检索结果-内蒙古大学图书馆

UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2025年第1期87卷 21-34页

作者： Contașel, Cristian Rughiniș, Răzvan Trancă, Dumitru Cristian Țurcanu, Dinu Dept. of Computer Science and Engineering National University of Science and Technology POLITEHNICA Bucharest Romania Dep. of Software Engineering and Automatics Technical University of Moldova Chișinău Moldova

This study provides an innovative architectural model for e-Health systems that aims to improve cyber resilience while maintaining high availability under fluctuating traffic loads. We examined typical cybersecurity incidents in the field of e-Health, their correlations with architectural defects, and frequent design patterns in currently operational systems. A testing approach based on our research finds those weaknesses and proposes viable fixes. In this paper, a comprehensive support strategy for transitioning from conventional monolithic architectures to microservices is presented. This change makes use of cloud computing's vertical and horizontal scalability to maximize resource utilization while ensuring system reliability. We also discuss dep.oyment ideas for the new microservices, focusing on operational resilience and cybersecurity in e-Health environments. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Electronic health record

来源：评论

学校读者我要写书评

暂无评论

Vision Transformer Model for Gastrointestinal Tract Diseases Classification from WCE Images 8

Vision Transformer Model for Gastrointestinal Tract Diseases...

引用

8th IEEE International Conference on Image and Signal Processing and their Applications, ISPA 2024

作者： Bella, Faiza Berrichi, Ali Moussaoui, Abdelouahab University of m'Hamed Bougara Dep. of Computer Science LIMOSE Boumerdes Algeria University of Ferhat Abbes Setif I Dep. of Computer Science Setif Algeria

ISBN: (纸本)9798350309249

Accurate disease classification utilizing endoscopic images indeed poses a significant challenge within the field of gastroenterology. This research introduces a methodology for assisting medical diagnostic procedures and detecting gastrointestinal (GI) tract diseases by categorizing features extracted from endoscopic images using Vision Transformer (ViT) models. We propose three ViT-inspired models for classifying GI tract diseases using colon images acquired through wireless capsule endoscopy (WCE). The highest achieved accuracy among our models is 97.83%. We conducted a comparative analysis with three pre-trained CNN (Convolutional Neural Network) models namely, Xception, DenseNet121, and MobileNet, alongside recent research papers to validate our findings. © 2024 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

The State of the Art in Machine Learning-Based information Security: Identifying the Gaps 6

The State of the Art in Machine Learning-Based Information S...

引用

6th International Conference on Intelligent Computing in Data sciences, ICDS 2024

作者： Langa, Thobeka Venter, Hein S. University of Pretoria Dep. of Computer Science Pretoria South Africa

ISBN: (纸本)9798350351200

Machine Learning (ML) has emerged as a constantly evolving and powerful technology with the potential to transform the field of information security. Its ability to handle enormous quantities of data at high speeds, detect abnormalities, and automate efficient responses to security risks makes ML very promising in this domain. However, its application in the field of information security has not been extensively investigated, and a comprehensive understanding of existing research gaps in ML-based information security is still lacking. To accomplish this objective, the authors use previous publications to conduct an analysis of the machine learning techniques that have been adopted or explored within the field of information security. The outcome is then used to produce a state-of-The-Art paper, identifying areas where more research is required. © 2024 IEEE.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Real-Time Audio Analysis for Detection of Apnea Intervals in Health-Care System 10

Real-Time Audio Analysis for Detection of Apnea Intervals in...

引用

10th International Conference on Signal Processing and Intelligent Systems, ICSPIS 2024

作者： Vahdani, Alireza Rahmati, Mahdieh Sharifi, Mehdi Ghatee, Mehdi Amirkabir University of Technology Iran Dep. Of Math. And Computer Science Tehran Iran

ISBN: (纸本)9798331532543

Accurate detection of respiratory pauses is crucial in patients undergoing cataract surgery under sedation, as undetected pauses can lead to serious complications. Conventional monitoring techniques, such as pulse oximetry and capnography, often fail to detect respiratory pauses in a timely manner, limiting their effectiveness in high-stakes clinical settings. To address this gap, we propose an automated method leveraging tracheal sound analysis using a deep learning model based on ResNet18. Our approach incorporates signal processing techniques, noise reduction, Mel-spectrogram extraction, and data augmentation, to optimize the model's performance. The model was evaluated using multiple performance metrics, including AUC of the precision-recall curve, F1 score, etc. It achieved an AUC of 92.5% and an F1 score of 89% for the apnea class, demonstrating the system's potential for precise, real-time respiratory monitoring in clinical environments. © 2024 IEEE.

