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8th Conference on Information Communication technology and Society, ICTAS 2024

作者： Khoza, Nokuthula Owolawi, Pius Malele, Vusumuzi Soshanguve Campus Tshwane University of Technology Faculty of Information and Communication Technology Department of Computer Systems Engineering Pretoria South Africa North-West University Unit for Data Science and Computing School of Computer Science and Information Systems Vanderbijlpark Campus Vanderbijlpark South Africa

ISBN: (纸本)9798350314892

Tracking a person with an onboard camera is a very difficult and perhaps technically impossible if one camera is used. In this regard, real-life projects use a series of cameras to achieve the task. The advent of camera installed drone technology has made it possible for researchers and designers to resolve the tracking issues of a single or multiple stagnant devices. This paper presents a method that makes it possible for a drone to recognize hand gestures as control mechanism and follow the person who control it. Furthermore, the method assists in drone object detection using an integrated depth camera that provides video capturing. The OpenCV and Tello were used in this project. A stabilized depth video is for use with current person trackers like the OpenCV tracker. The estimated Tello pose deduced from vision to stabilize the depth image by warping it to a virtual-static camera. This method allows the Tello to obtain not only the tracked person's position and orientation but also their full body pose, which can then be used, for instance, to recognize hand gestures and alter the Tello's behavior. This work has a potential of contributing or enhancing cutting-edge applications such as hands-free photography and videography. © 2024 IEEE.

关键词： Drones

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Utilizing Genetic Programming to Enhance Polygenic Risk Score Calculation

Utilizing Genetic Programming to Enhance Polygenic Risk Scor...

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2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Hurta, Martin Schwarzerova, Jana Naegele, Thomas Weckwerth, Wolfram Provaznik, Valentine Sekanina, Lukas Brno University of Technology Faculty of Information Technology Department of Computer Systems Brno Czech Republic Brno University of Technology Faculty of Electrical Engineering and Communication Department of Biomedical Engineering Brno Czech Republic Vienna Austria Lmu Munich Plant Evolutionary Cell Biology Faculty of Biology Munich Germany Vienna Austria

ISBN: (纸本)9798350337488

The polygenic risk score has proven to be a valuable tool for assessing an individual's genetic predisposition to phenotype (disease) within biomedicine in recent years. However, traditional regression-based methods for polygenic risk scores calculation have limitations that can impede their accuracy and predictive power. This study introduces an innovative approach to enhance polygenic risk scores calculation through the application of genetic programming. By harnessing the power of genetic programming, we aim to overcome the limitations of traditional regression techniques and improve the accuracy of polygenic risk scores predictions. Specifically, we showed that a polygenic risk score generated through Cartesian genetic programming yielded comparable or even more robust statistical distinctions between groups that we evaluated within three independent case studies. © 2023 IEEE.

关键词： Computational biology Genetic Programming Genetic Variations Polygenic risk score

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Modeling of COVID-19 outbreak in Gaza Strip using SEIR model

Modeling of COVID-19 outbreak in Gaza Strip using SEIR model

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2023 International Conference on Computer Science, Information technology and engineering, ICCoSITE 2023

作者： Radwan, Akram M. Mortaja, Waleed Alzaq, Husam University College of Applied Sciences Information Technology Faculty Gaza Palestine University College of Applied Sciences Engineering & Smart Systems Faculty Gaza Palestine Istinye University Computer Engineering Department Istanbul Turkey

