检索结果-内蒙古大学图书馆

Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

CAAI Transactions on Intelligence Technology 2023年第4期8卷 1140-1149页

作者： Mian Imtiaz ul Haq Ruhul Amin Khalil Muhannad Almutiry Ahmad Sawalmeh Tanveer Ahmad Nasir Saeed Faculty of Electrical Engineering Swedish College of Engineering and TechnologyWah CanttPakistan Department of Electrical Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawarPakistan Department of Electrical Engineering Remote Sensing UnitNorthern Border UniversityArarSaudi Arabia Data Science and Artificial Intelligence Department‐College of Science and Information Technology Irbid National UniversityIrbadJordan Innovation Education and Research Center for On‐Device AI Software(Bk21) Department of Computer Science and EngineeringChungnam National UniversityDaejeonRepublic of Korea Department of Electrical and Communication Engineering United Arab Emirates University(UAEU)Al AinUnited Arab Emirates

Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various ***,a novel localisation algorithm is proposed for noisy range measurements in IIoT *** position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position ***,the AMs selection algorithm for the localisation of BMs in the IIoT network is *** those AMs will participate in the localisation process,which increases the accuracy of the final location ***,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement *** results are compared with the state‐of‐the‐art and verified through numerous simulations.

关键词： Cramér‐Rao lower bound greedy successive anchorization industrial internet of things localization

来源：评论

学校读者我要写书评

暂无评论

Sparse Array Sensor Selection in ISAC with Identifiability Guarantees 58

Sparse Array Sensor Selection in ISAC with Identifiability G...

引用

58th Asilomar Conference on Signals, systems and computers, ACSSC 2024

作者： Rajamäki, Robin Pal, Piya Aalto University Department of Information and Communications Engineering Finland University of California Department of Electrical and Computer Engineering San Diego United States

ISBN: (数字)9798350354058

ISBN: (纸本)9798350354058

This paper investigates array geometry and waveform design for integrated sensing and communications (ISAC) employing sensor selection. We consider ISAC via index modulation, where various subsets of transmit (Tx) sensors are used for both communications and monostatic active sensing. The set of Tx subarrays make up a codebook, whose cardinality we maximize (for communications) subject to guaranteeing a desired target identifiability (for sensing). To characterize the size of this novel optimal codebook, we derive first upper and lower bounds, which are tight in case of the canonical uniform linear array (ULA) and any nonredundant array. We show that the ULA achieves a large codebook-comparable to the size of the conventional unconstrained case-as satisfying the identifiability constraint only requires including two specific sensors in each Tx subarray (codeword). In contrast, nonredundant arrays, which have the largest identifiability for a given number of physical sensors, only have a single admissible codeword, rendering them ineffectual for communications via sensor selection alone. The results serve as a step towards an analytical understanding of the limits of sensor selection in ISAC and the fundamental trade-offs therein. © 2024 IEEE.

关键词： Redundancy

来源：评论

学校读者我要写书评

暂无评论

Enhancing Communication Accessibility:UrSL-CNN Approach to Urdu Sign Language Translation for Hearing-Impaired Individuals

引用

computer Modeling in engineering & Sciences 2024年第10期141卷 689-711页

作者： Khushal Das Fazeel Abid Jawad Rasheed Kamlish Tunc Asuroglu Shtwai Alsubai Safeeullah Soomro Department of Computer Engineering Modeling Electronics and Systems EngineeringUniversity of CalabriaRende Cosenza87036Italy Department of Information Systems University of Management and TechnologyLahore54770Pakistan Department of Computer Engineering Istanbul Sabahattin Zaim UniversityIstanbul34303Turkey Department of Software Engineering Istanbul Nisantasi UniversityIstanbul34398Turkey Department of Computer Science COMSATS University IslamabadLahore CampusLahore54700Pakistan Faculty of Medicine and Health Technology Tampere UniversityTampere33720Finland Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Second Department of Computer Science College of Engineering and ComputingGeorge Mason UniversityFairfaxVA 4418USA

