• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.3
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• pp.278-284
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• 2016

Software reliability in the software development process is an important issue. In infinite failure NHPP software reliability models, the fault occurrence rates may have constant, monotonic increasing or monotonic decreasing pattern. In this paper, infinite failures NHPP models that the situation was reflected for the fault occurs in the repair time, were presented about comparing property. Commonly, the software model of the infinite failures using the linear hazard rate distribution software reliability based on intercept parameter was used in business economics and actuarial modeling, was presented for comparison problem. The result is that a relatively large intercept parameter was appeared effectively form. The parameters estimation using maximum likelihood estimation was conducted and model selection was performed using the mean square error and the coefficient of determination. The linear hazard rate distribution model is also efficient in terms of reliability because it (the coefficient of determination is 90% or more) in the field of the conventional model can be used as an alternative model could be confirmed. From this paper, the software developers have to consider intercept parameter of life distribution by prior knowledge of the software to identify failure modes which can be able to help.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5164-5171
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• 2011

In fuzzy modeling for nonlinear process, typically using the given data, the fuzzy rules are formed by the input variables and the space division by selecting the input variable and dividing the input space for each input variables. The premise part of the fuzzy rule is identified by selection of the input variables, the number of space division and membership functions and the consequent part of the fuzzy rule is identified by polynomial functions in the form of simplified and linear inference. In general, formation of fuzzy rules for nonlinear processes using the given data have the problem that the number of fuzzy rules exponentially increases. To solve this problem complex nonlinear process can be modeled by separately forming the fuzzy rules by means of fuzzy division of each input space. Therefore, this paper utilizes individual input space to generate fuzzy rules. The premise parameters of the fuzzy rules are identified by Min-Max method using the minimum and maximum values of input data set and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. And lastly, using the data which is widely used in nonlinear process we evaluate the performance and the system characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.639-647
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• 2019

Recently, as the semiconductor integration technology due to miniaturization and high density of electronic equipment have developed, it is importantly recognized the application of thermal control system in order to release inner heat generated from chips, modules, In this study, we considered the heat transfer and pressure drop characteristics in a horizontal channel with four blocks using k-${\omega}$ SST turbulence model During CFD (Computational Fluid Dynamics) analysis, the parameters applied block width, block height, heat source and turbulence generator placement etc. As the boundary conditions of analysis, the channel inlet temperature and flow velocity were respectively 300 K and 3.84 m/s, the heat flux was $358W/m^2$. As a result, the heat transfer performance was decreased as the block width ratio (w/h) was increased, while it was increased as the block height ratio (h/w) was increased. In addition, as the arrangement of heat source size was increased to high heat flux from low heat flux, it was influenced by heat source size and the heat transfer coefficient showed a tendency to increase, When the turbulence generator was installed in the upper part of block No. 1 position the closely to the channel entrance, the heat transfer characteristics was greatly influenced on the whole of four heating blocks. and in oder to consider the pressure drop characteristics, we are able to select the most appropriate turbulence generator's position.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.135-141
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• 2019

Internet of thing becomes more active, many sensor devices are increasing. Sensors can use network wired network or use mobile communication network. From the viewpoint of the transmission rate, the mobile communication network can be roughly divided into two types of high-speed communication and low-speed communication. In the case of hundreds of millions of sensors in the mobile communication network, resources are wasted to use high-speed communication. Communication is required to reduce the transmission rate and appropriately allocate resources without wasting such resources. As the Internet of Thing has been activated, Narrowband Internet of Thing(NB-IoT), which is one of the low-power technologies in recent mobile communications, is in the spotlight from various companies. Currently, it can be seen that only NB-IoT or other low power consumption communication has the potential to be able to connect to the Internet with rapidly increasing sensor devices. In this paper, we designed and implemented a heater controller using Huawei NB-IoT communication Module, a server that collects controller information, and an application that allows default settings for devices. The main function of this system is to collect temperature and heater status and give it to the server, control the heater from the server, and set parameters for the heater to operate automatically. The system can be applied to places where wired communication is not established, such as road information, smart agriculture, and small reservoirs as well as heaters.

