检索结果-内蒙古大学图书馆

21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Gradinaru, Mihai Negru, Andrei Boiangiu, Costin-Anton Tarba, Nicolae Voncila, Mihai-Lucian Deaconescu, Razvan Adrian Politehnica University Faculty of Automatic Control and Computers Computer Science and Engineering Department Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The field of Optical Character Recognition (OCR) consists of techniques that are mainly focused on document image analysis. Aside from generating significant speedups of everyday procedures, OCR has a considerable role in the preservation of historical sources of information. Most of the World War 2 (WW2) documents are of great importance, especially with applications in virtual archives, museums, and research. The situation asks for an efficient, yet not aggressive, transcribing method using OCR tools. This paper describes an approach in the context of the given problem. The focus is oriented towards extracting the information from documents affected by their age, but with simpler structures, mainly split into paragraphs, such as letters and military reports. The approach is based on combining the results of multiple OCR engines, with the final objective of achieving better performance compared to the individual performance of each engine. © 2022 IEEE.

关键词： Engines

来源：评论

学校读者我要写书评

暂无评论

Increasing communication security for Bluetooth Medical Devices in eHealth systems 21

Increasing communication security for Bluetooth Medical Devi...

引用

21st RoEduNet Conference on Networking in Education and Research, RoEduNet 2022

作者： Contasel, Cristian Tranca, Dumitru-Cristian Palacean, Alexandru-Viorel Rosner, Daniel University Politehnica of Bucharest Faculty of Automatic Control and Computers Department of Computer Engineering Bucharest Romania

ISBN: (数字)9781665455282

ISBN: (纸本)9781665455282

The market of Medical Devices has an annual growth rate perspective of 5.4% in the 2022 - 2028 period. The growth rate is mainly supported by the increased usage of devices for chronic diseases prevention and for remote patient monitoring. The growth rate is also supported by the population's appetite for mobile devices. The continuously growing number of mobile devices has led to an increase in the number of cyber-attacks against them. In this paper we present Personal Medical Hub, an optimized security solution for Bluetooth enabled medical devices, that enhances data privacy and is aimed to offer protection against man-in-the-middle attacks and other security breaches and backdoors. © 2022 IEEE.

关键词： Cybersecurity

来源：评论

学校读者我要写书评

暂无评论

Deep Learning-Based Retinal Blood Vessel Segmentation Using U-Net Architecture

Deep Learning-Based Retinal Blood Vessel Segmentation Using ...

引用

E-Health and Bioengineering Conference (EHB)

作者： Ligia-Gabriela Boazu Marian-Alexandru Petraru Otilia Zvorișteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iași Iași Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Retinal blood vessel segmentation is an essential component in the diagnosis and monitoring of various ophthalmological conditions, such as diabetic retinopathy, glaucoma or macular degeneration, providing valuable information about the state of blood vessels and ocular blood circulation. Traditional methods for segmenting blood vessels from retinal images present certain limitations in terms of accuracy and robustness, especially under variable lighting conditions, the presence of artifacts or low-quality images. However, current techniques based on convolutional neural networks have demonstrated the ability to achieve precise and robust segmentations in a variety of conditions, outperforming traditional methods. Nevertheless, neural networks face challenges regarding the limited availability of retinal image datasets necessary for training and evaluating these solutions. In this paper we describe a solution for retinal blood vessel segmentation using the U-Net architecture. This neural network achieves impressive results even with very small datasets, demonstrating the efficiency and robustness of the U-Net architecture for retinal blood vessel segmentation.

关键词： Training Macular degeneration Image segmentation Neural networks Blood vessels Network architecture Retina Robustness Monitoring Biomedical imaging

来源：评论

学校读者我要写书评

暂无评论

Enhancing Learning and Therapy for Children with Autism: Innovative Activities with the NAO Robot

Enhancing Learning and Therapy for Children with Autism: Inn...

