检索结果-内蒙古大学图书馆

2023 International Conference on Cyber Management and engineering, CyMaEn 2023

作者： Salau, Ayodeji Olalekan Abeje, Bekalu Tadele Faisal, Abeer Naser Asfaw, Tesfa Tegegne Afe Babalola University Department of Electrical/Electronics and Computer Engineering Ado-Ekiti Nigeria Haramaya University College of Computing and Informatics Department of Information Technology Ethiopia Institute of Technology Faculty of Computing Bahir Dar University Department of Computer Science Ethiopia University of Sumer College of Computer Science and Information Technology Al-Rifai Iraq

ISBN: (纸本)9781665493291

Faba bean (Vicia faba L.) is an important cash crop for animal and human consumption in many countries, especially Ethiopia due to its high protein content and high rate of production. It also improves soil fertility with the help of bacteria, which forms nodules on its roots. Ethiopia is the second largest faba bean producer;however, according to research, the yield is generally low. Among the constraints contributing to low productivity of the crop, disease is the most important. Even though there are countermeasures such as the use of chemical sprays, which is used to reduce the damage or eliminate the disease, an effective disease identification technique is still required. Chocolate spot, faba bean gal, and rust are the most common diseases of faba beans. To effectively detect the disease, in this paper, we propose an end-to-end CNN model for training before and after the dataset is preprocessed. The CNN end-to-end model is trained with raw images and achieves 92.1% training accuracy. Also, the model is trained with preprocessed data and it achieves a training accuracy of 98.14% for the end-to-end CNN classifier. The results show that the proposed approach is suitable for faba bean disease detection and can be employed to detect diseases of other crops. © 2023 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Evaluating Beam Sweeping for AoA Estimation with an RIS Prototype: Indoor/Outdoor Field Trials

Evaluating Beam Sweeping for AoA Estimation with an RIS Prot...

引用

2025 IEEE Wireless Communications and Networking Conference, WCNC 2025

作者： Vordonis, Dimitris Kompostiotis, Dimitris Paliouras, Vassilis Alexandropoulos, George C. Grec, Florin University of Patras Electrical and Computer Engineering Department Greece National and Kapodistrian University of Athens Department of Informatics and Telecommunications Greece Noordwijk Netherlands

ISBN: (纸本)9798350368369

Reconfigurable Intelligent Surfaces (RISs) have emerged as a promising technology to enhance wireless communication systems by enabling dynamic control over the propagation environment. However, practical experiments are crucial towards the validation of the theoretical potential of RISs while establishing their real-world applicability, especially since most studies rely on simplified models and lack comprehensive field trials. In this paper, we present an efficient method for configuring a 1-bit RIS prototype at sub-6 GHz, resulting in a codebook oriented for beam sweeping;an essential protocol for initial access and Angle of Arrival (AoA) estimation. The measured radiation patterns of the RIS validate the theoretical model, demonstrating consistency between the experimental results and the predicted beamforming behavior. Furthermore, we experimentally prove that RIS can alter channel properties and by harnessing the diversity it provides, we evaluate beam sweeping as an AoA estimation technique. Finally, we investigate the frequency selectivity of the RIS and propose an approach to address indoor challenges by leveraging the geometry of environment. © 2025 IEEE.

关键词： beam sweeping field trials MIMO prototype radiation pattern Reconfigurable intelligent surfaces

来源：评论

学校读者我要写书评

暂无评论

Gray-Level Co-Occurrence Matrix and Geometric Shape for Classification of Rubber Tree Maturity 2

Gray-Level Co-Occurrence Matrix and Geometric Shape for Clas...

引用

2nd International Seminar on Machine Learning, Optimization, and Data Science, ISMODE 2022

作者： Saputra, Wanvy Arifha Ahyati, Inayatul Ulya Yunanto, Andhik Ampuh Noor, Syamsudin Asyikin, Arifin Noor Permadi, Dimas Fanny Hebrasianto Politeknik Negeri Banjarmasin Department of Informatics Engineering Banjarmasin Indonesia Politeknik Elektronika Negeri Surabaya Department of Informatics and Computer Engineering Surabaya Indonesia Politeknik Negeri Banjarmasin Department of Electrical Engineering Banjarmasin Indonesia Politeknik Negeri Banjarmasin Department of Smart Cities Information System Banjarmasin Indonesia Institut Teknologi Telkom Purwokerto Department of Informatics Engineering Purwokerto Indonesia

