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2023 IEEE International Conference on Smart Information Systems and Technologies, SIST 2023

作者： Dolhopolov, Serhii Honcharenko, Tetyana Savenko, Volodymyr Balina, Olena Bezklubenko, Iryna Liashchenko, Tamara Kyiv National University of Construction and Architecture Dept. of Cyber Security and Computer Engineering Kyiv Ukraine Kyiv National University of Construction and Architecture Dept. of Information Technologies of Design and Applied Mathematics Kyiv Ukraine Kyiv National University of Construction and Architecture Dept. of Organization and Management of Construction Kyiv Ukraine Kyiv National University of Construction and Architecture Dept. of Information Technologies Kyiv Ukraine

ISBN: (纸本)9798350335040

This study presents a multi-stage approach for building object models (BOMs) on a construction site, aimed at creating an 'evolutionary' digital twin. The integration of building information modeling (BIM) and artificial intelligence is used to achieve this goal, with the use of photo modeling using moving cameras and the potential integration of IoT technologies also discussed. A comprehensive artificial intelligence system, combining Convolutional Neural Network (CNN) and Feed Forward Neural Network (FFNN) architectures, has been developed to detect, categorize, and evaluate BIM projects throughout their life cycle. The scalability prospects for point cloud and mesh models, as well as the use of big data technology to optimize the representation of the digital twin, are also addressed. The study determines the effectiveness of construction site conformance detection during the construction of a BIM model, providing consistency and a quantitative evaluation of the processes taking place on the construction site. The findings of this research can be used to enhance BIM modeling methods and concepts toward a multi-stage representation of the digital twin of the construction site. © 2023 IEEE.

关键词： Architectural design

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Ship Data Clustering for Improved Fuel Efficiency Optimization Decision Support Systems

Ship Data Clustering for Improved Fuel Efficiency Optimizati...

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OCEANS 2024 - Halifax, OCEANS 2024

作者： Piercey, Caitlin Hamilton, Matthew Veitch, Brian Barnes, Joshua Jiang, Xianta Memorial University of Newfoundland Dept. of Computer Science St. John's Canada Memorial University of Newfoundland Dept. of Engineering and Applied Sciences St. John's Canada Ocean Coastal and River Engineering National Research Council Canada St. John's Canada

ISBN: (纸本)9798331540081

In this paper, we propose a hybrid clustering algorithm based on hierarchical clustering in combination with string clustering, similar to that used in clustering genetic sequences, to extract clusters of operational activities from ship data. After extracting clusters (n=9), the distribution and summary statistics of each cluster are compared to Canadian Coast Guard provided operational definitions to obtain context from the clusters. The clustered data is used as the input to a fuel flow prediction model, which will in turn form the basis of an on-board decision support system for marine vessels with the goal of reducing fuel consumption. Finally, we compare the results of fuel flow predictions with models trained on a) different clusters and b) the full dataset, to determine the usefulness of these clusters in improving the performance of a fuel-optimization decision support system for on-board marine vessel use. © 2024 IEEE.

关键词： Ships

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Prediction of Cardiac Arrest using Generalized Soft Computing Techniques 18

Prediction of Cardiac Arrest using Generalized Soft Computin...

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18th INDIAcom;11th International Conference on Computing for Sustainable Global Development, INDIACom 2024

作者： Hota, Radhanath Dash, Sachikant Mishra, Sujogya Das, Subhalaxmi Lenka, S. Pradhan, G. Giet University Department of Computer Science Engineering Odisha Gunupur India Gandhi Institute for Education and Technology Department of Computer Science Engineering Odisha Gunupur India Odisha University of Technology and Research Department of Mathematics Bhubaneswar India Odisha University of Technology and Research Dept. of Computer Science and Engineering Bhubaneswar India Utkal University Department of Computer Science and Application Bhubaneswar India

ISBN: (纸本)9789380544519

Cardiac-related diseases always lead to fatal consequences around the globe. This research includes vague data analysis of the data related to cardiac anomalies. This study proposes a method to develop a dimension reduction model using vague data related to cardiac diseases using rough set theory (RST). The overall research is divided into two different sections. The first section of this study proposes analyses of the raw cardiac-related data using RST, and the second section calculates the performance accuracy using Principal Component Analysis (PCA) applied to the universal data set;the performance measures also include a combination of two Universal data sets. The above claims are verified using statistical tests © 2024 Bharati Vidyapeeth, New Delhi.