引用

E-Health and Bioengineering Conference (EHB)

作者： Iustina-Bianca Bulai Otilia Zvorişteanu Dept. of Computer Science and Engineering Faculty of Automatic Control and Computer Engineering “Gheorghe Asachi” Technical University of Iaşi Iaşi Romania

ISBN: (数字)9798331532147

ISBN: (纸本)9798331532154

Worldwide, autism affects 1 in 100 children, with diagnoses steadily rising since the 2000s. Romania lacks official statistics on autism prevalence, but global estimates suggest similarity. Children with autism struggle with social interactions and verbal communication, prompting interest in social robots for therapy and education. Tailored robot-assisted sessions offer potential for cognitive development, vocabulary enhancement, social interaction, and behavioral stimulation like concentration and attention. The NAO robot's user-friendly design, technical capabilities, and integrated features make it well-suited for these purposes. This paper presents activities that exemplify the concept of “learning through play,” allowing children to engage in exploration, experimentation, and effective learning in an enjoyable manner.

关键词： Autism Vocabulary Hospitals Social robots Education Biomedical engineering

来源：评论

学校读者我要写书评

暂无评论

Analysis of Radio Frequency and Ultraviolet Signals Emitted by Surface Partial Discharges 23

Analysis of Radio Frequency and Ultraviolet Signals Emitted ...

引用

23rd International Scientific Conference on Electric Power engineering, EPE 2023

作者： Koziol, Michal Kunicki, Michal Urbaniec, Ireneusz Nagi, Lukasz Kabot, Ondrej Klein, Lukas Opole University of Technology Faculty of Electrical Engineering Automatic Control and Informatics Opole Poland ENET Centre VSB - Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9798350335934

Partial discharges (PD) occurring in high-voltage insulation systems can cause equipment failures and pose safety hazards. Commonly used techniques for detecting and characterizing PD activity, especially on the surface of insulation systems, include radio frequencies signal analysis and detection of ultraviolet radiation emissions. The aim of the research work was to perform a comparative analysis of the signals emitted by surface partial discharges in radio frequencies and the phenomena accompanying ultraviolet radiation emissions, as well as indicating possible directions for further basic research aimed at building a knowledge base and improving measurement methods. This paper presents an analysis of VHF, UHF and UV signals emitted by surface PD generated under laboratory conditions. The obtained results confirm that radio frequencies and UV signal analysis can provide important information about the activity and surface location of PD, including information on the intensity and nature of PD. © 2023 IEEE.

关键词： Partial discharges

来源：评论

学校读者我要写书评

暂无评论

GMA: Gap Imputing Algorithm for time series missing values

引用

Journal of Electrical Systems and Information Technology 2023年第1期10卷 1-20页

作者： Khattab, Abd Alhamid Rabia Elshennawy, Nada Mohamed Fahmy, Mahmoud Computer and Automatic Control Departmaent Faculty of Engineering Tanta University Tanta Egypt

Data collected from the environment in computer engineering may include missing values due to various factors, such as lost readings from sensors caused by communication errors or power outages. Missing data can result in inaccurate analysis or even false alarms. It is therefore essential to identify missing values and correct them as accurately as possible to ensure the integrity of the analysis and the effectiveness of any decision-making based on the data. This paper presents a new approach, the Gap Imputing Algorithm (GMA), for imputing missing values in time series data. The Gap Imputing Algorithm (GMA) identifies sequences of missing values and determines the periodic time of the time series. Then, it searches for the most similar subsequence from historical data. Unlike previous work, GMA supports any type of time series and is resilient to consecutively missing values with different gaps distances. The experimental findings, which were based on both real-world and benchmark datasets, demonstrate that the GMA framework proposed in this study outperforms other methods in terms of accuracy. Specifically, our proposed method achieves an accuracy score that is 5 to 20% higher than that of other methods. Furthermore, the GMA framework is well suited to handling missing gaps with larger distances, and it produces more accurate imputations, particularly for datasets with strong periodic patterns.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Machine Learning-Based Calibration Approaches for Single-Beam and Multiple-Beam Distance Sensors

