• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.503-510
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• 2006

Readout circuit is to convert signal occurred in a defector into suitable signal for image signal processing. In general, it has to possess functions of impedance matching with perception element, amplification, noise reduction and cell selection. It also should satisfies conditions of low-power, low-noise, linearity, uniformity, dynamic range, excellent frequency-response characteristic, and so on. The technical issues in developing image processing equipment for focal plane way (FPA) can be categorized as follow: First, ultraviolet (UV) my detector material and fine processing technology. Second, ReadOut IC (ROIC) design technology to process electric signal from detector. Last, package technology for hybrid bonding between detector and ROIC. ROIC enables intelligence and multi-function of image equipment. It is a core component for high value added commercialization ultimately. Especially, in development of high-resolution image equipment ROIC, it is necessary that high-integrated and low-power circuit design technology satisfied with design specifications such as detector characteristic, signal dynamic range, readout rate, noise characteristic, ceil pitch, power consumption and so on. In this paper, we implemented a $8\times8$ FPA prototype ROIC for reduction of period and cost. We tested unit block and overall functions of designed $8\times8$ FPA ROIC. Also, we manufactured ROIC control and image boards, and then were able to verify operation of ROIC by confirming detected image from PC's monitor through UART(Universal Asynchronous Receiver Transmitter) communication.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.5
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• pp.879-885
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• 2013

Satellites provide a lot of information and essay roles in the areas of defense and space observations. The precise distances to the satellites are measured by emitting and retro-reflecting a laser. For such surveys, satellite laser ranging (SLR) systems have been developed in different forms and for different areas. The structural integrity of the tracking mount is essential for it to be able to track a high-speed satellite precisely, overcoming the various external and internal disturbances and operating conditions. In this study, the analysis of a tracking mount was performed for weight, wind loads, and inertia loads in order to verify its soundness. The results of the comparison between aluminum and steel were analyzed in order to select the optimal material for the fork and main housing part. In addition, the natural frequency and mode shape were predicted. Optimal material selection and structural integrity will also be verified using static analysis.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.104-112
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• 2002

In this paper, it is suggested that the selection method of parameter of Power System Stabilizer(PSS) with robustness in low frequency oscillation for Thyristor Controlled Series Capacitor(TCSC) using Geletic Algorithm(GA). A TCSC meddle consists of a stories capacitor and a parallel path with a thyristor valve and a series inductor. Also in in parallel, as is typical with series capacitor applications, is a metal-oxide varistor(MOV) for overvoltage protection. The proposed PSS parameters are optimized using GA in order to maintain optimal operation of TCSC which is expected to be applied in transmission system to achieve a number of benefits under the various operating conditions. In order to verify the robustness of the proposed method, we considered the dynamic response of angular velocity deviation and terminal voltage deviation under a power fluctuation and rotor angle variation.

• Progress in Medical Physics
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• v.3 no.2
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• pp.43-57
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• 1992

Phase detector techique provides a unique probe to membrane recycling phenomenon by enabling dynamic monitoring of cell membrane capacitance. However, it has inherent errors due to constant changes in measurement environments. The present study analyzed several error sources to develope application criteria of this technique. and the following was found based on a theoretical analysis. The initial phase angle has to be appropriately selected to minimize the error due to perturbation of access and membrane conductances. Excitation frequency is also important to determine the initial phase angle. However. deviation of the phase angle from a predetermined initial value during the measurement period does not affect capacitance estimation to a significant degree. Despite an appropriate initial phase selection an error in scaling factor is expected for a large increase in capacitance during exocytosis. which may be overcome by iteratively correcting the scaling factor over the measurement period. These results will provide a useful guideline in practical application of this technique.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.1
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• pp.42-50
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• 2008

