• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.63-70
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• 2022

Although 2D Object detection has been largely improved in the past years with the advance of deep learning methods and the use of large labeled image datasets, 3D object detection from 2D imagery is a challenging problem in a variety of applications such as robotics, due to the lack of data and diversity of appearances and shapes of objects within a category. Google has just announced the launch of Objectron that has a novel data pipeline using mobile augmented reality session data. However, it also is corresponding to 2D-driven 3D object detection technique. This study explores more mature 2D object detection method, and applies its 2D projection to Objectron 3D lifting system. Most object detection methods use bounding boxes to encode and represent the object shape and location. In this work, we explore a stochastic representation of object regions using Gaussian distributions. We also present a similarity measure for the Gaussian distributions based on the Hellinger Distance, which can be viewed as a stochastic Intersection-over-Union. Our experimental results show that the proposed Gaussian representations are closer to annotated segmentation masks in available datasets. Thus, less accuracy problem that is one of several limitations of Objectron can be relaxed.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.91-98
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• 2023

PET is used effectively for biochemical or pathological phenomena, disease diagnosis, prognosis determination after treatment, and treatment planning because it can quantify physiological indicators in the human body by imaging the distribution of various biochemical substances. However, since respiratory motion artifacts may occur due to the movement of the diaphragm due to breathing, we would like to evaluate the practical effect by using the a device-less data-driven gated (DDG) technique called MotionFree with the phase-based gating correction method called Q.static scan mode. In this study, images of changes in moving distance (0 cm, 1 cm, 2 cm, 3 cm) are acquired using a breathing-simulated moving phantom. The diameters of the six spheres in the phantom are 10 mm, 13 mm, 17 mm, 22 mm, 28 mm, and 37 mm, respectively. According to maximum standardized uptake value (SUVmax) measurements, when DDG was applied based on the moving distance, the average SUVmax of the correction effect by the moving distance was improved by 1.92, 2.48, 3.23 and 3.00, respectively. When DDG was applied based on the diameter of the phantom spheres, the average SUVmax of the correction effect by the moving distance was improved by 2.37, 2.02, 1.44, 1.20, 0.42 and 0.52 respectively.

• Investigative Magnetic Resonance Imaging
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• v.13 no.1
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• pp.31-39
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• 2009

Purpose : This study proposes the keyhole method in order to improve the time resolution of the proton resonance frequency(PRF) MR temperature monitoring technique. The values of Root Mean Square (RMS) error of measured temperature value and Signal-to-Noise Ratio(SNR) obtained from the keyhole and full phase encoded temperature images were compared. Materials and Methods : The PRF method combined with GRE sequence was used to get MR temperature images using a clinical 1.5T MR scanner. It was conducted on the tissue-mimic 2% agarose gel phantom and swine's hock tissue. A MR compatible coaxial slot antenna driven by microwave power generator at 2.45GHz was used to heat the object in the magnetic bore for 5 minutes followed by a sequential acquisition of MR raw data during 10 minutes of cooling period. The acquired raw data were transferred to PC after then the keyhole images were reconstructed by taking the central part of K-space data with 128, 64, 32 and 16 phase encoding lines while the remaining peripheral parts were taken from the 1st reference raw data. The RMS errors were compared with the 256 full encoded self-reference temperature image while the SNR values were compared with the zero filling images. Results : As phase encoding number at the center part on the keyhole temperature images decreased to 128, 64, 32 and 16, the RMS errors of the measured temperature increased to 0.538, 0.712, 0.768 and 0.845$^{\circ}C$, meanwhile SNR values were maintained as the phase encoding number of keyhole part is reduced. Conclusion : This study shows that the keyhole technique is successfully applied to temperature monitoring procedure to increases the temporal resolution by standardizing the matrix size, thus maintained the SNR values. In future, it is expected to implement the MR real time thermal imaging using keyhole method which is able to reduce the scan time with minimal thermal variations.

• The Journal of Fisheries Business Administration
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• v.17 no.2
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• pp.65-106
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• 1986

