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The Relation Between a Tensor and Its Associated Semi-Symmetric Form

Numerical Mathematics(Theory,Methods and Applications) 2022年第2期15卷 530-564页

作者： Hassan Bozorgmanesh Masoud Hajarian Anthony Theodore Chronopoulos Department of Applied Mathematics Faculty of Mathematical SciencesShahid Beheshti UniversityTehranIran Department of Computer Science University of TexasSan AntonioTexas 78249USA (Visiting Faculty)Department of Computer Engineering&Informatics University of PatrasRio 26500Greece

It is known that every tensor has an associated semi-symmetric *** purpose of this paper is to investigate the shared properties of a tensor and its semi-symmetric *** particular,a corresponding semi-symmetric tensor has smaller Frobenius norm under some conditions and can be used to get smaller bounds for eigenvalues and solutions of dynamical systems and tensor complementarity *** addition,every tensor has the same eigenvalues as its corresponding semi-symmetric form,also a corresponding semi-symmetric tensor inherits properties like being circulant,Toeplitz,Z-tensor,M-tensor,H-tensor and some ***,there are a two-way connection for properties like being positive definite,P-tensor,semi-positive,primitive and several others.

关键词： Tensor eigenvalue semi-symmetric tensor eigenvalue bound logarithmic norm tensor complementarity problem

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Application of ensemble models approach in anemia detection using images of the palpable palm

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Medicine in Novel Technology and Devices 2023年第4期20卷 76-86页

作者： Peter Appiahene Samuel Segun Dzifa Dogbe Emmanuel Edem Yaw Kobina Philip Sackey Dartey Stephen Afrifa Emmanuel Timmy Donkoh Justice Williams Asare Department of Computer Science and Informatics University of Energy and Natural ResourcesGhana Department of Information and Communication Engineering Tianjin UniversityChina c Department of Basic and Applied Biology University of Energy and Natural ResourcesGhana

Anemia is a public health issue with serious ramifications for human health *** particularly affects pregnant women and children from 6 to 59 months old even though every individual is at *** occurs when the Hb level is below its normal threshold or when the red blood cells are weakened or *** discover medical remedies on time,early detection or diagnosis of anemia assist patients to understand their *** invasive approach for anemia detection is costive and time-consuming as compared to the non-invasive approach which is reliable and suitable for developing communities where medical resources and personnel are *** study uses palpable palm images(dataset)collected from 710 participants in selected hospitals in *** images were extracted,segmented and converted into RGB percentile to train,validate and tested the machine learning models.A hybrid model was developed with the application of ensemble learning models using the R programming language on the R Studio ***,voting,boosting and bagging ensemble model techniques were used to build the hybrid models,the stacking ensemble model achieved an accuracy of 99.73%.The study justifies that ensemble models are efficient for medical disease diagnosis or detection such as anemia.

关键词： Machine learning Anemia detection Ensemble learning Algorithms

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Developing an Artificial Intelligence Tool for Image Generation Using a Unique Dataset with Image-to-Image Functionality 24

Developing an Artificial Intelligence Tool for Image Generat...

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25th International Conference on computer Systems and Technologies, CompSysTech 2024

作者： Toktosunova, Akbiike Ergeshov, Alymbek Esenalieva, Gulzada Ermakov, Andrei Isaev, Ruslan Department of Applied Mathematics and Informatics Ala-Too International University Kyrgyzstan Department of Compute Science Ala-Too International University Kyrgyzstan Faculty of Engineering and Computer Science Ala-Too International University Kyrgyzstan

ISBN: (纸本)9798400716843

This article describes the application of a unique artificial intelligence model, trained on the basis of a special dataset, for drawing images. Artificial intelligence is very important in the modern world because it is a key driver of progress, offering innovative solutions to improve processes in various fields. A feature of this work is the use of the Stable Diffusion model and the creation of the LoRa model to create a specific object. The use of a special dataset, which is a classified set of images, to train models based on a stable propagation mechanism. The application of the image-to-image method, which consists in completely generating an image by having the model reproduce all the objects in the image, trying to preserve the maximum amount of detail in the image. As a result, a tool has been developed that can generate images of characters of a certain style. © 2024 ACM.