Deaf people or people facing hearing issues can communicate using sign language(SL),a visual *** works based on rich source language have been proposed;however,the work using poor resource language is still *** other SLs,the visuals of the Urdu Language are *** study presents a novel approach to translating Urdu sign language(UrSL)using the UrSL-CNN model,a convolutional neural network(CNN)architecture specifically designed for this *** existingworks that primarily focus on languageswith rich resources,this study addresses the challenge of translating a sign language with limited *** conducted experiments using two datasets containing 1500 and 78,000 images,employing a methodology comprising four modules:data collection,pre-processing,categorization,and *** enhance prediction accuracy,each sign image was transformed into a greyscale image and underwent noise *** analysis with machine learning baseline methods(support vectormachine,GaussianNaive Bayes,randomforest,and k-nearest neighbors’algorithm)on the UrSL alphabets dataset demonstrated the superiority of UrSL-CNN,achieving an accuracy of ***,our model exhibited superior performance in Precision,Recall,and F1-score *** work not only contributes to advancing sign language translation but also holds promise for improving communication accessibility for individuals with hearing impairments.

关键词： Convolutional neural networks Pakistan sign language visual language

来源：评论

学校读者我要写书评

暂无评论

A Novel Ensemble Learning Model Using CNNs and Vision Transformers for Waste Classification 8

A Novel Ensemble Learning Model Using CNNs and Vision Transf...

引用

8th International Symposium on Innovative Approaches in Smart Technologies, ISAS 2024

作者： Cisse, Mohamed Lamine Aderinwale, David Adeyinka Sah, Melike Cyprus International University Department of Information Systems Engineering Nicosia Cyprus Cyprus International University Department of Computer Engineering Nicosia Cyprus

ISBN: (纸本)9798331540104

Automatic waste classification is challenging due to the variety and complexity of waste types. Automatic waste classification with deep learning can enable faster and more accurate sorting for waste management. In this work, we focus on this problem and propose a novel ensemble approach by applying transfer learning on various pre-trained model combinations of Convolutional Neural Networks (CNNs) and Vision Transformers (ViT) for precise classification of waste images. We used the six-class Trashnet dataset for evaluations. Among the tested pre-trained CNN models, DenseNet121 and InceptionV3 achieved the best accuracies of 95.25 % and 93. 46 % respectively on the Trashnet dataset. For the vision transformer, ViT_b16, and ViT_b32 achieved accuracies of 95. 45 %, and 93. 47 % respectively. We call these models base models. Results analysis on base models showed that specific models learned certain features of the dataset better for different waste class types. Then, we applied two types of ensemble approaches to combine the predictions of base learners: Weighted averaging and model averaging. Weighted averaging assigns different importance to each model's predictions based on their accuracy, while model averaging combines all models' predictions equally. Furthermore, after checking the overall performance of those models on the test set, it was noticed that the model averaging ensemble approach had 97,92 % accuracy, and the weighted averaging ensemble approach had 98, 22 % accuracy. Base models performed worse than the weighted average ensemble approach and the model averaging ensemble approach showing that the ensemble approach improved the accuracy by up to 4%. Our contribution is developing a novel ensemble method based on both ViTs and CNNs for the first time on the TrashNet that demonstrates state-of-the-art performance. © 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

Distributed Energy and Reserve Scheduling in Local Energy Communities Using L-BFGS Optimization

引用

CSEE Journal of Power and Energy systems 2024年第3期10卷 942-952页

作者： Mohammad Dolatabadi Alireza Zakariazadeh Alberto Borghetti Pierluigi Siano Department of Management&Innovation Systems University of SalernoSalernoItaly Department of Electrical Electronicand Information EngineeringUniversity of BolognaBolognaItaly University of Science and Technology of Mazandaran BehshahrIran Department of Power Systems National University of Science and Technology POLITEHNICA BucharestBucharestRomania IEEE

Encouraging citizens to invest in small-scale renewable resources is crucial for transitioning towards a sustainable and clean energy *** energy communities(LECs)are expected to play a vital role in this ***,energy scheduling in LECs presents various challenges,including the preservation of customer privacy,adherence to distribution network constraints,and the management of computational *** paper introduces a novel approach for energy scheduling in renewable-based LECs using a decentralized optimization *** proposed approach uses the Limitedmemory Broyden–Fletcher–Goldfarb–Shanno(L-BFGS)method,significantly reducing the computational effort required for solving the mixed integer programming(MIP)*** incorporates network constraints,evaluates energy losses,and enables community participants to provide ancillary services like a regulation reserve to the grid *** assess its robustness and efficiency,the proposed approach is tested on an 84-bus radial distribution *** indicate that the proposed distributed approach not only matches the accuracy of the corresponding centralized model but also exhibits scalability and preserves participant privacy.