• Journal of Korean Medicine Rehabilitation
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• v.32 no.3
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• pp.131-140
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• 2022

Objectives This study aimed to investigate whether the concurrent use of conventional and herbal medications affects liver and kidney function, by examining blood test data. Methods We retrospectively reviewed the electronic medical records of 590 inpatients with musculoskeletal diseases between 2013 and 2017. We investigated cases of drug-induced liver injury (DILI) according to the Roussel Uclaf Causality Assessment Method criteria and cases of drug-induced kidney injury (DIKI) based on the Kidney Disease Improving Global Outcomes definition. Results One case (0.17%) of DILI and one case (0.17%) of DIKI were identified. Significant improvements in serum laboratory data were observed after the concurrent use of both types of medications (p<0.05). The kappa coefficients ranged from 0.26 to 0.72, indicating that the values after the concurrent use of conventional and herbal medications showed a fair similarity to the baseline values of the patients. The linear regression test showed that female sex and high body mass index (BMI) were risk factors for an increase in the serum blood levels of liver function parameters. Conclusions The concurrent use of conventional and herbal medications for musculoskeletal disorders is relatively safe; however, clinicians should exercise caution when prescribing these medications to female patients and patients with a high BMI because of their potential effect on hepatic function.

• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.174-174
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• 2000

A strong antiferromagnetic coupling in Fe/Si multilayered films (MLF) had been recently discovered and much consideration has been given to whether the coupling in the Fe/Si MLF system has the same origin as the metal/metal MLF. Nevertheless, the nature of the interfacial ron silicide is still controversial. On one hand, a metal/ semiconductor structure was suggested with a narrow band-gap semiconducting $\varepsilon$-FeSi spacer that mediates the coupling. However, some features show that the nature of coupling can be well understood in terms of the conventional metal/metal multilayered system. It is well known that both magneto-optical (MO) and optical properties of a metal depend strongly on their electronic structure that is also correlated with the atomic and chemical ordering. In this study, the nature of the interfacial regions is the Fe/Si multilayers has been investigated by the experimental and computer-simulated MO and optical spectroscopies. The Fe/Si MLF were prepared by rf-sputtering onto glass substrates at room temperature with the number of repetition N=50. The thickness of Fe sublayer was fixed at 3.0nm while the Si sublayer thickness was varied from 1.0 to 2.0 nm. The topmost layer of all the Fe/Si MLF is Fe. In order to carry out the computer simulations, the information on the MO and optical parameters of the materials that may constitute a real multilayered structure should be known in advance. For this purpose, we also prepared Fe, Si, FeSi2 and FeSi samples. The structural characterization of Fe/Si MLF was performed by low- and high -angle x-ray diffraction with a Cu-K$\alpha$ radiation and by transmission electron microscopy. A bulk $\varepsilon$-FeSi was also investigated. The MO and optical properties were measured at room temperature in the 1.0-4.7 eV energy range. The theoretical simulations of MO and optical properties for the Fe/Si MLF were performed by solving exactly a multireflection problem using the scattering matrix approach assuming various stoichiometries of a nonmagnetic spacer separating the antiferromagnetically coupled Fe layers. The simulated spectra of a model structure of FeSi2 or $\varepsilon$-FeSi as the spacer turned out to fail in explaining the experimental spectra of the Fe/Si MLF in both intensity and shape. Thus, the decisive disagreement between experimental and simulated MO and optical properties ruled out the hypothesis of FeSi2 and $\varepsilon$-FeSi as the nonmagnetic spacer. By supposing the spontaneous formation of a metallic ζ-FeSi, a reasonable agreement between experimental and simulated MO and optical spectra was obtained.