ISBN: (纸本)9798350320954

The novel coronavirus (COVID-19) pandemic is a major global health threat that was spreading very quickly around the world. Many mathematical models are being formulated to study the spread of COVID-19 and to predict its evolution, in order to help mitigating future outbreaks. The Susceptible-Exposed-Infectious-Recovered (SEIR) model is considered a prevalent model that describes various diseases outbreaks including COVID-19. The model divides the individuals into four groups;susceptible, exposed, infectious, recovered. To predict the evolution of the pandemic using the SEIR model, we first estimate the parameters as well as initial conditions. In this work, we model the spreading of COVID-19 pandemic using the SEIR in Gaza Strip to identify the better fitting model for forecasting future spread. The data required for estimation was collected between March 1st, 2021 and December 31st, 2021. The simulation results using SEIR model showed a significant model fitting, as there is no considerable difference from the real data compared to the respective model values. We also study the severity of the pandemic by identifying two important parameters;the basic reproduction rate (Ro), which determines the speed of the spread of COVID-19;and the infection fatality ratio (IFR) which estimates the proportion of deaths among all infected individuals. We obtained a value of Ro = 0. 89. IFR value is ranged between 0.079% and 0.085%, which is less than the global average of about 0.15%. © 2023 IEEE.

关键词： COVID-19

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Feed-Forward Probabilistic Error Cancellation with Noisy Recovery Gates 17

Feed-Forward Probabilistic Error Cancellation with Noisy Rec...

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17th IEEE International Symposium on Embedded Multicore/Many-core systems-on-Chip, MCSoC 2024

作者： Kurosawa, Leo Saito, Yoshiyuki Lee, Xinwei Yan, Xinjian Xie, Ningyi Cai, Dongsheng Shin, Jungpil Asai, Nobuyoshi University of Aizu School of Computer Science and Engineering Aizu-Wakamatsu Fukushima Japan Singapore Management University School of Computing and Information Systems Singapore University of Tsukuba School of Science and Technology Tsukuba Japan University of Tsukuba Faculty of Engineering Information and Systems Tsukuba Japan

ISBN: (纸本)9798331530471

Probabilistic Error Cancellation (PEC) aims to improve the accuracy of expectation values for observables. This is accomplished using the probabilistic insertion of recovery gates, which correspond to the inverse of errors. However, the inserted recovery gates also induce errors. Thus, it is difficult to obtain accurate expectation values with PEC since the estimator of PEC has a bias due to noise induced by recovery gates. To address this challenge, we propose an improved version of PEC that considers the noise resulting from gate insertion, called Feed-Forward PEC (FFPEC). FFPEC provides an unbiased estimator of expectation values by cancelling out the noise induced by recovery gates. We demonstrate that FFPEC yields more accurate expectation values compared to the conventional PEC method through analytical evaluations. Numerical experiments are used to evaluate analytical results. © 2024 IEEE.

关键词： Inverse problems

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The Balance Model for V2X System with Variable Infrastructure

The Balance Model for V2X System with Variable Infrastructur...

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2025 systems of Signals Generating and Processing in the Field of on Board Communications, SOSG 2025

作者： Plotnikov, Pavel V. Tambovtsev, Gleb I. Vladyko, Andrei G. The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Faculty of Information Technology and Software Engineering Saint Petersburg Russia The Bonch-Bruevich Saint-Petersburg State University of Telecommunications Faculty of Radioelectronic Systems and Robotics Saint Petersburg Russia

ISBN: (纸本)9798331532635

This paper addresses the optimization problem and seeks a balance equation between key performance-influencing parameters in a Vehicle-to-Everything (V2X) network. A novel mathematical optimization model is proposed, focusing on the interaction between On-Board Units (OBUs) and both stationary and mobile Roadside Units (RSUs/mRSUs). The optimization problem is expressed through a multi-objective function considering critical parameters such as data transmission latency, energy consumption, and resource availability. The study demonstrates how RSU density and mobility impact key network performance indicators, including system stability and data loss percentage during peak hours. This work provides a structured analytical approach to optimizing Intelligent Transportation System (ITS) infrastructure, ensuring more reliable and efficient communication between vehicles. © 2025 IEEE.

关键词： Motor transportation

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Empirical Research on 3D Analysis and Flow Prediction of Upstream Rivers Using Drones 13

Empirical Research on 3D Analysis and Flow Prediction of Ups...

