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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

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Influence of quality of pixel level annotations on text detection performance in natural images 46

Influence of quality of pixel level annotations on text dete...

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46th ICT and Electronics Convention, MIPRO 2023

作者： Dorkic, I. Brisinello, M. Grbic, R. Herceg, M. TTTech Auto Central and Eastern Europe Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (纸本)9789532331042

Text detection in natural images is a task that arises in many computer vision applications. State-of-the-art text detection methods are mainly based on deep neural networks designed for instance segmentation task. However, most of the available datasets for text detection do not have fine annotations at the pixel level which are required during supervised learning of such networks. Usually, a whole or reduced text bounding box is used as a segmentation mask. In this paper, a method that generates a synthetic dataset with precise annotations at the pixel level is proposed. The method is based on the available Synthtext script for generating synthetic datasets with text instances. By creating synthetic datasets with precise and coarse annotations at the pixel level we explore the efficiency of the state-of-the-art text detector TextFuseNet. © 2023 MIPRO Croatian Society.

关键词： Deep neural networks

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Wound Tissue Classification: A Comparative Analysis of Deep Neural Network Models

Wound Tissue Classification: A Comparative Analysis of Deep ...

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International Conference on Smart Systems and Technologies (SST)

作者： Antonio Antunović Emmanuel Karlo Nyarko Damir Filko Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Computer Engineering and Automation Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350386394

ISBN: (纸本)9798350386400

Wound tissue classification is an important task in medical imaging, with applications ranging from wound assessment to treatment planning. In this study, we investigated different neural network architectures and loss functions to improve the accuracy and efficiency of wound tissue classification. The study included eight different neural network architectures, including classic U-Net, MobileNet U-Net, Attention U-Net, Recurrent Residual Convolutional Neural Network based on U-Net (R2U-Net), Attention Recurrent Residual U-Net (R2AU-Net), Residual Network (ResNet-50), EfficientNet and SegFormer. Each architecture was trained separately with four different loss functions: categorical cross-entropy, weighted categorical cross-entropy, focal loss and soft dice loss. The comparative analysis revealed that the SegFormer architecture in conjunction with soft dice loss function achieved the most promising results on all classification metrics. The results of the study highlight the potential for further research in this area and emphasise the need for more comprehensive datasets to improve model performance.

关键词： Training Semantic segmentation Transformers Smart systems Robustness Distance measurement Data models Planning Decoding Residual neural networks

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Secure Cancelable Template Based on Double Random Phase Encoding and Entropy Segmentation

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computers, Materials & Continua 2022年第11期73卷 4067-4085页

作者： Ahmed M.Ayoup Ashraf A.M.Khalaf Fathi E.Abd El-Samie Fahad Alraddady Salwa M.Serag Eldin Faculty of Engineering Electrical Engineering DepartmentMinia UniversityMinia61111Egypt Department of Electronics and Electrical Communications Engineering Faculty of Electronic EngineeringMenoufia UniversityMenoufia32952Egypt Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif 21944Saudi Arabia

In this paper,a proposed cancellable biometric scheme is based on multiple biometric image identifiers,Arnold’s cat map and double random phase encoding(DRPE)to obtain cancellable biometric *** proposed segmentation scheme that is used to select the region of interest for generating cancelable templates is based on chaos entropy low correlation statistical *** objective of segmentation is to reduce the computational cost and reliability of template *** left and right biometric(iris,fingerprint,palm print and face)are divided into non-overlapping blocks of the same *** define the region of interest(ROI),we select the block with the highest *** shorten the registration process time and achieve a high level of security,we select 25%of the image volume of the biometric *** addition,the low-cost security requirement lies in the use of selective encryption(SE)*** step of selecting the maximum entropy is executed on all biometric *** maximum right and left multi-biometric blocks are arranged in descending order from the entropy perspective and select 50%of each biometric couple and store the single *** obtained matrix is scrambled with a certain number of iterations using Arnold’s Cat Map(ACM).The obtained scrambled matrix is encrypted with the DRPE to generate the cancellable biometric templates,which are further *** simulation results display better performance of the suggested cancellable biometric system in noise scenarios using the area under the receiver operating characteristic(AROC).The strength of the suggested technique is examined with correlation,irregular deviation,maximum difference and maximum *** recommended proposed approach shows that the ability to distinguish the authentic and imposter biometrics of user seven in different levels of the noise environment.

