检索结果-内蒙古大学图书馆

2024 International Conference on Advances in Computing, Communication, electrical, and Smart Systems, iCACCESS 2024

作者： Cheragee, Sheikh Hasib Pall, Shuvo Chandra Kanchan, Muntasir Hasan Islam, Md. Samiul Tarek, Muhammad Masud Joy, Shoriful Huq Rahman, Md Toufiqur Bangladesh University of Engineering and Technology Electrical and Electronic Engineering Dhaka Bangladesh State University of Bangladesh Computer Science and Engineering Dhaka Bangladesh University of Rajshahi Electrical and Electronic Engineering Rajshahi Bangladesh

ISBN: (纸本)9798350350289

Planning and managing a power grid relies heavily on accurate predictions of future load. Operational choices involving resource utilization, infrastructural management, implementation schedule planning, investment plans, and maximizing power use while minimizing waste due to under or over-generation all rely on load prediction. In this study, it is utilized three different machine learning algorithms for medium- and short-term load forecasting, namely K-Nearest Neighbors (KNN) based Regression, Random Forest (RF) based regression, and Decision Tree (DT) Regression, to see how well these methods work on half-hourly historical electricity load data from the Bangladesh Power system (BPS) network, which can be found on the Power Grid Company of Bangladesh (PGCB) website and was downloaded between January 2021 and December 2022. To determine the most appropriate method for load forecasting of BPS, a comparison is made between the three approaches concerning the accuracy, mean absolute percentage error (MAPE), root means squared error (RMSE), and mean squared error (MSE). According to the findings, the RF model is superior to the others in making short- and medium-term forecasts due to its greater accuracy, minimal MSE, RMSE, and MAPE. © 2024 IEEE.

关键词： Decision trees

来源：评论

学校读者我要写书评

暂无评论

Human Tissue Cell Image Segmentation optimization Algorithm Based on Improved U-net Network 6

Human Tissue Cell Image Segmentation optimization Algorithm ...

引用

6th International Conference on Information and computer Technologies, ICICT 2023

作者： Ying, Jie Jing, Xin Qin, Chenyang Huang, Wei University of Shanghai for Science and Technology School of Optical Electrical and Computer Engineering Shanghai200093 China

ISBN: (纸本)9798350300956

In medical testing and diagnosis, cells as the basic structure of human body, have received extensive attention in pathological research. The detection and segmentation of cells or nuclei play an important role in describing molecular morphological information. The accuracy of human tissue cells segmentation still needs to be improved, and the network segmentation results have boundary blurring and noise pixels interference. In this paper, an improved U-net network model is proposed. Aiming at the problem of simple stacking of the same convolution operation, a parallel structure for multi-scale image feature extraction is designed. Through the setting of multiple convolution operations and combining different feature fusion methods, a better convolution block structure is obtained. The network segmentation image is optimized through the secondary segmentation of Otsu method and morphological processing, and the final segmentation result is obtained. Finally, the cell contour and centroid are displayed on the original image, and the nuclear center was calculated by image moment. The experiments were carried out on the human organ H&E cell data set. The experimental results show that the Dice coefficient, Jaccard similarity coefficient, recall and accuracy of the improved U-net network model for H&E cell image segmentation reach 0.8260, 0.60, 0.8380 and 0.8270 respectively. Compared with U-net network, the above parameters of the improved U-net model are increased by 1.7%, 3.9%, 1.2% and 2.2% respectively. Compared with CNN network, the accuracy rate is improved by 3.5%, and cell segmentation is more accurate than other literatures. © 2023 IEEE.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Using Peer Grading to Improve the Objectivity of Grades in GUI Design Courses 65

Using Peer Grading to Improve the Objectivity of Grades in G...

引用

65th International Symposium ELMAR, ELMAR 2023

作者： Romic, Kresimir Leventic, Hrvoje Mandic, Laura Galic, Irena Faculty of Electrical Engineering Computer Science and Information Technology Osijek OsijekHR-31000 Croatia

ISBN: (纸本)9798350325126

This paper deals with examining the possibility of peer grading when ranking graphical user interface (GUI) design images. The assessment was made on real images created by students on a GUI design course. Students' assignments to design a graphical user interface were being subjected to pairwise comparison and ranking was made based on pairwise comparison matrix. Obtained students' ranking was compared to experts' opinion using Spearman's and Kendall's metrics. The results suggest the possibility of using students' peer to peer grades to obtain objective rank from their subjective comparisons. © 2023 IEEE.

关键词： Graphical user interfaces

来源：评论

学校读者我要写书评

暂无评论

Configurable Dynamics of Electromagnetic Suspension by Fuzzy Takagi-Sugeno Controller 21st

Configurable Dynamics of Electromagnetic Suspension by Fuzzy...

