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Impact of Parameters for the In-situ Measurement of the Electric Field Strength of the SSB Signal in a 5G NR System Using the Frequency-Selective Method in Zero-Span Mode

Impact of Parameters for the In-situ Measurement of the Elec...

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International Conference on Smart Systems and Technologies (SST)

作者： Vanja Mandrić Slavko Rupčić Bogdan Pavković Josip Ilakovac Department of Communication Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia Faculty of Electrical Engineering Computer Science and Information Technology Osijek Osijek Croatia

ISBN: (数字)9798350386394

ISBN: (纸本)9798350386400

Measuring 5G systems is a major challenge for measurement engineers, who need to be aware of all the limitations of the new generation The parameters of the frequency-selective measurement system (spectrum analyzer - ROHDE & SCHWARZ FSH8) were investigated in the measurement of 5G NR SSB signals (3.4 – 3.8 GHz). The focus was on the setting parameters which, according to the literature, have an influence on the measurement: RBW, VBW, SWEEP TIME and the duration of the measurement. All measurements were carried out in zero-span mode. In the second part of the measurement, these SSB synchronization signal measurement results were compared with the 5G signal measurement results at the same location using the NARDA SRM-3006 device equipped with a decoder for the 5G NR system (FR1) to determine the optimal method for measuring these signals with a spectrum analyzer (SA).The measurement results show that the resolution bandwidth (RBW) has the largest variation in the measured electric field (EF) strength values of the SSB 5G NR signal of 17.20 dB (MH/RMS) and 17.70 (RMS/AGV10). It is therefore necessary to pay particular attention to the setting of this measurement parameter. In addition, the video resolution (VBW) shows a significantly lower field strength variation of 2.50 dB, but also the same deviation from the reference value of 2.50 dB (RMS/AGV10). Other analyzed parameters have a negligible influence on the measurement of the EF *** post-processing was performed in the work to determine the final (maximum) value of the EF strength at the points of assumed highest exposure, which is used to assess the impact and compliance with the permissible values according to the relevant standards.

关键词： Time-frequency analysis 5G mobile communication Measurement uncertainty Electric variables measurement Amplitude modulation Time measurement Frequency measurement Decoding Electric fields Signal resolution

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Explainable Artificial Intelligence Solution for Online Retail

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Computers, Materials & Continua 2022年第6期71卷 4425-4442页

作者： Kumail Javaid Ayesha Siddiqa Syed Abbas Zilqurnain Naqvi Allah Ditta Muhammad Ahsan M.A.Khan Tariq Mahmood Muhammad Adnan Khan Department of Computer Science University of South AsiaLahore54000Pakistan Department of Mechatronics and Control Engineering University of Engineering and TechnologyLahore54000Pakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Division of Science and Technology University of EducationLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of SoftwareGachon UniversitySeongnam13557Korea

Artificial intelligence(AI)and machine learning(ML)help in making predictions and businesses to make key decisions that are beneficial for *** the case of the online shopping business,it’s very important to find trends in the data and get knowledge of features that helps drive the success of the *** this research,a dataset of 12,330 records of customers has been analyzedwho visited an online shoppingwebsite over a period of one *** main objective of this research is to find features that are relevant in terms of correctly predicting the purchasing decisions made by visiting customers and build ML models which could make correct predictions on unseen data in the *** permutation feature importance approach has been used to get the importance of features according to the output variable(Revenue).Five ML models i.e.,decision tree(DT),random forest(RF),extra tree(ET)classifier,Neural networks(NN),and Logistic regression(LR)have been used to make predictions on the unseen data in the *** performance of each model has been discussed in detail using performance measurement techniques such as accuracy score,precision,recall,F1 score,and ROC-AUC *** model is the bestmodel among all five chosen based on accuracy score of 90%and F1 score of 79%followed by extra tree ***,our study indicates that RF model can be used by online retailing businesses for predicting consumer buying *** research also reveals the importance of page value as a key feature for capturing online purchasing *** may give a clue to future businesses who can focus on this specific feature and can find key factors behind page value success which in turn will help the online shopping business.

关键词： Explainable artificial intelligence online retail neural network random forest regression

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Impact of energy leakage on the energy performance of green IoT nodes

Impact of energy leakage on the energy performance of green ...

