• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.31-40
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• 2008

This paper presented the development and real-time control of a magnetostrictive micro actuator. Magnetostrictive material has many advantages such as high response time, precision displacement and powerful output force. But Magnetostrictive material has characteristic of hysteresis. Conventional Preisach model which based on experimental data is not suitable to the real-time control because of controlling a magnetostrictive system by Preisach model costs a lot of calculating time. And, we prove the validity of proposed model through the experimental comparison between the classical Preisach model and the proposed one.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.4
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• pp.201-212
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• 2002

This paper proposes a reconfigurable scheduler model that can support various real-time scheduling algorithms. The proposed model consists of two hierarchical upper and lower components, task scheduler and scheduling framework, respectively. The scheduling framework provides a job dispatcher and software timers. The task scheduler implements an appropriate scheduling algorithm, which supports a specific real-time application, based on the scheduling framework. If system developers observe internal kernel interfaces to communicate between two hierarchical components, they can implement a new scheduling algorithm independent of complex low kernel mechanism. Once a task scheduler is developed, it can be reused in a new real-time system in future. In Real-Time Linux (5), we implemented the proposed scheduling framework and several representative real-time scheduling algorithms. Throughout these implementations, we confirmed that a new scheduling algorithm could be developed independently without updates of complex low kernel modules. In order to confirm efficiency of the proposed model, we measured the performance of representative task schedulers. The results showed that the scheduling overhead of proposed model, which has two separated components, is similar to that of a classic monolithic kernel scheduler.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.9
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• pp.105-111
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• 1999

The paper presents development of a Hardware-In-the-Loop simulation (HILS) system for the purpose of testing performance, stability, and reliability of an electronic power steering system(EPS). In order to realistically test an EPS by the proposed HILS apparatus, a simulated uniaxial dynamic rack force is applied physically to the EPS hardware by a pnumatic actuator. An EPS hardware is composed of steering wheel &column, a rack & pinion mechanism, andas motor-driven power steering system. A command signal for a pneumatic rack-force actuator is generated from the vehicle handling lumped parameter dynamic model 9software) that is simulated in real time by using a very fast digital signal processor. The inputs to the real-time vehicle dynamic simulation model are a constant vehicle forward speed and from wheel steering angles driven through a steering system by a driver. The output from a real-time simulation model is an electric signal that is proportional to the uniaxial rack force. The vehicle handling lumped parameter dynamic model is validated by a fully nonlinear constrained multibody vehicle dynamic model. The HILS system simulation results sow that the proposed HILS system may be used to realistically test the performance stability , and reliability of an electronic power steering system is a repeated way.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.44-55
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• 2024

High-utility itemset mining (HUIM) is a dominant technology that enables enterprises to make real-time decisions, including supply chain management, customer segmentation, and business analytics. However, classical support value-driven Apriori solutions are confined and unable to meet real-time enterprise demands, especially for large amounts of input data. This study introduces a groundbreaking model for top-N high utility itemset mining in real-time enterprise applications. Unlike traditional Apriori-based solutions, the proposed convolutional sequential embedding metrics-driven cosine-similarity-based multilayer perception learning model leverages global and contextual features, including semantic attributes, for enhanced top-N recommendations over sequential transactions. The MATLAB-based simulations of the model on diverse datasets, demonstrated an impressive precision (0.5632), mean absolute error (MAE) (0.7610), hit rate (HR)@K (0.5720), and normalized discounted cumulative gain (NDCG)@K (0.4268). The average MAE across different datasets and latent dimensions was 0.608. Additionally, the model achieved remarkable cumulative accuracy and precision of 97.94% and 97.04% in performance, respectively, surpassing existing state-of-the-art models. This affirms the robustness and effectiveness of the proposed model in real-time enterprise scenarios.

• Journal of Power Electronics
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• v.11 no.2
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• pp.202-210
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• 2011

Polymer electrolyte membrane (PEM) fuel cell is one of the popular renewable energy sources and widely used in commercial medium power areas from portable electronic devices to electric vehicles. In addition, the increased integration of the PEM fuel cell with power electronics, dynamic loads, and control systems requires accurate electrical models and simulation methods to emulate their electrical behaviors. Advancement in parallel computation techniques, various real-time simulation tools, and smart power hardware have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper builds up advancements of optimized model constructions for a fuel cell stack system on a real-time simulator in the view points of improving dynamic model accuracy and boosting computation speed. In addition, several considerations for a power hardware-in-the-loop (PHIL) simulation are provided to electrically emulate the PEM fuel cell stack system with power facilities. The effectiveness of the proposed PHIL simulation method developed on Opal RT's RT-Lab Matlab/Simulink based real-time engineering simulator and a programmable power supply is verified using experimental results of the proposed PHIL simulation system with a Ballard Nexa fuel cell stack.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.25 no.6
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• pp.310-316
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• 2013

