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Defect Detection Model Using Time Series Data Augmentation and Transformation

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computers, Materials & Continua 2024年第2期78卷 1713-1730页

作者： Gyu-Il Kim Hyun Yoo Han-Jin Cho Kyungyong Chung department of computer Science Kyonggi UniversitySuwon-si16227Korea Contents convergence Software Research Institue Kyonggi UniversitySuwon-si16227Korea department of Energy IT engineering Far East UniversityEumsung-gun27601Korea Division of ai computer Science and engineering Kyonggi UniversitySuwon-si16227Korea

Time-series data provide important information in many fields,and their processing and analysis have been the focus of much ***,detecting anomalies is very difficult due to data imbalance,temporal dependence,and ***,methodologies for data augmentation and conversion of time series data into images for analysis have been *** paper proposes a fault detection model that uses time series data augmentation and transformation to address the problems of data imbalance,temporal dependence,and robustness to *** method of data augmentation is set as the addition of *** involves adding Gaussian noise,with the noise level set to 0.002,to maximize the generalization performance of the *** addition,we use the Markov Transition Field(MTF)method to effectively visualize the dynamic transitions of the data while converting the time series data into *** enables the identification of patterns in time series data and assists in capturing the sequential dependencies of the *** anomaly detection,the PatchCore model is applied to show excellent performance,and the detected anomaly areas are represented as heat *** allows for the detection of anomalies,and by applying an anomaly map to the original image,it is possible to capture the areas where anomalies *** performance evaluation shows that both F1-score and Accuracy are high when time series data is converted to ***,when processed as images rather than as time series data,there was a significant reduction in both the size of the data and the training *** proposed method can provide an important springboard for research in the field of anomaly detection using time series ***,it helps solve problems such as analyzing complex patterns in data lightweight.

关键词： Defect detection time series deep learning data augmentation data transformation

Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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computer Modeling in engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen Viet Tiep Quynh-Anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania department of Civil engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India department of Civil engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Intelligent Real-Time IoT Traffic Steering in 5G Edge Networks

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computers, Materials & Continua 2021年第6期67卷 3433-3450页

作者： Sa Math Prohim Tam Seokhoon Kim department of Software convergence Soonchunhyang UniversityAsan31538Korea department of computer Software engineering Soonchunhyang UniversityAsan31538Korea

In the Next Generation Radio Networks(NGRN),there will be extreme massive connectivity with the Heterogeneous Internet of Things(HetIoT)*** millimeter-Wave(mmWave)communications will become a potential core technology to increase the capacity of Radio Networks(RN)and enable Multiple-Input and Multiple-Output(MIMO)of Radio Remote Head(RRH)***,the challenging key issues in unfair radio resource handling remain unsolved when massive requests are occurring *** imbalance of resource utilization is one of the main issues occurs when there is overloaded connectivity to the closest RRH receiving exceeding *** handle this issue effectively,Machine Learning(ML)algorithm plays an important role to tackle the requests of massive IoT devices to RRH with its obvious capacity *** paper proposed a dynamic RRH gateways steering based on a lightweight supervised learning algorithm,namely K-Nearest Neighbor(KNN),to improve the communication Quality of Service(QoS)in real-time IoT *** supervises the model to classify and recommend the user’s requests to optimal RRHs which preserves higher *** experimental dataset was generated by using computer software and the simulation results illustrated a remarkable outperformance of the proposed scheme over the conventional methods in terms of multiple significant QoS parameters,including communication reliability,latency,and throughput.

关键词： Machine learning Internet of Things traffic steering mobile edge computing

Improved Hybrid Precoding Technique with Low-Resolution for MIMO-OFDM System

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computers, Materials & Continua 2021年第8期68卷 2205-2220页

作者： Seulgi Lee Ji-Sung Jung Young-Hwan You Hyoung-Kyu Song department of Information and Communication engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea department of computer engineering Sejong UniversitySeoul05006Korea

This paper proposes an improved hybrid beamforming system based on multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM)*** proposed beamforming system improves energy efficiency compared to the conventional hybrid beamforming *** sub-connected and full-connected structure are considered to apply the proposed *** the conventional hybrid beamforming,the usage of radio frequency(RF)chains and phase shifter(PS)gives high power and hardware *** this paper,the phase over sampling(POS)with switches(SW)is used in hybrid beamforming system to improve the energy *** POS-SW structure samples the value of analog beamformer to make lower resolution than conventional *** number of output data in POS is decided by the resolution of POS *** limited number of POS decides the resolution of antenna array and the values of POSs are designed from maximum and minimum phase angle antenna *** efficiency without the phase shifter is high although channel capacity is nearly similar with conventional ***,the amplifier with POS-SW system is proposed to improve the BER *** to the data bits,the output signals of POS are *** system with 2,3 and 4 bits is simulated to prove the proposed *** order to overcome the loss of low-resolution system,the amplifier with POS-SW system using channel information is *** average sum-rate of 4 bits system shows the similar performance with the conventional hybrid beamforming *** structure can play an important role by increasing the energy efficiency of the wireless communication system that many antennas are *** is shown that the BER,average sum rate and energy efficiency of the proposed scheme are more improved than the conventional hybrid beamforming system.