关键词： PCA Performance and accuracy Rough Set Theory Statistical method Vague data

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Enhancement of Virtual Machine Migration using Artificial Bee Colony Algorithm 11

Enhancement of Virtual Machine Migration using Artificial Be...

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11th International Conference on Reliability, Infocom Technologies and Optimization, ICRITO 2024

作者： Thind, Anu Gagandeep Singh, Harvinder Kaushal, Priyanka Kumari, Nisha Singh, Harpal Lamba, Shweta Sharma, Avinash CEC-CGC Dept. of Computer Sci. Engg. Punjab Landran India CEC-CGC Dept. of Mechanical Engg. Punjab Landran India CEC-CGC Dept. of Mathematics Punjab Landran India CEC-CGC Dept. of Electronics. Engg. Punjab Landran India CEC-CGC Punjab Landran India Chandigarh Engineering College Director Engineering Jhanjeri India

ISBN: (纸本)9798350350357

The use of large-scale computer devices is expanding more quickly, which has led to a significant rise in energy consumption and carbon emissions. Controlling these adverse consequences is necessary to make the computer platform environmentally friendly. Scheduling is one such element that has to be addressed in order to improve the cloud architecture. In light of the Scheduling process, load balancing is a crucial component that requires optimization. In addition to maximizing throughput and reaction time and facilitating efficient resource usage, load balancing also guards against overloading. The virtual machines are moved among many hosts to improve CPU resources and load balancing. The virtual machines that are moved will be determined by taking into account the CPU usage under three different conditions: when the CPU utilization reaches 90%, 10%, and 0%, depending on the performance of different machines. Taking this into consideration, this study suggests a general method to start the virtual machine migration, which might enhance the load balancing procedure overall. © 2024 IEEE.

关键词： Virtual machine

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Evolution of Metallic Connection Technologies of Busbar in Silicon Solar Cells: Brief Review 15

Evolution of Metallic Connection Technologies of Busbar in S...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： Silveira, A.M.C. Neves, M.R.M. Garcia, R. Alvarez, H. Villalva, M.G. Marques, F.C. Kretly, L.C. School of Electrical and Computer Engineering Communications Department - DECOM Campinas Brazil School of Electrical and Computer Engineering Dept. of Systems and Energy - DSE Campinas Brazil Institute of Physics Gleb Wataghin Dept. of Applied Physics - DFA Campinas Brazil Build Your Dreams Company - BYD Dept. Research and Development - R&D Campinas Brazil

ISBN: (纸本)9798350314182

This work consists of presenting a brief review of the evolution of metallic connection technologies in busbars applied to the front and rear of solar cells, thus demonstrating their fundamentals, materials and essential manufacturing processes that impact on improving the energy efficiency of solar modules. In this brief review, one can follow the technical limitations that led to the evolution of metallic connection technologies in busbars over time and their impacts on the photovoltaic market. Contributing to a broad understanding of the resistive components of solar cells that consists of the series resistance parameter. © 2023 IEEE.

关键词： Busbarless Effective Shadow Ribbon Busbar Serie Resistance Solar cell TLM Wire Busbar

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Comparison of 2D SURE and 3D CT imaging of cortical vessels in a rat kidney

Comparison of 2D SURE and 3D CT imaging of cortical vessels ...

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2023 IEEE International Ultrasonics Symposium, IUS 2023

作者： Hansen, Lauge Naur Kjer, Hans Martin Amin-Naji, Mostafa Panduro, Nathalie Sarup Sørensen, Charlotte Mehlin Gundlach, Carsten Dahl, Anders Bjorholm Jensen, Jørgen Arendt Technical University of Denmark Dept. of Health Technology Kgs. Lyngby Denmark Technical University of Denmark Dept. of Applied Mathematics and Computer Science Kgs. Lyngby Denmark University of Copenhagen Dept. of Biomedical Sciences Copenhagen Denmark Technical University of Denmark Dept. of Physics Kgs. Lyngby Denmark