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Joint 13th International Conference on Soft Computing and Intelligent systems and 25th International Symposium on Advanced Intelligent systems, SCIS and ISIS 2024

作者： Hoshino, Yukinobu Rathnayake, Namal Dang, Tuan Linh Rathnayake, Upaka School of Systems Engineering Kochi University of Technology Kochi Kami City Japan University of Tokyo River and Environmental Engineering Laboratory 7-3-1 Hongo Bunkyoku Tokyo Japan School of Information and Communications Technology Hanoi University of Science and Technology Hanoi Viet Nam Atlantic University of Technology Faculty of Engineering and Design Sligo Ireland

ISBN: (纸本)9798350373332

This study aims to develop an AI prediction system for watersheds, utilizing data from Sri Lanka and Vietnam in collaboration with overseas researchers. Initially, a foundational AI prediction system will be constructed, and basic data will be gathered based on river data from Japan. Subsequently, topographic data of the watershed area, managed by the joint research partner institution, will be incorporated into the AI prediction system through drone-based aerial measurement and analysis. Moreover, visits to the joint research institution will be conducted to gather information on water damage and electricity supply. This information will then be integrated into the AI prediction system. Utilizing the collected data and additional observation data, efforts will be made to enhance the accuracy of the AI prediction algorithm, identify potential issues, and overcome them. The ultimate goal is to establish new AI pre-diction technology by comparing the results of this study with both domestic and international research outcomes. This paper will present data from a drone scan of the upstream watershed and discuss the future use of AI based on the results of three-dimensional analysis and image processing. © 2024 IEEE.

关键词： Flood damage

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An Evaluation of Integrating ERP System to Develop a Strategy Business 8

An Evaluation of Integrating ERP System to Develop a Strateg...

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8th International Conference on Information Management and technology, ICIMTech 2023

作者： Wijaya, Santo Fernandi Wiratama, Jansen Kuswanto, Verri School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Universitas Multimedia Nusantara Faculty of Engineering and Informatics Information Systems Department Tangerang11480 Indonesia Buddhi Dharma University Faculty of Science and Technology Information Systems Department Tangerang11480 Indonesia

ISBN: (纸本)9798350326093

The digital changes business patterns that require companies by using an integrated system for strategic decision-making. ERP system is one technological innovation that enable to have a competitive advantage. But the fact is that only a few companies have succeeded in implementing the ERP system. The objective of this research is to integrate the ERP system with business strategy in implementing ERP systems. The research focuses on developing an ERP system integration model for implementing the SAP ERP success. The methodology is based on previous research for the ERP implementation. This research examines quantitative data to determine indicators using entropy and conducts case studies in the industry. The research results prove that the management support indicator is an essential factor in integrating ERP systems to develop the company's strategic business. The output research is the design of the integration model development of the ERP system. © 2023 IEEE.

关键词： Decision making

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RDM: A Light Field Super-Resolution Model Improved with Retinex Decomposition 16

RDM: A Light Field Super-Resolution Model Improved with Reti...

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16th International Conference on Signal Processing systems, ICSPS 2024

作者： Lyu, Wenqi Ke, Wei Sheng, Hao Ma, Xiao Liu, Lixue Faculty of Applied Sciences Macao Polytechnic University China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

ISBN: (纸本)9781510689251

Light field cameras hold significant value in applications such as depth estimation, 3D video acquisition, and image super-resolution. Compared to traditional single-image super-resolution methods, light field images can capture object information from multiple spatial and angular perspectives, which is more conducive to capturing detail information. However, current advanced light field super-resolution models still exhibit issues like blurriness, jaggedness, and dimness in 4x light field super-resolution. To address this, we propose a novel light field super-resolution framework that utilizes the Retinex decomposition concept to solve common problems such as ghosting and overlap, thereby improving image quality. By decomposing the light field image into illumination and reflection components and processing them separately, our model significantly enhances detail preservation and color consistency. Experimental results on multiple datasets demonstrate that our model exhibits outstanding performance, both subjectively and objectively, highlighting the effectiveness of this framework and its broad application potential in the field of computational imaging. © 2025 SPIE.