关键词： Image identifier computation segmentation ACM (DRPE)

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Impact of tool integration on the efficiency of test execution

Impact of tool integration on the efficiency of test executi...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Feric, Franjo Job, Josip Bilonic, Barbara Kedacic, Davor TTTech Auto D.o.o. Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Croatia

ISBN: (纸本)9798350347722

Testing is a crucial part of software development. Testing uses a combination of tools to execute test cases and record their results. This paper addresses the integration process of such tools (Windchill and JIRA) into a single application that can be used for overall test case management, as well as exploring the potential for shortening the testing process duration. In addition, test execution and reporting times for tests executed using the integrated test management tool and for tests executed without the aforementioned tool will be analyzed to determine if test execution and reporting times have been reduced as a result of integrating multiple tools. © 2023 IEEE.

关键词： Integration testing

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Efficient Cloud Resource Scheduling with an Optimized Throttled Load Balancing Approach

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computers, Materials & Continua 2023年第11期77卷 2179-2188页

作者： V.Dhilip Kumar J.Praveenchandar Muhammad Arif Adrian Brezulianu Oana Geman Atif Ikram Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India Department of Computer Science and Engineering Karunya Institute of Technology and SciencesCoimbatoreTamil Nadu641114India Department of Computer Science Superior UniversityLahorePakistan Faculty of Electronics Telecommunications and Information Technology Gheorghe Asachi Technical University of IasiIa¸si700050Romania Department of Health and Human Development Stefan cel Mare University of SuceavaSuceava720229Romania Faculty of Ocean Engineering Technology and Informatics University Malaysia TerengganuKuala NerusMalaysia

Cloud technology is a new platform that offers on-demand computing Peripheral such as storage,processing power,and other computer system *** is also referred to as a system that will let the consumers utilize computational resources like databases,servers,storage,and intelligence over the *** a cloud network,load balancing is the process of dividing network traffic among a cluster of available servers to increase *** is also known as a server pool or server *** a single node is overwhelmed,balancing the workload is needed to manage unpredictable *** load balancer sends the load to another free node in this *** focus on the Balancing of workflows with the proposed approach,and we present a novel method to balance the load that manages the dynamic scheduling *** of the preexisting load balancing techniques is considered,however it is somewhat modified to fit the scenario at *** on the experimentation’s findings,it is concluded that this suggested approach improves load balancing consistency,response time,and throughput by 6%.

关键词： Load balancing throttled algorithm efficient resource allocation

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Enhancing Service Management in Industry 4.0: The Role of AI-Powered Chatbots

Enhancing Service Management in Industry 4.0: The Role of AI...

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2024 Advances in Science and engineering technology International Conferences, ASET 2024

作者： Albeshr, Asraa Mohammed Alnajjar, Fady Abdulmouti, Hassan Mubin, Omar College of Information Technology Uae University Alain United Arab Emirates Faculty of Engineering Higher College of Technology Engineering Technology & Science Sharjah United Arab Emirates School of Computer Data and Mathmatical Science Westren Sydney University Sydney Australia

ISBN: (纸本)9798350344134

In the era of Industry 4.0, where digital transformation is crucial, developing advanced chatbot system becomes essential to revolutionize service management and bolstering business continuity. By leveraging Artificial Intelligence (AI) within such industrial frameworks, smartchatbots promise to streamline operations, ensure seamless customer interactions, and drive efficiency, thereby fortifying businesses in today's competitive landscape. This study presents an adaptable smart chatbot model designed to mimic and absorb the expertise of technical officers within a factory setting, responding to employee technical queries. This approach aims to alleviate the burden on technical personnel while enhancing response efficiency. Unlike traditional systems, this adaptive model benefits from continuous learning capabilities, enabling it to refine its responses over time based on new interactions and corrections made by technical officers. Furthermore, the chatbot's 24/7 availability and the collaborative feedback mechanism for evaluating its responses ensure that it not only meets but exceeds user expectations. Through detailed analysis and empirical evidence, we demonstrate how this chatbot significantly enhances work quality and operational continuity, setting a new benchmark for digital service management in the context of Industry 4.0. The results from conducting surveys among the technical officers regarding the chatbot's usefulness were overwhelmingly positive. All participants expressed high satisfaction, confirming that the implementation of such a smart chatbot model significantly reduces their load and enhances the user experience. © 2024 IEEE.

关键词： Efficiency

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Virtual Laboratory Learning Experience in engineering: An Extended technology Acceptance Model (TAM) 3

Virtual Laboratory Learning Experience in Engineering: An Ex...