1, The Purpose of Study This is a study on the Evaluation of the operating of Fisheries Extension Services of Korea, for performing the activities such as guiding fisheries technique as well as offering industrial information to the fishermen in fishing village. By doing so, the Fisheries Extension Sevices(FES) can materialize the continued growth of fisheries, the social and economic development of fishing village, and the increase in income by enhancing the knowledge level of Fishermen, etc. In performing fisheries policy, this activity plays a great role on the research and development activity, and it has become practical since 1976 in Korea. In order to meet immediately with the problem of fisheries technical innovation and rapid environmental changes surrounding the fisheries, the fishermen should not only enhance their scientific and comprehensive capacity in fisheries technique but abtain various effective information. Generally, as most of all the fishemen are poor in the managerial structure and scattered in fishing villages, they have little opportunity in the contact of information. As a result, it is nessessary for the FES to perform the fishing business by the extension service officials who has received special training and acquired fisheries know-how in these fields. And yet, FES is under the unfullfilled circumstance in such factors as manpower, technical know-how, equipment, and the service system etc., which is required in promoting the social, economic development of fishing village and in resolving the high technique demand of fisherman. This study on the fisheries extension services have been studied from those backgrounds. 2. Research Method The data of collecting methods which were necessary in carrying out this study was adopted by the questionaire research on the present extension service activity, through the subject of the extension services (driving agency of the work and the officials), the object(fishemen) and the 3rd observers to the extension services (the authorities concerned). The research sample was taken by the sampling extraction of total 1, 774 men from the above 3 groups. And the research was carried out from August, 1986 to October, 1986, supported from the Fisheries Extension Office (FEO) located in field during the research process. In this study, the levels of the extension operating were determined and estimated in accordance with the extension service method, morale of extension service officials and the extension service system, etc. through the collected data of the research questionaire paper. And based on this result, the essential conditions of the extension services were grasped, and also we tried to present the various activity plan necessary to promote the operating of the extension services. The questionaire research data was calculated by the computer center of National Fisheries University of Pusan, and the total result was again tried on the one demension analysis along with two dimension analysis to search out the relativity between the questionaire, and the statistical test was done $\chi$$^2$test in significance level of l~5%. 3. Contents of Study This study consists of 7 chapters and the contents are as follows : Chapter I : The object and method of the study Chapter II : The assessment and analysis of the extension services Chapter III : The contents and method of the extension services Chapter IV : Analysis of the essential conditions for the extension services Chapter V : The evaluation of activities of extension services Chapter Ⅵ : Conclusion.4. Results and RecommendationTherefore, the results of this study estimated by logical process and analysis are as follows : 1) Most of Korean fishing villages and coastal fishermen have shown much concerns about fisheries technique and social changes, thus many of them were confronted with new problems on how to adapt and to meet changes. 2) Majority of fishermen estimated FEO as an organization of specific technologies with all the thing concerning the fisheries technique in general. Therefore the fishermen wanted to utilize the FEO as an adaptable method for the modern fisheries techniques as well as the environmental changes. 3) In contrast with the fast changes of the fisheries technique, the complexity and variety of technical system and the broadness of fishing village and fishermen, it was revealed that the necessary factors such as the facilities, manpower, budget, and the level of applying techniques of the FEO located in field were highly insufficient. Accordingly, the guiding efficiency was low and the extension services did not provide full solution to the various request from fishermen. 4) It is possible to classify the activation factor for the extension service into two large dimension ; personal dimension relevant to guidance officials and work dimension relevant to the organization. And it was found that the activation level of the work dimension was far lower than the personal dimension between them. So, the activation should be done first in the dimesion to promote the activation of the extension services. 5) The extension services officials are now demoralized in general, thus it is necessary to take reality into consideration : the expense of activity, the adequate endowment of activity scope and the reasonable operation of the position class, etc to enhance its morale. However, in order to do the FES activation, first of all, the systems should be established which is lain unsettled stage until now. And there must be change in the understanding of government i.e. the fisheries extension services are the essential policy subject to build up the base of fisheries growth and modernize the fisheries management. And it should be driven positively with the recognition of the "lasting project".g project".uot;.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.23-46
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• 2017

Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.565-577
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• 2016

The objective of this study is to propose a method for computing the Natural Drought Index (NDI) that does not consider man-made drought facilities. Principal Component Analysis (PCA) was used to estimate the NDI. Three monthly moving cumulative runoff, soil moisture and precipitation were selected as input data of the NDI during 1977~2012. Observed precipitation data was collected from KMA ASOS (Korea Meteorological Association Automatic Synoptic Observation System), while model-driven runoff and soil moisture from Variable Infiltration Capacity Model (VIC Model) were used. Time series analysis, drought characteristic analysis and spatial analysis were used to assess the utilization of NDI and compare with existing SPI, SRI and SSI. The NDI precisely reflected onset and termination of past drought events with mean absolute error of 0.85 in time series analysis. It explained well duration and inter-arrival time with 1.3 and 1.0 respectively in drought characteristic analysis. Also, the NDI reflected regional drought condition well in spatial analysis. The accuracy rank of drought onset, termination, duration and inter-arrival time was calculated by using NDI, SPI, SRI and SSI. The result showed that NDI is more precise than the others. The NDI overcomes the limitation of univariate drought indices and can be useful for drought analysis as representative measure of different types of drought such as meteorological, hydrological and agricultural droughts.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.48 no.10
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• pp.773-782
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• 2020

The development of joint FE models for deep learning neural network (DLNN)-based hybrid FEA is presented. Material models of bolts and bearings in the front axle of tractor, showing complex behavior induced by various tightening conditions, were replaced with DLNN models. Bolts are modeled as one-dimensional Timoshenko beam elements with six degrees of freedom, and bearings as three-dimensional solid elements. Stress-strain data were extracted from all elements after finite element analysis subjected to various load conditions, and DLNN for bolts and bearing were trained with Tensorflow. The DLNN-based joint models were implemented in the ABAQUS user subroutines where stresses from the next increment are updated and the algorithmic tangent stiffness matrix is calculated. Generalization of the trained DLNN in the FE model was verified by subjecting it to a new loading condition. Finally, the DLNN-based FEA for the front axle of the tractor was conducted and the feasibility was verified by comparing with results of a static structural experiment of the actual tractor.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.236-242
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• 2015

