• Title/Summary/Keyword: Systems engineering

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A Design of Ultra-low Noise LDO Regulator for Low Voltage MEMS Microphones (저전압 MEMS 마이크로폰용 초저잡음 LDO 레귤레이터 설계)

  • Moon, Jong-il;Nam, Chul;Yoo, Sang-sun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.630-633
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    • 2021
  • Microphones can convert received voice signals to electric signals. They have been widely used in various industries such as radios, smart devices and vehicles. Recently, the demands for small size and high sensitive microphones are increased according to the minimization of wireless earphone with the development of smart phone. A MEMS system is a good candidate for an ultra-small size microphone of a next generation and a read out IC for high sensitive MEMS sensor is researched from many industries and academies. Since the microphone system has a high sensitivity from environment noise and electric system noise, the system requires a low noise power supply and some low noise design techniques. In this paper, a low noise LDO is presented for small size MEMS microphone systems. The input supply voltage of the LDO is 1.5-3.6V, and the output voltage is 1.3V. Then, it can support to 5mA in the light load condition. The integrated output noise of proposed LDO form 20Hz to 20kHz is about 1.9uV. These post layout simulation results are performed with TSMC 0.18um CMOS technology and the size of layout is 325㎛ × 165㎛.

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Comparison of Carbon Dioxide Emission Concentration according to the Age of Agricultural Heating Machine (농업용 난방기의 사용 연식에 따른 이산화탄소 배출농도 비교)

  • Na-Eun Kim;Dae-Hyun Kim;Yean-Jung Kim;Hyeon-Tae Kim
    • Journal of Bio-Environment Control
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    • v.32 no.3
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    • pp.190-196
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    • 2023
  • This study was carried out to collect gas emitted from agricultural heaters using kerosene and to identify the emission concentration of carbon dioxide according to the age of agricultural heating machine. As a result of the linear regression analysis, the carbon dioxide emissions according to the year of agricultural heating machine are R2 = 0.84, which follows y = 26.99x+721.98. Distributed analysis was classified into three groups according to the age of agricultural heating machine. As a result of the distributed analysis, it was 2.196×10-13, which was smaller than the 0.05 probability set for the analysis, which means that there is a difference in at least one group. As a result, the age of the agriculture machine was divided into three groups and the difference between groups was tested. A statistical analysis result was derived that there was a difference in the emission concentration of carbon dioxide according to the age of agricultural heating machine. It is thought that it can be used to investigate greenhouse gas emissions by investigating the amount of carbon dioxide generated by agricultural heaters in the agricultural field of Korea.

Comprehensive analysis of deep learning-based target classifiers in small and imbalanced active sonar datasets (소량 및 불균형 능동소나 데이터세트에 대한 딥러닝 기반 표적식별기의 종합적인 분석)

  • Geunhwan Kim;Youngsang Hwang;Sungjin Shin;Juho Kim;Soobok Hwang;Youngmin Choo
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.4
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    • pp.329-344
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    • 2023
  • In this study, we comprehensively analyze the generalization performance of various deep learning-based active sonar target classifiers when applied to small and imbalanced active sonar datasets. To generate the active sonar datasets, we use data from two different oceanic experiments conducted at different times and ocean. Each sample in the active sonar datasets is a time-frequency domain image, which is extracted from audio signal of contact after the detection process. For the comprehensive analysis, we utilize 22 Convolutional Neural Networks (CNN) models. Two datasets are used as train/validation datasets and test datasets, alternatively. To calculate the variance in the output of the target classifiers, the train/validation/test datasets are repeated 10 times. Hyperparameters for training are optimized using Bayesian optimization. The results demonstrate that shallow CNN models show superior robustness and generalization performance compared to most of deep CNN models. The results from this paper can serve as a valuable reference for future research directions in deep learning-based active sonar target classification.

A Development of Optimum Operation Models for Express-Rail Systems (급행열차 도입을 통한 최적운행방안 수립에 관한 연구 - 수도권 광역 도시철도를 중심으로 -)

  • Park, Jeong-Soo;Lee, Hoon-Hee;Won, Jai-Mu
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.679-686
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    • 2006
  • Recently, the city railway in the Seoul Metropolitan Area (SMA) has offered a low quality of service as a passage time, because it was operated slowly. So, the people who live in modern society are not satisfied about passage time, therefore, this study tried to make that the subway in the SMA becomes a more functional and effective wide-area-transportation-network through an express train introduction's method which examined cases from abroad and current system. and then presented how express train could be applied to current system. In a case study, We used the An-San Line and Su-In Line as a examples and developed a schedule which can minimize the delaying time of subway by using Branch & Bound Algorithm. The train operational plan was loaded to consider a railroad siding, Obtained site, and the dispatch interval(three to ten minutes) for the express and local lines and finally, We presented an alternative operational plan which made by those factors.

