• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.25-33
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• 2021

With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.12
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• pp.491-498
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• 2019

Digital twin is a technology that virtualizes physical objects of the real world on a computer. It is used by collecting sensor data through IoT, and using the collected data to connect physical objects and virtual objects in both directions. It has an advantage of minimizing risk by tuning an operation of virtual model through simulation and responding to varying environment by exploiting experiments in advance. Recently, artificial intelligence and machine learning technologies have been attracting attention, so that tendency to virtualize a behavior of physical objects, observe virtual models, and apply various scenarios is increasing. In particular, recognition of each robot's motion is needed to build digital twin for co-robot which is a heart of industry 4.0 factory automation. Compared with modeling based research for recognizing motion of co-robot, there are few attempts to predict motion based on sensor data. Therefore, in this paper, an experimental environment for collecting current and inertia data in co-robot to detect the motion of the robot is built, and a motion prediction model based on the collected sensor data is proposed. The proposed method classifies the co-robot's motion commands into 9 types based on joint position and uses current and inertial sensor values to predict them by accumulated learning. The data used for accumulating learning is the sensor values that are collected when the co-robot operates with margin in input parameters of the motion commands. Through this, the model is constructed to predict not only the nine movements along the same path but also the movements along the similar path. As a result of learning using SVM, the accuracy, precision, and recall factors of the model were evaluated as 97% on average.

• Journal of the Korea Organic Resources Recycling Association
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• v.8 no.4
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• pp.93-99
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• 2000

Treatment of shaving scrap, a chrome containing solid scrap generated by leather manufacturing process, has been so far depended on mainly incineration, soil landfill and ocean dumping, which give bad impact on environment and cause pollution. Shaving scrap generates from the mechanical work for controlling the final thickness of leather and its main components are collagen protein and pan of chromium compound. For the purpose of reusing this leather waste as resources, researches in connection with collagen fiber recovery, gelable protein recovery and liquid fertilizer is being speedily progressed. In the experiment, shaving scrap went through wet pulverizing treatment by physical and chemical methods. Then, making the leather sheet evenly, it is mixed with natural latex and every kind of binding materials in the container, and the mixtures were passed through experimental hydraulic press machine and applied to Fourdrinier machine respectively. Lastly, a test for fading out physical strength and properties of multiple-purpose of leather-like material was performed on a continuous leather sheet prepared by the experiment. In result, the physical strength and properties of leather-like material showed noticeable differences according to mixing ratio of binding materials, beating methods and the Ends of binding materials selected, and generally tear strength was the weakest property among others. Also, by the pilot scale experiment in sequence, it was possible to manufacture recycled goods made of soft and hard types of leather-like material with various performances.

• The International Journal of Costume Culture
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• v.7 no.2
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• pp.103-111
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• 2004

The shrinkproof-finished wool fibers treated with resin coating and chlorination methods were used to find out an optimal shrinkproof finishing method keeping the quality properties of wool fabric to manufacturers. Shrinkage during repeated washing, electrostatic propensity, thermal resistance and pilling propensity of shrinkproof-finished wool knits, and analysis of finishing methods were measured. Upon the results from the surface examination of shrinkproof-finished wool fibers, the patterns of scale layer and degree of scale removal were subject to change according to the finishing processes. The shrink resistance was significantly enhanced on repeated washing of shrinkproof-finished knits, especially, chlorinated wool. Addition of strong physical force and alkali detergent applied in this washing experiment brought about superior effects with the low shrinkage rate although it was very severe washing conditions for wool fabrics. The results from the washing experiment implies that shrinkproof-finished knitted fabrics can be machine washed at individual households with other ordinary laundry. There was some changes and variation found in thermal resistance, electrostatic propensity, and pilling, however, it seems to be minor within standard limits. Therefore, shrinkproof-finished knitted fabrics did not bring serious changes to other physical properties comparing with original wool, which helps consumers handle wool knitted clothes more conveniently.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3712-3729
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• 2020

Smoke detection is helpful for early fire detection. With its large coverage area and low cost, vision-based smoke detection technology is the main research direction of outdoor smoke detection. We propose a two-stage smoke detection method combined with block Deep Normalization and Convolutional Neural Network (DNCNN) and visual change image. In the first stage, each suspected smoke region is detected from each frame of the images by using block DNCNN. According to the physical characteristics of smoke diffusion, a concept of visual change image is put forward in this paper, which is constructed by the video motion change state of the suspected smoke regions, and can describe the physical diffusion characteristics of smoke in the time and space domains. In the second stage, the Support Vector Machine (SVM) classifier is used to classify the Histogram of Oriented Gradients (HOG) features of visual change images of the suspected smoke regions, in this way to reduce the false alarm caused by the smoke-like objects such as cloud and fog. Simulation experiments are carried out on two public datasets of smoke. Results show that the accuracy and recall rate of smoke detection are high, and the false alarm rate is much lower than that of other comparison methods.