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International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS)

作者： Godlove Suila Kuaban Tadeusz Czachórski Erol Gelenbe Piotr Pecka Valery Nkemeni Piotr Czekalski Polish Academy of Sciences (IITiS PAN) Institute of Theoretical and Applied Informatics Gliwice Poland Laboratory of Electrical Engineering and Computing Faculty of Engineering and Technology University of Buea Cameroon Faculty of Automatic Control Electronics and Informatics Silesian University of Technology Gliwice Poland

ISBN: (数字)9798331531300

ISBN: (纸本)9798331531317

In the present paper, we investigate the impact of imperfections (non-idealities) of the energy storage system (e.g., batteries, capacitors, or supercapacitors) on the energy performance of green IoT nodes. In particular, we investigate the impact of energy leakage from the Energy Storage System (ESS) on important energy performance metrics, such as service outage probability, the density of the lifetime of the node, and the time-dependent mean number of energy packets (EPs) in the ESS. Also, we explore various strategies that can be employed to compensate for the impact of energy losses due to energy leakage on the energy performance metrics. Specifically, we examine two potential strategies for improving the energy performance of the IoT nodes: (i) through increasing the energy generation rate of the energy harvesters (e.g., by adding additional solar panels or replacing the existing solar panels with more efficient ones that can produce more energy), and (ii) through reducing the energy consumption rate of the IoT node (e.g., by configuring ESS energy thresholds below which the nodes are forced to operate in low energy consumption states).

关键词： Measurement Energy consumption Green products Production Probability Energy efficiency Sensors Power system reliability Solar panels Internet of Things

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Energy performance of Internet of Things (IoT) networks for pipeline monitoring

Energy performance of Internet of Things (IoT) networks for ...

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International Wireless Communications and Mobile computing Conference, IWCMC

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Pipelines are the most convenient ways to transport fluids (e.g., water, oil, and gas). However, leakage of fluids into the environment results in resource wastage (primarily water, which is becoming a scarce resource) and environmental pollution (in the case of leakage of toxic fluids like oil and gas). Emerging technologies like the Internet of Things (IoT), Wireless Sensor Networks (WSNs), Artificial Intelligence (AI), distributed computing, and cloud computing enable continuous monitoring of pipelines to detect leakages and corrosion on the pipeline. The main challenge with using battery-powered sensor nodes to monitor pipelines is the energy constraint, necessitating frequent battery replacement. Thus, there is a need to develop energy-saving mechanisms to prolong the lifetime of these sensor nodes. In this paper, we use the diffusion approximation modelling framework in which the data from the experimental testbed are used to model the dynamics of the battery’s energy content and to estimate the mean and variance of the device’s lifetime. The novelty in the proposed diffusion model of the battery of an IoT node is the introduction of multiple energy thresholds that split the energy state-space of the battery into multiple energy-saving regimes. As the battery discharges, the node gradually transitions into energy-saving regimes by reconfiguring some of its parameters to reduce energy consumption (sometimes at the cost of trading off some performance metrics). We investigate the impact of energy-saving regimes or the number of thresholds on the node’s lifetime.

关键词： Wireless sensor networks Fluids Pipelines Data models Water pollution Batteries Sensors

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Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4027-4041页

作者： Doaa Sami Khafaga El-Sayed M.El-kenawy Fadwa Alrowais Sunil Kumar Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt School of Computer Science University of Petroleum and Energy StudiesDehradun248001India Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

In data mining and machine learning,feature selection is a critical part of the process of selecting the optimal subset of features based on the target *** are 2n potential feature subsets for every n features in a dataset,making it difficult to pick the best set of features using standard ***,in this research,a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm(ASSOA)has been *** using metaheuristics to pick features,it is common for the selection of features to vary across runs,which can lead to *** of this,we used the adaptive squirrel search to balance exploration and exploitation duties more evenly in the optimization *** the selection of the best subset of features,we recommend using the binary ASSOA search strategy we developed *** to the suggested approach,the number of features picked is reduced while maximizing classification accuracy.A ten-feature dataset from the University of California,Irvine(UCI)repository was used to test the proposed method’s performance *** other state-of-the-art approaches,including binary grey wolf optimization(bGWO),binary hybrid grey wolf and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hybrid GWO and genetic algorithm 4028 CMC,2023,vol.74,no.2(bGWO-GA),binary firefly algorithm(bFA),and *** results confirm the superiority and effectiveness of the proposed algorithm for solving the problem of feature selection.