ISBN: (纸本)9798350346459

SUper-Resolution ultrasound imaging using the Erythrocytes (SURE) can visualize blood vessels at about 25 to 50 μm resolution, but validation is required to assess how accurately the vasculature and its morphology are represented. Previous work compared ultrasound imaging to maximum intensity projections (MIP) of micro-CT volumes at an insufficient voxel size of 22.6 μm. Here, a 5 μm voxel size micro-CT volume of a cortical region in an excised rat kidney was acquired to test the hypothesis that blood vessels down to 50 μm in diameter are detected with SURE imaging. For the micro-CT volume, the blood vessels were segmented by an intensity threshold, and local thickness estimates were computed using expanding spheres within the segmentation mask. An affine registration between the SURE image and the micro-CT volume was manually defined, and a MIP of the micro-CT volume across 2 mm from the ultrasound imaging plane was computed for vessels with diameter estimates greater than 50 μm. The SURE image depicts 12 cortical radial vessels with high intensities and 9 dimmer cortical radial vessels. Notably, the 12 high intensity vessels are also depicted in the micro-CT projection, but 5 cortical radial vessels and 2 arcuate blood vessels are only visible in the SURE image. Of the faintly depicted cortical radial vessels, 5 vessels are not readily matched to vessels in the micro-CT projection. On the other hand, the micro-CT projection contains 6 cortical radial vessel segments and 2 arcuate blood vessels not depicted in the SURE image. These discrepancies in the comparison may arise from the challenging registration of the ultrasound focus beam and the micro-CT volume that is complicated further by the different states of the imaged tissue. Despite these challenges, SURE depicts most vessels at least down to 50 μm and even resolves parallel vessels not visible in the micro-CT projection, thus highlighting its clinical potential. © 2023 IEEE.

关键词： Blood vessels

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RadioModRec-l: A Large Scale Radio Frequency Dataset for Automatic Modulation Recognition Research 4

RadioModRec-l: A Large Scale Radio Frequency Dataset for Aut...

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4th International Conference on Emerging Trends in Networks and computer Communications, ETNCC 2024

作者： Adetiba, Emmanuel Olasina, Jamiu R. Obiyemi, Obiseye Covenant University Covenant Applied Informatics and Communication Africa Center of Excellence Dept. of Electrical and Information Engineering Ota Nigeria HRA Institute for Systems Science Durban University of Technology Durban4001 South Africa Federal Polytechnic Ilaro Dept. of Computer Engineering Ilaro Nigeria Durban University of Technology Space Science Centre Dept. of Electrical Power Engineering Durban South Africa

ISBN: (纸本)9798350353266

Access to well-curated large datasets remains a significant bottleneck in AI-based research within wireless communication. Rapid advancements in neighbouring fields, such as computer vision and natural language processing, are largely due to the availability of extensive open-access datasets. However, similar progress has not been observed in wireless communication. To address this gap, we curated a comprehensive dataset for fifteen digital modulation schemes, including 4QAM, 16QAM, 64QAM, 256QAM, 8PSK, 16PSK, 32PSK, 64PSK, 128PSK, 256PSK, CPFSK, DBPSK, DQPSK, GFSK, and GMSK. Our dataset considers Rayleigh and Rician channel models under Additive White Gaussian Noise (A WGN) with SNRs ranging from -20dB to + 20dB in 5dB increments. The data samples were converted to constellation signal images and carefully pre-processed. Named RadioModRec, this dataset provides a valuable resource for researchers to train and evaluate AI models. It is freely accessible on Kaggle, promoting further innovation in the wireless communication domain. © 2024 IEEE.

关键词： Signal to noise ratio

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On the constitutive behavior of linear viscoelastic solids under the plane stress condition

arXiv

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arXiv 2025年

作者： Guzina, Bojan B. Bonnet, Marc Dept. of Civil Environmental and Geo-Engineering University of Minnesota United States Dept. of Applied Mathematics ENSTA Paris France

