检索结果-内蒙古大学图书馆

International Conference on electrical, Telecommunication and computer engineering (ELTICOM)

作者： Rohana Rohana Surya Hardi Nasaruddin Nasaruddin Yuwaldi Away Doctoral Program. School of Engineering Universitas Syiah Kuala Banda Aceh Indonesia and Universitas Muhammadiyah Sumatera Utara Indonesia Dept. of Electrical Engineering Universitas Sumatera Utara Medan Indonesia Dept. of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia

Solar energy is environmentally friendly energy and is available in large quantities. The energy produced is commonly converted into electricity by using solar panel (PV) systems for utilization. PV systems are generally located in open areas such as hillsides, deserts, and water surfaces, so they become more sensitive against lightning strikes. Commonly, the PV is equipped with a lightning protection system (LPS). This paper discusses the grounding system at the solar power center (PLTS) Weh Island, Sabang City. Evaluation and comparison under certain conditions are carried out through measurements, calculations, and simulations. The grounding system is modeled for one rod, four rods in parallel, and plate rod. The measurement process during field observations and the induce voltage simulation are carried out to get the results of the analysis calculations. The result obtained shows that the grounding system fulfills the PUIL standard, namely being smaller than $5 \Omega$. When using plate electrodes, the resistance value is greater than that of rod electrodes. So that the lower conductor can be more resistant and easier to maintain. Improving the quality of the protection system, this research is used as a reference to evaluate LPS conditions in PV fields.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Image Processing Pipeline to Compute Homologous Recombination Score 22

Image Processing Pipeline to Compute Homologous Recombinatio...

引用

12th International Conference on Biomedical engineering and Technology, ICBET 2022

作者： Vundavilli, Haswanth Tumiati, Manuela Hautaniemi, Sampsa Datta, Aniruddha Kauppi, Liisa Texas A&M University United States The University of Texas MD Anderson Cancer Center United States Research Program in Systems Oncology Faculty of Medicine University of Helsinki Finland Department of Electrical and Computer Engineering The Center for Bioinformatics and Genomic Systems Engineering Texas A&M University United States

ISBN: (纸本)9781450395779

DNA double-strand breaks (DSBs) occur frequently in eukaryotic cells, and the homologous recombination pathway (HR) is one of the major pathways required to repair these breaks. However, tumor cells that are able to repair DSBs are unlikely to die due to damage incurred by DNA damaging chemotherapies, such as platinum compounds. While platinum-based therapies have been effective in treating various cancers, they also carry harsh side effects, and thus ideally platinum should be used when the probability of treatment resistance is low. HR scores provide a measure for patients' tumor's HR capacity and have been shown to predict their chemotherapy response and long-term survival. Calculating this score manually from immunofluorescence microscopy images for each patient is error-prone and time-consuming. Herein, we propose an image processing pipeline that takes as input imaging data from three emission channels (representing nuclei, S-phase cells, and HR-mediated repair in a tumor slice) from an epifluorescence microscope and computes the HR score. Our open-source methodology forms a rationale to develop similar approaches in predicting chemotherapeutic responses and facilitating to make treatment decisions. © 2022 ACM.

关键词： Chemotherapy

来源：评论

学校读者我要写书评

暂无评论

Performance of Building-Integrated Photovoltaic and Addressing the Challenges of Color, Safety, and Light-Emitting Diode Integration

引用

Physica Status Solidi (A) Applications and Materials Science 2025年第10期222卷

作者： Mohammed, Shurouq Abdulqadir Yousuf, Hasnain Jony, Jaljalalul Abedin Khokhar, Muhammad Quddamah Rahman, Rafi Ur Aida, Maha Nur Alamgeer Park, Sangheon Yi, Junsin Department of Electrical and Computer Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of Interdisciplinary Program in Photovoltaic System Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of Department of Future Energy Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of College of Information and Communication Engineering Sungkyunkwan University Gyeonggi-Do Suwon16419 Korea Republic of

