检索结果-内蒙古大学图书馆

A deep learning-based model for automated STN localization using local field potentials in Parkinson’s disease

Soft Computing 2025年第4期29卷 2343-2362页

作者： Hosny, Mohamed Naeem, Mohamed A. Zhu, Minwei Gao, Wenpeng Elshenhab, Ahmed M. Fu, Yili Department of Electrical Engineering Benha Faculty of Engineering Benha University Benha Egypt State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin150080 China Department of Mechatronics and Robotics Engineering Faculty of Engineering South Valley University Qena Egypt First Affiliated Hospital Harbin Medical University Harbin150001 China School of Life Science and Technology Harbin Institute of Technology Harbin150080 China Department of Mathematics Faculty of Science Mansoura University Mansoura35516 Egypt

Accurate identification of the subthalamic nucleus (STN) borders is time-consuming, relying heavily on the neurosurgeon expertise in manually interpreting the electrophysiological signals. Local field potentials (LFPs) have garnered imperative attention due to their strong correlation with the STN. However, existing detection models often face challenges with high computational complexity, hyperparameter optimization and lack of explainability, making them unreliable for clinicians. Therefore, this study introduces an explanatory framework using convolutional neural networks (CNN) for detecting the STN region from LFPs. Continuous wavelet transform is employed to convert LFPs signals into scalogram images, which are then processed by sixteen CNN models. We evaluated our framework by examining the impact of various limiting factors on the classification performance, including model size, learning rate (LR), optimizers and data scaling. Deep features are extracted from the top-performing CNN architectures to capture rich representations of the scalograms. These features are then fused and classified using k-nearest neighbour algorithm. Gradient-weighted class activation mapping is used to explain the decisions made by the proposed model. Our approach achieved an accuracy of 99.61%, outperforming individual CNN models for STN localization. The experimental results revealed that CNN models, embedded with additional hyperparameters and layers, generally outperformed smaller models. Besides, low LR significantly enhanced the performance compared to high LR. Moreover, features extracted from untuned networks produced lower performance than tuned networks. The proposed system could revolutionize deep brain stimulation surgery by increasing efficiency and reducing reliance on clinician expertise for STN detection. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

Development of Automatic Cartesian Robot Cannabis Seeder using LabVIEW 10

Development of Automatic Cartesian Robot Cannabis Seeder usi...

引用

10th International Conference on Digital Arts, Media and technology and 8th ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunications engineering, ECTI DAMT and NCON 2025

作者： Kosarat, Rujipan Sangwai, Keattipoom Wongjan, Anan Rajamangala University of Technology Lanna Faculty of Engineering Department of Software Engineering Chiangmai Thailand Rajamangala University of Technology Lanna Faculty of Engineering Department of Electronic Engineering and Automatic Control Systems Chiangmai Thailand

ISBN: (纸本)9798331543273

This article describes the invention of autonomous cannabis seeding equipment to reduce contamination and planting time. The automated cannabis seeder employs an NI myRIO control board to operate a y-axis stepper motor attached to a ball screw to move along the breadth of each row of 14 seed trays. Soil drilling and burial Drill all holes at the same depth. This promotes seed germination and lowers human-seed germ contamination. These 7 soil drill heads and 7 seeders use 3D printers to design and shape the workpiece. An 800-watt air pump smokes the cannabis seeds. Linear electric motors function in two rows in the z-axis. The buffer reverses the drowning process from row 14 to the first row, starting from the 3rd row and continuing through the final series of steps until 14 rows in the y-axis are complete. The hardware controls all program activities in LabVIEW. We tested the automated cannabis seeding machine 100 times on average, sowing cannabis seeds into 98 seed trays and dropping 93 seeds at 94.80% efficiency in 10.38 minutes. A 16 percent faster machine than human work is available. © 2025 IEEE.