关键词： Metaheuristics adaptive squirrel search algorithm optimization methods binary optimizer

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Autonomous Exploration of Unknown 3D Environments Using a Frontier-Based Collector Strategy

Autonomous Exploration of Unknown 3D Environments Using a Fr...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Iván D. Changoluisa Caiza Ana Milas Marco A. Montes Grova Francisco Javier Pérez-Grau Tamara Petrovic University of Zagreb Faculty of Electrical Engineering and Computing LARICS Laboratory for Robotics and Intelligent Control Systems Zagreb Croatia Advanced Center for Aerospace Technologies (CATEC) Aerospace Technology Park of Andalusia Seville Spain

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Autonomous exploration using unmanned aerial vehicles (UAVs) is essential for various tasks such as building inspections, rescue operations, deliveries, and warehousing. However, there are two main limitations to previous approaches: they may not be able to provide a complete map of the environment and assume that the map built during exploration is accurate enough for safe navigation, which is usually not the case. To address these limitations, a novel exploration method is proposed that combines frontier-based exploration with a collector strategy that achieves global exploration and complete map creation. In each iteration, the collector strategy stores and validates frontiers detected during exploration and selects the next best frontier to navigate to. The collector strategy ensures global exploration by balancing the exploitation of a known map with the exploration of unknown areas. In addition, the online path replanning ensures safe navigation through the map created during motion. The performance of the proposed method is verified by exploring 3D simulation environments in comparison with the state-of-the-art methods. Finally, the proposed approach is validated in a real-world experiment.

关键词： Three-dimensional displays Video on demand Navigation Warehousing Buildings Inspection Web sites

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Biomedically Informed ECG Synthesis: Customizing Cardiac Cycle Phases with Diffusion Model

Biomedically Informed ECG Synthesis: Customizing Cardiac Cyc...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yuxin Lin Jing Ma Wei Wang Zhihao Wu Suyu Dong Gongning Luo Kuanquan Wang School of Computer Science and Technology Harbin Institute of Technology Shenzhen China College of Computer and Control Engineering Northeast Forestry University Harbin China Faculty of Computing Harbin Institute of Technology Harbin China

ISBN: (数字)9798350386226

ISBN: (纸本)9798350386233

Cardiovascular diseases are a major global health challenge, with electrocardiography (ECG) being critical for diagnosis and monitoring. As artificial intelligence and automated ECG diagnostic technologies rapidly advance, the demand for large-scale ECG databases continues to grow. Generative ECG has become a mainstream method to enhance database size and diversity. However, existing methods typically generate ECG randomly or focus on limited physiological categories, lacking the ability to synthesize ECG with varying physiological features and cardiac cycles, which is crucial for various practical applications. In response to this need, we propose a novel approach introducing a diffusion model called DIFF-ECG to generate precisely customized ECG that accurately reflect diverse cardiac conditions. Segmentation-based quality assessments confirmed that the synthesized ECG accurately followed the specified cardiac cycle information, with our model significantly outperforming baseline diffusion and GAN-based methods. Therefore, our approach addresses the critical need for generating clinically relevant and customizable ECG, contributing significantly to the field of automated cardiac disease diagnosis. By enabling fine-tuning of cardiac cycle phases, our method significantly expands the application range of generative ECG, potentially improving the diagnostic accuracy for rare diseases and advancing personalized medicine.

关键词： Databases Biological system modeling Precision medicine Electrocardiography Diffusion models Data models Quality assessment Biomedical monitoring Monitoring Synthetic data

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Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic

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Computers, Materials & Continua 2023年第4期75卷 427-442页

作者： Reem Alkanhel El-Sayed M.El-kenawy D.L.Elsheweikh Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Doaa Sami Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Specific EducationMansoura UniversityEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh 11671Saudi Arabia