• Resources Recycling
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• v.31 no.6
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• pp.81-91
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• 2022

The use of lithium-ion batteries increases significantly with the rapid spread of electronic devices and electric vehicle and thereby an increase in the amount of waste batteries is expected in the near future. Therefore, studies are continuously being conducted to recover various resources of cathode active material (Ni, Co, Mn, Li) from waste battery. In order to recover the cathode active material, black mass is generally recovered from waste battery. The general process of recovering black mass is a waste battery collection - discharge - dismantling - crushing - classification process. This study focus on the crushing/classification process among the processes. Specifically, the particle size distribution of various samples at each crushing/classification step were evaluated, and the particle shape of each particle fraction was analyzed with a microscope and SEM (Scanning Electron Microscopy)-EDS(Energy Dispersive Spectrometer). As a result, among the black mass particle, fine particle less than 74 ㎛ was the mixture of cathode and anode active material which are properly liberated from the current metals. However, coarse particle larger than 100 ㎛ was present in a form in which the current metal and active material were combined. In addition, this study developed a PBM(Population Balance Model) system that can simulate two-species mixture sample with two different crushing properties. Using developed model, the breakage parameters of two species was derived and predictive performance of breakage distribution was verified.

• Journal of Adhesion and Interface
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• v.25 no.1
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• pp.157-161
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• 2024

Amphiphilic gold nanoparticles, synthesized by the simultaneous binding of hydrophilic and hydrophobic ligands on their surfaces, find diverse applications in energy, bio, optical, electronic technologies, and various other fields. Particularly, these amphiphilic gold nanoparticles possess both hydrophilic and hydrophobic characteristics, enabling them to activate interface at the interface of immiscible fluids and form organized structures. The surface properties of gold nanoparticles play a crucial role in influencing the behaviors of amphiphilic gold nanoparticles at the interface of two fluids. Therefore, this study investigated the adsorption behaviors of gold nanoparticles at the organic solvent-water interface based on the surface characteristics of amphiphilic gold nanoparticles and the type of organic solvents. It was observed that the amount of adsorbed gold nanoparticles at the interface increased with the length of hydrocarbon chains in hydrophobic ligands and increased with shorter hydrocarbon chains in the organic solvent. Furthermore, using the Langmuir isotherm model, the study confirmed the formation of a monolayer by amphiphilic gold nanoparticles and obtained significant thermodynamic parameters simultaneously.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.121-129
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• 2024

The rapid advancement of digital technology and the COVID-19 pandemic have significantly accelerated the growth of online commerce, highlighting the need for support mechanisms that enable small business owners to effectively respond to these market changes. In response, this paper presents a foundational technology leveraging the Online to Offline (O2O) strategy to automatically capture products displayed on retail shelves and utilize these images to create virtual stores. The essence of this research lies in precisely identifying and recognizing the location and names of displayed products, for which a single-class-targeted, lightweight model based on YOLOv8, named ESD-YOLOv8, is proposed. The detected products are identified by their names through feature-point-based technology, equipped with the capability to swiftly update the system by simply adding photos of new products. Through experiments, product name recognition demonstrated an accuracy of 74.0%, and position detection achieved a performance with an F2-Score of 92.8% using only 0.3M parameters. These results confirm that the proposed method possesses high performance and optimized efficiency.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.4
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• pp.205-212
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• 2024

This study developed a deep learning model that distinguishes the front (with garnish) and the back (without garnish) surface of the dried semi-finished product (dried bukak) for screening operation before transfter the dried bukak to oil heater using robot's vacuum gripper. For deep learning model training and verification, RGB images for the front and back surfaces of 400 dry bukak that treated by data preproccessing were obtained. YOLO-v5 was used as a base structure of deep learning model. The area, surface information labeling, and data augmentation techniques were applied from the acquired image. Parameters including mAP, mIoU, accumulation, recall, decision, and F1-score were selected to evaluate the performance of the developed YOLO-v5 deep learning model-based surface detection model. The mAP and mIoU on the front surface were 0.98 and 0.96, respectively, and on the back surface, they were 1.00 and 0.95, respectively. The results of binary classification for the two front and back classes were average 98.5%, recall 98.3%, decision 98.6%, and F1-score 98.4%. As a result, the developed model can classify the surface information of the dried bukak using RGB images, and it can be used to develop a robot-automated system for the surface detection process of the dried bukak before deep frying.