ISBN: (纸本)9781665455640

Rubber trees can be said to be mature by having a trunk circumference of more than 45 cm at the height of 130 cm from the ground. It influences the use of digital imagery to determine the classification of 'mature rubber trees' and 'immature rubber trees'. The challenge in the image of rubber trees is that they have similar colour characteristics between tree trunks and the ground, and multi-object rubber trees in one picture. We propose a method using the gray-level co-occurrence matrix (GLCM) and geometric shape for the classification of Rubber Tree Maturity. GLCM is used to measure neighbouring pixels with grey intensity, distance, and angle in solving the first characteristic problem. Geometric shapes used to solve the second characteristic problem with the help of determining a region of interest (ROI). The research results show that the proposed method was successfully carried out with the strongest evidence on the support vector machine (SVM), namely 0.800 f1-score, 0.778 precision and 0.824 recall. © 2022 IEEE.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Price Prediction of Seasonal Items Using Time Series Analysis

引用

computer Systems Science & engineering 2023年第7期46卷 445-460页

作者： Ahmed Salah Mahmoud Bekhit Esraa Eldesouky Ahmed Ali Ahmed Fathalla Faculty of Computers and Informatics Zagazig UniversitySharkeya44523Egypt Information Technology Department the University of Technology and Applied SciencesIbriOman School of Electrical and Data Engineering University of Technology SydneySydney2007Australia College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Computer Science Department Faculty of Computers and InformaticsSuez Canal UniversityIsmailia41522Egypt Higher Future Institute for Specialized Technological Studies Cairo3044Egypt Department of Mathematics Faculty of ScienceSuez Canal UniversityIsmailia41522Egypt

The price prediction task is a well-studied problem due to its impact on the business *** are several research studies that have been conducted to predict the future price of items by capturing the patterns of price change,but there is very limited work to study the price prediction of seasonal goods(e.g.,Christmas gifts).Seasonal items’prices have different patterns than normal items;this can be linked to the offers and discounted prices of seasonal *** lack of research studies motivates the current work to investigate the problem of seasonal items’prices as a time series *** proposed utilizing two different approaches to address this problem,namely,1)machine learning(ML)-based models and 2)deep learning(DL)-based ***,this research tuned a set of well-known predictive models on a real-life *** models are ensemble learning-based models,random forest,Ridge,Lasso,and Linear ***,two new DL architectures based on gated recurrent unit(GRU)and long short-term memory(LSTM)models are ***,the performance of the utilized ensemble learning and classic ML models are compared against the proposed two DL architectures on different accuracy metrics,where the evaluation includes both numerical and visual comparisons of the examined *** obtained results show that the ensemble learning models outperformed the classic machine learning-based models(e.g.,linear regression and random forest)and the DL-based models.

关键词： Deep learning price prediction seasonal goods time series analysis

来源：评论

学校读者我要写书评

暂无评论

A hybrid deep learning-based approach for rolling bearing fault prognostics

引用

IFAC-PapersOnLine 2023年第2期56卷 6588-6593页

作者： Domício Neto Lorena Petrella Jorge Henriques Paulo Gil Alberto Cardoso University of Coimbra Department of Informatics Engineering Centre for Informatics and Systems of the University of Coimbra (CISUC) Coimbra Portugal CTS-UNINOVA Department of Electrical and Computer Engineering NOVA School of Science and Technology Caparica Portugal

Predictive Maintenance (PdM) has the potential to revolutionize the industry by providing advanced techniques to assess the condition of an industrial system and yield key information that can help optimize maintenance planning and prevent unexpected faults and breakdowns. Nevertheless, PdM is far from being universally applied and it is still the subject of increasing research. Thus, developing new approaches has great relevance to help PdM become a practical reality for the industry. PdM can also bring benefits in terms of sustainability, by reducing human and material resources waste, which is one of the main objectives of Circular Manufacturing initiatives. In this context, rolling bearings are one of the most studied components, as most industrial systems with rotating mechanisms contain bearings, which are prone to a number of faults caused by natural and unnatural wear. In this work, an hybrid Deep Learning (DL) approach is proposed, combining a Convolutional Neural Network (CNN) with a Gated Recurrent Unit (GRU) network to predict Remaining Useful Life (RUL) using rolling bearing vibration data preprocessed with the Short-Time Fourier Transform (STFT). This model was trained and validated using the PRONOSTIA public dataset, which is a popular benchmark for rolling bearing prognostics. The obtained results are satisfactory, providing RUL estimates close to the true values in most test cases, proving the competitiveness of the approach and its potential.