关键词： Stepping motors

来源：评论

学校读者我要写书评

暂无评论

A review on computational fluid dynamics modeling of fixed-bed biomass gasifiers: Recent advances and design analysis

引用

International Journal of Hydrogen Energy 2025年 130卷 654-671页

作者： Ngamsidhiphongsa, Nathada Limleamthong, Phantisa Prasertcharoensuk, Phuet Arpornwichanop, Amornchai Center of Excellence in Process and Energy Systems Engineering Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand Department of Chemical Engineering Faculty of Engineering Kasetsart University Bangkok10900 Thailand Bio-Circular-Green-economy Technology & Engineering Center Department of Chemical Engineering Faculty of Engineering Chulalongkorn University Bangkok10330 Thailand

Biomass gasifiers, especially fixed-bed type, have been perceived as a promising technology for small-scale power generation from renewable sources. Depending on production capacity and end-use applications, various modifications of fixed-bed gasifiers have emerged to generate clean synthesis gas (syngas) with less waste disposal and higher gasifier efficiency. Recently, H2-rich and CO2-free syngas production has been experimented with by modifying operating conditions and gasifier design. Computational fluid dynamics (CFD) modeling, incorporating hydrodynamics, chemical reaction mechanism, reactor development, and process intensification, has been brought to pursue a rigorous investigation of gasifier design and the gasification process. This review presents a recent advance in developing the CFD model of fixed-bed gasifiers. A detailed characterization of the biomass gasification process, including devolatilization, homogeneous gas oxidation and reduction, and heterogeneous char reactions, is highlighted. Design analysis of fixed-bed gasifiers is also discussed. Tar species in the devolatilization reaction and their cracking mechanism are interpreted. In addition, the effects of a gasifier configuration and an equivalence ratio of gasifying agents on the producer gas composition, tar content in the producer gas, and the cold gas efficiency are analyzed as a basis for further improvement of the CFD gasifier models. © 2025 Hydrogen Energy Publications LLC

关键词： Hydrogen production

来源：评论

学校读者我要写书评

暂无评论

GACL-Net:Hybrid Deep Learning Framework for Accurate Motor Imagery Classification in Stroke Rehabilitation

引用

Computers, Materials & Continua 2025年第4期83卷 517-536页

作者： Chayut Bunterngchit Laith H.Baniata Mohammad H.Baniata Ashraf ALDabbas Mohannad A.Khair Thanaphon Chearanai Sangwoo Kang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Computing Gachon UniversitySeongnam13120Republic of Korea Computer Science Department Faculty of Information TechnologyThe World Islamic Sciences and Education UniversityAmman11947Jordan Intelligent Systems Department Faculty of Artificial IntelligenceAl-Balqa Applied UniversityAl-Salt19117Jordan IT Infrastructure Department Qatrana Cement CompanyAmman11821Jordan Division of Industrial and Logistics Engineering Technology Faculty of Engineering and TechnologyKing Mongkut’s University of Technology North BangkokRayong CampusRayong21120Thailand

Stroke is a leading cause of death and disability worldwide,significantly impairing motor and cognitive *** rehabilitation is often hindered by the heterogeneity of stroke lesions,variability in recovery patterns,and the complexity of electroencephalography(EEG)signals,which are often contaminated by *** classification of motor imagery(MI)tasks,involving the mental simulation of movements,is crucial for assessing rehabilitation strategies but is challenged by overlapping neural signatures and patient-specific *** address these challenges,this study introduces a graph-attentive convolutional long short-term memory(LSTM)network(GACL-Net),a novel hybrid deep learning model designed to improve MI classification accuracy and ***-Net incorporates multi-scale convolutional blocks for spatial feature extraction,attention fusion layers for adaptive feature prioritization,graph convolutional layers to model inter-channel dependencies,and bidi-rectional LSTM layers with attention to capture temporal *** on an open-source EEG dataset of 50 acute stroke patients performing left and right MI tasks,GACL-Net achieved 99.52%classification accuracy and 97.43%generalization accuracy under leave-one-subject-out cross-validation,outperforming existing state-of-the-art ***,its real-time processing capability,with prediction times of 33–56 ms on a T4 GPU,underscores its clinical potential for real-time neurofeedback and adaptive *** findings highlight the model’s potential for clinical applications in assessing rehabilitation effectiveness and optimizing therapy plans through precise MI classification.

