检索结果-内蒙古大学图书馆

5th National and the 1st International Conference on Applied Research in Electrical engineering, AREE 2025

作者： Mousavi, Mohammad Hossein Moradi, Hassan Rouzbehi, Kumars Razi University Department of Computer and Electrical Engineering Kermanshah Iran University of Seville Department of System Engineering and Automatic Control Seville Spain

ISBN: (纸本)9798350377170

The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as offshore wind farms, ADENs enable efficient long-distance power transmission through HVDC technology. This design enhances the balance of supply and demand across regions and countries, significantly improving grid stability and resilience. However, the implementation of ADENs presents substantial technical, regulatory, and cybersecurity challenges. This study delves into these challenges while also addressing the geopolitical complexities of transnational connections, underscoring the critical importance of policy alignment for successful deployment. © 2025 IEEE.

关键词： Wind power integration

来源：评论

学校读者我要写书评

暂无评论

Sustainable Water Futures: Enhancing Efficiency And Conservation In Madinah AL Munawara

Journal of Applied Science and Engineering

引用

Journal of Applied Science and engineering 2024年第10期28卷 2027-2042页

作者： Syed, Toqeer Ali Naqash, Muhammad Tayyab Nawaz, Waqas Namoun, Abdallah Muhammad, Munir Azam Faculty of Computer and Information System Islamic University of Madinah Saudi Arabia Civil Engineering Department Faculty of Engineering Islamic University of Madinah Madinah42351 Saudi Arabia AI Center Faculty of Computer and Information Systems Islamic University of Madinah Madinah42351 Saudi Arabia Khwaja Fareed University of Engineering & Information Technology Faculty of Computer and Information System Punjab Rahim Yar Khan Pakistan

Water resource management worldwide faces significant challenges, including high consumption rates, scarcity, and ageing infrastructure. This paper proposes a comprehensive approach to address these issues through five key solutions. Advanced Metering Infrastructure (AMI) first facilitates real-time data collection and consumer awareness campaigns. Secondly, wastewater recycling and reuse are promoted by upgrading wastewater treatment plants and fostering public-private partnerships. Thirdly, reducing network losses is achieved through leak detection systems and regular maintenance. Fourthly, policy enhancement and regulatory frameworks are strengthened by implementing regulations for new developments and incentives for water-saving technologies. Lastly, community engagement and education initiatives are undertaken to promote sustainable water practices. This multifaceted strategy aims to improve water conservation, efficiency, and resilience of the water supply system. This paper proposes solutions that can be applied to the Madinah AL Munawara region of Saudi Arabia, an area of utmost importance, demonstrating the applicability and effectiveness of these solutions in addressing regional water management challenges. © The Author(’s).

关键词： Wastewater treatment

来源：评论

学校读者我要写书评

暂无评论

Automatic Transportation Mode Classification Using a Deep Reinforcement Learning Approach With Smartphone Sensors

引用

IEEE Access 2024年 12卷 514-533页

作者： Taherinavid, Siavash Moravvej, Seyed Vahid Chen, Yen-Lin Yang, Jing Ku, Chin Soon Yee, Por Lip Iran University of Science and Technology School of Civil Engineering Tehran13114-16846 Iran Isfahan University of Technology Department of Electrical and Computer Engineering Isfahan84156-83111 Iran National Taipei University of Technology Department of Computer Science and Information Engineering Taipei106344 Taiwan Universiti Malaya Faculty of Computer Science and Information Technology Department of Computer System and Technology Kuala Lumpur50603 Malaysia Universiti Tunku Abdul Rahman Department of Computer Science Kampar31900 Malaysia