关键词： Predictive Maintenance Circular Manufacturing Remaining Useful Life Rolling Bearings Deep Learning

来源：评论

学校读者我要写书评

暂无评论

An Efficient Text Recognition System from Complex Color Image for Helping the Visually Impaired Persons

引用

computer Systems Science & engineering 2023年第7期46卷 701-717页

作者： Ahmed Ben Atitallah Mohamed Amin Ben Atitallah Yahia Said Mohammed Albekairi Anis Boudabous Turki MAlanazi Khaled Kaaniche Mohamed Atri Department of Electrical Engineering College of EngineeringJouf UniversitySakakaSaudi Arabia Laboratory of Informatics Gaspard-MongeA3SIESIEE ParisCNRSGustave Eiffel UniversityFrance LETI ENISUniversity of SfaxSfaxTunisia Remote Sensing Unit College of EngineeringNorthern Border UniversityArarSaudi Arabia Laboratory of Electronics and Microelectronics(LR99ES30) University of MonastirTunisia Department of Computer Engineering and Networks College of Computer and Information SciencesJouf UniversitySakakaSaudi Arabia College of Computer Sciences King Khalid UniversityAbhaSaudi Arabia

The challenge faced by the visually impaired persons in their day-today lives is to interpret text from *** this context,to help these people,the objective of this work is to develop an efficient text recognition system that allows the isolation,the extraction,and the recognition of text in the case of documents having a textured background,a degraded aspect of colors,and of poor quality,and to synthesize it into *** system basically consists of three algorithms:a text localization and detection algorithm based on mathematical morphology method(MMM);a text extraction algorithm based on the gamma correction method(GCM);and an optical character recognition(OCR)algorithm for text recognition.A detailed complexity study of the different blocks of this text recognition system has been *** this study,an acceleration of the GCM algorithm(AGCM)is *** AGCM algorithm has reduced the complexity in the text recognition system by 70%and kept the same quality of text recognition as that of the original *** assist visually impaired persons,a graphical interface of the entire text recognition chain has been developed,allowing the capture of images from a camera,rapid and intuitive visualization of the recognized text from this image,and text-to-speech *** text recognition system provides an improvement of 6.8%for the recognition rate and 7.6%for the F-measure relative to GCM and AGCM algorithms.

关键词： Text recognition system GCM AGCM OCR color images graphical interface

来源：评论

学校读者我要写书评

暂无评论

Utilisation of Energy Storage System in Power System 11

Utilisation of Energy Storage System in Power System

引用

11th International Scientific Symposium on electrical Power engineering, ELEKTROENERGETIKA 2022

作者： Medved, Dušan Kolcun, Michal Király, Jozef Shavolkin, Olexandr Shvedchykova, Iryna Department of Electrical Power Engineering Electrical Engineering and Informatics Technical University of Košice Mäsiarska 74 Košice041 20 Slovakia Department of Computer Engineering and Electromechanics Kyiv National University of Technologies and Design Kyiv Ukraine

ISBN: (纸本)9788055341040

This paper deals with the contribution of energy storage system (ESS) to power system. According to a distribution network parameters there were implemented elements that are very popular and common in power system configuration. For that reason a power network consisted of sources such as wind farm, photovoltaic farm and in specific undesirable condition the distribution network connection as a backup was considered as a power source. Load, in this power system, was considered of constant power. During the simulation, there was implemented energy storage system that compensate the missing power until the specific state of discharge, when the connection to distribution system (DS) was implemented. Simulations were realized in Matlab/Simulink environment where 48-hours interval of various states of above mentioned elements cooperation was investigated. Results were analyzed and the recommendations were mentioned in conclusion. © 2022 Technical University of Košice.

关键词： Energy storage

来源：评论

学校读者我要写书评

暂无评论

Sensitive Content Detection in Social Networks Using Deep Learning Models and Explainability Techniques

Sensitive Content Detection in Social Networks Using Deep Le...