Traffic prediction of wireless networks attracted many researchersand practitioners during the past decades. However, wireless traffic frequentlyexhibits strong nonlinearities and complicated patterns, which makes it challengingto be predicted accurately. Many of the existing approaches forpredicting wireless network traffic are unable to produce accurate predictionsbecause they lack the ability to describe the dynamic spatial-temporalcorrelations of wireless network traffic data. In this paper, we proposed anovel meta-heuristic optimization approach based on fitness grey wolf anddipper throated optimization algorithms for boosting the prediction accuracyof traffic volume. The proposed algorithm is employed to optimize the hyperparametersof long short-term memory (LSTM) network as an efficient timeseries modeling approach which is widely used in sequence prediction *** prove the superiority of the proposed algorithm, four other optimizationalgorithms were employed to optimize LSTM, and the results were *** evaluation results confirmed the effectiveness of the proposed approachin predicting the traffic of wireless networks accurately. On the other hand,a statistical analysis is performed to emphasize the stability of the proposedapproach.

关键词： Network traffic soft computing LSTM metaheuristic optimization

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Fractional calculus in modelling hereditariness and nonlocality in transmission lines 11

Fractional calculus in modelling hereditariness and nonlocal...

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11th International Conference of the Balkan Physical Union, BPU 2022

作者： Zorica, Dušan Cvetićanin, Stevan M. Rapaić, Milan R. Department of Physics Faculty of Sciences University of Novi Sad Trg D. Obradovića 4 Novi Sad Serbia Mathematical Institute Serbian Academy of Arts and Sciences Kneza Mihaila 36 Beograd Serbia Department of Power Electronic and Telecommunication Engineering Faculty of Technical Sciences University of Novi Sad Trg D. Obradovića 6 Novi Sad Serbia Department of Computing and Control Engineering Faculty of Technical Sciences University of Novi Sad Trg D. Obradovića 6 Novi Sad Serbia

Transmission lines are traditionally modelled by considering Heaviside's elementary circuit that contains a resistor and inductor in the series branch, accounting for the energy losses and magnetic effects, while the shunt branch contains a resistor and a capacitor, accounting for the energy losses and capacitive phenomena. Classical telegrapher's equations, modelling the signal propagation in a transmission line, are obtained by assuming the infinitesimal length of the elementary circuit and by passing to a continuum. The generalization of elementary circuit is two-fold: topological by adding the capacitor in the series branch in order to account for the charge accumulation effects along the line and constitutive in order to account for the memory effects that transmission line may display. The constitutive generalization is performed by changing the constitutive relation describing the capacitive and inductive material properties using the fractional calculus approach accounting for the short-tail memory. On the other hand, the inclusion of nonlocal material properties of a transmission line is performed by considering the magnetic coupling of inductors in the series branch of Heaviside's elementary circuit, so that the magnetic flux is obtained as a superposition of local and constitutively given nonlocal magnetic flux through the cross-inductivity kernel. Signal propagation is studied in the case of power, exponential, and Gauss type cross-inductivity kernels. The presented results are published in [1-3]. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).

关键词： Electric lines

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Performance Comparison of Teleoperation Interfaces for Ultra-Lightweight Anthropomorphic Arms

Performance Comparison of Teleoperation Interfaces for Ultra...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Filip Zorić Alejandro Suarez Goran Vasiljević Matko Orsag Zdenko Kovačić Anibal Ollero Laboratory for Robotics and Intelligent Control Systems (LARICS) Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia GRVC Robotics Lab University of Seville Sevilla Spain

This paper presents a comparative performance evaluation of three different teleoperation interfaces for very low weight (<3 kg) anthropomorphic dual arms intended to conduct complex manipulation tasks involving a certain level of dexterity, accuracy and agility, either in ground service or in aerial manipulation applications. A visual human pose estimation system is developed to obtain the Cartesian and joint values of the user, which are mapped to the corresponding pose of the dual arm manipulator exploiting the equivalent human-robot kinematics. A leader-follower scheme is also presented, using a reduced scale dual arm that can replicate directly the joint positions of the leader arms to the follower arms. A 6-DOF (degrees of freedom) joystick is proposed to generate linear motions more accurately. A total of 60 ground tests were conducted involving 10 participants to determine the accuracy and time performance in two benchmarks (box edges and S contour tracking). Finally, the visual and leader-follower interfaces were evaluated with the dual arm aerial manipulator on flight tests, reporting several findings derived from the system evaluation.

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