Motivated by the recent experimental and analytical developments enabling high-fidelity material characterization of (heterogeneous) sheet-like solid specimens, we seek to elucidate the constitutive behavior of linear viscoelastic solids under the plane stress condition. More specifically, our goal is to expose the relationship between the plane-stress viscoelastic constitutive parameters and their (native) "bulk" counterparts. To facilitate the sought reduction of the three-dimensional (3D) constitutive behavior, we deploy the concept of projection operators and focus on the frequency-domain behavior by resorting to the Fourier transform and the mathematical framework of tempered distributions, which extends the Fourier analysis to functions (common in linear viscoelasticity) for which Fourier integrals are not convergent. In the analysis, our primary focus is the on class of linear viscoelastic solids whose 3D rheological behavior is described by a set of constant-coefficient ordinary differential equations, each corresponding to a generic arrangement of "springs" and "dashpots". On reducing the general formulation to the isotropic case, we proceed with an in-dept. investigation of viscoelastic solids whose bulk and shear modulus each derive from a suite of classical "spring and dashpot" configurations. To enable faithful reconstruction of the 3D constitutive parameters of natural and engineered solids via (i) thin-sheet testing and (ii) applications of the error-in-constitutive-relation approach to the inversion of (kinematic) sensory data, we also examine the reduction of thermodynamic potentials describing linear viscoelasticity under the plane stress condition. The analysis is complemented by a set of analytical and numerical examples, illustrating the effect on the plane stress condition on the behavior of isotropic and anisotropic viscoelastic solids. Copyright © 2025, The Authors. All rights reserved.

关键词： Frequency domain analysis

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Thermal Error Modelling using Features selected from Particle Swarm Optimization 5

Thermal Error Modelling using Features selected from Particl...

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5th International Conference on Circuits, Control, Communication and Computing, I4C 2024

作者： Ajith Kumar, B. Nayana, B.R. Shashank, P. M. S. Ramaiah University of Applied Sciences Dept. of Computer Science and Engineering Bengaluru India Ace Designers Ltd. Research and Technology Development Group Bengaluru India

ISBN: (数字)9798331528539

ISBN: (纸本)9798331528539

computer Numerical Control (CNC) machines are employed in various industrial manufacturing processes to produce precise components. The CNCs are prone to thermal deviations from the heat generated during machining. Axis motors, rotary bearings, and spindle motors are the main sources of heat. In this context, temperature sensitive areas (TSAs) apply to these locations. The accuracy of the machining process is directly affected by the heat-induced deviation between the tool and the workpiece. The objective is to minimize these deviations between the tool and the workpiece. The most challenging aspect of creating thermal error compensation models is figuring out which TSAs to use. This work proposes employing particle swarm optimization (PSO), a computational intelligence (CI) technique, to choose significant features. First, information about the machine's temperature and thermal deviation is collected. Second, the outliers are eliminated by cleaning the data. Following this, PSO optimizes the error band to identify which TSAs are significant. Advanced machine learning (ML) models like polynomial regression (PR) and random forest (RF) regression are trained utilizing these TSAs as features. The proposed approach is compared with matching models developed with features selected through the brute force (BF) approach. While PSO-RF outperformed BF-RF in providing 16.60% error reduction with different features, PSO-PR and BF-PR provided 47.12% error band reduction with similar features. Based on the findings, it can be concluded that PSO-PR can be used on the machine and that PSO outperforms BF in terms of identifying the ideal subset of influential features. © 2024 IEEE.

关键词： Error compensation

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A Deep Learning Based Critical Analysis Of Skin Lesion Classification

A Deep Learning Based Critical Analysis Of Skin Lesion Class...

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2024 International Conference on Advances in Modern Age Technologies for Health and engineering Science, AMATHE 2024

作者： Rahul Gupta, Meenu Kumar, Rakesh Obaid, Ahmed J. Chandigarh University Dept. Of Cse Punjab India University Of Kufa Faculty Of Computer Science And Mathematics Najaf Iraq College Of Technical Engineering National University Of Science And Technology Dhi Qar Iraq

ISBN: (纸本)9798350371567

In everyday life, various exposures at work or at home can lead to skin conditions such as allergies or infections. Skin lesions serve as essential indications, alerting to future issues and requiring immediate care and attention. To search for publications concerning skin lesions and diverse procedures, the most well-known scientific databases, such as web of science, scopus, and IEEE Xplore, were used. To find comparable documents, search engines use keywords such as 'skin lesion,' 'CNN,' 'skin diseases,' and so on. Following a comprehensive screening method, 658 abstracts from databases are collected, and 19 full-text articles are identified for consideration. This paper investigates the profound impact of machine learning in dermatology, with a focus on skin lesion classification. This study provides a critical examination of CNN-based models, emphasizing their importance and difficulties in increasing precision diagnosis and treatment in dermatology. Overall, this study provides helpful insights into various approaches for skin lesion classification. © 2024 IEEE.

关键词： Dermatology

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