This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.110-116
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• 2021

This paper proposed a real-time earlobe detection system using deep learning on the web. Existing deep learning-based detection methods often find independent objects such as cars, mugs, cats, and people. We proposed a way to receive an image through the camera of the user device in a web environment and detect the earlobe on the server. First, we took a picture of the user's face with the user's device camera on the web so that the user's ears were visible. After that, we sent the photographed user's face to the server to find the earlobe. Based on the detected results, we printed an earring model on the user's earlobe on the web. We trained an existing YOLO v5 model using a dataset of about 200 that created a bounding box on the earlobe. We estimated the position of the earlobe through a trained deep learning model. Through this process, we proposed a real-time earlobe detection system on the web. The proposed method showed the performance of detecting earlobes in real-time and loading 3D models from the web in real-time.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.22-29
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• 2022

In this paper, for the purpose of designing an real-time unmanned monitoring system, the YOLOv5s (small) object detection model was applied on the NVIDIA TX2^TM AI (Artificial Intelligence) edge computing platform in order to design the fundamental function of an unmanned monitoring system that can detect objects in real time. YOLOv5s was applied to the our real-time unmanned monitoring system based on the performance evaluation of object detection algorithms (for example, R-CNN, SSD, RetinaNet, and YOLOv5). In addition, the performance of the four YOLOv5 models (small, medium, large, and xlarge) was compared and evaluated. Furthermore, based on these results, the YOLOv5s model suitable for the design purpose of this paper was ported to the NVIDIA TX2^TM AI edge computing system and it was confirmed that it operates normally. The real-time unmanned monitoring system designed as a result of the research can be applied to various application fields such as an security or monitoring system. Future research is to apply NMS (Non-Maximum Suppression) modification, model reconstruction, and parallel processing programming techniques using CUDA (Compute Unified Device Architecture) for the improvement of object detection speed and performance.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.172-181
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• 2023

In this study, real-time damage evaluation of cable-stayed bridges was conducted for cable damage. ICP type acceleration sensors were used for real-time damage assessment of cable-stayed bridges, and Kinetic Energy Optimization Techniques (KEOT) were used to select the optimal conditions for the location and quantity of the sensors. When a structure vibrates by an external force, KEOT measures the value of the maximum deformation energy to determine the optimal measurement position and the quantity of sensors. The damage conditions in this study were limited to cable breakage, and cable damage was caused by dividing the cable-stayed bridge into four sections. Through FE structural analysis, a virtual model similar to the actual model was created in the real-time damage evaluation method of cable. After applying random oscillation waves to the generated virtual model and model structure, cable damage to the model structure was caused. The two data were compared by defining the response output from the virtual model as a corruption-free response and the response measured from the real model as a corruption-free data. The degree of damage was evaluated by applying the data of the damaged cable-stayed bridge to the Improved Mahalanobis Distance (IMD) theory from the data of the intact cable-stayed bridge. As a result of evaluating damage with IMD theory, it was identified as a useful damage evaluation technology that can properly find damage by section in real time and apply it to real-time monitoring.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.115-124
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• 2016

In this paper, a method to generate the extended model automatically on the critical elements in enterprise system based real time distributed architecture as well as the platform specific model(PSM) for Microsoft(MS) .NET platform is proposed. The key ideas of this method are real time distributed architecture should performed with satisfying strict constraints on life cycle of object and response time such as synchronization, transaction and so on, and .NET platform is able to implement functionalities including before mentioned by only specifying Attribute Code and maximizing advantages of MDA. In order to realize the ideas, functionalities which should be considered enterprise system development are specified and these are to be defined in Meta Model and extended UML profile. In addition, after definition of UML profile for .NET specification, by developing and applying these into plug-in of open source MDA tool, and extended models are generated automatically through this tool. Accordingly, by using proposed specification technology, the profile and tools easily and quickly reusable extended model can be generated even though low level of detailed information for functionalities which is considered in .NET platform and real time distributed architecture. In addition, because proposed profile is MOF which is basis of standard extended and applied, UML and MDA tools which observed MOF is reusable.