The increasing dependence on smartphones with advanced sensors has highlighted the imperative of precise transportation mode classification, pivotal for domains like health monitoring and urban planning. This research is motivated by the pressing demand to enhance transportation mode classification, leveraging the potential of smartphone sensors, notably the accelerometer, magnetometer, and gyroscope. In response to this challenge, we present a novel automated classification model rooted in deep reinforcement learning. Our model stands out for its innovative approach of harnessing enhanced features through artificial neural networks (ANNs) and visualizing the classification task as a structured series of decision-making events. Our model adopts an improved differential evolution (DE) algorithm for initializing weights, coupled with a specialized agent-environment relationship. Every correct classification earns the agent a reward, with additional emphasis on the accurate categorization of less frequent modes through a distinct reward strategy. The Upper Confidence Bound (UCB) technique is used for action selection, promoting deep-seated knowledge, and minimizing reliance on chance. A notable innovation in our work is the introduction of a cluster-centric mutation operation within the DE algorithm. This operation strategically identifies optimal clusters in the current DE population and forges potential solutions using a pioneering update mechanism. When assessed on the extensive HTC dataset, which includes 8311 hours of data gathered from 224 participants over two years. Noteworthy results spotlight an accuracy of 0.88±0.03 and an F-measure of 0.87±0.02, underscoring the efficacy of our approach for large-scale transportation mode classification tasks. This work introduces an innovative strategy in the realm of transportation mode classification, emphasizing both precision and reliability, addressing the pressing need for enhanced classification mechanisms in an eve

关键词： Smartphones

来源：评论

学校读者我要写书评

暂无评论

YOLO-Based Damage Detection with StyleGAN3 Data Augmentation for Parcel Information-Recognition system

引用

computers, Materials & Continua 2024年第7期80卷 195-215页

作者： Seolhee Kim Sang-Duck Lee Department of Electrical and Computer Engineering Sungkyunkwan UniversitySuwon16419Republic of Korea Logistics System Research Division Korea Railroad Research InstituteUiwang16105Republic of Korea

Damage to parcels reduces customer satisfactionwith delivery services and increases return-logistics *** can be prevented by detecting and addressing the damage before the parcels reach the ***,various studies have been conducted on deep learning techniques related to the detection of parcel *** study proposes a deep learning-based damage detectionmethod for various types of *** is intended to be part of a parcel information-recognition systemthat identifies the volume and shipping information of parcels,and determines whether they are damaged;this method is intended for use in the actual parcel-transportation *** this purpose,1)the study acquired image data in an environment simulating the actual parcel-transportation process,and 2)the training dataset was expanded based on StyleGAN3 with adaptive discriminator ***,3)a preliminary distinction was made between the appearance of parcels and their damage status to enhance the performance of the parcel damage detection model and analyze the causes of parcel ***,using the dataset constructed based on the proposed method,a damage type detection model was trained,and its mean average precision was *** model can improve customer satisfaction and reduce return costs for parcel delivery companies.

关键词： Parcel delivery service damage detection damage classification data augmentation generative adversarial network

来源：评论

学校读者我要写书评

暂无评论

Communication-less Management Strategy for Electric Vehicle Charging in Droop-controlled Islanded Microgrids

引用

Journal of Modern Power systems and Clean Energy 2024年第4期12卷 1227-1238页

作者： Abdullah Azhar Al-Obaidi Mohammed Zaki El-Sharafy Hany E.Z.Farag Saifullah Shafiq Ali Al-Awami Independent Electricity System Operator(IESO) MississaugaCanada Department of Electrical Engineering and Computer Science York UniversityTorontoCanada University of Queensland StLucia QLD 4067Australia Department of Electrical Engineering King Fahd University of Petroleum&MineralsDhahranSaudi Arabia

Adopting high penetration levels of electric vehicles(EVs) necessitates the implementation of appropriate charging management systems to mitigate their negative impacts on power distribution networks. Currently, most of the proposed EV charging management techniques rely on the availability of high-bandwidth communication links. Such techniques are far from realization due to(1) the lack of utility-grade communication systems in many cases such as secondary(low-voltage) power distribution systems to which EVs are connected, rural areas, remote communities, and islands, and(2) existing fears and concerns about the data privacy of EV users and cyber-physical security. For these cases, appropriate local control schemes are needed to ensure the adequate management of EV charging without violating the grid operation requirements. Accordingly, this paper introduces a new communication-less management strategy for EV charging in droop-controlled islanded microgrids. The proposed strategy is autonomous, as it is based on the measurement of system frequency and local bus voltages. The proposed strategy implements a social charging fairness policy during periods when the microgrid distributed generators(DGs) are in short supply by allocating more system capacity to the EVs with less charging in the past. Furthermore, a novel communication-less EV load shedding scheme is incorporated into the management strategy to provide relief to the microgrid during events of severe undervoltage or underfrequency occurrences due to factors such as high loading or DG outages. Numerical simulations demonstrate the superiority of the proposed strategy over the state-of-the-art controllers in modulating the EV charging demand to counteract microgrid instability.

