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32nd Telecommunications Forum, TELFOR 2024

作者： Bajovic, Dragana Jakovetic, Dusan Kar, Soummya Vukovic, Manojlo University of Novi Sad Faculty of Technical Sciences Department of Power Electronic and Communication Engineering Serbia University of Novi Sad Faculty of Sciences Department of Mathematics and Informatics Serbia Carnegie Mellon University Department of Electrical and Computer Engineering United States University of Novi Sad Faculty of Technical Sciences Department of Fundamental Sciences Serbia

ISBN: (纸本)9798350391053

We present an algorithm for distributed estimation of an unknown vector parameter θ∗ ∈ M in the presence of heavy-tailed observation and communication noises. Heavy-tailed noises frequently appear, e.g., in densely deployed Internet of Things (IoT) or wireless sensor network systems. The presented algorithm falls within the class of consensus+innovation estimators and combats the effect of the heavy-tailed noises by adding general nonlinearities in the consensus and innovations update parts. We present results on almost sure convergence and asymptotic normality of the estimator. In addition, we provide novel analytical studies that reveal interesting tradeoffs between the system noises and the underlying network topology. © 2024 IEEE.

关键词： Internet of things

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RMSD Calculations for Comparing Protein Three-Dimensional Structures 10th

RMSD Calculations for Comparing Protein Three-Dimensional S...

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10th International Conference on Numerical Methods and Applications, NMA 2022

作者： Sapundzhi, Fatima Popstoilov, Metodi Lazarova, Meglena Department of Communication and Computer Engineering Faculty of Engineering South-West University "Neofit Rilski" Blagoevgrad2700 Bulgaria Department of Mathematical Modelling and Numerical Methods Faculty of Applied Mathematics and Informatics Technical University of Sofia Sofia1000 Bulgaria

ISBN: (纸本)9783031324116

The root Mean Square Deviation (RMSD) is a popular measure of structural similarity between protein structures in the field of bioinformatics. The RMSD calculations involve alignment and optimal superposition between matched pairs of atoms, searching for the lowest RMSD result for both structures. Among the popular methods for calculating the optimal rotation matrix that minimizes the RMSD are the Kabsch algorithm and the Quaternion algorithm. The aim of this research is to present a simple tool for calculation of the RMSD between pairs of aligned three dimensional structures by applying the methods mentioned above. As an implementation language the object-oriented C# programming language has been chosen. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Proteins

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Non-GPS-based ETA Models Constructed from Historical GPS Data and Traffic Contexts 8

Non-GPS-based ETA Models Constructed from Historical GPS Dat...

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8th International Conference on Business and Industrial Research, ICBIR 2023

作者： Phon-Amnuaisuk, Somnuk Tan, Soon-Jiann Khor, Kok-Chin Tham, Mau-Luen Chong, Yung-Wey Omar, Saiful Ibrahim, Noor Farizah Binti Yusoff, Mohd Najwadi Mashud, Idham School of Computing and Informatics Universiti Teknologi Brunei Brunei Universiti Teknologi Brunei Faculty of Engineering Brunei Universiti Tunku Abdul Rahman Lkc Faculty of Engineering and Science Malaysia Universiti Sains Malaysia School of Computer Sciences Malaysia

ISBN: (纸本)9798350399646

Without GPS data, ETA can be estimated with good precision from historical GPS data and the context of the traffic environment. In this paper, the estimated travel duration between bus stops was computed based on historical GPS data with time stamps. Three approaches were employed to compute the duration between bus stops: (i) statistical central tendencies, (ii) nonlinear regression techniques i.e., decision tree regressor, random forest regressor and k-nearest neighbors regressor, and (iii) an ANN predictive model. These three approaches capture different characteristics of the traffic environment. Statistical central tendencies give the overall view of the ETA information while nonlinear regressors can capture context from the time stamps (e.g., weekdays vs holidays). Finally, predicting the duration required to reach the next bus stop based on previous timespans on the same route implicitly captures temporal dynamics of the traffic environment from previous time steps and the ANN predictive model exploits this temporal information. The feasibility of ETA estimation using these three approaches was explained, evaluated and discussed. © 2023 IEEE.