引用

21st Polish Control Conference, PCC 2023

作者： Pilat, Adam Krzysztof Milanowski, Hubert Bieszczad, Rafal Sikora, Bartiomiej Faculty of Electrical Engineering Automatics Computer Science and Biomedical Engineering Department of Automatic Control and Robotics AGH-University of Science and Technology Krakow Poland

ISBN: (纸本)9783031351693

This elaboration presents the synthesis of the Takagi-Sugeno type Fuzzy Logic controller realizing the programmable parameters of the state feedback controller together with the steady state current for the active magnetic levitation system. Closed-loop dynamics was calculated precisely with respect to the requested dynamics. Two cases were considered: fixed-and variable-closed-loop dynamics. The Fuzzy Logic Controller was considered under four scenarios with linear, nonlinear, and constant in-range output. The study was supported by simulations and experimental investigations. The position of the levitating sphere stands as an illustration of the system in operation. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Dynamics

来源：评论

学校读者我要写书评

暂无评论

A Comparative Analysis of Multi-Plant Disease Detection and Classification Using Neural Network Architectures

A Comparative Analysis of Multi-Plant Disease Detection and ...

引用

2024 IEEE International Women in engineering (WIE) Conference on electrical and computer engineering, WIECON-ECE 2024

作者： Majumder, Sweety Rani Islam, Akib Jayed Salehin, Sultanus Bhowmik, Subashis Roy Amrine, Taofica Nur, Shafayet Port City International University Computer Science and Engineering Chattogram Bangladesh Norwegian University of Science and Technology Computational Colour and Spectral Imaging Gjovik Norway The University of Alabama Electrical and Computer Engineering Tuscaloosa United States

ISBN: (纸本)9798331535476

Plant diseases severely impact agriculture and economies, causing significant c rop l osses. E arly a nd accurate detection is essential to minimize damage and spread. Traditional manual inspection methods are time-consuming and error-prone, highlighting the need for automated solutions. This research investigates the use of neural networks for multi-plant disease detection and classification t o p romote s ustainable agriculture. Data from bell peppers, potatoes, tomatoes, rice, and maize were preprocessed through scaling, grayscale conversion, and augmentation. Multiple deep learning models, including CNN, MobileNetV2, VGG16, Hybrid CNN-LSTM, InceptionV3, and EfficientNetB3, w ere e valuated. A mong t hese, EfficientNetB3 consistently outperformed others, achieving notable accuracy rates using an 80-20% data split: 99.59% for bell peppers, 98.04% for potatoes, 92.52% for tomatoes, 97.52% for rice, and 96.25% for maize. For the 70-30% split, EfficientNetB3 achieved 94% for bell peppers and 84% for potatoes, while for the 90-10% split, it maintained competitive performance with 89% for bell peppers and 90% for potatoes. Video classification using EfficientNetB3 f urther d emonstrated i ts e ffectiveness in identifying diseases. These findings u nderscore t he p otential of EfficientNetB3 in enhancing plant disease detection accuracy and efficiency, c ontributing t o s ustainable a gricultural practices. © 2024 IEEE.

关键词： Fruits

来源：评论

学校读者我要写书评

暂无评论

OH-DRL: An AoI-Guaranteed Energy-Efficient Approach for UAV-Assisted IoT Data Collection

引用

IEEE Transactions on Wireless Communications 2025年第6期24卷 5009-5022页

作者： Yang, Bowen Yu, Yao Hao, Xin Yeoh, Phee Lep Zhang, Junxiong Guo, Lei Li, Yonghui Northeastern University School of Computer Science and Engineering Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110819 China Deakin University School of Information Technology VIC Melbourne3216 Australia University of the Sunshine Coast School of Science Technology and Engineering QLD Sunshine Coast4556 Australia Chongqing University of Posts and Telecommunications School of Communication and Information Engineering Chongqing400065 China The University of Sydney School of Electrical and Computer Engineering SydneyNSW2006 Australia

In this paper, we propose a hierarchical optimization approach that guarantees the maximum age of information (AoI) for uncrewed aerial vehicle (UAV) assisted Internet-of-Things (IoT) data collection. Our model is based on an energy-efficient simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) beamforming model. We formulate the optimization to minimize the UAV flight energy consumption subject to a maximum average AoI threshold by optimizing the UAV trajectory, IoT device scheduling, and STAR-RIS beamforming. To solve this, we develop an optimization-based hierarchical deep reinforcement learning (OH-DRL) algorithm that decomposes the formulated problem into an inter-cluster UAV visiting policy and STAR-RIS-based intra-cluster IoT scheduling policy. In OH-DRL, we jointly optimize the two policies in a high-level loop and a low-level loop, respectively. In the high-level loop, we design an AoI-guided DRL algorithm to determine the AoI-guaranteed UAV hovering position with minimal flight distance. In the low-level loop, a semidefinite relaxation (SDR)-based optimization algorithm further reduces the UAV’s flying time by minimizing the average AoI. Simulation results validate that OH-DRL achieves better convergence performance and energy-saving efficiency across different network scales. Compared to the state-of-the-art DRL algorithm, OH-DRL reduces the UAV flight energy consumption by 14.4% and decreases the number of training episodes required for convergence by 66% © 2002-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

Distributed Super-Twisting Sliding Mode Protocol for Formation and Tracking of Multiple Quadcopters 11

Distributed Super-Twisting Sliding Mode Protocol for Formati...

