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8th International Congress on information and Communication technology, ICICT 2023

作者： Stupavský, Igor Dakić, Pavle Faculty of Informatics and Information Technologies Institute of Informatics Information Systems and Software Engineering Slovak University of Technology in Bratislava Bratislava Slovakia Faculty of Informatics and Computing Singidunum University Belgrade Serbia

ISBN: (纸本)9789819932351

The aim of this review is to explore the relationship between the architecture of microservices and antisocial behavior. Microservice architecture is a software design approach that involves decomposing a system into small, independent services that can offer benefits such as flexibility and scalability. Expected result is to analyze dataset of statuses, which defines the length of time the status displays on the user’s device. Because people spend time on social networks at every opportunity, even for hours. When combined with the time-valued, we try to gain a deeper understanding of social networks and users behavior. They are forced into this behavior through the feedback loop mechanism of the neurotransmitter Dopamine. Main goal is to understand how to minimize the impact of antisocial behavior on social networks and what exactly makes users spend a disproportionate amount of time on these platforms. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： software design

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Harris Hawks Optimizer with Graph Convolutional Network Based Weed Detection in Precision Agriculture

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Computer Systems Science & engineering 2023年第8期46卷 1533-1547页

作者： Saud Yonbawi Sultan Alahmari T.Satyanarayana Murthy Padmakar Maddala E.Laxmi Lydia Seifedine Kadry Jungeun Kim Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddahSaudi Arabia King Abdul Aziz City for Science and Technology RiyadhKingdom of Saudi Arabia Chaitanya Bharathi Institute of Technology HyderabadTelanganaIndia Department of Civil Engineering Vignan’s Institute of Information and Technology(A)DuvvadaVisakhapatnamAP530049India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Applied Data Science Noroff University CollegeKristiansandNorway Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon Department of Software Kongju National UniversityCheonan31080Korea

Precision agriculture includes the optimum and adequate use of resources depending on several variables that govern crop *** agriculture offers a novel solution utilizing a systematic technique for current agricultural problems like balancing production and environmental *** control has become one of the significant problems in the agricultural *** traditional weed control,the entire field is treated uniformly by spraying the soil,a single herbicide dose,weed,and crops in the same *** more precise farming,robots could accomplish targeted weed treatment if they could specifically find the location of the dispensable plant and identify the weed *** may lessen by large margin utilization of agrochemicals on agricultural fields and favour sustainable *** study presents a Harris Hawks Optimizer with Graph Convolutional Network based Weed Detection(HHOGCN-WD)technique for Precision *** HHOGCN-WD technique mainly focuses on identifying and classifying weeds for precision *** image pre-processing,the HHOGCN-WD model utilizes a bilateral normal filter(BNF)for noise *** addition,coupled convolutional neural network(CCNet)model is utilized to derive a set of feature *** detect and classify weed,the GCN model is utilized with the HHO algorithm as a hyperparameter optimizer to improve the detection *** experimental results of the HHOGCN-WD technique are investigated under the benchmark *** results indicate the promising performance of the presented HHOGCN-WD model over other recent approaches,with increased accuracy of 99.13%.

关键词： Weed detection precision agriculture graph convolutional network harris hawks optimizer hyperparameter tuning

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Sparse Learning for Linear Twin Parameter-margin Support Vector Machine 24

Sparse Learning for Linear Twin Parameter-margin Support Vec...

