• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.237-258
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• 2022

As the global market environment changes, the domestic ICT industry has a growing influence on the world economy. This industry is regarded as an important driving force in the national economy from a technological and social point of view. In particular, small and medium-sized enterprises (SMEs) in the ICT industry are regarded as essential actors of domestic economic development in terms of company diversity, technology development and job creation. However, since it is small compared to large-sized enterprises, it is difficult for SMEs to survive with a differentiated strategy in an incomplete and rapidly changing environment. Therefore, SMEs must make a lot of efforts to improve their own capabilities, and the government needs to provide the desirable help suitable for corporate internal resources so that they can continue to be competitive. This study classifies the types of ICT SMEs participating in government support programs, and analyzes the relationship between resources and performance creation of each type. The data from the "ICT Small and Medium Enterprises Survey" conducted annually by the Ministry of Science and ICT was used. In the first stage, ICT SMEs were clustered based on common factors according to their experiences with government support programs. Three clusters were meaningfully classified, and each cluster was named "active participation type," "initial support type," and "soloist type." As a second step, this study compared the characteristics of each cluster through profiling analysis for each cluster. The third step carried out in this study was to find out the mechanism of R&D performance creation for each cluster through regression analysis. Different factors affected performance creation for each cluster, and the magnitude of the influence was also different. Specifically, for "active participation type", "current manpower", "technology competitiveness", and "R&D investment in the previous year" were found to be important factors in creating R&D performance. "Initial support type" was identified as "whether or not a dedicated R&D organization exists", "R&D investment amount in the previous year", "Ratio of sales to large companies", and "Ratio of vendors supplied to large companies" contributed to the performance. Lastly, in the case of "soloist type", "current workforce" and "future recruitment plan", "technological competitiveness", "R&D investment", "large company sales ratio", and "overseas sales ratio" showed a significant relationship with the performance. This study has practical implications of showing what strategy should be established when supporting SMEs in the future according to the government's participation in the startup program and providing a guide on what kind of support should be provided.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.183-190
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• 2017

Recently the scale and area of greenhouse cultivation have been enlarged in Korea, and its importance in domestic agriculture is being increased. According to these situation, environment control systems are widely used in greenhouses. Even though development of greenhouse facilities and control devices, cultivation skill using them is in lower level more than european countries and Japan. In this study, we propose intelligent information system based on information-communication technology that supports environment control systems. Proposed system is able to support to maintain optimal environment for plant growth using data from environment control system, and also give useful knowledge for cultivation by active way. Furthermore, it estimates future status of plant growth, and suggest best strategy of environment control for current stage.

• Investigative Magnetic Resonance Imaging
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• v.22 no.4
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• pp.218-228
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• 2018

Purpose: The objective of this study is to determine the effect of physical changes on MR temperature imaging at 7.0T and to examine proton-resonance-frequency related changes of MR phase images and T1 related changes of MR magnitude images, which are obtained for MR thermometry at various magnetic field strengths. Materials and Methods: An MR-compatible capacitive-coupled radio-frequency hyperthermia system was implemented for heating a phantom and swine muscle tissue, which can be used for both 7.0T and 3.0T MRI. To determine the effect of flip angle correction on T1-based MR thermometry, proton resonance frequency, apparent T1, actual flip angle, and T1 images were obtained. For this purpose, three types of imaging sequences are used, namely, T1-weighted fast field echo with variable flip angle method, dual repetition time method, and variable flip angle method with radio-frequency field nonuniformity correction. Results: Signal-to-noise ratio of the proton resonance frequency shift-based temperature images obtained at 7.0T was five-fold higher than that at 3.0T. The T1 value increases with increasing temperature at both 3.0T and 7.0T. However, temperature measurement using apparent T1-based MR thermometry results in bias and error because B1 varies with temperature. After correcting for the effect of B1 changes, our experimental results confirmed that the calculated T1 increases with increasing temperature both at 3.0T and 7.0T. Conclusion: This study suggests that the temperature-induced flip angle variations need to be considered for accurate temperature measurements in T1-based MR thermometry.