引用

11th IEEE Region 10 Humanitarian technology Conference, R10-HTC 2023

作者： Modi, Akash Joshi, Nikita Mehta, Axaykumar Institute of Infrastructure Technology Research And Management Electrical and Computer Science Engineering Ahmedabad380026 India

ISBN: (纸本)9798350326147

In this paper, a distributed super-twisting sliding mode protocol (DSTSM) is designed for achieving the formation and tracking of non-linear model of multiple Quadcopters using multiagent system (MAS) concept. The undirected graph theory and leader-follower protocol is used to establishing the communication between the neighborhood Quadcopters and achieving the formation. The protocol is validated for the formation of five Q uadcopters f or t he given pattern. T he stability 0 f the formation protocol is also ensured using the Lyapunov function. The simulation results show that the formation is achieved in finite time a nd tracking t he predefined tr ajectory. Al so, the protocol is robust against disturbance and parameter variation. © 2023 IEEE.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Massive Natural Language Processing in Distributed Environment 20th

Massive Natural Language Processing in Distributed Environm...

引用

20th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2023

作者： Krechowicz, Adam Faculty of Electrical Engineering Automatic Control and Computer Science Kielce University of Technology Kielce Poland

ISBN: (纸本)9783031383175

Natural Language Processing (NLP) models are one of the most promising topics nowadays. Applications like ChatGPT uncover the power of such models and their broad applications. However, developing such models requires an extensive amount of training data sets to operate on. As such data sets grow, it becomes impossible to process them on a single machine, even using parallel computations. In this paper, the problem of distributing the NLP computations is taken into consideration. The Scalable Distributed Two-Layer Data Structures were used to organize the distributed environment. Stanford Core NLP library was used to perform accurate NLP computations. The experiments focused on the efficiency of the computation in the distributed environment and the accuracy of the predictions in relation to the scale of the distributions. The results clearly show that an increase in performance can be obtained without a significant decrease in accuracy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Natural language processing systems

来源：评论

学校读者我要写书评

暂无评论

DRL-Based Satellite Network Slice Planning and Handover in the Korean Peninsula Scenarios 14

DRL-Based Satellite Network Slice Planning and Handover in t...

引用

14th International Conference on Information and Communication technology Convergence, ICTC 2023

作者： Kim, Seonghoon Kim, Taeyeoun Kwak, Jeongho Choi, Jihwan P. Korea Advanced Institute of Science and Technology Dept. of Aerospace Engineering Korea Republic of Daegu Gyeongbuk Institute of Science and Technology Dept. of Electrical Engineering and Computer Science Korea Republic of

ISBN: (纸本)9798350313277

This paper introduces a novel approach using deep reinforcement learning (DRL) to enhance network slicing planning and handovers in satellite networks. We propose a proactive handover trigger based on remaining service time and employ the deep deterministic policy gradient (DDPG) algorithm to maximize the utility of virtual networks (VNs). Focusing on the Korean Peninsula, we simulate a low earth orbit (LEO) satellite network based on Starlink satellite specifications and demonstrate the superiority of our intelligent network management technique compared to baseline methods, particularly in terms of latency performance and the number of handovers. © 2023 IEEE.

关键词： deep reinforcement learning handover Satellite network satellite network slicing planning

来源：评论

学校读者我要写书评

暂无评论

A Comparison and Evaluation of Named Entity Recognition Methods in Thai Traditional Medicine Texts 13

A Comparison and Evaluation of Named Entity Recognition Meth...

引用

13th International electrical engineering Congress, iEECON 2025

作者： Phungjununt, Warodom Lee, Wilaiporn Prayote, Akara Pipanmekaporn, Luepol Srisomboon, Kanabadee King Mongkut's University of Technology North Bangkok Faculty of Engineering Department of Electrical and Computer Engineering Bangkok10800 Thailand King Mongkut's University of Technology North Bangkok Faculty of Applied Science Department of Computer and Information Science Bangkok10800 Thailand

ISBN: (纸本)9798331543952

The knowledge extraction and transliteration processes for the Thai traditional medicine documents requires experts to extract information from the textbook and spend a plenty of time. To reduce the complexity of these processes, the named entity recognition (NER) from the machine learning principle is applied to extract the key information from the document. In this work, three NER models including, CRFSuite, Bi-LSTM-CRF, and pre-trained model (WangchanBERTa) are considered the accuracy of each model of NER for the Thai traditional documents. After the testing process, the experimental results show that CRFSuite model is the most computationally efficient model and deliver high precision and recall. Moreover, CRFSuite model has the highest scores of each entity. While the accuracy of the WangchanBERTa model is the highest and faster convergence in the training process. Although the results from the Bi-LSTM-CRF model provide moderate accuracy, the Bi-LSTM-CRF can detect the common entities higher than other models. © 2025 IEEE.

关键词： Natural language processing systems

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：