关键词： Decision trees

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Estimating Mutual Information for Link Adaptation in Generalized Spatial Modulation Systems with Neural Networks 26

Estimating Mutual Information for Link Adaptation in General...

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26th International ITG Workshop on Smart Antennas, WSA 2023 and 13th Conference on Systems, Communications, and Coding, SCC 2023

作者： Bailon, Daniel Nicolas Kühn, Volker Shavgulidze, Sergo Freudenberger, Jürgen Institute for System Dynamics HTWG Konstanz University of Applied Sciences Germany Institute of Communications Engineering Faculty of Computer Science and Electrical Engineering University of Rostock Germany Faculty of Informatics and Control Systems Georgian Technical University Georgia Germany

ISBN: (纸本)9783800760510

Spatial modulation (SM) is a low-complexity multiple-input/multiple-output transmission technique that combines index modulation and quadrature amplitude modulation for wireless communications. In this work, we consider the problem of link adaption for generalized spatial modulation (GSM) systems that use multiple active transmit antennas simultaneously. Link adaption algorithms require a real-time estimation of the link quality of the time-variant communication channels, e.g., by means of estimating the mutual information. However, determining the mutual information of SM is challenging because no closed-form expressions have been found so far. Recently, multilayer feedforward neural networks were applied to compute the achievable rate of an index modulation link. However, only a small SM system with two transmit and two receive antennas was considered. In this work, we consider a similar approach but investigate larger GSM systems with multiple active antennas. We analyze the portions of mutual information related to antenna selection and the IQ modulation processes, which depend on the GSM variant and the signal constellation. © VDE VERLAG GMBH · Berlin · Offenbach.

关键词： Complex networks

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Improved LOPCOW-SAW Method for Optimal Supplier Selection in Supply Chain Management

Improved LOPCOW-SAW Method for Optimal Supplier Selection in...

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International Conference on Cyber and IT Service Management (CITSM)

作者： Sumanto Sumarna Hafis Nurdin Taufik Asra Irwan Agus Sobari Herman Kuswanto Indra Chaidir Ibnu Akil Felix Wuryo Handono Informatics Faculty of Engineering and Informatics Universitas Bina Sarana Informatika Jakarta Indonesia Information System Faculty of Engineering and Informatics Universitas Nusa Mandiri Jakarta Indonesia Software Engineering Faculty of Engineering and Informatics Universitas Bina Sarana Informatika Jakarta Indonesia Information System Faculty of Engineering and Informatics Universitas Nusa Mandiri Universitas Bina Sarana Informatika Computer Engineering Faculty of Engineering and Informatics Universitas Nusa Mandiri Universitas Bina Sarana Informatika

ISBN: (数字)9798331528799

ISBN: (纸本)9798331528805

Supplier selection is a critical component of Supply Chain Management (SCM), as suppliers provide raw materials or services essential for supporting a company's operations. Traditional supplier selection methods often rely on subjective assessments to determine the weighting of criteria, which can lead to biases and suboptimal decision making. To address this issue, this study combines the Logarithmic Percentage Change of Weight (LOPCOW) method with the Simple Additive Weighting (SAW) method to enhance objectivity in the supplier selection process. The LOPCOW method is used to assign criterion weights objectively based on logarithmic percentage changes, which helps minimize subjectivity, These weights are then applied using the SAW method to evaluate and rank suppliers. The results of the study show that this combined approach is more reliable for selecting suppliers objectively and accurately. The study suggests integrating other Multi-Criteria Decision-Making (MCDM) methods to further strengthen the results while recommending the inclusion of real-time data analytics to improve the model's adaptability to dynamic market conditions. The LOPCOW-SAW approach can be applied across various industries for more effective and efficient SCM supplier selection.