关键词： Image coding

来源：评论

学校读者我要写书评

暂无评论

Study on the Robotic Arm Trajectory Compensation System with Deviation Sensing 3

Study on the Robotic Arm Trajectory Compensation System with...

引用

3rd International Conference on Mechatronics and Automation technology, ICMAT 2024

作者： Liu, Chao-Chung Liu, Jun-Chi Liu, Chao-Shu Dep. of Computer Science Zhaoqing University Zhaoqing526061 China Dep. of Industrial Design National United University Miaoli360301 Taiwan Dep. of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan

ISBN: (纸本)9781643685649

Robotic arms play an important role in the automation industry. Robotic arms plan processing paths based on the shape of the workpiece. However, the processing path often deviates due to inaccurate placement of the workpiece. To solve the issue of deviations, this paper develops a trajectory compensation system for a robotic arm with offset perception. This system uses the concept of workpiece boundary projection and designs an offset calculation algorithm by comparing the dimensions of the workpiece drawings, correcting errors caused by missing corners of the workpiece. In terms of operation, the system uses photoelectric sensors to quickly scan the workpiece boundary and immediately calculate the displacement and rotational offset of the workpiece. Subsequently, when deviations occur due to different placement positions of the workpiece, the robotic arm's motion path and action must be corrected and compensated to maintain precision. Tests on selected workpieces show that the corrected rotational angle error is less than 0.4 degrees, and the translational error is less than 0.7 millimeters. Since these correction error values are lower than the 1.0 mm error threshold for the robotic arm's trajectory tracking control. The offset-sensing robotic arm trajectory compensation system developed in this study can satisfy the requirements of smart automation production lines and arrive at the manufacturer's application standards. © 2024 The Authors.

关键词： Robotic arms

来源：评论

学校读者我要写书评

暂无评论

Detecting 5G Signal Jammers with Autoencoders Based on Loose Observations

Detecting 5G Signal Jammers with Autoencoders Based on Loose...

引用

2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Varotto, Matteo Valentin, Stefan Tomasin, Stefano University of Padova Dep. of Information Engineering Padova Italy Darmstadt University of Applied Sciences Dep. of Computer Science Darmstadt Germany University of Padova Dep. of Information Engineering Dep. of Mathematics Padova Italy

ISBN: (纸本)9798350370218

Fifth-generation (5G) networks are prone to jamming attacks, which are particularly dangerous in mission-critical applications such as factory automation. In this paper, we present a simple method to detect jamming attacks with machine learning techniques operating on in-phase and quadrature (IQ) modulated signals. In particular, a convolutional autoencoder (CAE) learns the structure of the clean signal to distinguish it from jammed signals in real time. This approach requires only a loose synchronization to the OFDM symbol, while equalization and decoding are not necessary. Despite its simplicity, our technique has shown high detection rates in experiments on a 5G testbed. © 2023 IEEE.

关键词： 5G Convolutional Autoencoder IQ Signals Jamming Detection New Radio Wireless Intrusion Prevention

来源：评论

学校读者我要写书评

暂无评论

A Frontier-Based Exploration Approach Making Use of Jointly Updated Local and Global Trees 29

A Frontier-Based Exploration Approach Making Use of Jointly ...

引用

29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Tauler-Rossello, Antoni Garcia-Fidalgo, Emilio Ortiz, Alberto University of the Balearic Islands Dep. of Mathematics and Computer Science Palma Spain

ISBN: (纸本)9798350361230

In this work, we propose a 3D frontier-based exploration solution for aerial robots, focused on indoor and closed environments. Our approach provides fast and exhaustive frontier detection by expanding two trees, one local and other global, using a custom RRT algorithm. Furthermore, to enhance the expansion of the global tree, which is also used to compute paths through the environment, key branches of the local tree are joined to this structure. Moreover, in contrast to other solutions that make use of separate local and global planning processes, our strategy relies on a single-plan strategy, which permits involving frontiers found at both levels by the decision making process. Finally, to demonstrate the effectiveness of our solution, we compare its performance with GBPlanner2 in a challenging environment by using a simulated aerial robot. © 2024 IEEE.

关键词： Forestry

来源：评论

学校读者我要写书评

暂无评论

Investigation of a 7-Axis Suspended Robotic Arm for Automated Spraying System 3

Investigation of a 7-Axis Suspended Robotic Arm for Automate...