Building-integrated photovoltaics (BIPVs) provide a dual-purpose solution, functioning as both energy-generating systems and integral building materials. BIPV adoption has been limited due to a lack of color integration, preventing the panels from being used in building designs. However, efforts to incorporate color into the BIPV layers have been made, but they often reduce panel efficiency. BIPV implementation faces several challenges that hinder widespread adoption, such as fire safety concerns and the integration of color aesthetics and light-emitting diode technology. This article explores these challenges and recent advancements that enhance the aesthetic versatility and efficiency of BIPV systems, including the use of quantum dots, Bragg reflectors, and silver-alloyed copper indium gallium selenide cells. The study also highlights critical considerations for optimizing BIPV systems, such as energy performance and fire safety. PVsyst 7.2 simulation results for a 10 kW BIPV system installed in South Korea demonstrate effective strategies for mitigating efficiency losses through investigating the orientation of angles. Results showcase a high-performance ratio of 0.891, a high production of 14 147 kWh year−1 at a tilt angle of 30° while facing south, and a peak energy of almost 1450 kWh injected into the grid under varying conditions. © 2025 Wiley-VCH GmbH.

关键词： building-integrated photovoltaics colors efficiencies light-emitting diodes technologies

来源：评论

学校读者我要写书评

暂无评论

Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting

arXiv

引用

arXiv 2024年

作者： Kang, Bong Gyun Lee, Dongjun Kim, HyunGi Yoon, Sungroh Chung, DoHyun Interdisciplinary Program in Artificial Intelligence Seoul National University Korea Republic of Department of Electrical and Computer Engineering Seoul National University Korea Republic of Department of Future Automotive Mobility Seoul National University Korea Republic of

Sequence modeling faces challenges in capturing long-range dependencies across diverse tasks. Recent linear and transformer-based forecasters have shown superior performance in time series forecasting. However, they are constrained by their inherent inability to effectively address long-range dependencies in time series data, primarily due to using fixed-size inputs for prediction. Furthermore, they typically sacrifice essential temporal correlation among consecutive training samples by shuffling them into mini-batches. To overcome these limitations, we introduce a fast and effective Spectral Attention mechanism, which preserves temporal correlations among samples and facilitates the handling of long-range information while maintaining the base model structure. Spectral Attention preserves long-period trends through a low-pass filter and facilitates gradient to flow between samples. Spectral Attention can be seamlessly integrated into most sequence models, allowing models with fixed-sized look-back windows to capture long-range dependencies over thousands of steps. Through extensive experiments on 11 real-world time series datasets using 7 recent forecasting models, we consistently demonstrate the efficacy of our Spectral Attention mechanism, achieving state-of-the-art results. © 2024, CC BY-NC-ND.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat

arXiv

引用

arXiv 2023年

作者： Ghosh, Shantanu Yu, Ke Arabshahi, Forough Batmanghelich, Kayhan Department of Electrical and Computer Engineering Boston University MA United States Intelligent Systems Program University of Pittsburgh PA United States MetaAI MenloParkCA United States

ML model design either starts with an interpretable model or a Blackbox and explains it post hoc. Blackbox models are flexible but difficult to explain, while interpretable models are inherently explainable. Yet, interpretable models require extensive ML knowledge and tend to be less flexible and underperforming than their Blackbox variants. This paper aims to blur the distinction between a post hoc explanation of a Blackbox and constructing interpretable models. Beginning with a Blackbox, we iteratively carve out a mixture of interpretable experts (MoIE) and a residual network. Each interpretable model specializes in a subset of samples and explains them using First Order Logic (FOL), providing basic reasoning on concepts from the Blackbox. We route the remaining samples through a flexible residual. We repeat the method on the residual network until all the interpretable models explain the desired proportion of data. Our extensive experiments show that our route, interpret, and repeat approach (1) identifies a diverse set of instance-specific concepts with high concept completeness via MoIE without compromising in performance, (2) identifies the relatively "harder" samples to explain via residuals, (3) outperforms the interpretable by-design models by significant margins during test-time interventions, and (4) fixes the shortcut learned by the original Blackbox. The code for MoIE is publicly available at: https://***/batmanlab/ ICML-2023-Route-interpret-repeat. © 2023, CC BY.

