检索结果-内蒙古大学图书馆

A preliminary study on design and development of template-based for license plate recognition system applying artificial coordinates auxiliary techniques

A preliminary study on design and development of template-ba...

引用

IEEE International Conference on Industrial Engineering and Engineering Management

作者： Bih-Yaw Shih Chen-Yuan Chen Jin-Wei Kuo Po-Wei Chen Tsung-Hao Chen Cheng-Wu Chen Pei-Yin Chung Wan-I Lee Department of Computer Science National Ping Tung University of Education Ping Tung Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Departments of Business Administration Shu Te University Kaohsiung Taiwan Institute of Maritime Information and Technology National Kaohsiung Marine University Taiwan Department of Information Management Meiho University Ping Tung Taiwan Marketing and Distribution Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan

With the rapid improvement of technology and economy, the percentage of transportation, like automobile, gradually increases. However, the number of cars increases, the methods of management stretches lots of problems, such as parking, traffic and thievery. Hence, Intelligent Transportation System (ITS) have been emphasized step by step and set up one after another around the world. In addition, ITS also established in Taiwan on July 20, 1998.

关键词： Licenses Image color analysis Image recognition Color Vehicles computer science

来源：评论

学校读者我要写书评

暂无评论

Backpropagation Network Optimization Using One Step Secant (OSS) Algorithm

引用

IOP Conference Series: Materials science and Engineering 2020年第1期769卷

作者： Solikhun Mochamad Wahyudi M. Safii Muhammad Zarlis Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Sumatera Utara Indonesia. Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

Education is one of the main indicators in national development efforts. The government in its efforts to realize national goals to educate the nation's life has made a policy for compulsory 9-year schools, namely elementary and junior high schools. To find out how many residents use the education facilities provided by the government can be seen through school enrollment rates (SPR). A high School Participation Rate (SPR) means showing greater opportunities to access education in general. This study aims to optimize artificial neural networks with the One Step Secant (OSS) algorithm. Artificial Neural Network (ANN) is part of the artificial intelligence system (Artificial Intelligence, AI) which is one of the artificial representations of the human brain that always tries to simulate the learning process in the human brain. The sample data used for optimization is SPR Indonesia data by province. Using 4 architectural models with 5 input variables, 1 shadow layer and 1 output. The best results obtained between architectures 5-4-1, 5-8-1, 5-16-1 and 5-32-1 are architectures 5-16-1. Obtained prediction accuracy comparisons using the One Step Secant (OSS) algorithm and standard algorithms namely 96.97% and 100%. The standard algorithm is superior in accuracy, the One Step Secant (OSS) algorithm is superior in terms of iterations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Resilient Algorithm In Predicting Fertilizer Imports by Major Countries

引用

IOP Conference Series: Materials science and Engineering 2020年第1期769卷

作者： Solikhun Mochamad Wahyudi M Safii Muhammad Zarlis Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Sumatera Utara Indonesia. Faculty of Computer Science and Information Technology Universitas Sumatera Utara Indonesia

In the last five years (2013-2017) Indonesia's fertilizer production experienced volatile growth, but overall tended to increase at a rate of 1.7% per year. The research aims to optimize artificial neural networks with a resilient backpropagation algorithm (Rprop), artificial neural networks are one of the artificial representations of the human brain that always tries to simulate the learning process in the human brain. Sample data used for optimization is fertilizer import data according to the main country of origin and uses 4 architectures, the best results are obtained between architectures 6-8-1, 6-12-1, 6-16-1, and 6-32-1 is architecture 6-32-1 with 100% accuracy.

关键词：

来源：评论

学校读者我要写书评

暂无评论

The Smart Analysis of Performing Scalable Inference for Big Data Analytics

The Smart Analysis of Performing Scalable Inference for Big ...

引用

International Conference on Power Energy, Environment and Intelligent Control (PEEIC)

作者： Vishakha D Bhandarkar Aruna Sri Rongali Mohamed Dawood Shamout Prof. Sachin Pund Gigih Forda Nama Shrishailappa Patil Applied Mathematics and Humanities Yeshwantrao Chavan College of Engineering India Graduate Doctoral Information Technology/Graduate (Information Technology Emphasis/Information Technology Ph.D.) University of The Cumberlands US Department of Management College of Business Administration University of Sharjah Sharjah United Arab Emirates Department of Industrial Engineering Shri Ramdeobaba College of Engineering and Management Nagpur Maharashtra India Department of Informatics Doctoral Program of Environtmental Science University of Lampung Bandar Lampung Computer engineering Vishwakarma Institute of Technology Pune

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the “performing Scalable Inference” technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way..

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhancing Blockchain Scalability: Innovative Solutions for Optimized Performance in Decentralized Networks

Enhancing Blockchain Scalability: Innovative Solutions for O...