关键词： Distributed optimization flexibility services L-BFGS method local energy community renewables reserve

来源：评论

学校读者我要写书评

暂无评论

Optimal Load Forecasting Model for Peer-to-Peer Energy Trading in Smart Grids

引用

computers, Materials & Continua 2022年第1期70卷 1053-1067页

作者： Lijo Jacob Varghese K.Dhayalini Suma Sira Jacob Ihsan Ali Abdelzahir Abdelmaboud Taiseer Abdalla Elfadil Eisa Department of Electrical and Electronics Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Electrical and Electronics Engineering K.Ramakrishnan College of EngineeringTiruchirappalli621112India Department of Computer Science and Engineering Christian College of Engineering and TechnologyOddanchatram624619India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of Malaya50603Kuala LumpurMalaysia Department of Information Systems King Khalid UniversityMuhayel Aseer62529Saudi Arabia Department of Information Systems-Girls Section King Khalid UniversityMahayil62529Saudi Arabia

Peer-to-Peer(P2P)electricity trading is a significant research area that offers maximum fulfilment for both prosumer and *** also decreases the quantity of line loss incurred in Smart Grid(SG).But,uncertainities in demand and supply of the electricity might lead to instability in P2P market for both prosumer and *** recent times,numerous Machine Learning(ML)-enabled load predictive techniques have been developed,while most of the existing studies did not consider its implicit features,optimal parameter selection,and prediction *** order to overcome fulfill this research gap,the current research paper presents a new Multi-Objective Grasshopper Optimisation Algorithm(MOGOA)with Deep Extreme Learning Machine(DELM)-based short-term load predictive technique i.e.,MOGOA-DELM model for P2P Energy Trading(ET)in *** proposed MOGOA-DELM model involves four distinct stages of operations namely,data cleaning,Feature Selection(FS),prediction,and parameter *** addition,MOGOA-based FS technique is utilized in the selection of optimum subset of ***,DELM-based predictive model is also applied in forecasting the load *** proposed MOGOA model is also applied in FS and the selection of optimalDELM parameters to improve the predictive *** inspect the effectual outcome of the proposed MOGOA-DELM model,a series of simulations was performed using UK Smart Meter *** the experimentation procedure,the proposed model achieved the highest accuracy of 85.80%and the results established the superiority of the proposed model in predicting the testing data.

关键词： Peer to Peer energy trade smart grid load forecasting machine learning feature selection

来源：评论

学校读者我要写书评

暂无评论

Internet of things technology, research, and challenges: a survey

引用

Multimedia Tools and Applications 2025年第11期84卷 8455-8490页

作者： Vishwakarma, Amit Kumar Chaurasia, Soni Kumar, Kamal Singh, Yatindra Nath Chaurasia, Renu Management science and technology Khalifa University Abu Dhabi United Arab Emirates Computer science & Engineering SGT University Gurugram India Department of Information Technology IGDTUW New Delhi India Electrical Engineering IIT Kanpur Kanpur India Computer science & Engineering AIT Rooma Kanpur India

The world of digitization is growing exponentially;data optimization, security of a network, and energy efficiency are becoming more prominent. The Internet of Things (IoT) is the core technology of modern society. This paper is based on a survey of recent and past technologies used for IoT optimization models, such as IoT with Blockchain, IoT with WSN, IoT with ML, and IoT with big data analysis. Suppose anyone wants to start core research on IoT technologies, research opportunities, challenges, and solutions. In that case, this paper will help me understand all the basics, such as security, interoperability, standards, scalability, complexity, data management, and quality of service (QoS). This paper also discusses some recent technologies and the challenges in implementation. Finally, this paper discusses research possibilities in basic and applied IoT Domains. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Reservoir Computing Utilizing Ferroelectric-Gate-Insulator FETs and Capacitors

Reservoir Computing Utilizing Ferroelectric-Gate-Insulator F...

