• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.23 no.8
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• pp.759-769
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• 2013

Electronic equipment has been applied to virtually every area associated with commercial, industrial, and military applications. Specifically, electronics have been incorporated into avionics components installed in aircraft. This equipment is exposed to dynamic loads such as vibration, shock, and acceleration. Especially, avionics components installed in a helicopter are subjected to simultaneous sine and random base excitations. These are denoted as sine on random vibrations according to MIL-STD-810F, Method 514.5. In the past, isolators have been applied to avionics components to reduce vibration and shock. However, an isolator applied to an avionics component installed in a helicopter can amplify the vibration magnitude, and damage the chassis, circuit card assembly, and the isolator itself via resonance at low-frequency sinusoidal vibrations. The objective of this study is to investigate the dynamic characteristics of an avionics component installed in a helicopter and the structural dynamic modification of its tray plate without an isolator using both a finite element analysis and experiments. The structure is optimized by dynamic loads that are selected by comparing the vibration, shock, and acceleration loads using vibration and shock response spectra. A finite element model(FEM) was constructed using a simplified geometry and valid element types that reflect the dynamic characteristics. The FEM was verified by an experimental modal analysis. Design parameters were extracted and selected to modify the structural dynamics using topology optimization, and design of experiments(DOE). A prototype of a modified model was constructed and its feasibility was evaluated using an FEM and a performance test.

• Journal of Environmental Impact Assessment
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• v.26 no.4
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• pp.227-241
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• 2017

A human in urban areas has depended on ecosystem for well-being, so it is important to evaluate urban ecosystem services which contribute significantly to human well-being. In this study we classified ecosystem functions and set indicators used for evaluating ecosystem services of urban park by Delphi method. As a result, it derived 12 items and 14 indicators of ecosystem services to evaluate them such as vegetable garden, canopy cover, biodiversity, and educational programs. Based on the derived evaluation indicators, the feasibility of the indicators was examined by applying to two urban parks, Maetan park and Seoho-Ggotme park, in Suwon City. We also suggested strategies to improve each ecosystem services based on the results of evaluation. It is significant to recognize unknown services in urban parks. The results can be used for improving urban ecosystem services consistently in response to current rapid urbanization. In the future, the city should make a master plan on ecosystem service on urban area, beyond urban park, considering both of quality and quantity.

• Journal of rehabilitation welfare engineering & assistive technology
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• v.11 no.1
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• pp.45-52
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• 2017

EEG signals that are the same as those that have the same disabled people. So, the EEG signals are becoming the next generation. In this paper, we propose an internet of things system that controls the indoor environment using EEG signal. The proposed system consists EEG measurement device, EEG simulation software and indoor environment control device. We use data as EEG signal data on emotional imagination condition in a comfortable state and logical imagination condition in concentrated state. The noise of measured signal is removed by the ICA algorithm and beta waves are extracted from it. then, it goes through learning and test process using SVM. The subjects were trained to improve the EEG signal accuracy through the EEG simulation software and the average accuracy were 87.69%. The EEG signal from the EEG measurement device is transmitted to the EEG simulation software through the serial communication. then the control command is generated by classifying emotional imagination condition and logical imagination condition. The generated control command is transmitted to the indoor environment control device through the Zigbee communication. In case of the emotional imagination condition, the soft lighting and classical music are outputted. In the logical imagination condition, the learning white noise and bright lighting are outputted. The proposed system can be applied to software and device control based BCI.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4805-4815
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• 2015

Dementia is targeted at the elderly and dependent family members, care providers, and the types of problem behaviors of the elderly with dementia by care providers learn how to cope with the relationship was tried for. Dementia in the elderly problem behaviour is the program's descriptive statistics, t-test, ANOVA, and dementia in the elderly problem behaviors for coping with behavior and the relationship between discrete variable using correlation analysis. The findings support the family and nursing experience of senile elderly issues, acting as a provider edge actions appeared the most high, and repeat the same question or request. ', ' Making loud noises or shouting. ' and '. 'Being stubborn, not listening to the words of the caregiver.' etc. In addition, this study, which appeared in dementia in the elderly cope with behavior based on behavioral problems and discuss the ' Verbal discussion ', ' Removal of the cause for incidents ' and ' Restriction of actions ' action causes this correlation. Therefore, caring for the elderly with dementia in a nursing institution and sanction providers related to dementia in the elderly appear to be frequently problem behaviors of the problematic behavior is not much need to be able to cope with the regular education, this study to the development of behavioral problems in dementia patients by an individualized nursing intervention program for caregivers caring for dementia patients, as basic materials will be provided.