关键词： Iterative methods

来源：评论

学校读者我要写书评

暂无评论

Compressive Sensing via Variational Bayesian Inference 1

Compressive Sensing via Variational Bayesian Inference

引用

1st Intermountain engineering, Technology and Computing, IETC 2020

作者： Shekaramiz, Mohammad Moon, Todd K. Utah Valley University Electrical and Computer Engineering Program Engineering Department United States Utah State University Electrical and Computer Engineering Department United States

ISBN: (数字)9781728142913

ISBN: (纸本)9781728142913

The sparse signal recovery problem from a set of compressively sensed noisy measurements using sparse Bayesian learning (SBL) modeling and variational Bayesian (VB) inference technique is considered. In the context of SBL, two main approaches are considered here. In the first approach, each component of the sparse signal is modeled via a Gaussian prior with a Gamma/inverse-Gamma hyper prior on its variance/precision. In the second model, each component of the sparse signal is modeled via a Gaussian prior combined with a Bernoulli prior along with a Gamma/inverse-Gamma hyper prior on its variance/precision. In this work, we consider such modeling and derive the update rules for the latent variables and parameters of each modeling in detail. We believe that such rigorous details on these two modeling and inferences provide sufficient intuition for better understanding the inference using variational Bayes, which can also serve as basic models when incorporating any further structures on the sparse/compressible signal. © 2020 IEEE.

关键词： Compressed sensing

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning for Keypoint Detection in Low-Resolution Thermal TUG Test Images

arXiv

引用

arXiv 2025年

作者： Chen, Wei-Lun Hsieh, Chia-Yeh Kao, Yu-Hsiang Liu, Kai-Chun Peng, Sheng-Yu Tsao, Yu Research Center for Information Technology Innovation Academic Sinica Taiwan Graduate Institute of Electrical Engineering National Taiwan University Taiwan Bachelor’s Program in Medical Informatics and Innovative Applications Fu Jen Catholic University Taiwan Department of Electrical Engineering National Taiwan University Taiwan College of Information and Computer Sciences University of Massachusetts AmherstMA01003 United States Department of Electrical Engineering National Taiwan University of Science of Technology Taiwan

This study presents a novel approach to human keypoint detection in low-resolution thermal images using transfer learning techniques. We introduce the first application of the Timed Up and Go (TUG) test in thermal image computer vision, establishing a new paradigm for mobility assessment. Our method leverages a MobileNetV3-Small encoder and a ViTPose decoder, trained using a composite loss function that balances latent representation alignment and heatmap accuracy. The model was evaluated using the Object Keypoint Similarity (OKS) metric from the COCO Keypoint Detection Challenge. The proposed model achieves better performance with AP, AP50, and AP75 scores of 0.861, 0.942, and 0.887 respectively, outperforming traditional supervised learning approaches like Mask R-CNN and ViTPose-Base. Moreover, our model demonstrates superior computational efficiency in terms of parameter count and FLOPS. This research lays a solid foundation for future clinical applications of thermal imaging in mobility assessment and rehabilitation monitoring. Copyright © 2025, The Authors. All rights reserved.

关键词： Thermography (imaging)

来源：评论

学校读者我要写书评

暂无评论

Q-learning based Path Planning Method for UAVs using Priority Shifting

Q-learning based Path Planning Method for UAVs using Priorit...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Kevin B. de Carvalho Iure Rosa L. de Oliveira Daniel K. D. Villa Alexandre G. Caldeira Má rio Sarcinelli-Filho Alexandre S. Brandã o Department of Electrical Engineering Graduate Program in Computer Science Nucleus of Specialization in Robotics Universidade Federal de Vi&#x00E7 osa Vi&#x00E7 osa MG Brazil Department of Electrical Engineering Graduate Program in Electrical Engineering Universidade Federal do Esp&#x00ED rito Santo Vit&#x00F3 ria ES Brazil

ISBN: (数字)9781665405935

ISBN: (纸本)9781665405942

Path planning is a crucial part of autonomous navigation when regarding autonomous aerial vehicles, often demanding different priorities such as the length, safety or energy consumption. Dynamic programming and geometric methods have been applied to solve this problem, but in recent years, more work has been developed using artificial intelligence approaches, such as reinforcement learning. In this paper we propose an offline path planning method for static environments using Q-learning. An optimal policy is found weighting three important factors: path length, safety and energy consumption. Due to a well balanced exploring/exploiting ratio, the proposed method can lead the agent to the desired destination starting from anywhere in the map. Simulations are done in different scenarios to address the performance of the proposed method and it showcased that the algorithm is able to find feasible paths in each scenario while regarding different set of priorities.