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3rd Asia Conference on Algorithms, Computing and Machine Learning, CACML 2024

作者： Qu, Shuanghong De Leone, Renato Huang, Min College of Mathematics and Information Science College of Software Engineering Zhengzhou University of Light Industry Zhengzhou China School of Science and Technology University of Camerino Camerino Italy College of Software Engineering Zhengzhou University of Light Industry Zhengzhou China

ISBN: (纸本)9798400716416

Twin Parameter-margin support vector machine (TPMSVM) is a recent very powerful binary classifier. To improve its sparsity, a linear sparse TPMSVM (Lin-STPMSVM) is proposed in this paper. In the primal problem, the vectors defining the hyperplane are replaced with their expression in terms of the dual variables as derived from Karush Khun Tucker (KKT) conditions. Then the new primal problems are directly optimized, thus ensuring the sparsity of the solutions. Numerical experiments show that the solution obtained by new model is more sparse without reducing the accuracy. Therefore, Lin-STPMSVM not only inherits the advantages of TPMSVM, but also has the characteristics of sparsity, stability and robustness in dealing with classification problems. © 2024 ACM.

关键词： Vectors

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MQTT based monitoring and control system for remote stations in automotive industry

MQTT based monitoring and control system for remote stations...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Ivanovic, Denis Job, Josip Puntaric, Marko Herceg, Marijan TTTech-Auto CX Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Software Engineering Osijek Croatia Faculty of Electrical Engineering Computer Science and Information Technology Department of Communications Osijek Croatia

ISBN: (纸本)9798350347722

In this paper is presented implementation of a lightweight supervisory control and data acquisition system for remote test stations as a part of a larger test house in the automotive industry. It is necessary to allow remote set up and monitoring of the test stations, which means defining the structure of a system with numerous test stations as endpoints. The test stations are meant to be virtual machines but can be both virtual and physical machines. A communication protocol must be used that enables this within the organization's network, regardless of actual distance and location. The parameters of the test stations to be monitored can be defined according to the needs and purpose. Even when creating your own tool, this function is not unique, i.e. on one test station parameters of operating system resources such as memory usage can be monitored, while on another test station logged-in users or running programs, reported system errors and others must be monitored. Data storage is one of the mandatory functions of this system. This process allows viewing data throughout history and more detailed analysis of events. There are numerous benefits that can be drawn and used from the data stored in the database. It is necessary to pay attention to the data stored as well as the scope and retention throughout history. The correct and secure setup of a database is one of the prerequisites for any serious system that processes data. Appropriate views should be created for users involved in the data monitoring process using all the elements mentioned so far. Creating a visually acceptable and easy-To-use interface that serves the main purpose is the final presentation of the entire system to users. A complete system leads to higher productivity, profitability and better organization of the company. It also allows project managers to better plan the use and occupancy of test stations. At any time, they have insight into the status of individual test stations, their activitie

关键词： Automotive industry

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Improved Stereo Matching Algorithm Based on Sparse Window 28

Improved Stereo Matching Algorithm Based on Sparse Window

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28th International Conference on Automation and Computing, ICAC 2023

作者： Tang, Qi Xu, Yuanping Zhou, Jiliu Kong, Chao Jin, Jin Xu, Zhijie Zhang, Chaolong Shi, Yajing School of Software Engineering Chengdu University of Information Technology Chengdu China School of Computing & Engineering University of Hudderseld Hudderseld United Kingdom

ISBN: (纸本)9798350335859

This study presents a sparse window-based stereo-matching algorithm that enhances the accuracy and efficiency of the semi-global matching algorithm. Unlike traditional methods, this algorithm processes pixel areas based on their texture features, resulting in more efficient encoding. The proposed approach systematically samples pixels within the original encoding window to reduce the number of pixels involved in the process. Additionally, using the FAST feature detection method distinguishes texture areas and applies different encoding processes for each area to obtain the feature encoding of the center pixels. Experimental results show that compared with traditional semi-global stereo matching algorithms, our proposed sparse window-based algorithm improves processing speed by 0.06 seconds and reduces average error by 10.92%. © 2023 IEEE.