引用

Big Data, Cloud Computing, Data Science & engineering (BCD)

作者： Isidoros Perikos Computer Engineering and Informatics Department University of Patras Patras Greece Electrical and Computer Engineering Dept. Computer Technology Institute and Press “Diophantus” University of Peloponnese Patras Greece

ISBN: (数字)9798350394191

ISBN: (纸本)9798350394207

In the dynamic landscape of online social networks, recognizing sensitive content is essential for safeguarding user privacy, fostering inclusivity, and enhancing diversity awareness. Building on prior research, this study explores new dimensions and methodologies for detecting sensitive content. We examine the temporal evolution of sensitive content, revealing how patterns shift over time, and address cross-linguistic challenges, emphasizing cultural and contextual nuances in detection. We employ advanced machine learning techniques, including deep learning models and BERT that improve the accuracy and robustness of the detection procedure. In the experimental study, BERT transformer reported the best performance in detecting sensitive content in text. Additionally, we incorporate explainability techniques such as LIME and SHAP to provide deeper insights into the model's decision-making processes, ensuring predictions are interpretable and reliable. Our work enhances the theoretical framework of sensitive content detection in social networks and provide methods that are accurate and scalable and can facilitate the creation of user-centric interaction that prioritize privacy and user experience.

关键词： Deep learning Privacy Sensitivity Accuracy Social networking (online) Decision making Predictive models Transformers User experience Cultural differences

来源：评论

学校读者我要写书评

暂无评论

Using Linear Regression Model to Predict the Wholesale of the Electric Car in Indonesia: What Can Be Learned from the Model? 2nd

Using Linear Regression Model to Predict the Wholesale of th...

引用

2nd International Conference on Renewable Power, ICRP 2023

作者： Al-Hakim, Rosyid R. Soelaiman, Nur F. Riani, Sri Arief, Yanuar Z. Department of Electrical Engineering Faculty of Information Sciences and Engineering Jakarta Global University Kota Depok Indonesia Graduate School IPB University Bogor Indonesia Department of Computer and Informatics Jakarta State Polytechnic Depok Indonesia Faculty of Information and Communication Technology Universiti Teknikal Melaka Malacca Malaysia Department of Biology International Women University Bandung Indonesia Faculty of Biology Universitas Jenderal Soedirman Purwokerto Indonesia Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Malaysia Sarawak Sarawak Kota Samarahan Malaysia

ISBN: (纸本)9789819967483

We analyze wholesale datasets from Indonesian Automobile Industry Data for electric cars in Indonesia using statistical analysis to predict the electric cars used in the future. We apply a linear regression approach that adjusts the regression model according to wholesale electric cars between 2020 and 2022, as well as a statistical correlation test and the Wilcoxon test to support the regression result. We find a strong positive relationship for electric cars bought in the future, with a not significantly different population median of the total number of wholesale electric cars. It might be 210 cars estimated per year. Among the regression model, it is more effective for policymakers, as well as car industries. We estimate that there are various reasons and conditions for Indonesian people regarding buying electric cars inside conventional ones. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

来源：评论

学校读者我要写书评

暂无评论

Variant of Implementation of a Grid-Tied Solar-Wind System with a Storage Battery for Self-Consumption of Local Object 8

Variant of Implementation of a Grid-Tied Solar-Wind System w...

引用

8th IEEE International Conference on Energy Smart Systems, ESS 2022

作者： Shavolkin, Olexandr Shvedchykova, Iryna Kolcun, Michal Medved, Dusan Kyiv National University of Technologies and Design Department of Computer Engineering and Electromechanics Kyiv Ukraine Technical University of Kosice Faculty of Electrical Engineering and Informatics Košice Slovakia

ISBN: (数字)9798350334418

ISBN: (纸本)9798350399202

The purpose of the work is the improvement the technique of the parameter's choice and control of the solar-wind system. The calculation of the system parameters for the taken schedule of the load is considered in the example. The given values are the degree of reduction of electrical energy consumption from the grid and the use of installed power of the photovoltaic battery. The boundary modes of renewable energy sources generation are taken into account. The base is the calculated values of the average monthly generation of renewable energy sources and the dependency of distribution of energy of the photovoltaic battery for a month for five years according to the archival data. With a coefficient of installed power use close to 0.9, it is possible to have a ratio of the powers of a photovoltaic battery and a wind generator of 6.9:1 with an average value over 5 years of a decrease in consumption from the grid in December by 3.48 times. When generation is below the monthly average one, it is proposed to regulate the consumption of active power according to the forecast. This allows equalizing power consumption in the daytime with a reduction during peak hours. The formation of the SOC battery graph is carried out by taking into account the forecast for the next day. The modeling confirms the possibility of reducing the consumption of electricity from the grid from 2.5 times to the full exclusion of consumption. © 2022 IEEE.

关键词： Energy utilization

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：