关键词： Motor imagery EEG stroke rehabilitation deep learning brain-computer interface

来源：评论

学校读者我要写书评

暂无评论

Detecting Advanced Persistent Threat Exfiltration with Ensemble Deep Learning Tree Models and Novel Detection Metrics

引用

IEEE Access 2025年 13卷 81803-81822页

作者： Cai, Xiaojuan Zhang, Haibo Ahmed, Chuadhry Mujeeb Koide, Hiroshi Kyushu University Faculty of Information Science and Electrical Engineering Department of Information Science and Technology Fukuoka819-0395 Japan Kyushu Institute of Technology Faculty of Computer Science and Systems Engineering Department of Artificial Intelligence Fukuoka Iizuka820-8502 Japan Newcastle University School of Computing Secure and Resilient Systems Group Newcastle upon TyneNE1 7RU United Kingdom Kyushu University Section of Cyber Security for Information Systems Research Institute for Information Technology Fukuoka819-0395 Japan

Advanced Persistent Threats (APTs) involve attackers maintaining a long-term presence on victim systems, leading to the stealthy exfiltration of sensitive data during network transfers. Despite existing methods to detect and halt APT data exfiltration, these attacks continue to pose significant threats to sensitive information and result in substantial commercial losses. Current approaches primarily focus on preemptive measures, which are insufficient once early-stage detection fails due to a lack of continuous monitoring. We propose an effective and efficient network monitoring method to address this gap and detect APT exfiltration during data transfer. Our approach assumes the presence of an undetected APT attacker within the victim system. We examine data exfiltration across three exfiltration traffic environments: exfiltration over command control channels, exfiltration over transfer size limitations, and their combinations. We introduce two detection metrics: Package Transfer Rate and Byte Transfer Rate. Utilizing these metrics, we measure network traffic, categorize APT attack environments, and train deep neural network models, named EDXGB, using ensembled decision trees to predict APT exfiltration. Our method is validated on two public datasets and compared against six baseline methods. Additionally, we simulate real-world exfiltration scenarios by creating three exfiltration traffic environments for each dataset. The results demonstrate that our method effectively detects APT exfiltration across various network environments, enhancing data protection and secure transfer. The code is open source and available at https://***/cxjuan/EDXGB-for-APT. © 2013 IEEE.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Supervisory Control of Discrete Event systems Modeled With Labeled Petri Nets for Diagnosability Enforcement

引用

IEEE Transactions on Automation Science and engineering 2025年 22卷 13855-13870页

作者： Li, Chengzong Chen, Yufeng Mostafa, Almetwally M. Khalgui, Mohamed Qinghai University School of Energy and Electrical Engineering Xining810000 China Macau University of Science and Technology Institute of Systems Engineering Taipa China King Saud University College of Computer and Information Sciences Department of Information Systems Riyadh11543 Saudi Arabia German International University Faculty of Engineering Berlin13507 Germany

This paper proposes an active fault diagnosis method to enforce the diagnosability of discrete event systems using labeled Petri nets by constructing a diagnostic supervisor. For a non-diagnosable net model, its diagnosability is viewed as a control specification and addressed by using supervisory control techniques. First, an event-based monitor and a Petri net structure, referred to as data isolation arcs, are introduced to apply control specifications for labeled Petri nets. Then, a diagnostic supervisor reachability graph is generated to estimate the current state of the diagnoser. By analyzing the diagnostic supervisor reachability graph, an integer linear programming model is formulated to design a diagnostic supervisor, which can prevent the system from entering into any indeterminate cycle only by observing the occurrence of events. Finally, by the obtained diagnostic supervisor, the resulting net model is shown to be diagnosable. Some examples are presented to demonstrate the proposed method. © 2004-2012 IEEE.