关键词： Pixels

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Improving Thyroid Disorder Diagnosis via Ensemble Stacking and Bidirectional Feature Selection

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Computers, Materials & Continua 2024年第3期78卷 4225-4241页

作者： Muhammad Armghan Latif Zohaib Mushtaq Saad Arif Sara Rehman Muhammad Farrukh Qureshi Nagwan Abdel Samee Maali Alabdulhafith Yeong Hyeon Gu Mohammed A.Al-masni Department of Computer and Information System Cleveland State UniversityOhio44115USA Department of Electrical Electronics and Computer SystemsCollege of Engineering and TechnologyUniversity of SargodhaSargodha40100Pakistan Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl-Ahsa31982Saudi Arabia Department of Biomedical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Electrical Engineering Riphah International UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Artificial Intelligence College of Software and Convergence TechnologySejong UniversitySeoul05006Korea

Thyroid disorders represent a significant global health challenge with hypothyroidism and hyperthyroidism as two common conditions arising from dysfunction in the thyroid *** and timely diagnosis of these disorders is crucial for effective treatment and patient *** research introduces a comprehensive approach to improve the accuracy of thyroid disorder diagnosis through the integration of ensemble stacking and advanced feature selection *** forward feature selection,sequential backward feature elimination,and bidirectional feature elimination are investigated in this *** ensemble learning,random forest,adaptive boosting,and bagging classifiers are *** effectiveness of these techniques is evaluated using two different datasets obtained from the University of California Irvine-Machine Learning Repository,both of which undergo preprocessing steps,including outlier removal,addressing missing data,data cleansing,and feature *** experimentation demonstrates the remarkable success of proposed ensemble stacking and bidirectional feature elimination achieving 100%and 99.86%accuracy in identifying hyperthyroidism and hypothyroidism,*** enhancing detection accuracy,the ensemble stacking model also demonstrated a streamlined computational complexity which is pivotal for practical medical *** significantly outperformed existing studies with similar objectives underscoring the viability and effectiveness of the proposed *** research offers an innovative perspective and sets the platform for improved thyroid disorder diagnosis with broader implications for healthcare and patient well-being.

关键词： Ensemble learning random forests boosting dimensionality reduction machine learning smart healthcare computer aided diagnosis

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Determination of the critical rainfall of runoff-initiated debris flows by the perspective of physical mechanics and Shields stress

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Journal of Mountain Science 2024年第4期21卷 1160-1173页

作者： MA Chao ZHU Yongtai LU Lu DU Cui LYU Liqun DONG Jie School of Soil and Water Conservation Beijing Forestry UniversityBeijing 100083China Beijing Institute of Geological Hazard Prevention Beijing 100120China School of Software Engineering Chengdu University of Information TechnologyChengdu610225China Civil and Environmental Engineering Department Clarkson UniversityNY 13699USA

The critical rainfall of runoff-initiated debris flows is utmost importance for local early hazard *** paper presents research on the critical rainfall of runoff-initiated debris flows through comparisons between slope gradients and three key factors,including topographic contributing area,dimensionless discharge,and Shields *** rainfall amount was estimated by utilizing in-situ rainfall records and a slope-dependent Shields stress model was *** created model can predict critical Shields stress more accurately than the other two ***,a new dimensionless discharge equation was proposed based on the corresponding discharge-gradient *** new equation,along with factors such as contributing area above bed failure sites,channel width,and mean diameter of debris flow deposits,predicts a smaller rainfall amount than the in-situ measured *** the slope-dependent Shields stress model performs well and the estimated rainfall amount is lower than the in-situ records,the sediment initiation in the experiments falls within sheet flow regime due to a large Shields ***,further sediment initiation experiments at a steeper slope range are expected in the future to ensure that the sediment transport belongs to mass failure regime characterized by a low level of Shields ***,a more accurate hazard forecast on the runoff-initiated debris flow holds promise when the corresponding critical slope-dependent dimensionless discharge of no motion,fluvial sediment transport,mass flow regime,and sheet flow regime are considered.