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3rd IEEE International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and computer engineering, MI-STA 2023

作者： Ahmed Alnagrat, Ahmed Jamah Ahmed, Khamiss M. S. Alkhallas, Muhannad Ismail Almakhzoom, Osama Abulaqasim Ibrahim Syed Idrus, Syed Zulkarnain Che Ismail, Rizalafande Higher Institute of Science and Technology Wadi Al-Shati Department of Computer Science and Information Technology Wadi al-Shati Fezzan Libya Sebha University Faculty of Information Technology Department of Computer Science Sebha Libya Faculty of Engineering Technology in Zuwarah Department of Software Engineering Zuwarah Libya Department of Communication Perlis Kangar01000 Malaysia Arau02600 Malaysia

ISBN: (纸本)9798350319897

This research presents an enhanced version of the technology Acceptance Model (TAM), which integrates usability and learning objectives to evaluate the effect of adopting virtual laboratories on student performance. Data from 97 participants, gathered via a survey, was used to examine the correlation between perceived usefulness (PU), perceived ease of use (PEOU), and intention to use (IU) concerning their experiences and outcomes with a simulation-based virtual laboratory. A custom questionnaire was designed to assess TAM components, namely PU, PEOU, and IU, specifically in the context of virtual laboratory learning environments. Findings indicate that the integration of specific laboratory learning objectives fosters the creation of a more credible and authentic simulation tool. This, in turn, optimizes the learning process and enhances students' learning outcomes. The refined TAM model provides valuable insights into the determinants of user acceptance of virtual laboratories and offers practical guidance for educators and instructional designers to construct more effective and efficient virtual laboratory environments in educational contexts. © 2023 IEEE.

关键词： Virtual reality

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Multi-Scale Network for Thoracic Organs Segmentation

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computers, Materials & Continua 2022年第2期70卷 3251-3265页

作者： Muhammad Ibrahim Khalil Samabia Tehsin Mamoona Humayun N.Z Jhanjhi Mohammed A.AlZain Department of Computer Science Bahria UniversityIslamabadPakistan Department of Information systems College of Computer and Information SciencesJouf UniversityKSA School of Computer Science and Engineering(SCE) Taylor’s UniversityMalaysia Center for Smart Society 5.0(CSS5) Faculty of Innovation and Technology(FIT)Taylor’s UniversityMalaysia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Medical Imaging Segmentation is an essential technique for modern medical *** is the foundation of many aspects of clinical diagnosis,oncology,and computer-integrated surgical *** significant successes have been achieved in the segmentation of medical images,DL(deep learning)*** delineation of OARs(organs at risk)is vastly dominant but it is prone to errors given the complex irregularities in shape,low texture diversity between tissues and adjacent blood area,patientwide location of organisms,and weak soft tissue contrast across adjacent organs in CT *** now several models have been implemented onmulti organs segmentation but not caters to the problemof imbalanced classes some organs have relatively small pixels as compared to *** segment OARs in thoracic CT images,we proposed the model based on the encoder-decoder approach using transfer learning with the efficientnetB7 DL *** have built a fully connected CNN(Convolutional Neural network)having 5 layers of encoding and 5 layers of decoding with efficientnetB7 specifically to tackle imbalance class pixels in an accurate way for the segmentation of *** methodology achieves 0.93405 IOU score,0.95138 F1 score and class-wise dice score for esophagus 0.92466,trachea 0.94257,heart 0.95038,aorta 0.9351 and background *** results showed that our proposed framework can be segmented organs accurately.

关键词： Deep learning convolutional neural network computed tomography organs at risk computer-aided diagnostic

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Transformer-Based Single-Cell Language Model:A Survey

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Big Data Mining and Analytics 2024年第4期7卷 1169-1186页

作者： Wei Lan Guohang He Mingyang Liu Qingfeng Chen Junyue Cao Wei Peng Guangxi Key Laboratory of Multimedia Communications and Network Technology School of ComputerElectronic and InformationGuangxi UniversityNanning 530004China School of Computer and Electronic Information Guangxi UniversityNanning 530004China College of Life Science and Technology Guangxi UniversityNanning 530004China Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming 650500China

The transformers have achieved significant accomplishments in the natural language processing as its outstanding parallel processing capabilities and highly flexible attention *** addition,increasing studies based on transformers have been proposed to model single-cell *** this review,we attempt to systematically summarize the single-cell language models and applications based on ***,we provide a detailed introduction about the structures and principles of ***,we review the single-cell language models and large language models for single-cell data ***,we explore the datasets and applications of single-cell language models in downstream tasks,such as batch correction,cell clustering,cell type annotation,gene regulatory network inference,and perturbation ***,we discuss the challenges of single-cell language models and provide promising research *** hope this review will serve as an up-to-date reference for researchers who are interested in the direction of single-cell language models.

关键词： language model transformers deep learning single-cell data

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