关键词： Hybrid beamforming MIMO-OFDM system analog precoding POS-SW

LoRa Backscatter Network Efficient Data Transmission Using RF Source Range Control

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computers, Materials & Continua 2023年第2期74卷 4015-4025页

作者： Dae-Young Kim SoYeon Lee Seokhoon Kim department of computer Software engineering Soonchunhyang UniversityAsan31538Korea department of Software convergence Soonchunhyang UniversityAsan31538Korea

Networks based on backscatter communication provide wireless data transmission in the absence of a power source.A backscatter device receives a radio frequency(RF)source and creates a backscattered signal that delivers data;this enables new services in battery-less domains with massive Internet-of-Things(IoT)*** is highly energy-efficient in the context of massive IoT ***,long-range(LoRa)backscattering facilitates large IoT services.A backscatter network guarantees timeslot-and contention-based ***-based transmission ensures data transmission,but is not scalable to different numbers of transmission *** contention-based transmission is used,collisions are *** reduce collisions and increase transmission efficiency,the number of devices transmitting data must be *** control device activation,the RF source range can be modulated by adjusting the RF source power during LoRa *** reduces the number of transmitting devices,and thus collisions and retransmission,thereby improving transmission *** performed extensive simulations to evaluate the performance of our method.

关键词： Backscatter communication LoRa backscatter RF source range control activated device control internet of things

Intelligent Resource Allocations for Software-Defined Mission-Critical IoT Services

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computers, Materials & Continua 2022年第11期73卷 4087-4102页

作者： Chaebeen Nam Sa Math Prohim Tam Seokhoon Kim department of Software convergence Soonchunhyang UniversityAsan31538Korea department of computer Software engineering Soonchunhyang UniversityAsan31538Korea

Heterogeneous Internet of Things(IoT)applications generate a diversity of novelty applications and services in next-generation networks(NGN),which is essential to guarantee end-to-end(E2E)communication resources for both control plane(CP)and data plane(DP).Likewise,the heterogeneous 5th generation(5G)communication applications,including Mobile Broadband Communications(MBBC),massive Machine-Type Commutation(mMTC),and ultra-reliable low latency communications(URLLC),obligate to perform intelligent Quality-of-Service(QoS)Class Identifier(QCI),while the CP entities will be suffered from the complicated massive HIOT ***,the existing management and orchestration(MANO)models are inappropriate for resource utilization and allocation in large-scale and complicated network *** cope with the issues mentioned above,this paper presents an adopted software-defined mobile edge computing(SDMEC)with a lightweight machine learning(ML)algorithm,namely support vector machine(SVM),to enable intelligent MANO for real-time and resource-constraints IoT applications which require lightweight computation ***,the SVM algorithm plays an essential role in performing QCI ***,the software-defined networking(SDN)controller allocates and configures priority resources according to the SVM classification ***,the complementary of SVM and SDMEC conducts intelligent resource MANO for massive QCI environments and meets the perspectives of mission-critical communication with resource constraint *** on the E2E experimentation metrics,the proposed scheme shows remarkable outperformance in key performance indicator(KPI)QoS,including communication reliability,latency,and communication throughput over the various powerful reference methods.

关键词： Mobile edge computing Internet of Things software defined networks traffic classification machine learning resource allocation

Real-time Volume Preserving Constraints for Volumetric Model on GPU

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computers, Materials & Continua 2022年第10期73卷 831-848页

作者： Hongly Va Min-Hyung Choi Min Hong department of Software convergence Soonchunhyang UniversityAsan31538Korea department of computer Science and engineering University of Colorado DenverDenver80217COUSA department of computer Software engineering Soonchunhyang UniversityAsan31538Korea