关键词： Supervisory personnel

来源：评论

学校读者我要写书评

暂无评论

The Inhibition Activity of Fatty Imidazoline Acetate Derived from Waste Cooking Oil on the AISI 1018 Mild Steel Corrosion

引用

Journal of Bio- and Tribo-Corrosion 2025年第1期11卷 1-11页

作者： Cholidah, Tsana Kusumasari, Lutfiah Lila Febriyanti, Tria Firdaus, Achmad Fadjar Maulana Fuadi, Raihana Putri Nariswari Madurani, Kartika A. Chemistry Department Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Sukolilo East Java Surabaya60111 Indonesia Department of Materials and Metallurgical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Sukolilo East Java Surabaya60111 Indonesia

Imidazoline and its derivatives have been proposed as effective organic corrosion inhibitors for AISI 1018 mild steel, though challenges remain regarding their production processes and efficiency in CO2/H2S-saturated brine solutions. In this study, fatty imidazoline acetate (FIA) was synthesized from waste cooking oil and evaluated for its ability to protect AISI 1018 steel in corrosive environments. The chemical composition of the synthesized FIA was confirmed through gas chromatography-mass spectroscopy (GC–MS) and Fourier transform infrared (FTIR) spectroscopy. Corrosion inhibition performance was assessed using potentiodynamic polarization at room temperature, with the most promising results further examined via weight loss measurements and contact angle analyses. A commercial inhibitor commonly used in pipelines with CO2/H2S-saturated brine was also evaluated for comparison. Surface characterization of the steel samples, both with and without inhibitors, was conducted using scanning electron microscopy (SEM). The FIA demonstrated an inhibition efficiency (IE%) of 99.89% at a concentration of 40 mg/L, closely matching the performance of the commercial inhibitor (IE% = 99.96%). This study underscores the potential of FIA as a sustainable and effective corrosion inhibitor in CO2/H2S-saturated environments. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Gas chromatography

来源：评论

学校读者我要写书评

暂无评论

An Improved Power Factor Correction Converter for Switched Reluctance Motor Drive Performance Analysis

引用

IEEE Access 2025年 13卷 71187-71196页

作者： Mohanraj, Deepak Samithas, Devakirubakaran Balachandran, Praveen Kumar Mohd Zainuri, Muhammad Ammirrul Atiqi KIT-Kalaignarkarunanidhi Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Coimbatore641402 India SRM Institute of Science and Technology Faculty of Engineering and Technology Department of Automobile Engineering Tamil Nadu Kattankulathur603203 India Vardhaman College of Engineering Department of Electrical and Electronics Engineering Telangana Hyderabad501218 India Chennai Institute of Technology Department of Electrical and Electronics Engineering Tamil Nadu Chennai600069 India Chitkara University Institute of Engineering and Technology Chitkara University Centre for Research Impact and Outcome Punjab Rajpura140401 India Universiti Kebangsaan Malaysia Faculty of Engineering and Built Environment Department of Electrical Electronic and Systems Engineering Selangor Bangi43600 Malaysia