关键词： Adversarial machine learning

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Synergistic Swarm Optimization Algorithm

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computer Modeling in engineering & Sciences 2024年第6期139卷 2557-2604页

作者： Sharaf Alzoubi Laith Abualigah Mohamed Sharaf Mohammad Sh.Daoud Nima Khodadadi Heming Jia Faculty of Computer Sciences and Informatics Amman Arab UniversityAmman11953Jordan Computer Science Department Al Al-Bayt UniversityMafraq25113Jordan Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan MEU Research Unit Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains MalaysiaPulau Pinang11800Malaysia School of Engineering and Technology Sunway University MalaysiaPetaling Jaya27500Malaysia Department of Industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia College of Engineering Al Ain UniversityAbu Dhabi112612United Arab Emirates Department of Civil and Architectural Engineering University of MiamiCoral Gables1251USA School of Information Engineering Sanming UniversitySanming365004China

This research paper presents a novel optimization method called the Synergistic Swarm Optimization Algorithm(SSOA).The SSOA combines the principles of swarmintelligence and synergistic cooperation to search for optimal solutions efficiently.A synergistic cooperation mechanism is employed,where particles exchange information and learn from each other to improve their search *** cooperation enhances the exploitation of promising regions in the search space while maintaining exploration ***,adaptive mechanisms,such as dynamic parameter adjustment and diversification strategies,are incorporated to balance exploration and *** leveraging the collaborative nature of swarm intelligence and integrating synergistic cooperation,the SSOAmethod aims to achieve superior convergence speed and solution quality performance compared to other optimization *** effectiveness of the proposed SSOA is investigated in solving the 23 benchmark functions and various engineering design *** experimental results highlight the effectiveness and potential of the SSOA method in addressing challenging optimization problems,making it a promising tool for a wide range of applications in engineering and *** codes of SSOA are available at:https://***/matlabcentral/fileexchange/153466-synergistic-swarm-optimization-algorithm.

关键词： Synergistic swarm optimization algorithm optimization algorithm metaheuristic engineering problems benchmark functions

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Efficient Time-Delay System Optimization with Auto-Configured Metaheuristics

Efficient Time-Delay System Optimization with Auto-Configure...

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2023 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2023

作者： Senkerik, Roman Byrski, Aleksander Guzowski, Hubert Janku, Peter Kadavy, Tomas Oplatkova, Zuzana Kominkova Matusu, Radek Pluhacek, Michal Pekar, Libor Smolka, MacIej Viktorin, Adam Tomas Bata University A.I. Lab Faculty of Applied Informatics Department of Informatics and Artificial Intelligence Zlin Czech Republic Tomas Bata University Faculty of Applied Informatics Department of Automation and Control Engineering Zlin Czech Republic Institute of Computer Science Agh University of Science and Technology Krakow Poland

ISBN: (纸本)9798350337020

This paper presents an experimental study that compares the performance of four selected metaheuristic algorithms for optimizing a time delay system model. Time delay system models are complex and challenging to optimize due to their inherent characteristics, such as non-linearity, multi-modality, and constraints. The study includes an explanation of the choice and core functionality of the selected algorithms, which are both baseline and state-of-the-art variants of self-organizing migrating algorithm (SOMA), state-of-the-art variant from the Success-History-based Adaptive Differential Evolution family of algorithms, with emphasis on diverse search (DISH algorithm), and Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. The hyperparameters of the metaheuristic algorithms were set using the iRace automatic algorithm configuration framework. The paper emphasizes the importance of metaheuristic algorithms in control engineering for time-delay systems to develop more effective and efficient control strategies and precise model identifications. The experimental results highlight the effectiveness of the state-of-the-art algorithms with specific adaptive mechanisms like population organization process, diverse search and adaptation mechanisms ensuring a gradual transition from exploration to exploitation. Overall, this study contributes to understanding the challenges and advantages of using metaheuristic algorithms in control engineering for time delay systems. The results provide valuable insights into the performance of modern metaheuristic algorithms and can help guide the selection of appropriate adaptive mechanisms of metaheuristics. © 2023 IEEE.

