检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Raeisi, Mahmoud Koc, Asil Yildirim, Ibrahim Basar, Ertugrul Le-Ngoc, Tho CoreLab Department of Electrical and Electronics Engineering Koc University Istanbul Sariyer34450 Turkey Department of Electrical and Computer Engineering McGill University MontrealQC Canada Faculty of Electrical and Electronics Engineering Istanbul Technical University Istanbul Sariyer34469 Turkey

This paper investigates the effect of various antenna array structures, i.e., uniform linear array (ULA), uniform rectangular array (URA), uniform circular array (UCA), and concentric circular array (CCA), on cluster index modulation (CIM) enabled massive multiple-input multiple-output (mMIMO) millimeter-wave (mmWave) communications systems. As the CIM technique indexes spatial clusters to convey additional information bits, the different radiation characteristics caused by different array structures can significantly affect system performance. By analyzing the effects of array characteristics such as radiation pattern, array directivity, half-power beam width (HPBW), and radiation side lobes on bit error rate (BER) performance, we reveal that URA achieves better error performance than its counterparts in a CIM-enabled mmWave system. We demonstrate that narrower beams alone cannot guarantee better BER performance in a CIM-based system. Instead, other radiation characteristics, especially radiation side lobes, can significantly influence system performance by entailing extra interference in the non-intended directions. Illustrative results show that URA owes its superiority to its lower side lobes. We also propose an algorithm to implement fixed phase shifters (FPS) as a hardware-efficient (HE) analog network structure (beamformer/combiner) to reduce cost and energy consumption in mmWave systems and investigate the effect of a non-ideal analog network on the BER performance for different array structures. It is demonstrated that HE systems with a few FPSs can achieve similar BER performance compared to the optimum (OP) analog network structure. © 2023, CC BY.

关键词： Bit error rate

来源：评论

学校读者我要写书评

暂无评论

Smart Posture System Design for Scoliosis Patients Based on the Internet of Things (IoT)

Smart Posture System Design for Scoliosis Patients Based on ...

引用

International Conference on electrical engineering and Informatics (ICon EEI)

作者： Anhar Anhar Salpiana Salpiana Siva Kumar Subramaniam Indra Yasri Febrizal Ujang Ery Safrianti Electrical Engineering Department University of Riau Pekanbaru Indonesia Faculty of Electronics and Computer Eng. Universiti Teknikal Malaysia Melaka Melaka Malaysia

ISBN: (数字)9798331540791

ISBN: (纸本)9798331540807

Scoliosis, a spine deformity characterized by an abnormal curvature, often in the shape of the letter C or S, is a condition with an unknown cause in most cases (75-85% are idiopathic scoliosis). In this context, our research is a comprehensive exploration, aiming to design an intelligent body posture system for people with scoliosis using Internet of Things (IoT) technology. The system employs a flex sensor to measure the angle of spinal curvature and ESP 32 as a processor and controller server. The research yields hardware and software angles and conditions. There are three scenarios to test the performance of the system; testing on normal patients without complaint, with complaint, and scoliosis patients. Voltage measurements show error values ranging from 0,87%-17,7%, and the tool functions effectively. The device testing is conducted on both regular patients and scoliosis sufferers for monitoring and early detection.

关键词： Vibrations Flexible printed circuits Scoliosis Motors Light emitting diodes Software Hardware Distance measurement Internet of Things Monitoring

来源：评论

学校读者我要写书评

暂无评论

Analysis of SARIMA Models for Forecasting Electricity Demand

Analysis of SARIMA Models for Forecasting Electricity Demand

引用

International Smart Grid Workshop and Certificate Program (ISGWCP)

作者： Ahmet Aksöz Saadin Oyucu Emre Biçer Ramazan Bayındır Mobilers Team Sivas Cumhuriyet University Sivas Türkiye Department of Computer Engineering Faculty of Engineering Adıyaman Türkiye Faculty of Engineering and Natural Sciences Battery Research Laboratory Sivas University of Science and Technology Sivas Türkiye Faculty of Technology Electrical and Electronics Engineering Department Gazi University Ankara Türkiye

ISBN: (数字)9798350361612

ISBN: (纸本)9798350361629

This article presents an in-depth evaluation of electricity consumption predictions using the Seasonal Autoregressive Integrated Moving Average (SARIMA) model. Leveraging historical electricity consumption data, the SARIMA model demonstrates a commendable ability to forecast future consumption patterns. Our analysis reveals a strong alignment between the model’s predictions and actual consumption data, affirming the efficacy of time series modeling in capturing complex energy consumption dynamics. Notably, while the model excels in predicting near-term consumption trends, uncertainties widen for long-term forecasts, prompting critical reflections on the model’s evolving accuracy and reliability over time. For future research endeavors, we recommend comparing the performance of diverse time series models to discern optimal modeling approaches. Further optimization of model parameters stands as a paramount endeavor to refine prediction accuracy and mitigate uncertainties. Specifically, efforts to identify and address potential overfitting or underfitting tendencies within the model are advised. Additionally, leveraging supplementary data sources and integrating seasonal factors could bolster the reliability of future predictions, expanding the model’s predictive scope and ensuring more robust and precise forecasts.