Unlike a cellular network, a mobile ad hoc network(MANET) is constructed only by mobile nodes without access point. Mobile nodes in MANET operate with scarce resources and restricted battery. If battery of intermediate node is exhausted, overall network might be diverged. Therefore, power-aware is really important. An on-demand multipath routing protocol which is proposed to compensate for shortcoming of on-demand single path routing protocol can reduce mute discovery overhead because route discovery starts only when all routes are disconnected. AOMDV(Ad hoc On-demand Multipath Distance Vector) which is on-demand multipath routing protocol based on AODV, reduces 40% of route discovery frequency. However, AOMDV have none of power-aware. So AOMDV have problem that route discovery for power exhaustion is not reduced at all. This paper proposes new power-aware path selection algorithm for AOMDV and scheme that broadcast REER packets when mobile node's battery can be gone. Performance comparison of proposed algorithm with AOMDV using ns-2 simulator shows that route discovery of proposed algorithm is reduced maximally 36.57% than AOMDV's.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6360-6367
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• 2015

The location selection of the element that should guarantee easy visual perception, like the landmark, is the a topic that appears much in the design process. Recently, a graph analysis technique using computers has been applied in order to evaluate the visibility of the visual element, but the analytic frame is flat and the setting of the visual pont and the matrix are fixed so there were great limitations in obtaining the results of the practical analysis. Thus, this study presented Nondirectional Multi-Dimensional Calculation (MDVC-N), an analytic methodology available for the analysis of the dynamic visual point in the 3D environment. It thus attempted to establish the analytic application using the 3D computer graphics technology and designed a script structure to set the visual point and the matrix. In addition to that, this study tried to verify the analytic methodology by applying the complex land as an example model, where buildings in various heights of terrains with a high-differences are located, verifying the same analytic methodology. It thus tried to identify the visual characteristics of each alternative location. The following results were gained from the study. 1) The visibility can be measured quantitatively trough the application of the 6-alternatives. 2) Using the 3dimensional graph, intuitive analysis was possible. 3) It attempted to improve the analytic applicability by calculating the results corrected as a variable behavior from the local integration variable of the space syntax.

• Journal of Distribution Science
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• v.10 no.7
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• pp.5-11
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• 2012

The core objective of this research article is to investigate different challenges and opportunities in management as well as start-ups of small businesses in India. The prudence behind this research is to examine various problems in front of the small businesses and to offer vital support and cooperation to overcome those with the support of concerned institutions through consultancy and training programs. The researchers have an intention to make available the research results to the governmental agencies, concerned small business institutions and also to the educational institutions which are continually design plans, programs, policies and strategies to upgrade the managerial and technical dexterities of the small business Indian operators. After thorough revision of relevant literature on small businesses and its management, the researchers used a well structured questionnaire and in-depth personal interviews with 586small business operators selected from manufacturing, trading (retailing and wholesaling), finance, servicing/repair businesses which are located in the coastal districts of Andhra Pradesh in India. The researchers have used convenience sampling and collected data was analyzed with the support of Microsoft Excel and frequency distribution. Noticeably, majority of the small businessmen in India are facing myriad number of challenges both in management and at the time of establishment of their business operations. In particular, 72.47 percent of small businesses operators' have substantiated their strong opinion towards the challenges they are facing particularly finance, marketing and other problems while managing their businesses. The researchers also attempted to get the opinions on problems of the various categories of small businesses while starting their operations. A staggering 68percent of respondents identified the problems related to preparation of business plan, location selection, marketing and other problems like lack of proper credit facilities, skilled manpower, and other infra related problems while setting up of their businesses. On an average, 64.62 and 63.51 percent of small businesses are facing various kinds of problems both at the time of day-to-day management as well as start-up of their businesses respectively. The present research confined with the opinions of only four categories of small business operators particularly from the manufacturing, finance, trading (retailing and wholesaling), and servicing/repair which are continuing their business operations from the nine coastal districts of Andhra Pradesh in India. The present study emphatically provides concrete information required to the business community for identifying an assortment of challenges faced by different small business operators in managing and at the time of their inception. This research paper is first of its kind from this part of the world by offering extensive and credible information required for prospective entrepreneurs in facing the dynamic challenges in managing their business. Furthermore, this research presents invaluable inputs to the stakeholders like all types of governments, policy makers, practitioners, researchers, and educators' about the various impediments faced by the small business community in India.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2060-2077
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• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.