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K-Banhatti Invariants Empowered Topological Investigation of Bridge Networks

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computers, Materials & Continua 2022年第12期73卷 5423-5440页

作者： Khalid Hamid Muhammad Waseem Iqbal Erssa Arif Yasir Mahmood Ahmad Salman Khan Nazri Kama Azri Azmi Atif Ikram Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Software Engineering Faculty of Information TechnologyThe University of Lahore54000Pakistan Advanced Informatics Department Razak Faculty of Technology and InformaticsUniversiti Teknologi MalaysiaKuala Lumpur54100Malaysia Faculty of Informatics and Applied Mathematics University Malaysia TerengganuMalaysia Department of Computer Science&Information Technology Faculty of Information TechnologyThe University of Lahore54000Pakistan

Any number that can be uniquely determined by a graph is called graph *** the most recent twenty years’innumerable numerical graph invariants have been described and used for correlation *** the fast and advanced environment of manufacturing of networks and other products which used different networks,no dependable assessment has been embraced to choose,how much these invariants are connected with a network graph or molecular *** this paper,it will talk about three distinct variations of bridge networks with great capability of expectation in the field of computer science,chemistry,physics,drug industry,informatics,and mathematics in setting with physical and synthetic constructions and networks,since K-Banhatti invariants are newly introduced and have various forecast characteristics for various variations of bridge graphs or *** review settled the topology of bridge graph/networks of three unique sorts with three types of K-Banhatti *** concluded outcomes can be utilized for the modeling of interconnection networks of Personal computers(PC),networks like Local area network(LAN),Metropolitan area network(MAN)and Wide area network(WAN),the spine of internet and different networks/designs of PCs,power generation interconnection,bio-informatics and chemical structures.

关键词： Bridge networks invariants k-banhatti indices maple network graph molecular graph

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Emotion Recognition Techniques 1

引用

1st international conference on Machine Intelligence and computer Science Applications, ICMICSA 2022

作者： Knouzi, Maryam Ennaji, Fatima Zohra Hafidi, Imad Laboratory of Process Engineering Computer Science and Mathematics Department of Mathematics and Informatics National School of Applied Sciences University Sultan Moulay Slimane Beni-Mellal Morocco

ISBN: (数字)9783031293139

ISBN: (纸本)9783031288456

This article evaluates techniques for obtaining facial images from convolutional neural networks to identify emotion expressions. The primary goal of the paper is to discuss the most often used approaches to analyzing and recognizing emotional expressions on the face. The works that were reviewed might be divided into two major trends: the traditional techniques and those that were especially developed using neural *** analysis revealed that using CNNs improved level of performance. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Emotion Recognition

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Seafloor Imaging Maps by Incorporating Side Scan Sonar Technology on Hybrid Autonomous Underwater Glider 6

Seafloor Imaging Maps by Incorporating Side Scan Sonar Techn...

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6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023

作者： Atmaja, Ardian Budi Kusuma Hidayat, Egi Muhammad Idris Riyanto Trilaksono, Bambang Siregar, Simon Habibullah, Natsir School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Telkom University Doctoral Program of Electrical Engineering Department Computer Engineering Faculty of Applied Science Indonesia

ISBN: (纸本)9798350358346

This research aims to construct a two-dimensional image to represent an underwater geometry map with a Side Scan Sonar (SSS) mounted on a Hybrid Autonomous Underwater Glider (HAUG). Building the underwater map has two stages of the process. The first stage is preprocessing which includes Time-varying gains (TVG), slant range correction, and ground range correction. The second is HAUG navigation, the movement of HAUG orientation to the angle and distance of SSS readings and plotting the geometry of the grid map. With these two stages, a two-dimensional grid map will be formed. Meanwhile, the 3D plot utilizes slant range and ground range correction to obtain the surface height of the bottom of the pool. From the experiments conducted to conduct mapping in the pool, two-dimensional and three-dimensional visual forms of the pool floor and pool walls were produced. The results of the estimated measurement of the width of the pool obtained 14.05 meters and the height of the pool 3.199 meters with an SSS beam angle of 58 degrees. © 2023 IEEE.