Detecting Nonlinearity of Hydrologic Time Series by BDS Statistic and DVS Algorithm (BDS 통계와 DVS 알고리즘을 이용한 수문시계열의 비선형성 분석)

  • Choi, Kang Soo;Kyoung, Min Soo;Kim, Soo Jun;Kim, Hung Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2B
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    • pp.163-171
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    • 2009
  • Classical linear models have been generally used to analyze and forecast hydrologic time series. However, there is growing evidence of nonlinear structure in natural phenomena and hydrologic time series associated with their patterns and fluctuations. Therefore, the classical linear techniques for time series analysis and forecasting may not be appropriate for nonlinear processes. In recent, the BDS (Brock-Dechert-Scheinkman) statistic instead of conventional techniques has been used for detecting nonlinearity of time series. The BDS statistic was derived from the statistical properties of the correlation integral which is used to analyze chaotic system and has been effectively used for distinguishing nonlinear structure in dynamic system from random structures. DVS (Deterministic Versus Stochastic) algorithm has been used for detecting chaos and stochastic systems and for forecasting of chaotic system. This study showed the DVS algorithm can be also used for detecting nonlinearity of the time series. In this study, the stochastic and hydrologic time series are analyzed to detect their nonlinearity. The linear and nonlinear stochastic time series generated from ARMA and TAR (Threshold Auto Regressive) models, a daily streamflow at St. Johns river near Cocoa, Florida, USA and Great Salt Lake Volume (GSL) data, Utah, USA are analyzed, daily inflow series of Soyang dam and the results are compared. The results showed the BDS statistic is a powerful tool for distinguishing between linearity and nonlinearity of the time series and DVS plot can be also effectively used for distinguishing the nonlinearity of the time series.

Study on the Quantitative Analysis of the Major Environmental Effecting Factors for Selecting the Railway Route (철도노선선정에 영향을 미치는 주요환경항목 정량화에 관한 연구)

  • Kim, Dong-ki;Park, Yong-Gul;Jung, Woo-Sung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.6D
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    • pp.761-770
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    • 2009
  • The energy efficiency and environment-friendly aspect of the railway system would be superior to other on-land ransportation systems. In a preliminary feasibility study stage and selection of optimal railway route, the energy efficiency and problems related to environment are usually considered. For the selection of optimal railway route, geographical features and facility of management are generally considered. Environment effect factors for the selection of environment-friendly railway router are focused and studied in this paper. In this study, various analysis of opinion of specialists (railway, environment, transport, urban planning, survey) and the guideline for construction of environment-friendly railway were accomplished. From these results of various analysis, 7 major categories (topography/geology, flora and fauna, Nature Property, air quality, water quality, noise/vibration, visual impact/cultural assets) were extracted. To select environment friendly railway route, many alternatives should be compared optimal route must be selected by a comprehensive assessment considering these 7 categories. To solve this problem, the selected method was AHP which simplifies the complex problems utilizing hierarchy, quantifying qualitative problems through 1:1 comparison, and extracting objective conclusions by maintaining consistency. As a result, a GUIbased program was developed which provides basic values of weighted parameters of each category defined by specialists, and a quantification of detailed assessment guidelines to ensures consistency.

Study on the Application of Dry-Ice Blaster for Development of Automatic Stripe-Line Removal (노면표시 제거 장비 개발을 위한 드라이아이스 블래스터 적용에 관한 연구)

  • Koo, Ja Kyung;Moon, Deuk Soo;Bernold, Leonhard E.;Lee, Tai Si
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2D
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    • pp.245-253
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    • 2009
  • Road facility is the most fundamental infrastructure for traffic and various information for smooth traffic is included in road surfaces. Various information included in road surfaces should be often removed and reinstalled by partial damage and aging. In addition, the existing road surface information should be removed in order to mark new information as traffic information changes. The existing road surface removal method suing grinders and torches had problems such as dangerous working equipment and workers' direct exposure to cars. In addition, although water-jet system using super high-pressure water was used to remove road surface in order of improvement of traditional method, there are another problems such as limitations according to water-tanks and water frost on the road surfaces after work. Therefore, this study analyzes and suggests systems to develop prototype after analyzing dry ice blaster in order to improve the current road surface removal methods. In addition, the study analyzes the possibility of introduction of dry ice blaster through a test for proposing an automatized equipment for new road surface mark removal considering environment and work efficiency, and compare traditional method with introduced dry ice blaster for operating cost.