• Journal of the Korean Academy of Clinical Electrophysiology
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• v.1 no.2
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• pp.1-9
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• 2003

The purpose of this study was to analyze the effect given to the variable details which disturb the flow of blood in brain artery disease through Aerobic exercises. It chose the subjects of study : 5 persons in an exercise group and 5 persons in a non-exercise group. Peak brain blood velocity, mean velocity, and resistance & artery stricture ratio were measured with TCD, measure machine for brain artery blood flow. The conclusion of the study was as follows: 1. At pre-test of an exercises group and a non-exercise group, PBV, MBV, BRI, ASI of a non-exercise group were showed much lower in the variation of left common carotid artery(LCCA). 2. At post-test of an aerobic exercises group and a non-exercise group, PBV, MBV, BRI, ASI of a non-exercise group were showed just a little decrease ratio but were not significant different in the variation of left common carotid artery(LCCA). Viewing on the base of these result, continuing exercises promote the functional improvement of the heart blood system and were showed the positive variation of artery stricture ratio according to brain blood flow velocity, the pulse and resistance or blood velocity. Therefore programs for prescriptions through aerobic exercises must be developed in many ways.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1448-1453
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• 2004

The major parameters governing the fluid dynamical and thermo-dynamical behavior in the large pipeline network system are friction loss and the pipeline length. But in local pipeline networks and relatively short distance pipeline system, secondary loss and the considerations of the moving states of the fluid machine are also important. One of the major element in local pressure control system is pressure regulator. It causes the variations of the physical properties in that pipeline system. Especially, as there is not enough information to obtain reliable physical property values such as density, temperature etc. at the downstream of the pressure regulator, It is hard to calculate accurate solution in the pipeline network analysis. In this study, some numerical approaches to investigate the critical-flow-characteristics of the pressure regulator have been done and the detail examinations and considerations of the pressure regulator as a pipeline network elements according to the variations of the inlet-outlet pressure ratio have been carried. Finally the flow-flied distributions, relations and critical-flow-characteristics have been studied. in detail and the 1D analytic method to analyze critical pipe flow have been investigated

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1520-1542
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• 2020

Traditional software testing typically uses many physical resources to manually build various test environments, resulting in high resource costs and long test time due to limited resources, especially for small enterprises. Cloud computing can provide sufficient low-cost virtual resources to alleviate these problems through the virtualization of physical resources. However, the provision of various test environments and services for implementing software testing rapidly and conveniently based on cloud computing is challenging. This paper proposes a multilayer cloud testing model based on cloud computing and implements a hybrid cloud testing system based on virtual machines (VMs) and networks. This system realizes the automatic and rapid creation of test environments and the remote use of test tools and test services. We conduct experiments on this system and evaluate its applicability in terms of the VM provision time, VM performance and virtual network performance. The experimental results demonstrate that the performance of the VMs and virtual networks is satisfactory and that this system can improve the test efficiency and reduce test costs through rapid virtual resource provision and convenient test services.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.488-492
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• 2007

Since Equipment-Noises occurring in machine room penetrate wall-body and travel to the adjacent room in the form of air-borne sound and structure-borne sound, it is appearing as the main factor that injures a peaceful residential environment, and due to this, such noise-damage is currently increasing rapidly. Consequently, despite the measures for sound-insulation and soundproof against the equipment-noise penetrated wall-body is urgently required, but as the subjective evaluation considered for psychological response about the equipment-noise was not practiced, many dissatisfactions are still raising even after some measure was taken. On such point of view, this Research, at the spot, has actually measured the equipment-noise that had permeated various wall-bodies, and examined its physical characteristics, thence based upon this, has conducted Psycho-Acoustics Experiment and investigated the interrelation between the physical evaluation value and psychological reaction value. It is considered that such study result could be utilized as the useful material at the time of establishment of the Grading Standard for the insulation performance against the Architectural Plumbing Noise, in the future.

• Korean Journal of Applied Biomechanics
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• v.15 no.2
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• pp.139-146
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• 2005

We selected six kinds of stretching exercises that can be easily acquired and put to practical use by back pain patients and arranged the practicing order of the exercising method after measuring the % MlVC of the muscle power when a normal person was exercising with a surface EMG. Among the patients complaining of back pain, 20 case groups were given the selected exercise and physical therapy, and 20 control groups were only given a physical therapy. Before and 2 weeks, 4weeks, 6 weeks and 8 weeks after the exercise therapy, a muscle power was measured with a fitness machine and the effectiveness of the exercise was compared. After six weeks difference of the muscle power between the case group and control group was shown, and after 8weeks the case group manifested the stronger muscle power than that of the control group in both male and female. Exercising therapy clearly seems to be helpful in strengthening the muscle power of the back pain patients.