关键词： Infinite slope stability Shields stress Contributing area-slope gradient Rainfall back estimation

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Local and Global Feature Interaction Network for Endoscope Image Classification 1

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12th International Conference on Image and Graphics, ICIG 2023

作者： Dong, Zhengqi Xu, Benzhu Shi, Jun Zheng, Liping School of Computer Science and Information Engineering Hefei University of Technology Hefei China School of Software Hefei University of Technology Hefei China

ISBN: (数字)9783031463143

ISBN: (纸本)9783031463136

Convolutional Neural Network (CNN) shows great performance in the field of endoscopic image classification in past few years. It can capture local features of endoscopic images, but it fails to exploit global semantic information. Recently transformer is proposed and successfully applied in computer vision, which can model global long-range dependencies based on the self-attention mechanism. Considering the advantages of CNN and transformer, we propose a novel local and global feature interaction network for endoscope image classification. Different from the existed methods fusing CNN and transformer features, our method achieves these two kinds of features interaction during feature learning and further enhances the feature discrimination ability of CNN and transformer features. Specifically, our backbone consists of multiple CNN-FIB-Transformer (CFT) modules which includes CNN block, feature interaction block (FIB) and transformer encoder. Features extracted from CNN block and transformer encoder are fed into our proposed FIB in parallel, which can interact local and global features of endoscopic images through cross-attention mechanism and further improve their own feature representation capability. Furthermore, we also introduce the loss function of prediction alignment to guarantee the prediction consistency of CNN and transformer features, in addition of conventional cross-entropy loss functions for their own features. Experiments on two public endoscope image datasets (Kvasir2 and HyperKvasir) have demonstrated the feasibility and effectiveness of the proposed method for endoscope image classification. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Forecasting

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Scheduling Tool for Deterministic Communication in Distributed Real-Time Systems 10

Scheduling Tool for Deterministic Communication in Distribut...

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10th Workshop on software Quality Analysis, Monitoring, Improvement, and Applications, SQAMIA 2023

作者： Mach, Jan Tašková, Valéria Kohútka, Lukáš Institute of Computer Engineering and Applied Informatics Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

A network with critical data streams, where the timing of incoming and outgoing data is a necessity, is called a deterministic network. These networks are mostly used in association with real-time systems that use periodic hard-real-time data which need to be scheduled. The algorithm proposed in this paper is focused on achieving the lowest possible latency within the specified network topology depending on the physical parameters of the network and the periodic requirements of the communicating nodes. The algorithm allows to add priorities to the data flow between nodes and also the option to specify if preemption is allowed within the network, since not all devices support it. The result is a schedule of hard-real-time data communication within a specified network topology where all requirements of communicating nodes are met if such a solution is possible. © 2023 Copyright for this paper by its authors.

关键词： deadline deterministic scheduling Ethernet scheduling algorithm time-sensitive networking

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Mobile Fighter Plane Game Manipulation: Touch-based Method vs. Camera-Based Method 9

Mobile Fighter Plane Game Manipulation: Touch-based Method v...

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9th International Conference on Systems and Informatics, ICSAI 2023

作者： Chen, Liang Chengdu University of Information Technology School of Software Engineering Chengdu China Sichuan Prov. Eng. Technology Research Center of Support Software of Informatization Application Chengdu China

ISBN: (纸本)9798350383706

Direct touch input has already been ubiquitously used on various mobile devices. However, direct touch manipulation sometimes degrades mobile game experience due to its limitations, such as the occlusion problem and the virtual button-based manipulation. In this paper, we investigate camera-based mobile game manipulation which takes advantage of camera input to enable button-free interactions without hand occlusion. The results of a preliminary user study indicate that, on the whole, the participants believe that the camera-based manipulation is intuitive, easy-to-learn, and easy-to-use. In addition, overall, they also give positive feedbacks on the bullet-firing control, button-free and occlusion-free manipulation, and believe that the camera-based manipulation is better than the touch-based manipulation. © 2023 IEEE.

关键词： Cameras

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