A Guidance Methodology Using Ubiquitous Sensor Network Information in Large-Sized Underground Facilities in Fire (대형 지하시설물에서 화재발생 시 USN정보를 이용한 피난 유도 방안)

  • Seo, Yonghee;Lee, Changju;Jung, Jumlae;Shin, Seongil
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4D
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    • pp.459-467
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    • 2008
  • Because of the insufficiency of ground space, the utilization of underground is getting more and more in these days. Moreover, underground space is being used not only buildings but multipurpose space for movement, storage and shopping. However, ground space has vital weakness for fire compared to ground space. Especially in case of underground shopping center, there are various stuffs to burn and poisonous gas can be exposed on this count when the space is burned. A large number of casualties can be also occurred from conflagration as underground space has closed structures that prevent rapid evacuation and access. Therefore, this research proposes the guidance methodology for evacuation from conflagration in large-sized underground facilities. In addition, suggested methodology uses high technology wireless sensor information from up-to-date ubiquitous sensor networks. Fire information collected by sensors is integrated with existing underground facilities information and this is sent to guidance systems by inducing process. In the end, this information is used for minimum time paths finding algorithm considering the passageway capacity and distance. Also, usefulness and inadequacies of proposed methodology is verified by a case study.

Street Transit Network Analysis and Evaluation (노면 대중교통노선 평가틀 구축에 관한 연구)

  • Shin, Yong Eun
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.4D
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    • pp.477-483
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    • 2008
  • If designed properly, street transit systems can provide many useful functions with the flexibility of serving an unlimited range of locations throughout an urban area. Over the last decades urban regions of Korea cities have seen rapidly changing travel patterns and urban conditions. Under this circumstance transit planners need frequent evaluations of its street transit routes so as to restructure or modify them rationally. It should be noted that the changing network influences passengers, operators, as well as the city itself. However, there is no proper framework with which to evaluate the street transit network comprehensively. This paper develops and provides a framework including criteria and indicators for evaluating street transit networks. Five criteria, such as network size, network structure, service requirements, efficiency of operation and the relationship to the city are presented. A number of indicators and measures representing each criteria are then suggested. As a practical example, an analysis and comparison of three minibus networks in Busan are presented, utilizing the developed measures and indicators. The results of this study will be of great use for planners responsible for transit route planning, particularly for planning of new or analysis of existing routes; their comparison with routes/networks of various cities.

Quantitative Deterioration and Maintenance Profiles of Typical Steel Bridges based on Response Surface Method (응답면 기법을 이용한 강교의 열화 및 보수보강 정량화 이력 모델)

  • Park, Seung-Hyun;Park, Kyung Hoon;Kim, Hee Joong;Kong, Jung-Sik
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.6A
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    • pp.765-778
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    • 2008
  • Performance Profiles are essential to predict the performance variation over time for the bridge management system (BMS) based on risk management. In general, condition profiles based on experts opinion and/or visual inspection records have been used widely because obtaining profiles based on real performance is not easy. However, those condition profiles usually don't give a good consistency to the safety of bridges, causing practical problems for the effective bridge management. The accuracy of performance evaluation is directly related to the accuracy of BMS. The reliability of the evaluation is important to produce the optimal solution for distributing maintenance budget reasonably. However, conventional methods of bridge assessment are not suitable for a more sophisticated decision making procedure. In this study, a method to compute quantitative performance profiles has been proposed to overcome the limitations of those conventional models. In Bridge Management Systems, the main role of performance profiles is to compute and predict the performance of bridges subject to lifetime activities with uncertainty. Therefore, the computation time for obtaining an optimal maintenance scenario is closely related to the efficiency of the performance profile. In this study, the Response Surface Method (RSM) based on independent and important design variables is developed for the rapid computation. Steel box bridges have been investigated because the number of independent design variables can be reduced significantly due to the high dependency between design variables.