• Resources Recycling
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• v.19 no.3
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• pp.24-32
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• 2010

In the present work, a new separation system with rotating rakes has been developed to separate the film-based plastics from the recyclable materials, and environment assessment is also carried out during operation of the device. Capacity of the device was about 5.3 ton/hr at a rakes rotation speed of 26.0 rpm (the number of rakes in the 1st, 2nd and 3rd trials were 39, 52 and 48, respectively) and a belt conveyor speed of 38.5m/min, which satisfied the initial design capacity (5.0 ton/hr). Recovery ratio and purity of the plastic films were 92.6% and 96.5%, respectively at a rotation speed of 28 rpm. The levels of noise, vibration and particulate emission were below material standard regulatory limits. Plastic refused fuel (RPF) was also prepared with the recovered films. The calorific value and chlorine content of the prepared RPF were 9,740 kcal/kg and 0.18%, respectively which satisfy the first grade quality specification of the Korean RPF standard. As a result of this work, recovery of energy resources from the municipal solid waste is possible by adopting the developed separation device.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.283-290
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• 2020

Porous asphalt pavement is used widely in advanced countries to reduce traffic accidents and noise. On the other hand, it is not applied widely in Korea due to concerns about its durability. This study aims to find a statistical method to improve the durability of porous asphalt pavement. A Cantabro test was selected to test the durability. The Cantabro test was performed on an asphalt mixture made of a binder and aggregate. This test was repeated three times for each of the four groups to obtain the Cantabro loss rate. The average values of each of the four groups satisfied all the reference values. In addition, through an analysis of variance (ANOVA), it was possible to quantitatively classify test groups with differences in durability, thereby finding problems and improving the durability. Furthermore, the Pay Factor method can lead to voluntary improvements in quality, and the Pay factor can be calculated through statistical analysis of limited data. Through the Pay factor, it is possible to induce definite quality improvement of the contractor and continuously improve the durability of the porous asphalt mixture by evaluating the adequacy of the quality standard.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.87-93
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• 2014

If one identifies the detailed distribution of pressure and axial velocity at a source plane, the position and strength of major noise sources can be known, and the propagation characteristics in axial direction can be well understood to be used for the low noise design. Conventional techniques are usually limited in considering the constant source characteristics specified on the whole source surface; then, the source activity cannot be known in detail. In this work, a method to estimate the pressure and velocity field distribution on the source surface with high spatial resolution is studied. The matrix formulation including the evanescent modes is given, and the nearfield measurement method is proposed. Validation experiment is conducted on a wide duct system, at which a part of the source plane is excited by an acoustic driver in the absence of airflow. Increasing the number of evanescent modes, the prediction of pressure spectrum becomes further precise, and it has less than -25 dB error with 26 converged evanescent modes within the Helmholtz number range of interest. By using the converged modal amplitudes, the source parameter distribution is restored, and the position of the driver is clearly identified at kR = 1. By applying the regularization technique to the restored result, the unphysical minor peaks at the source plane can be effectively suppressed with the filtering of the over-estimated pure radial modes.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.1
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• pp.32-38
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• 2024

In the case of apartment building, it is difficult to conduct non-destructive testing due to the actual presence of people and the dust and noise generated during the core test, so inspections are performed each time in the common area and underground parking lot, and the tests are conducted on the finishing material rather than on the concrete surface due to low-cost orders. As the process progresses, poor inspection is inevitable. In addition, the proposed formulas for strength estimation have large fluctuations depending on the differences in test conditions and environments, and even if they show the same measured value, the deviation between each proposed formula is large, making it difficult to accurately estimate strength, making it difficult to use. Accordingly, we would like to select finishing materials mainly used in apartment complexes and compare and evaluate the compressive strength of concrete according to the type of finishing material by using non-destructive testing methods directly on the finishing materials without removing the finishing materials. The reliability evaluation results of the estimated compressive strength of concrete using the ultrasonic velocity method according to the type of finishing material are as follows. The error rate between the estimated compressive strength and compressive strength derived through the ultrasonic velocity method shows a wide range of variation, ranging from 21.83% to 58.89%. The effect of the presence or absence of finishing materials on the estimated compressive strength was found to be insignificant. Accordingly, it is necessary to select more types of finishing materials and study ultrasonic velocity methods according to the presence or absence of finishing materials, and to study estimation techniques that can increase reliability.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.225-233
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• 2024

Active sonar transmits sound waves to detect covertly maneuvering underwater objects and detects the signals reflected back from the target. However, in addition to the target's echo, the active sonar's received signal is mixed with seafloor, sea surface reverberation, biological noise, and other noise, making target recognition difficult. Conventional techniques for detecting signals above a threshold not only cause false detections or miss targets depending on the set threshold, but also have the problem of having to set an appropriate threshold for various underwater environments. To overcome this, research has been conducted on automatic calculation of threshold values through techniques such as Constant False Alarm Rate (CFAR) and application of advanced tracking filters and association techniques, but there are limitations in environments where a significant number of detections occur. As deep learning technology has recently developed, efforts have been made to apply it in the field of underwater target detection, but it is very difficult to acquire active sonar data for discriminator learning, so not only is the data rare, but there are only a very small number of targets and a relatively large number of non-targets. There are difficulties due to the imbalance of data. In this paper, the image of the energy distribution of the detection signal is used, and a classifier is learned in a way that takes into account the imbalance of the data to distinguish between targets and non-targets and added to the existing technique. Through the proposed technique, target misclassification was minimized and non-targets were eliminated, making target recognition easier for active sonar operators. And the effectiveness of the proposed technique was verified through sea experiment data obtained in the East Sea.