关键词： Industries Analytical models Adaptation models Supply chain management Data analysis Real-time systems Data models Robustness MCDM Weighted sum model

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A Comparison Study on Generative Adversarial Networks (GANs) for Satellite Image Upscaling 12

A Comparison Study on Generative Adversarial Networks (GANs)...

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12th IEEE Conference on Systems, Process and Control, ICSPC 2024

作者： Li, Brandon Kah Wei Jasser, Muhammed Basheer Issa, Bayan Ajibade, Samuel-Soma M. Chua, Hui Na Wong, Richard T.K. Hamzah, Muzaffar Sunway University No. 5 Jalan Universiti School of Engineering and Technology Department of Computing and Information Systems Selangor Darul Ehsan Bandar Sunway47500 Malaysia School of Engineering and Technology Selangor Darul Ehsan Bandar Sunway47500 Malaysia University of Aleppo Faculty of Informatics Engineering Syria Istanbul Ticaret University Department of Computer Engineering Istanbul Turkey Universiti Malaysia Sabah Faculty of Computing and Informatics Sabah Kota Kinabalu88450 Malaysia

ISBN: (纸本)9798350391398

Satellite images that are publicly available on the internet such as Google Maps are mostly low-quality and blurry which is not very useful for research or decision-making due to the lack of details. Recently image upscaling has been increasing in popularity to address several real-world problems where one approach is using Convolutional Neural Networks (CNNs). However, CNNs have difficulty in restoring fine details and this has led to the use of Generative adversarial networks (GANs) for image scaling. In this paper, three GAN models are trained which are Enhanced Super-Resolution Generative Adversarial Networks (Real-ESRGAN), Image Restoration Using Swin Transformer (SwinIR-Medium), and Dual Aggregation Transformer (DAT-2). The models are evaluated with well-known image metrics to determine each model's effectiveness in upscaling low-resolution satellite images. The results show that all models can reconstruct the image to some degree where the best out of the three is DAT-2. Further fine-tuning of the best model by changing the loss functions has shown improvements in structural integrity for the upscaled image. © 2024 IEEE.

关键词： Generative adversarial networks

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A novel approach to predicting liquefaction-induced settlements using Kolmogorov–Arnold Networks (KANs)

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Discover Geoscience 2024年第1期2卷 1-14页

作者： Karakaş, Seyidcem Garanti BBVA Payment Systems İstanbul Turkey Faculty of Computer and Informatics Engineering Istanbul Technical University Istanbul Turkey

Soil liquefaction refers to the loss of strength and bearing capacity of soil under dynamic loads. Structures built on liquefied soils experience settlement. In this study, the newly developed Kolmogorov–Arnold Networks (KAN) method, an innovative artificial neural network technique, was utilized to predict liquefaction-induced settlement. The KAN method, which extends beyond the traditional Multi-Layer Perceptron (MLP) approach, was compared with the Random Forest method for benchmarking purposes. Using data derived from laboratory and field studies, models were constructed using both methods, and their performances were analyzed. According to the results, the KAN model outperformed the RF model in terms of R2, MAE, MSE, and RMSE metrics. Additionally, the feature importance analysis on the KAN model identified cyclic stress ratio (csr) and corrected SPT blow count (n1_60) as the most significant variables. These results underscore the potential of the KAN method in enhancing predictive accuracy and reliability in geotechnical applications, paving the way for its broader acceptance and implementation in real-world scenarios.