引用

IEEE Sensors Journal 2024年第1期24卷 975-983页

作者： Syu, Jia-Hao Lin, Jerry Chun-Wei Biernacki, Piotr Ziebinski, Adam National Taiwan University Department of Computer Science and Information Engineering Taipei10617 Taiwan Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Department of Distributed Systems and Informatics Devices Gliwice44-100 Poland Silesian University of Technology Department of Distributed Systems and Informatic Devices Gliwice44-100 Poland

Sensors are the foundation to facilitate smart cities, smart grids, and smart transportation, and distance sensors are especially important for sensing the environment and gathering information. Researchers have developed various methods to calibrate distance sensors;however, they mainly focus on using external information for calibration, which is inefficient and computationally expensive. To alleviate the above problems, we propose machine learning (ML)-based calibration approaches for distance sensors. We develop two calibration mechanisms, where the naive mechanism directly predicts the true distance, while the residual mechanism predicts the residual for calibration. The conventional ML regression algorithms are then adopted to predict the true distance or calibration residual. Experimental results show that the designed residual calibration mechanism outperforms the naive mechanism by reducing the root mean square error (RMSE) by 92.2% and mean absolute error (MAE) by 93.3% in the fitting task. In prediction, the proposed 2-D-residual mechanism achieves an improvement of 78.6% and 65.7% compared to the state-of-the-art method. The experimental results show the effectiveness and generalization of the proposed ML-based calibration method, especially for the 2-D mechanism, which achieves the highest robustness in all fitting and prediction tasks. © 2001-2012 IEEE.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

Designing Quantum-Resilient Blockchain Frameworks: Enhancing Transactional Security with Quantum Algorithms in Decentralized Ledgers

引用

International Journal of Advanced computer Science and Applications 2025年第4期16卷 618-628页

作者： Kale, Meenal R. Baker El-Ebiary, Yousef A. Sathiya, L. Burugari, Vijay Kumar Yulduz, Erkiniy Muniyandy, Elangovan Alanazi, Rakan Department of Humanities Yeshwantrao Chavan College of Engineering Hingna Nagpur India Faculty of Informatics and Computing UniSZA University Malaysia Department of CSE Panimalar Engineering College Chennai India Dept of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh Guntur India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Department of Biosciences-Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai India Applied Science Research Center Applied Science Private University Amman Jordan Department of Information Technology Faculty of Computing and Information Technology Northern Border University Rafha Saudi Arabia

Quantum computing is progressing at a fast rate and there is a real threat that classical cryptographic methods can be compromised and therefore impact the security of blockchain networks. All of the ways used to secure blockchain like Rivest–Shamir–Adleman (RSA), Elliptic Curve Cryptography (ECC) and Secure Hash Algorithm 256-bit (SHA256) are the characteristic of the traditional cryptographic techniques vulnerable to attack by quantum algorithms: Shor’s and Grover’s algorithms: can efficiently break asymmetric encryption and speed up brute force attacks. Because of this vulnerability, there exists a need to develop an advance quantum resilient blockchain framework to protect the decentralized ledgers from the future threats of the quantum. This research proposes Post-Quantum Cryptography (PQC), Quantum Key Distribution (QKD) and Quantum Random Number Generation (QRNG) as a formidable architectural integration, to fortify security of blockchain. Classical encryption is replaced with PQC, QKD with secure key exchange by detecting eavesdropping, and QRNG with improving cryptographic randomness to remove the predictable key vulnerability. Only with a small loss of transaction efficiency, we increase transaction encryption accuracy, key exchange security, and resistance to quantum attacks. In this quantum enhanced blockchain design, the idea is to preserve the decentralization, transparency and security and at the same time overcome the future quantum threat. By going through rigorous analysis and comparative evaluation, we demonstrate that the approach saves blockchain networks from the emerging quantum risks to make sure that the decentralized finance, smart contracts and cross chain transactions. © (2025), (Science and Information Organization). All rights reserved.