关键词： Energy consumption Q-learning Atmospheric modeling Autonomous aerial vehicles Path planning Safety Dynamic programming

来源：评论

学校读者我要写书评

暂无评论

Particle swarm optimization with local search for height-map surface reconstruction from point clouds in reverse engineering

引用

Neural Computing and Applications 2024年 1-20页

作者： Gálvez, Akemi Fister, Iztok Deb, Suash Fister, Iztok Iglesias, Andrés Dept. of Applied Mathematics and Computational Sciences E.T.S.I. Caminos Canales y Puertos University of Cantabria Avda. de los Castros s/n Santander39005 Spain Faculty of Pharmaceutical Sciences Toho University 2-2-1 Miyama Funabashi274-8510 Japan Faculty of Electrical Engineering and Computer Science University of Maribor Koroska cesta 34 Maribor2000 Slovenia IT & Educational Consultant Ranchi India Distinguished Professorial Associate Decision Sciences and Modeling Program Victoria University Melbourne Australia

Surface reconstruction is a classical process in industrial engineering and manufacturing, particularly in reverse engineering, where the goal is to obtain a digital model from a physical object. For that purpose, the real object is typically scanned or digitized and the resulting point cloud is then fitted to mathematical surfaces through numerical optimization. The choice of the approximating functions is crucial for the accuracy of the process. Real-world objects such as manufactured workpieces often require complex nonlinear approximating functions, which are not well suited for standard numerical methods. In a previous paper presented at the ISMSI 2023 conference, we addressed this issue by using manually selected approximation functions via optimization through the cuckoo search algorithm with Lévy flights. Building upon that work, this paper presents an enhanced and extended method for surface reconstruction by using height-map surfaces obtained through a combination of exponential, polynomial and logarithmic functions. A feasible approach for this goal is to consider continuous bivariate distribution functions, which ensures consistent models along with good mathematical properties for the output shapes, such as smoothness and integrability. However, this approach leads to a difficult multivariate, constrained, multimodal continuous nonlinear optimization problem. To tackle this issue, we apply particle swarm optimization, a popular swarm intelligence technique for continuous optimization. The method is hybridized with a local search procedure for further improvement of the solutions and applied to a benchmark of 15 illustrative examples of point clouds fitted to different surface models. The performance of the method is analyzed through several computational experiments. The numerical and graphical results show that the method is able to recover the shape of the point clouds accurately and automatically. Furthermore, our approach outperforms other alternati

关键词： Particle swarm optimization (PSO)

来源：评论

学校读者我要写书评

暂无评论

Control Design for 3-Phase Bidirectional Battery Chargers with Multiple Battery Charging Capabilities for Electric Vehicle Fleet Applications

Control Design for 3-Phase Bidirectional Battery Chargers wi...

引用

2021 North American Power Symposium, NAPS 2021

作者： Okon, Queen Urquizo, Javier Kondrath, Nisha Singh, Pritpal College of Engineering Sustainable Engineering Program Villanova University Department of Electrical and Computer Engineering VillanovaPA United States L3Harris Technologies Maritime Power Systems PhiladelphiaPA United States

ISBN: (纸本)9781665420815

This paper describes a control structure for a bidirectional battery charger model design which consists of three-phase PWM ac/DC converters linked to a DC/DC converter with a CLLC-type resonant tank circuit. It presents a control structure that accommodates: constant current, constant voltage (CCCV) charging algorithm of an Energy Storage System (ESS), a multiple battery charger setup, and the automation of the combined control system based upon certain conditions being satisfied. The proposed control scheme was simulated and validated for a system integrating two battery charger modules using the PLECS software tool while charging a Li-ion battery model. The interactions between the two modules during the charging process were investigated with and without the introduction of a DC bus. © 2021 IEEE.

关键词： Charging (batteries)

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：