引用

International Conference on Contemporary Computing and Informatics (IC3I)

作者： Akanksha Srivastav Sheenu Agarwal Arpit Jain Shikha Tayal Shalu Jain Khemraj Sharma Tula’s institute Dehradun U.K. India Department of Electronics and Communication Engineering Uttarakhand Technical University Dehradun U.K. India Department of Computer Science & Engineering Koneru Lakshamaiah Education Foundation Vadessahwaram A.P. India Department of Computer Science & Engineering Tula’s Institute Dehradun Uttarakhand India Maharaja Agrasen Himalayan Garhwal University Pauri Garhwal Uttarakhand Department: Department of Business Administration Doctoral Program in Management Sciences Nanhua University Dalin Chiayi R.O.C

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

A substantial number of people are presently making use of decentralised cryptocurrencies that are built on blockchain technology. These crypto currencies have garnered a lot of interest over the course of the last few years and are currently being used by their users. Being the first use of blockchain technology, Bitcoin has been a resounding success, which drives further research and improvement in the sector concerned with blockchain technology. Bitcoin was the first usage of blockchain technology. Bitcoin, on the other hand, is susceptible to significant performance issues due to the fact that it has a high transaction latency and a limited throughput. The operations of the cryptocurrency are considerably impacted as a result of these concerns. As a result of the fact that other cryptocurrencies that rely on proof-of-work also carry over its deficiencies, there has been an increase in the number of concerns about the scalability of blockchain technology. The fact that this is the case makes scaling blockchain technology more challenging. All during the course of this investigation, an effort is made to analyse and classify the various scaling mechanisms that are now being used for blockchains. In addition to this, we are going to look at a variety of various approaches and present a list of possible solutions to the issue of scalability that the blockchain technology is now dealing.

关键词： Hands computers Distributed ledger Scalability Bitcoin Throughput Proof of Work Fabrics Blockchains Informatics

来源：评论

学校读者我要写书评

暂无评论

Sonar-based obstacle avoidance using a path correction method for autonomous control of a biped robot for the Learning Stratification and Performance

Sonar-based obstacle avoidance using a path correction metho...

引用

IEEE International Conference on Industrial Engineering and Engineering Management, IEEM2010

作者： Tsai, Cheng-Hsuan Huang, Po-Hsuan Chou, Wei-Chung Shih, Chia-Hung Chen, Chen-Yuan Shih, Bih-Yaw Chang, Chin-Jui Chen, Cheng-Wu Chen, Tsung-Hao Lee, Wan-I. Chung, Pei-Yin Department of Computer Science National Pingtung University of Education No. 4-18 Ming Shen Rd. Pingtung 90003 Taiwan Doctoral Program in Management National Kaohsiung First University of Science and Technology Kaohsiung Taiwan Department of Information Management Transworld University No. 1221 Jen-Nang Road Chia-Tong Li Douliou Yunlin 64063 Taiwan Institute of Maritime Information and Technology National Kaohsiung Marine University No.142 Haijhuan Rd. Nanzih District Kaohsiung City 81143 Taiwan Departments of Business Administration Shu-Te University Yen Chau Kaohsiung 82445 Taiwan Marketing and Distribution Management National Kaohsiung First University of Science and Technology 2 Jhuoyue Rd. Nanzih Kaohsiung 811 Taiwan Department of Information Management Meiho University 23 Pingguang Rd. Neipu Pingtung Taiwan

ISBN: (纸本)9781424485031

In this paper, a simple path correction and obstacle avoidance method with a bipedal robot for the learning stratification and performance, using an ultrasonic sensor and electronic compass sensor, is proposed. This bipedal robot was comprised using the Lego NXT Intelligent Bricks. The proposed method is implemented on an autonomous humanoid robot (the ARSR). One ultrasonic sensor and one electronic compass sensor are installed on the ARSR to detect environmental information including obstacles, the distance to the obstacle, and the directional angle of the robot. Based on the obtained information, an obstacle avoidance and path correct method is proposed to decide the ARSR's behavior so that it can avoid obstacles and move effectively to the destination area. Obstacle avoidance experiments are carried out to confirm the effectiveness of the proposed method and confirm the learning stratification and performance. ©2010 IEEE.

关键词： Ultrasonic sensors

来源：评论

学校读者我要写书评

暂无评论

Synergizing Data Imputation and Electronic Health Records for Advancing Prostate Cancer Research: Challenges, and Practical Applications

arXiv

引用

arXiv 2023年

作者： Batouche, Abderrahim O. Czeizler, Eugen Koskinen, Miika Mirtti, Tuomas Rannikko, Antti S. Doctoral Programme in Computer Science University of Helsinki Helsinki Finland Research Program in Systems Oncology University of Helsinki Helsinki Finland ICAN-Digital Precision Cancer Medicine Flagship Helsinki Finland HUS Helsinki University Hospital Helsinki Finland Department of Pathology University of Helsinki Helsinki University Hospital Helsinki Finland Department of Urology University of Helsinki Helsinki University Hospital Helsinki Finland

The presence of detailed clinical information in electronic health record (EHR) systems presents promising prospects for enhancing patient care through automated retrieval techniques. Nevertheless, it is widely acknowledged that accessing data within EHRs is hindered by various methodological challenges. Specifically, the clinical notes stored in EHRs are composed in a narrative form, making them prone to ambiguous formulations and highly unstructured data presentations, while structured reports commonly suffer from missing and/or erroneous data entries. This inherent complexity poses significant challenges when attempting automated large-scale medical knowledge extraction tasks, necessitating the application of advanced tools, such as natural language processing (NLP), as well as data audit techniques. This work aims to address these obstacles by creating and validating a novel pipeline designed to extract relevant data pertaining to prostate cancer patients. The objective is to exploit the inherent redundancies available within the integrated structured and unstructured data entries within EHRs in order to generate comprehensive and reliable medical databases, ready to be used in advanced research studies. Additionally, the study explores potential opportunities arising from these data, offering valuable prospects for advancing research in prostate cancer. © 2023, CC BY.