关键词： Quantum cryptography

来源：评论

学校读者我要写书评

暂无评论

Neurophysiological Test with Use of EEG, GSR and Pulse Measurements Data for Focus Group Beverage Preference Aggregation 11

Neurophysiological Test with Use of EEG, GSR and Pulse Measu...

引用

11th International Scientific Conference on computer Science, COMSCI 2023

作者： Andonov, Stanimir Georgiev, Stiliyan Tsenov, Georgi Mladenov, Valeri Management Faculty Technical University Economics Industrial Engineering and Managemen Department Sofia Bulgaria Validation - Vision Analysis Team Visteon Electronics Bulgaria Sofia Bulgaria Automatic Control Faculty Technical University Fundamentals of Theoretical Electrical Engineering Department Sofia Bulgaria

ISBN: (纸本)9798350325256

The primary objective in this case study is introduction of a testing methodology framework for assessing the effectiveness of different drinks and flavors through neuromarketing. The framework involves use of focus groups for evaluation of the neurophysiological reactions of participants to various stimuli and drawing statistically significant conclusions based on the results. In the last past decade, there has been an increase in the availability of affordable and easy-to-use biosensors that provides the possibility for affordable and easy to use real-time measurements of bio-signals, such as electroencephalography (EEG), galvanic skin response (GSR), and pulse. Also, with the recent ongoing increase of the computational capabilities the signal processing and analysis of the recorded biometric data can also be processed in real-time with relatively affordable and mobile hardware. By analyzing these signals and identifying an informative features that are derived statistically from group averaging and independent of individual user's deviations, it is possible to classify and then apply the measured brainwaves and other biometrics data in various applications. In this paper, the authors apply data from voltage potential electrodes EEG brainwaves, along with GSR and pulse in order to recognize the variation response levels among a sample focus group and the results for determination of their aggregated preferences on tested sample drinks. © 2023 IEEE.

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Noise Reduction in Industry Based on Virtual Instrumentation

引用

computers, Materials & Continua 2021年第10期69卷 1073-1096页

作者： Radek Martinek Rene Jaros Jan Baros Lukas Danys Aleksandra Kawala-Sterniuk Jan Nedoma Zdenek Machacek Jiri Koziorek Faculty of Electrical Engineering and Computer Science Department of Cybernetics and Biomedical EngineeringVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia Faculty of Electrical Engineering Automatic Control and InformaticsOpole University of TechnologyOpolePoland Faculty of Electrical Engineering and Computer Science Department of TelecommunicationsVSB–Technical University of Ostrava70800Ostrava-PorubaCzechia

This paper discusses the reduction of background noise in an industrial environment to extend *** the Industry 4.0 era,the mass development of voice control(speech recognition)in various industrial applications is possible,especially as related to augmented reality(such as hands-free control via voice commands).As Industry 4.0 relies heavily on radiofrequency technologies,some brief insight into this problem is provided,including the Internet of things(IoT)and 5G *** study was carried out in cooperation with the industrial partner Brose CZ spol.s.r.o.,where sound recordings were made to produce a *** experimental environment comprised three workplaces with background noise above 100 dB,consisting of a laser/magnetic welder and a press.A virtual device was developed from a given dataset in order to test selected commands from a commercial speech recognizer from *** tested a hybrid algorithm for noise reduction and its impact on voice command recognition *** virtual devices,the study was carried out on large speakers with 20 participants(10 men and 10 women).The experiments included a large number of repetitions(100 times for each command under different noise conditions).Statistical results confirmed the efficiency of the tested *** welding environment efficiency was 27%before applied filtering,76%using the least mean square(LMS)algorithm,and 79%using LMS+independent component analysis(ICA).Magnetic welding environment efficiency was 24%before applied filtering,70%with LMS,and 75%with LMS+*** workplace environment efficiency showed no success before applied filtering,was 52%with LMS,and was 54%with LMS+ICA.

关键词： 5G hybrid algorithms signal processing speech recognition

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：