引用

3rd International Conference on Mechatronics and Automation technology, ICMAT 2024

作者： Liu, Chao-Chung Liu, Jun-Chi Liu, Chao-Shu Dep. of Computer Science ZhaoQing University ZhaoQing526061 China Dep. of Industrial Design National United University Miaoli360301 Taiwan Dep. of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan

ISBN: (纸本)9781643685649

This study successfully develops a 7-axis suspended robotic arm for an automated spraying system, considering factors such as flexible operation modes, spray area dimensions, workpiece geometry, and the degrees of freedom required for effective operation. By using SolidWorks software for verification, the endpoints of the robotic arm can reach all positions within the workspace. The design and fabrication of the arm are completed according to specifications for structural strength, load capacity, rated torque output, and rotational speed. Kinematic analyses, both forward and inverse, are applied to determine the posture and position of the 7-axis robotic arm, facilitating the planning and design of the spraying trajectory. The control system architecture utilizes a multi-axis servo control board, integrated with a manifold deformation control method for trajectory tracking. Simulations and experiments are conducted to use a car shell workpiece provided by the manufacturer. The results from the simulations of MATLAB analyses show that the maximum tracking error is less than 0.4 mm. In experiments with the robotic arm, the maximum error is less than 0.7 mm. The results of the simulation and experiment are quite close, indicating that the deformation control method effectively operates the posture and movement of the 7-axis suspended robotic arm. Therefore, the 7-axis suspended robotic arm developed in this study will be effectively utilized in the production line of the automated spraying system. © 2024 The Authors.

关键词： MATLAB

来源：评论

学校读者我要写书评

暂无评论

Automated Validation of Spatial Data 32

Automated Validation of Spatial Data

引用

32nd International Conference on Software, Telecommunications and computer Networks, SoftCOM 2024

作者： Salgado, Joao Victor T. Vinicius, Demostenes Z. Rodriguez Dias, Vitor Dos S. Rosa, Renata L. Univ. of Lavras Federal Dep. of Computer Science Minas Gerais Brazil

ISBN: (纸本)9789532901382

Spatial databases, are often based on relational database management systems (RDBMS), to incorporate geographical data essential for data planning and optimization. However, maintaining the integrity of spatial data poses challenges, particularly in enforcing topological rules and preventing performance degradation during query execution. In this context, we propose an automated geometry validation application tailored for database environments, complemented by a user-friendly web-based interface. Our solution addresses the issue of invalid geometries often encountered in datasets, enhancing the reliability and efficiency of spatial database operations. Through performance and accuracy evaluations, we demonstrate the effectiveness of our approach in improving the overall user experience and trust in data planning processes with minimal implementation efforts. © 2024 University of Split, FESB.

关键词： Data integrity

来源：评论

学校读者我要写书评

暂无评论

Logistic Regression Classification for Assessing the Risk of Kidney Tumor 2

Logistic Regression Classification for Assessing the Risk of...

引用

2nd International Engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Alzubi, Dalia Al Mamlook, Rabia Emhamed Nasayreh, Ahmad Aljaidi, Mohammad Alazab, Rami Gharaibeh, Hasan Al-Naamneh, Qais Concordia University Dep. Information and Systems Engineering Montreal Canada Trine University Dep. of Business Administration IN United States University Zawia Department of Industrial Engineering Tripoli Libya Yarmouk University Dep. Computer Science Irbid Jordan Zarqa University Dep. of Computer Science Zarqa Jordan Jordan University of Science and Technology Dep. Surgery and Urology Irbid Jordan Applied Science Private University Dep. of Cyber Security Amman Jordan

ISBN: (纸本)9798350373363

The kidneys have the important function of filtering waste products and toxins from the blood in the human body. Any problems affecting the kidneys can potentially impact their efficiency and overall function. Kidney Tumor (KT) is a disease that specifically affects kidney cells and causes the abnormal growth of tissue in one or both kidneys. Assessing the risk of developing a kidney tumor and identifying the key factors that contribute to this risk are crucial for ensuring patient well-being. Additionally, this information assists doctors and specialists in making faster and more accurate diagnoses, determining appropriate treatment methods, and potentially influencing the course of the disease to minimize its severity and impact. Machine learning algorithms have recently been introduced to evaluate disease risks, and in this study, we specifically focus on examining the risk of kidney tumor development and investigating the influencing factors. We employed a logistic regression model to predict if a patient is at risk of developing a kidney tumor or not, and further categorized the samples into high-risk and low-risk groups. Our model was trained and tested using a unique dataset obtained from the (KAUH) hospital in Jordan, consisting of well-balanced metadata from 120 patients with kidney issues. Our work demonstrated accuracy results ranging from 90% to 98%. Ultimately, specialists can utilize our model as an additional tool to enhance the speed and accuracy of patient diagnoses © 2023 IEEE.

关键词： Tumors

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：