We present two data-driven modeling methods, partial least square (PLS) and artificial neural network (ANN), to predict the major operating and performance variables of a polymer electrolyte membrane (PEM) fuel cell stack. PLS and ANN models were constructed using the experimental data obtained from the testing of a 30 kW-class PEM fuel cell stack, and then were compared with each other in terms of their prediction and computational performances. To reduce the complexity of the models, we combined a variables importance on PLS projection (VIP) as a variable selection method into the modeling procedure in which the predictor variables are selected from a set of input operation variables. The modeling results showed that the ANN models outperformed the PLS models in predicting the average cell voltage and cathode outlet temperature of the fuel cell stack. However, the PLS models also offered satisfactory prediction performances although they can only capture linear correlations between the predictor and output variables. Depending on the degree of modeling accuracy and speed, both ANN and PLS models can be employed for performance predictions, offline and online optimizations, controls, and fault diagnoses in the field of PEM fuel cell designs and operations.

• Asia pacific journal of information systems
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• v.17 no.3
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• pp.131-146
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• 2007

Recently, the role of IT service providers has been enlarged from managing a single function or system to reconstructing entire information management processes in new ways to contribute to shareholder value across the enterprise. This movement toward extensive and complex outsourcing agreements has been driven by the assumption that outsourcing information technology functions is a reliable approach to maximizing resource productivity. Hiring external IT service providers to manage part or all of its information-related services helps a firm focus on its core business and provides better services to its clients, thus obtaining sustainable competitive advantage. This practice of focusing on the strategic aspect of outsourcing is referred to as strategic sourcing where the focus is capability sourcing, not procurement. Given the importance of the strategic outsourcing, however, to our knowledge, there is little empirical research on the relationship between the strategic outsourcing orientation and outsourcing performance. Moreover, there is little research on the factor that makes the strategic outsourcing effective. This study is designed to investigate the relationship between strategic IT outsourcing orientation and IT outsourcing performance and the process through which strategic IT outsourcing orientation influences outsourcing performance, Based on the framework of strategic orientation-performance and core competence based management, this study first identifies core competency orientation as a proper strategic orientation pertinent to IT outsourcing and IT outsourcing process management capability as the mediator to affect IT outsourcing performance. The proposed research model is then tested with a sample of 200 firms. The findings of this study may contribute to the literature in two ways. First, it draws on the strategic orientation - performance framework in developing its research model so that it can provide a new perspective to the well studied phenomena. This perspective allows practitioners and researchers to look at outsourcing from an angle that emphasizes the strategic decision making to outsource its IT functions. Second, by separating the concept of strategic orientation and outsourcing process management capability, this study provides practices with insight into how the strategic orientation can work effectively to achieve an expected result. In addition, the current study provides a basis for future studies that examine the factors affecting IT outsourcing performance with more controllable factors such as IT outsourcing process management capability rather than external hard-to-control factors including trust and relationship management. This study investigates the major factors that determine IT outsourcing success. Based on strategic orientation and core competency theories, we develop the proposed research model to investigate the relationship between core competency orientation and IT outsourcing performance and the mediating role of IT outsourcing process management capability on IT outsourcing performance. The model consists of two independent variables (core-competency-orientation and IT outsourcing process management capability), and two dependent variables (outsourced task complexity and IT outsourcing performance). Comprehensive data collection was conducted through an outsourcing association. The survey data were analyzed using a structural analysis method. IT outsourcing process management capability was found to mediate the effect of core competency orientation on both outsourced task complexity and IT outsourcing performance. Further analysis and findings are discussed.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.184-192
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• 2022

Valve internal leakage is caused by damage to the internal parts of the valve, resulting in accidents and shutdowns of the piping system. This study investigated the possibility of a real-time leak detection method using the acoustic emission (AE) signal generated from the piping system during the internal leakage of a butterfly valve. Datasets of raw time-domain AE signals were collected and postprocessed for each operation mode of the valve in a systematic manner to develop a data-driven model for the detection and classification of internal leakage, by applying machine learning algorithms. The aim of this study was to determine whether it is possible to treat leak detection as a classification problem by applying two classification algorithms: support vector machine (SVM) and convolutional neural network (CNN). The results showed different performances for the algorithms and datasets used. The SVM-based binary classification models, based on feature extraction of data, achieved an overall accuracy of 83% to 90%, while in the case of a multiple classification model, the accuracy was reduced to 66%. By contrast, the CNN-based classification model achieved an accuracy of 99.85%, which is superior to those of any other models based on the SVM algorithm. The results revealed that the SVM classification model requires effective feature extraction of the AE signals to improve the accuracy of multi-class classification. Moreover, the CNN-based classification can be a promising approach to detect both leakage and valve opening as long as the performance of the processor does not degrade.