Power Factor Correction (PFC) is crucial for the efficient operation of Switched Reluctance Motor (SRM) converters, as it enhances energy utilization and minimizes system losses. Conventional PFC techniques often rely on passive components or simple active methods, which may not fully exploit the dynamic characteristics of SRM operation. Low power factors in SRM converters lead to increased reactive power consumption and potential grid disturbances, necessitating effective PFC strategies to optimize energy efficiency, enhance system performance, and ensure compliance with standards. Therefore, this paper proposes a buck-boost converter to efficiently regulate the DC voltage supplied to the load, enabling voltage levels higher or lower than the input voltage while improving PFC in SRM converters. The objective is to address current challenges and push the boundaries of efficiency and performance. The proposed control strategies leverage the unique characteristics of SRMs to achieve superior PFC performance by dynamically adjusting the converter’s operation in real time based on motor load conditions. This approach ensures optimal PFC across a wide range of operating conditions. The proposed model is developed and validated using MATLAB/Simulink. Simulation and experimental results assess the motor’s performance under both static and dynamic load conditions. Additionally, the effectiveness of the converter is evaluated by analyzing the total harmonic distortion of the input current. © 2013 IEEE.

关键词： Reluctance motors

来源：评论

学校读者我要写书评

暂无评论

The Effect of Adding Cone Rubber-Mass Dynamic Vibration Absorber to Boring Bar on Reduction of Vibration Response in Machinery Process (Lathe Machine) 6th

The Effect of Adding Cone Rubber-Mass Dynamic Vibration Abso...

引用

6th International Conference on Mechanical engineering, ICOME 2023

作者： Hendrowati, Wiwiek Meidina, Najya Rafa Mechanical Engineering Department Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Jl. Arief Rahman Hakim Surabaya60111 Indonesia Graduate of the Department of Mechanical Engineering Faculty of Industrial Technology and Systems Engineering Institut Teknologi Sepuluh Nopember Jl. Arief Rahman Hakim Surabaya60111 Indonesia

ISBN: (纸本)9789819778973

Boring bars with a large length-to-diameter (L/D) ratio in the machining process can cause excessive vibration or chatter, which reduces product quality. Dynamic vibration absorber (DVA) is a vibration reduction system that can reduce the chatter effect. In this study, DVA has the shape of a cone placed inside a boring bar, which consists of a mass of absorber made of brass covered with rubber. The rubber is varied, namely natural rubber and neoprene rubber. The simulation is carried out with various cutting parameters, including spindle speed, feed rate, and depth of cut. Based on the simulations, the DVA cone's shape allows it to reduce vibrations in all directions and produce the same reduction values on each axis. Customized boring bar L/D 9 with DVA natural rubber and cutting parameter 2 is the variation with the highest vibration response reduction value, namely 88.50% in the x-axis direction, 83.89% in the y-axis, and 88.52% in the z-axis. Customized boring bar L/D 7 is a geometry variation with the best operation because it can reduce vibration in most variations of cutting parameters compared to other variations of boring bars, namely 23 out of 27 cutting parameters. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Vibration analysis

来源：评论

学校读者我要写书评

暂无评论

Performance Optimization in SDN-VANET Using Particle Swarm Optimization and Differential Evolution Algorithms 3rd

Performance Optimization in SDN-VANET Using Particle Swarm O...

引用

3rd International Conference on Advances in Information and Communication technology, ICTA 2024

作者： Phong, Lam Thien Ninh, Bui Trung Mai, Dinh Thi Thai Department of Telecommunications Systems Faculty of Electronics and Telecommunications University of Engineering and Technology - VietNam National University HaNoi Viet Nam

ISBN: (纸本)9783031809422

Software-Defined Vehicular Ad Hoc Network (SDN-VANET), merging the Software-Defined Network (SDN) with VANET, offers many applications, from environmental monitoring to intelligent transportation systems. However, ensuring optimal performance of the networks amidst dynamic vehicular environments remains a formidable challenge. This paper proposes Particle Swarm Optimization Algorithm (PSO) and Differential Evolution Algorithm (DE) as optimal techniques in SDN-VANET, aiming to optimize TCP Window size and UDP Buffer size. After running simulations and evaluations, the results showed that these optimal algorithms effectively improved network performance components, such as increasing throughput, increasing bandwidth, reducing the number of TCP packet retransmissions, and reducing packet dropping rate (PDR). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Particle swarm optimization (PSO)

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：