关键词： Image acquisition

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Automatic speaker identification system based on MLP network and deep learning in the presence of severe interference

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Multimedia Tools and Applications 2025年 1-42页

作者： Shafik, Amira Sedik, Ahmed El-Shafai, Walid Khalaf, Ashraf A. M. El-Rabaie, El-Sayed M. El-Samie, Fathi E. Abd Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electrical Engineering Faculty of Engineering Minia University Minia61519 Egypt Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafr Elsheikh University Kafr El‑Shaikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Automatic Speaker Identification (ASI) is so crucial for security. Current ASI systems perform well in quiet and clean surroundings. However, in noisy situations, the robustness of an ASI system against additive noise and interference is a crucial factor. An investigation of the impact of interference on ASI system performance is presented in this paper, which introduces algorithms for achieving high ASI system performance. The objective is to resist the interference of various forms. This paper presents two models for the ASI task in the presence of interference. The first one depends on Normalized Pitch Frequency (NPF) and Mel-Frequency Cepstral Coefficients (MFCCs) as extracted features and Multi-Layer Perceptron (MLP) as a classifier. In this model, we investigate the utilization of a Discrete Transform (DT), such as Discrete Wavelet Transform (DWT), Discrete Cosine Transform (DCT) and Discrete Sine Transform (DST), to increase the robustness of extracted features against different types of degradation through exploiting the sub-band decomposition characteristics of DWT and the energy compaction property of DCT and DST. This is achieved by extracting features directly from contaminated speech signals in addition to features extracted from discrete transformed signals to create hybrid feature vectors. The enhancement techniques, such as Spectral Subtraction (SS), Winer Filter, and adaptive Wiener filter, are used in a preprocessing stage to eliminate the effect of the interference on the ASI system. In the second model, we investigate the utilization of Deep Learning (DL) based on a Convolutional Neural Network (CNN) with speech signal spectrograms and their Radon transforms to increase the robustness of the ASI system against interference effects. One of this paper goals is to introduce a comparison between the two models and build a more robust ASI system against severe interference. The experimental results indicate that the two proposed models lead to satisfa

关键词： Additive noise

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A Quantum Q-Learning Model for the Capacitated Vehicle Routing Problem 17

A Quantum Q-Learning Model for the Capacitated Vehicle Routi...

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17th IEEE International Symposium on Embedded Multicore/Many-core systems-on-Chip, MCSoC 2024

作者： Xu, Jiahua Xie, Ningyi Lee, Xinwei Saito, Yoshiyuki Asai, Nobuyoshi Cai, Dongsheng University of Tsukuba Graduate School of Science and Technology Japan Singapore Management University School of Computing and Information Systems Singapore University of Aizu Graduate School of Computer Science and Engineering Japan University of Aizu School of Computer Science and Engineering Japan University of Tsukuba Faculty of Engineering Information and Systems Japan

ISBN: (纸本)9798331530471

The research on Variational Quantum Algorithms (VQAs) has gained significant momentum because of their promising practicality in the noisy intermediate-scale quantum (NISQ) era. Recent studies highlight the potential of VQAs in reinforcement learning (RL) by replacing classical components with parameterized quantum circuits (PQCs). Building on this, we propose a quantum Q-learning model for the Capacitated Vehicle Routing Problem (CVRP), combining a PQC with an RL training process. We present a PQC for embedding both static and dynamic states in RL environments. The proposed PQC approximates the Q-value function by using the expectation values of different observables. Experimental results demonstrate that the proposed PQC outperforms the existing PQC for the CVRP with fewer quantum resources. Furthermore, our method shows competitive performance compared to the classical counterpart. © 2024 IEEE.

关键词： Vehicle routing

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