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Improving DL-Learner on a Malware Detection Use Case 36

Improving DL-Learner on a Malware Detection Use Case

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36th International Workshop on Description Logics, DL 2023

作者： Bisták, Tomáš Švec, Peter Kluka, Ján Šimko, Alexander Balogh, Štefan Homola, Martin Department of Applied Informatics Faculty of Mathematics Physics and Informatics Comenius University Mlynská dolina Bratislava842 48 Slovakia Institute of Computer Science and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovicova 3 Bratislava812 19 Slovakia

Automation of malware characterization has become increasingly important for early malware detection over the past decades. Since it is crucial to be able to perform malware detection transparently, explainable machine-learning methods may be considered particularly suitable for this application. In our previous work, we thus employed algorithms for learning description-logics concept expressions to obtain structured characterizations of malicious software. The results of our initial experiments, however, lead us to several inconsistencies in the behaviour of the studied algorithms included in DL-Learner, a widely adopted framework for concept learning. Hence, in this work, we make a couple of corrections to DL-Learner, along with a few further enhancements, and repeat the experiments to empirically assess the effects of our changes. The outcomes show that the modified algorithms can mark an improvement in terms of the predictability of their behaviour as well as evaluation metrics. © 2023 CEUR-WS. All rights reserved.

关键词： Malware

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Mobile Device Facial Beauty Prediction using Convolutional Neural Network as Makeup Reference

Mobile Device Facial Beauty Prediction using Convolutional N...

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2022 International Conference on computer engineering, Network and Intelligent Multimedia, CENIM 2022

作者： Luthfi, Muhammad Rachmadi, Reza Fuad Purnama, I Ketut Eddy Nugroho, Supeno Mardi Susiki Institut Teknologi Sepuluh Nopember Faculty of Electrical and Intellignet Informatics Department of Computer Engineering Surabaya60111 Indonesia

ISBN: (纸本)9781665476508

Beauty or good looks is one aspect of human attraction. Highly attractive people have an 8 to 12 % higher success in negotiations. One of the things that can be used to increase attractiveness is makeup or cosmetics. Makeup can be used alone or through the services of a Makeup Artist (MUA). MUA services are often used during important and once-in-A-lifetime events such as weddings. The difference in beauty before and after using this makeup cannot be measured but only seen and assessed manually. One application of machine learning in this field is Facial Beauty Predictions (FBP). FBP measures the value of a person's facial beauty or good looks. This paper investigated and implemented FBP on mobile devices, which makes it easier to assess anytime and anywhere. We investigated FBP models using five CNN architectures, including EfficientNetB0, VGG-16, ShuffleNet, MobileNet, and Inception. After evaluation, we choose MobileNetV2 CNN architecture as the primary model for mobile application FBP. Experiments on the FBP dataset show that MobileNetV2 achieves Pearson Correlation 0.7893 with only 10.5 MB for model file size. The model implemented for mobile devices works well in 13 different tests. © 2022 IEEE.

关键词： Forecasting

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Bad channel detection in EEG recordings

Bad channel detection in EEG recordings

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作者： Komosar, Milana Fiedler, Patrique Haueisen, Jens Institute of Biomedical Engineering and Informatics Faculty of Computer Sciences and Automation Technische Universität Ilmenau Ilmenau Germany

Electroencephalography (EEG) is widely used in clinical applications and basic research. Dry EEG opened the application area to new fields like self-application during gaming and neurofeedback. While recording, the signals are always affected by artefacts. Manual detection of bad channels is the gold standard in both gel-based and dry EEG but is time-consuming. We propose a simple and robust method for automatic bad channel detection in EEG. Our method is based on the iterative calculation of standard deviations for each channel. Statistical measures of these standard deviations serve as indications for bad channel detection. We compare the new method to the results obtained from the manually identified bad channels for EEG recordings. We analysed EEG signals during resting state with eyes closed and datasets with head movement. The results showed an accuracy of 99.69 % for both gel-based and dry EEG for resting state EEG. The accuracy of our new method is 99.38 % for datasets with the head movement for both setups. There was no significant difference between the manual gold standard of bad channel identification and our iterative standard deviation method. Therefore, the proposed iterative standard deviation method can be used for bad channel detection in resting state and movement EEG recordings. © 2022 The Author(s), published by De Gruyter.

关键词： Electroencephalography

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