This paper presents a parallel method for simulating real-time 3D deformable objects using the volume preservation mass-spring system method on tetrahedron *** general,the conventional mass-spring system is manipulated as a force-driven method because it is fast,simple to implement,and the parameters can be ***,the springs in traditional mass-spring system can be excessively elongated which cause severe stability and robustness issues that lead to shape restoring,simulation blow-up,and huge volume loss of the deformable *** addition,traditional method that uses a serial process of the central processing unit(CPU)to solve the system in every frame cannot handle the complex structure of deformable object in ***,the first order implicit constraint enforcement for a mass-spring model is utilized to achieve accurate visual realism of deformable objects with tough constraint *** this paper,we applied the distance constraint and volume conservation constraints for each tetrahedron element to improve the stability of deformable object simulation using the mass-spring system and behave the same as its real-world *** reduce the computational complexity while ensuring stable simulation,we applied a method that utilizes OpenGL compute shader,a part of OpenGL Shading Language(GLSL)that executes on the graphic processing unit(GPU)to solve the numerical problems *** applied the proposed methods to experimental volumetric models,and volume percentages of all objects are *** average volume percentages of all models during the simulation using the mass-spring system,distance constraint,and the volume constraint method were 68.21%,89.64%,and 98.70%,*** proposed approaches are successfully applied to improve the stability of mass-spring system and the performance comparison from our experimental tests also shows that the GPU-based method is faster than CPU-based implementation for all cases.

关键词： Deformable object simulation mass-spring system implicit constraint enforcement volume conservation constraint GPU parallel computing

Adaptive Emulation Framework for Multi-Architecture IoT Firmware Testing

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computers, Materials & Continua 2023年第5期75卷 3291-3315页

作者： Jihyeon Yu Juhwan Kim Youngwoo Lee Fayozbek Rustamov Joobeom Yun department of computer and Information Security and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea department of computer and Information Security Sejong UniversitySeoul05006Korea

Internet of things(IoT)devices are being increasingly used in numerous ***,the low priority on security and various IoT types have made these devices vulnerable to *** prevent this,recent studies have analyzed firmware in an emulation environment that does not require actual devices and is efficient for repeated ***,these studies focused only on major firmware architectures and rarely considered exotic *** addition,because of the diversity of firmware,the emulation success rate is not high in terms of large-scale *** this study,we propose the adaptive emulation framework for multi-architecture(AEMA).In the field of automated emulation frameworks for IoT firmware testing,AEMA considers the following issues:(1)limited compatibility for exotic firmware architectures,(2)emulation instability when configuring an automated environment,and(3)shallow testing range resulting from structured *** tackle these problems,AEMAcan emulate not onlymajor firmware architectures but also exotic firmware architectures not previously considered,such as Xtensa,ColdFire,and reduced instruction set computer(RISC)version five,by implementing a minority ***,we applied the emulation arbitration technique and input keyword extraction technique for emulation stability and efficient test case *** compared AEMA with other existing frameworks in terms of emulation success rates and fuzz *** a result,AEMA succeeded in emulating 864 out of 1,083 overall experimental firmware and detected vulnerabilities at least twice as fast as the experimental ***,AEMAfound a 0-day vulnerability in realworld IoT devices within 24 h.

关键词： Internet of things(IoT) emulation framework firmware fuzzing concolic execution vulnerability

Parallel Cloth Simulation Using OpenGL Shading Language

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computer Systems Science & engineering 2022年第5期41卷 427-443页

作者： Hongly Va Min-Hyung Choi Min Hong department of Software convergence Soonchunhyang UniversityAsan31538Korea department of computer Science and engineering University of Colorado DenverDenverCO 80217USA department of computer Software engineering Soonchunhyang UniversityAsan31538Korea

The primary goal of cloth simulation is to express object behavior in a realistic manner and achieve real-time performance by following the fundamental concept of *** general,the mass–spring system is applied to real-time cloth simulation with three types of ***,hard spring cloth simulation using the mass–spring system requires a small integration time-step in order to use a large stiffness ***,to obtain stable behavior,constraint enforcement is used instead of maintenance of the force of each *** force computation involves a large sparse linear solving *** to the large computation,we implement a cloth simulation using adaptive constraint activation and deactivation techniques that involve the mass-spring system and constraint enforcement method to prevent excessive elongation of *** the same time,when the length of the spring is stretched or compressed over a defined threshold,adaptive constraint activation and deactivation method deactivates the spring and generate the implicit *** method that uses a serial process of the Central Processing Unit(CPU)to solve the system in every frame cannot handle the complex structure of cloth model in *** simulation utilizes the Graphic Processing Unit(GPU)parallel processing with compute shader in OpenGL Shading Language(GLSL)to solve the system *** this paper,we design and implement parallel method for cloth simulation,and experiment on the performance and behavior comparison of the mass-spring system,constraint enforcement,and adaptive constraint activation and deactivation techniques the using GPU-based parallel method.

关键词： Adaptive constraint cloth simulation constraint enforcement GLSL compute shader mass–spring system parallel GPU