引用

2023 International Conference on IC Design and Technology, ICICDT 2023

作者： Takagi, Shinichi Toprasertpong, Kasidit Nako, Eishin Wang, Zeyu Suzuki, Rikuo Min, Shin-Yi Takenaka, Mitsuru Nakane, Ryosho The University of Tokyo Department of Electrical Engineering and Information Systems Tokyo Japan

ISBN: (纸本)9798350319316

HfO2-based ferroelectric-gate-insulator FETs (FeFETs) and metal/ferroelectrics/metal (MFM) capacitors are promising devices for AI computing applications. We have recently proposed and experimentally demonstrated physical reservoir computing using dynamic polarization switching of HfO2-based Si FeFETs and MFM capacitors. Here, history-dependent current waveforms of FeFETs are utilized for AI tasks. In this paper, we introduce the basic concept of reservoir computing using FeFETs, the fundamental characteristics, and an example of applications to speech recognition. In particular, to solve the problem of RC performance degradation under negative voltage conditions, which is a drawback of using a single n-FeFET, we describe a scheme that combines original and inverted inputs and obtains complementary outputs. © 2023 IEEE.

关键词： Hafnium oxides

来源：评论

学校读者我要写书评

暂无评论

A Method of Predicting Worker's Skill Level in SMEs for Estimating Changeover Time 13

A Method of Predicting Worker's Skill Level in SMEs for Esti...

引用

13th International Conference on the Internet of Things, IoT 2023

作者： Shibuya, Yuto Yamauchi, Taiga Ogihara, Shogo Kawasaki, Takafumi Okura, Yuki Iwamoto, Takeshi Electrical and Computer Engineering Graduate School of Engineering Toyama Prefectural University Toyama Japan Department of Information Systems Engineering Toyama Prefectural University Toyama Japan

ISBN: (纸本)9798400708541

IoT has been introduced to improve production efficiency in small and medium-sized manufacturing companies, and it is mainly aimed at measuring machinery statuses. The improvement of changeover time is significant for production efficiency and the changeover time is depends on the skill level of each worker. Thus, measuring the statuses of human-mediated processes is needed. Moreover, if the skill levels of each worker were quantified, it would be possible to predict setup changeover time based on the quantitative evaluation. Therefore, we define the components of worker proficiency in small and medium-sized manufacturing companies, measure and quantify them, and estimate the proficiency level of each worker. This study enables accurate prediction of setup time by realizing the above. It was 60% to predict the setup changeover time more accurately than the scheduled time, and some components showed a proportional relationship with skill level. © 2023 Owner/Author.

关键词： Production efficiency

来源：评论

学校读者我要写书评

暂无评论

Deep Learning for Fault Detection of Digital VLSI Circuits 21

Deep Learning for Fault Detection of Digital VLSI Circuits

引用

21st International Learning and Technology Conference, L and T 2024

作者： Gaber, Lamya Hussein, Aziza I. Minia University Computers and Systems Engineering Department Minia Egypt Effat University Electrical and Computer Engineering Department Jeddah Saudi Arabia

ISBN: (纸本)9798350393569

With the increasing complexity and scale of digital VLSI designs, ensuring reliability in IC design necessitates effective fault detection processes during the pre-silicon stage. Many fault detection algorithms lead to significant computational time due to the problem of search space explosion. To handle the ever-growing volume of data, deep learning algorithms, a subset of machine learning techniques, can be employed. In this paper, we propose two novel approaches for fault detection (FD) of digital VLSI circuits, specifically targeting stuck-at faults. The first proposed model is semi-supervised FD model that aims to mitigate the search space explosion issue by leveraging both unsupervised and supervised learning processes. The second presented model is based on an optimizer for finding the appropriate configurations for detecting stuck-at faults in digital circuits. The initial proposed model achieves maximum validation accuracy of approximately 98% applied to circuits from ISCAS'85. This model yields a higher accuracy compared to the second approach that achieves maximum accuracy of around 95% when applied to the same circuits from the ISCAS'85 benchmark. © 2024 IEEE.

关键词： Fault detection

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：