关键词： Charging battery management communication-less control droop control electric vehicle islanded microgrid

来源：评论

学校读者我要写书评

暂无评论

Preliminary Cognitive Modeling: Comparing Distraction-Based Cyber-Attacks and Alcohol-Related Impairments on Human Drivers 4

Preliminary Cognitive Modeling: Comparing Distraction-Based ...

引用

4th IEEE International Conference on Human-Machine systems, ICHMS 2024

作者： He, Fan Elhammady, Karim Fischmeister, Sebastian Burns, Catherine M. University Of Waterloo Department Of System Design Engineering WaterlooON Canada University Of Waterloo Department Of Electrical And Computer Engineering WaterlooON Canada

ISBN: (纸本)9798350315790

This research investigates the vulnerability and resilience of human cognitive processes in the context of rapidly advancing driving technologies susceptible to multi-modal cyber-attacks. By simulating scenarios where Advanced Driver Assistance systems (ADAS) are attacked to distract drivers, we aim to understand the decision-making process and cognitive limits affecting safe driving and to devise a systematic approach to assess cognitive impairments. Our simulations of three generic attack models revealed that attacks requiring complex cognitive processing pose greater risks than mere distractions. To assess human driver vulnerabilities in this rapidly evolving technological landscape, we utilized Blood Alcohol Concentration (BAC) levels as a benchmark. © 2024 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Development of a machine learning model for predicting abnormalities of commercial airplanes

引用

Data Science and Management 2024年第3期7卷 256-265页

作者： Rossi Passarella Siti Nurmaini Muhammad Naufal Rachmatullah Harumi Veny Fara Nissya Nur Hafidzoh Department of Computer Engineering Faculty of Computer ScienceUniversitas Sriwijaya30662Indonesia Intelligent System Research Group(ISysRG) Faculty of Computer ScienceUniversitas Sriwijaya30662Indonesia Department of Informatics Faculty of Computer ScienceUniversitas Sriwijaya30662Indonesia College of Engineering Studies Universiti Teknologi MARA(UiTM)Shah Alam40450Malaysia

Airplanes are a social necessity for movement of humans,goods,and *** are generally safe modes of transportation;however,incidents and accidents occasionally *** prevent aviation accidents,it is necessary to develop a machine-learning model to detect and predict commercial flights using automatic dependent surveillance–broadcast *** study combined data-quality detection,anomaly detection,and abnormality-classification-model *** research methodology involved the following stages:problem statement,data selection and labeling,prediction-model development,deployment,and *** data labeling process was based on the rules framed by the international civil aviation organization for commercial,jet-engine flights and validated by expert commercial *** results showed that the best prediction model,the quadratic-discriminant-analysis,was 93%accurate,indicating a“good fit”.Moreover,the model’s area-under-the-curve results for abnormal and normal detection were 0.97 and 0.96,respectively,thus confirming its“good fit”.

关键词： Automatic dependent surveillance-broadcast data Commercial airplanes accident Data-labeling Machine learning Prediction model

来源：评论

学校读者我要写书评

暂无评论

Multi‐granularity re‐ranking for visible‐infrared person re‐identification

引用

CAAI Transactions on Intelligence Technology 2023年第3期8卷 770-779页

作者： Yadi Wang Hongyun Zhang Duoqian Miao Witold Pedrycz Department of Computer Science and Technology Tongji UniversityShanghaiChina Key Laboratory of Embedded System and Service Computing Ministry of EducationShanghaiChina Department of Electrical and Computer Engineering University of AlbertaEdmontonAlbertaCanada System Research Institute Polish Academy of SciencesWarsawPoland

Visible‐infrared person re‐identification(VI‐ReID)is a supplementary task of single‐modality re‐identification,which makes up for the defect of conventional re‐identification under insufficient *** is more challenging than single‐modality ReID because,in addition to difficulties in pedestrian posture,camera shoot-ing angle and background change,there are also difficulties in the cross‐modality *** works only involve coarse‐grained global features in the re‐ranking calculation,which cannot effectively use fine‐grained ***,fine‐grained features are particularly important due to the lack of information in cross‐modality re‐*** this end,the Q‐center Multi‐granularity K‐reciprocal Re‐ranking Algorithm(termed QCMR)is proposed,including a Q‐nearest neighbour centre encoder(termed QNC)and a Multi‐granularity K‐reciprocal Encoder(termed MGK)for a more comprehensive feature *** converts the probe‐corresponding modality features into gallery corresponding modality features through modality transfer to narrow the modality *** takes a coarse‐grained mutual nearest neighbour as the dominant and combines a fine‐grained nearest neighbour as a supplement for similarity *** experiments on two widely used VI‐ReID benchmarks,SYSU‐MM01 and RegDB have shown that our method achieves state‐of‐the‐art ***,the mAP of SYSU‐MM01 is increased by 5.9%in all‐search mode.

