbine systems. It also compares the results from each and evaluates their effectiveness in enhancing the performance of wind turbines.

关键词： Renewable energy sources Wind energy Velocity control Carbon dioxide Control systems Wind turbines Steady-state

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Age Feature Enhanced Neural Network for RUL Estimation of Power Electronic Devices

Age Feature Enhanced Neural Network for RUL Estimation of Po...

引用

International Conference on Prognostics and Health Management, PHM

作者： Zhonghai Lu Rui Shi Chao Guo Mingrui Liu Department of Electrical Engineering KTH Royal Institute of Technology Stockholm Sweden Embedded Systems Master Program KTH Royal Institute of Technology Stockholm Sweden

Like other deep learning problems, critical features are critical to enable effective estimation of Remaining Useful Lifetime (RUL) for power electronic devices using Neural Networks (NNs). However, these critical features are often indirectly obtained after data pre-processing, complicated either in form (high dimension) or in computation (computation-intensive pre-processing). In the paper, we suggest adding a simple direct feature, age, into the NN based RUL estimation technique. The rationale for incorporating this feature is that the device lifetime is a sum of past time (age) plus RUL. Thus it has a strong correlation to RUL. In our experiments using accelerated aging tests, we show that the new age feature enhanced Recurrent Neural Network (RNN) model can significantly improve estimation accuracy and shorten training convergence time. It also outperforms a state-of-the-art RNN model using derived time-domain statistical features.

关键词：

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Design and Characterization of a Configurable Current Conveyor Circuit

Design and Characterization of a Configurable Current Convey...

引用

International Conference on Microelectronics, ICM

作者： Muneer A. Al Absi Ahmed Reda Mohamed Department of Electrical Engineering King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Interdisciplinary Research Center for Communications Systems and Sensing King Fahd University of Petroleum and Minerals (KFUPM) Dhahran Saudi Arabia

ISBN: (数字)9798350379396

ISBN: (纸本)9798350379402

This paper presents a new design of a high-precision and configurable second-generation current conveyor circuit for biomedical applications. It is composed of a Miller-compensated trans-conductance amplifier (OTA), feedback network (FBN), and feedforward network (FFN)-based class AB amplifier. In TSMC 180 nm, the circuit is designed and simulated with a power supply of 1.8V. Moreover, it occupies a relatively small silicon area of 27 μm × 195 μm and consumes a power of $73.3\ \mu \mathrm{W}$ . The post-layout simulation results indicate the voltage gain reached 0.731 mdB with a bandwidth of 2.8 MHz and the current gain is 23.5 dB with a bandwidth of 24.2 MHz. 0.7 mdB and $25\ \mu \text{dB}$ , respectively, are the deviations in voltage gain and current gain. In addition, the proposed conveyor has a low input impedance of $101\ \Omega$ and a high output impedance of up to $81.6\ \mathrm{M}\Omega$ . Process-voltage-temperature (PVT) and Monte-Carlo (MC) variations have been used to guarantee consistent performance in the manufacturing process. Furthermore, the comparison table shows that this work is superior to prior arts.

关键词： Art Monte Carlo methods Power supplies Simulation Voltage Bandwidth Silicon Microelectronics Impedance Gain

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Deep Learning-Based Residual Useful Lifetime Prediction for Assets With Uncertain Failure Modes

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Journal of Computing and Information Science in engineering 2025年第4期25卷 041002页

作者： Su, Yuqi Fang, Xiaolei Operations Research Graduate Program North Carolina State University 915 Partners Way Raleigh NC 27607 Edward P. Fitts Department of Industrial and Systems Engineering North Carolina State University 915 Partners Way Raleigh NC 27607

Industrial prognostics focuses on utilizing degradation signals to forecast and continually update the residual useful life of complex engineering systems. However, existing prognostic models for systems with multiple failure modes face several challenges in real-world applications, including overlapping degradation signals from multiple components, the presence of unlabeled historical data, and the similarity of signals across different failure modes. To tackle these issues, this research introduces two prognostic models that integrate the mixture (log)-location-scale distribution with deep learning. This integration facilitates the modeling of overlapping degradation signals, eliminates the need for explicit failure mode identification, and utilizes deep learning to capture complex nonlinear relationships between degradation signals and residual useful lifetimes. Numerical studies validate the superior performance of these proposed models compared to existing methods.

关键词： Failure mechanisms mixture (log)-location-scale distribution Failure Weibull distribution multiple failure modes Signals Service life (Equipment) prognostics data analytics Deep learning machine learning for engineering applications engineering systems and industry applications industrial Internet of things big data and analytics

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