关键词： Analytical models Uncertainty Accuracy Electricity Soft sensors Time series analysis Predictive models

来源：评论

学校读者我要写书评

暂无评论

Computationally Efficient Core Losses Calculation and Thermal Evaluation Using the VBR-Based Finite Element Model of Induction Motors

Computationally Efficient Core Losses Calculation and Therma...

引用

IEEE Energy Conversion Congress and Exposition, ECCE

作者： Zahra Valipoor Hossein Nejadi Koti Nabeel A. O. Demerdash Electrical and Computer Engineering Department Marquette University Milwaukee USA Motion Control Team Rockwell Automation Inc. Mequon USA

Accuracy of the simulation results obtained from the FEA analysis of electric motors is highly dependent on the quality of the motor performance metrics such as motor steady state temperatures and losses. In addition such FEA analysis is typically computationally burdensome and demanding. Improving the computational burden and accuracy of core losses calculation and thermal evaluation in Time-Stepping Finite Element (TS-FE) models of induction motors is addressed in this paper. The Virtual Blocked Rotor (VBR)-based Time-Stepping Finite Element (TS-FE) technique is utilized to mitigate the numerical transient response of the induction motor FE model. The motor core losses have been calculated through the harmonic based core loss calculation that assumes variable loss coefficients as a function of magnetic flux density. In addition, the motor estimated losses, including the calculated core losses are fed to a thermal network model to estimate the temperature of different motor components.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Attacks Detection in 6G Wireless Networks using Machine Learning

Attacks Detection in 6G Wireless Networks using Machine Lear...

引用

International Conference on computer and Communication engineering, ICCCE

作者： Mamoon M. Saeed Rashid A. Saeed Abdulguddoos S. A. Gaid Rania A. Mokhtar Othman O. Khalifa Zeinab E. Ahmed Department of Communications and Electronics Engineering Faculty of Engineering University of Modern Sciences (UMS) Yemen Department of Computer Engineering College of Computers and Information Technology Taif University P.O. Box 11099 Taif Saudi Arabia Department of Communication & Computer Engineering Faculty of Engineering & Information Technology Taiz University Taiz Yemen Department of Electrical and Computer Engineering International Islamic University Malaysia Malaysia Libyan Center for Engineering Research and Information Technology Bani Waleed Libya Electrical and Computer Engineering Dept International Islamic University Malaysia Malaysia Computer Engineering Dept University of Gezira Sudan

Unlike the fifth generation (5G), which is well recognized for network cloudification with micro-service-oriented design, the sixth generation (6G) of networks is directly tied to intelligent network orchestration and management. The Attacks Detection in 6G (AD6Gs) wireless networks created by this research uses a Machine Learning (ML) algorithm. The pre-processing stage of the ML-AD6Gs process is the initial step. The second stage involves the feature selection approach. Correlation Feature Selection algorithm (CFS) is used to implement the suggested hybrid strategy. It selects the best subset feature and reduces dimensionality for each independent analyses of the dataset CICDDOS2019. The voting average method is used as an aggregation step, and two classifiers—Random Forest (RF) and Support Vector Machine (SVM)—are modified to be used as ML Algorithms. The proposed method shown an outperformed the existing classification method. The accuracy was 99.9%% for CICDDOS2019 dataset with a false alarm rate of 0.00102

关键词：

来源：评论

学校读者我要写书评

暂无评论

Design and Qualification of a High-Speed Low-Power Comparator in 40 nm CMOS Technology

Design and Qualification of a High-Speed Low-Power Comparato...

引用

International Scientific Conference Electronics (ET)

作者： Alireza Mohammad Zaki Yutong Du Stoyan Nihtianov Department of Microelectronics Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology CD Delft The Netherlands

This paper presents the design methodology, test setup and experimental qualification results of a high-speed low-power threshold comparator in 40 nm CMOS technology intended for the registry of particles landing on a PIN-detector surface in particle detector readout electronics. The operation of the designed comparator is experimentally qualified for ideal digital pulses and analog signals generated by the preceding stages in a targeted potential application.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Video Indexing for Live Nature Camera on Digital Earth 37th

Video Indexing for Live Nature Camera on Digital Earth

引用

37th International Conference on Advanced Information Networking and Applications, AINA 2023

作者： Mimura, Hiroki Tahara, Masaya Takano, Kosuke Watanabe, Nobuya Li, Kin Fun Department of Information and Computer Sciences Kanagawa Institute of Technology 1030 Shimo-Ogino Kanagawa Atsugi243-0292 Japan International GIS Center Chubu University 1200 Matsumoto-Cho Aichi Kasugai487-8501 Japan Department of Electrical and Computer Engineering Faculty of Engineering University of Victoria 3800 Finnerty Road VictoriaBCV8P 5C2 Canada