关键词： Geometry

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CNN Architectures for Vehicle Detection in V2X Environments: A Comparative Study

CNN Architectures for Vehicle Detection in V2X Environments:...

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IEEE Conference on Standards for Communications and Networking (CSCN)

作者： Vasileios Efthymiou Stylianos Basagiannis Sophia Petridou Department of Applied Informatics University of Macedonia Greece Department of Computer Informatics & Telecommunications Engineering International Hellenic University Greece

ISBN: (数字)9798331507428

ISBN: (纸本)9798331507435

Leveraging convolutional neural networks (CNNs) to Vehicle-to-Everything (V2X) communication systems offers a promising approach to vehicle detection, which is essential for improving road safety and traffic efficiency. At the same time, parameterization of CNNs’ architectures in order to achieve high accuracy in moving objects’ detection becomes an engineering challenge, especially when data pre- and post-processing solutions need to respect timing requirements. Our study evaluates the performance of five CNN architectures, namely YOLO in v5, v8, and v9, Faster R-CNN, and VGG16, for car detection. We utilize an open dataset including images derived from road-traffic environments and assess the models’ performance using benchmark evaluation metrics, i.e., precision, recall, mean Average Precision (mAP50, mAP50 – 95), and F1-score. Furthermore, we analyze their computational requirements, in terms of execution time and resource demands, which are critical factors when considering real-time applications in V2X systems, such as autonomous driving and traffic management. Our evaluation results indicate that, while the YOLO architecture exhibits the best balance of speed and accuracy, Faster R-CNN has higher detection performance at the cost of greater computational demand. This paper provides insights into each model’s strengths and limitations offering guidance for selecting optimal architectures tailored to V2X-related applications.

关键词： YOLO Accuracy Vehicle detection Computational modeling computer architecture Road safety Timing Convolutional neural networks Vehicle-to-everything Standards

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The Calibration of Single Beam Distance Sensors based on Machine Learning Methods

The Calibration of Single Beam Distance Sensors based on Mac...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Biernacki, Piotr Ziebinski, Adam Syu, Jia-Hao Lin, Jerry Chun-Wei Silesian University of Technology Institute of Theoretical and Applied Informatics Polish Academy of Sciences Institute of Informatics Gliwice Poland Silesian University of Technology Institute of Informatics Gliwice Poland National Taiwan University Department of Computer Science and Information Engineering Taipei Taiwan

ISBN: (纸本)9798350324457

Smart cities require the use of many different types of sensors to make the communication, and distance sensors are one of the most commonly used elements in transportation systems and related infrastructures. The introduction of increasingly advanced autonomous systems in many areas of smart cities requires high measurement precision of the sensors used. High precision is essential for proper operation, long-term use, and safety in machine-to-machine or machine-to-human interactions. This paper presents a comparison of the accuracy of distance measurements for two commercially available single-beam LiDARs and two ultrasonic sensors. The aim of the research was to develop a calibration method in order to improve the accuracy of distance sensors. Based on the collected distance measurements, the sensors were calibrated using selected machine learning algorithms. The results of the experiments show the effectiveness of the proposed calibration methods, which yield an average mean absolute error (MAE) of 1.76 E-05 meters (m) and a root mean square error (RMSE) of 1.33 E-04 m for the tested sensors. © 2023 IEEE.

关键词： machine learning sensors calibration single-beam distance sensors

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