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

Integrating Noise Classification and Speech Enhancement Model for Hearing Aids

Integrating Noise Classification and Speech Enhancement Mode...

引用

International SoC Design Conference, ISOCC

作者： Ying-Hsiu Hung Yen-Ching Chang Shin-Chi Lai Wen-Ho Juang Ming-Hwa Sheu Jeng-Dao Lee Dept. Electronics Engineering National Yunlin University of Science and Technology Douliu Taiwan Doctoral Degree Program in Smart Industry Technology Research and Development National Formosa University Huwei Taiwan Dept. Automation Engineering & Smart Machinery and Intelligent Manufacturing Research Center National Formosa University Huwei Taiwan Dept. Computer Science and Information Engineering National Formosa University Huwei Taiwan Dept. Automation Engineering National Formosa University Huwei Taiwan

ISBN: (数字)9798350377088

ISBN: (纸本)9798350377095

As the global population ages, the number of elderly people needing hearing aids is increasing. This paper proposed an architecture designed to enhance speech based on noise conditions. After noise types are identified by a Convolutional Neural Network (CNN) noise classification model, these noise conditions are combined with the noisy speech and input into a conditional Generative Adversarial Network (cGAN) for speech enhancement. The CNN noise classification model achieves an average recognition accuracy of nearly 92%, with a Kappa value as high as 0.88. The cGAN speech enhancement achieves lower error values in the Mel-Cepstral Distortion (MCD) measure. Although some parts of the human voice may be filtered out, the results demonstrate the potential development of the proposed algorithm.

关键词： Accuracy Noise Noise reduction Speech recognition Speech enhancement Hearing aids Classification algorithms Convolutional neural networks Human voice Older adults

来源：评论

学校读者我要写书评

暂无评论

Assessment of IT solutions used in the Hungarian income tax microsimulation system

引用

IOP Conference Series: Materials science and Engineering 2017年第1期166卷

作者： I. Molnar S. Hardhienata Retired Faculty 4990 Sentinel Dr. Bethesda MD USA. Department of Computer Science and Doctoral Program of Pakuan University INDONESIA.

This paper focuses on the use of information technology (IT) in diverse microsimulation studies and presents state-of-the-art solutions in the traditional application field of personal income tax simulation. The aim of the paper is to promote solutions, which can improve the efficiency and quality of microsimulation model implementation, assess their applicability and help to shift attention from microsimulation model implementation and data analysis towards experiment design and model use. First, the authors shortly discuss the relevant characteristics of the microsimulation application field and the managerial decision-making problem. After examination of the salient problems, advanced IT solutions, such as meta-database and service-oriented architecture are presented. The authors show how selected technologies can be applied to support both data- and behavior-driven and even agent-based personal income tax microsimulation model development. Finally, examples are presented and references made to the Hungarian Income Tax Simulator (HITS) models and their results. The paper concludes with a summary of the IT assessment and application-related author remarks dedicated to an Indonesian Income Tax Microsimulation Model.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improving the accuracy of k-nearest neighbor (k-NN) using Synthetic Minority Oversampling Technique (SMOTE) and Gain Ratio (GR) for imbalanced class data

引用

AIP Conference Proceedings 2023年第1期2714卷

作者： Adli A. Nababan Sutarman Muhammad Zarlis Erna B. Nababan Doctoral Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia

k-Nearest Neighbor (k-NN) has fairly good accuracy results on data with almost the same class (balanced), whereas for data whose class distribution is not balanced, the accuracy value of k-NN tends to be low, moreover k-NN does not differentiate each feature data, meaning that each feature has the same weight in determining the new data class so that before classifying the feature selection process it is necessary to select the features that are most relevant to the data class. In this research, to overcome this problem, we will propose a framework using the Synthetic Minority Oversampling Technique (SMOTE) method to solve the class imbalance problem and the Gain Ratio (GR) to perform feature selection, so that get a new dataset with a balanced class distribution and features relevant to class data. The datasets used in this research such as E-Coli, Glass, and New Thyroid. For objective results, the 10-fold-cross validation method will be used as an evaluation method with k values 1 to 10. The results of the research prove that SMOTE and GR can increase the accuracy of the k-NN method, where the highest increase occurred in the Glass dataset by a difference increase of 18.43%. The lowest increase in accuracy occurred in the new thyroid dataset with an increase of 8.73%. The increase in accuracy occurred in all datasets used with an average increase of 12.87

关键词：

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：