ISBN: (纸本)9783031286933

This paper presents a method of indexing video stored from live nature cameras on digital Earth and its application. Since two feature vectors from scene images are not necessary identical in the metrical space even if they are similar, it is hard to get benefit of indexing feature vectors. That is, the search system consequently has to fully access to almost whole feature vectors in the storage. The feature of the proposed system is that for indexing feature vectors, similarity-based indexing by clustering feature vectors is applied, where the feature vectore can be indexed with a centorid vector of the corresponding cluster. Consequently, the computing cost for accsessing to the objective images can be majorly reduced without the almost full access to whole feature vectors. For making our concept clear, we show an application scenario using video data from live streaming cameras that are opened to the public and some aerial or satellite images. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Moving Object Segmentation by Combing Deep Learning and Geometric Constraints for Autonomous Driving

Moving Object Segmentation by Combing Deep Learning and Geom...

引用

Chinese automation Congress (CAC)

作者： Jianying Yuan Sidong Wu John K. Tsotsos School of Automation Chengdu University of Information Technology Chengdu China Department of Electrical Engineering and Computer Science York University Toronto Canada

Moving object segmentation is an important and challenging task in the field of autonomous driving. This paper presents a novel and effective method that combines deep learning and geometric constraints for moving object segmentation. First, potential moving objects in the traffic scene are segmented using SOLOV2. Next, the residual optical flows (ROFs) of feature points on the potential moving objects are calculated. Lastly, a strategy considering randomness of ROF angles and ROF magnitude thresholding is developed to estimate the motion status of these potential moving objects. The effectiveness of the proposed method is evaluated on the KITTI and KITTI MOD datasets, and the experimental results demonstrate that the proposed method can achieve higher precision and recall compared to the existing algorithms.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Improving the Area-Delay Tradeoff for Academic FPGA Architectures by Applying Rent’s Rule to Logic Block Modeling

Improving the Area-Delay Tradeoff for Academic FPGA Architec...

引用

International Scientific Conference Electronics (ET)

作者： Petar Minev Valentina Kukenska Matyo Dinev Ilian Varbov Department of Computer Systems and Technologies Faculty of Electrical Engineering and Electronics Technical University of Gabrovo 4 H. Dimitar str Gabrovo Bulgaria

ISBN: (数字)9798350376449

ISBN: (纸本)9798350376456

This paper presents a study on the effect of using a smaller number of inputs in the FPGA logic block calculated according to a pre-compiled model based on Rent’s rule. This rule, when applied to the FPGA logic block with a logic block crossbar, allows for the reduction of the size of its multiplexers, thereby reducing its area and the delays in the switching circuits. The study uses a set of benchmark circuits, which are implemented in FPGA architectures with predefined parameters. The obtained results allow for comparing the architectures based on the total area and the critical path delays of the benchmark circuits.

关键词： Multiplexing Analytical models Switches Benchmark testing Delays Logic Integrated circuit modeling Field programmable gate arrays Optimization Switching circuits

来源：评论

学校读者我要写书评

暂无评论

Multi-Scale Regularization and Bounding Box Refinement in Semi-Supervised Object Detection Framework

Multi-Scale Regularization and Bounding Box Refinement in Se...

引用

Integrated Circuits and Communication Systems (ICICACS), IEEE International Conference on

作者： Ramakrishnan Raman Karthick Rajan Falguni Tlajiya Manisha Paliwal Symbiosis International (Deemed University) Pune India Department of Computer Science and Engineering Chennai Institute of Technology Chennai India Department of Electrical Engineering Faculty of Engineering and Technology Parul University Vadodara India Balaji Institute of International Business (BIIB) Pune India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

Semi-supervised object detection (SSOD) has emerged as a critical approach to bridge the gap between the extensive labeled data requirements of supervised methods and the abundance of unlabeled data available. However, existing SSOD techniques often suffer from two significant limitations: inconsistent performance across scales and inaccuracies in object localization. To address these challenges, this paper introduces a novel framework that integrates Multi-Scale Regularization (MSR) and Bounding Box Refinement (BBR). The proposed MSR mechanism enforces consistency in predictions across different feature map scales, ensuring robust pseudo-labeling and mitigating scale-related variations. Simultaneously, BBR employs a two-stage optimization process to enhance the precision of bounding box predictions, correcting spatial errors in initial detections. The combined framework leverages both labeled and unlabeled datasets effectively, resulting in improved detection performance. Extensive experiments conducted on benchmark datasets such as COCO and Pascal VOC demonstrate the efficacy of the proposed approach, showing significant improvements in mean Average Precision (mAP) compared to existing state-of-the-art SSOD methods. Ablation studies further highlight the individual contributions of MSR and BBR to the overall performance gains. This study establishes a new benchmark in SSOD, paving the way for more accurate and efficient object detection systems that rely on minimal labeled data while leveraging abundant unlabeled data.

关键词： Location awareness Accuracy Object detection Benchmark testing Semisupervised learning Performance gain Robustness Data models Integrated circuit modeling Optimization

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：