关键词： computer vision recognition

来源：评论

学校读者我要写书评

暂无评论

Early Parkinson's Disease Detection and Classification using Machine Learning and Neutrosophic Sets

引用

Neutrosophic Sets and systems 2025年 82卷 873-886页

作者： Oudah, Hasan H. Metwaly, Ahmed A. Eassa, Mohamed Abdelhafeez, Ahmed Nagm, Ahmad M. Salama, Ahmed S. College of Arts Department of Journalism Ahl Al Bayt University Karbala Iraq Department of Computer Science Faculty of Computers and Informatics Zagazig University Zagazig44519 Egypt Computer Science Department Faculty of Information System and Computer Science October 6 University Giza12585 Egypt Applied Science Research Center Applied Science Private University Amman Jordan Department of Computer Engineering and Electronics Cairo Higher Institute for Engineering Computer Science and Management New Cairo Egypt

Optimizing therapy and rehabilitation for Parkinson's disease (PD) requires early identification and precise evaluation of the illness's course. However, there is disagreement about the best way to use gait analysis to categorize the severity of motor symptoms and identify early-stage Parkinson's disease. The precision of machine learning (ML) models in identifying early and intermediate stages of Parkinson's disease was assessed in this study. Six ML models are used in this study for the prediction of PD. Different metrics are used to evaluate ML models such as accuracy, precision, recall, f1-score, and AUC score. Then we propose a multi-criteria decision-making methodology (MCDM) to evaluate the ML models and select the best one. Two MCDM methods are used such as CRITIC method to compute the criteria weights and the TOPSIS method to rank the alternatives. These methods are used under the bipolar neutrosophic sets (BNSs) to deal with uncertainty information. The results show the support vector machine is the best ML model for the prediction of PD. © 2025, University of New Mexico. All rights reserved.

关键词： Neurodegenerative diseases

来源：评论

学校读者我要写书评

暂无评论

FUGAN: A GAN Based Facial Reconstructor for Accurate Unveiling of Hidden Faces 27th

FUGAN: A GAN Based Facial Reconstructor for Accurate Unveili...

引用

27th International Conference on Pattern Recognition, ICPR 2024

作者： Sadhukhan, Mrinmoy Bhattacharya, Indrajit Dutta, Paramartha Department of Computer and System Sciences Siksha Bhavana Visva Bharati Bolpur India Department of Computer Applications Kalyani Government Engineering College Kalyani India

ISBN: (纸本)9783031781711

Image-to-image translation has become a prominent trend in the field of computer vision. This innovative technique is widely employed for generating concealed facial features from given noise. It proves particularly useful in reconstructing obscured facial regions covered by masks. The underlying technology at the core of this method is the Generative Adversarial Network (GAN). The primary mechanism of GAN-based neural networks relies on an encoder-decoder structure combined with a discriminator network. The discriminator plays a crucial role in training the network to distinguish between authentic and generated images. FUGAN, a novel approach in this domain, incorporates a self-attention block and has demonstrated superior performance to other models. With an impressive SSIM and BRISQUE score of 0.928 and 27.990, respectively, FUGAN is at the forefront of achieving state-of-the-art results. The architecture of the FUGAN neural network is built upon the UNET framework, with modifications to enhance its effectiveness. These modifications involve increasing the network depth and incorporating batch instance normalization as a regularizer to achieve the desired outcomes. The resulting model attains a smaller size and exhibits high accuracy in image regeneration. This streamlined and efficient FUGAN model is well-suited for deploying low-resource Internet of Things (IoT) devices. Its capability to regenerate facial features from masked regions makes it instrumental in surveillance systems, detecting individuals wearing masks and reconstructing their facial details. Github link (FUGAN: https://***/mrinmoy-sadhukhan/FUGAN-model) of our work is provided. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gallium nitride

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：