• Information Systems Review
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• v.21 no.1
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• pp.135-152
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• 2019

Recently there are many development and support policies for start-up companies because of successful venture companies related to ICT services. However, as these policies have focused on the support for the initial stage of start-up, many start-up companies have difficulties to continuously grow up. The main reason for these difficulties is that they recognize start-up tasks as independent activities. However, many experts or related articles say that start-up tasks are composed of related processes from the initial stage to the stable stage of start-up firms. In this study, we models the start-up processes based on the survey collected by the start-up companies, and analyze the start-up process of ICT service companies with process mining techniques. Through process mining analysis, we can draw a sequential flow of tasks for start-ups and the characteristics of them. The analysis of start-up businessman, idea derivation, creating business model, business diversification processes are resulted as important processes, but marketing activity and managing investment funds are not. This result means that marketing activity and managing investment funds are activities that need ongoing attention. Moreover, we can find temporal and complementary tasks which could not be captured by independent individual-level activity analysis. Our process analysis results are expected to be used in simulation-based web-intelligent system to support start-up business, and more cumulated start-up business cases will be helpful to give more detailed individual-level personalization service. And our proposed process model and analyzing results can be used to solve many difficulties for start-up companies.

• Spatial Information Research
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• v.21 no.4
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• pp.25-34
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• 2013

The purpose of this study is to develop an efficient BIM-based FM(Facility Management) system architecture to integrate the heterogeneous solution data related to FM. The heterogeneous solution data can be an FM system, asset management system, or facility sensor database systems, as well as files created by a modeler. In this study, we define the consideration for the external heterogeneous data integration related to BIM-based FM and propose the methodology. To implement it, trends in related studies were reviewed and general use cases of BIM-based FM were derived to develop the architecture for the integration between BIM and the heterogeneous solution data. The component architecture was designed to implement the use cases, and the schema was developed for the prototype by using the proposed architecture.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.2-5
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• 2022

With the advent of deep learning and the rapid development of ICT (Information and Communication Technology), research using artificial intelligence is being actively conducted in various fields of society such as politics, economy, and culture and so on. Deep learning-based artificial intelligence technology is subdivided into various domains such as natural language processing, image processing, speech processing, and recommendation system. In particular, as the industry is advanced, the need for a recommendation system that analyzes market trends and individual characteristics and recommends them to consumers is increasingly required. In line with these technological developments, this paper extracts and classifies attribute information from structured or unstructured text and image big data through deep learning-based technology development of 'language processing intelligence' and 'image processing intelligence', and We propose an artificial intelligence-based 'customized fashion advisor' service integration system that analyzes trends and new materials, discovers 'market-consumer' insights through consumer taste analysis, and can recommend style, virtual fitting, and design support.

• Journal of Platform Technology
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• v.9 no.3
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• pp.78-83
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• 2021

The new industry drone research is increasing through convergence between 4th industrial revolution technology. In particular, the government indicates the D.N.A platform as a countermeasure of 4th industrial revolution. So, the research topics are remarkable which are using D.N.A platform. On the other hand, the drone for industrial and research has spatial factor based on sequential because, they performance scenario-based mission through control operation. When the drone flights as a control operation, they have necessity apply multi-dimensional methods to improve the security level. So, this study researched a scenario based drone platform to improve the security level. As a result, the space classified as a ground control system, drone, drone data server and designed the application method based on scenario security technology.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.194-199
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• 2019

Natural disasters destroy decades of human effort and investments, thereby placing new demands on society for reconstruction and rehabilitation. In most case, the natural phenomena triggering the disasters are beyond human control. In order to solve the problems that the information resources can not be shared among disaster management sectors and their work is hard to be coordinated in city, an idea of application of ubiquitous sense network and ICT technology to model the architecture of the disaster prevention system based on the analysis of characteristics of disasters. The proposed algorithm simulated that it is possible to locate the terminal by linking the direction angle and the estimated position that can be confirmed at the time of stopping, even if the movement direction of the terminal does not move in a certain direction with only a smaller number of mobile base stations. We also confirmed that the proposed algorithms analyzed through simulation are more efficient than existing algorithms.

• Journal of Advanced Navigation Technology
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• v.25 no.1
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• pp.96-101
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• 2021

This paper presents a machine learning model that predicts stroke risks in atrial fibrillation patients using public big data. As the training data, 68 independent variables including demographic, medical history, health examination were collected from the Korean National Health Insurance Service. To predict stroke incidence in patients with atrial fibrillation, we applied deep neural network. We firstly verify the performance of conventional statistical models (CHADS2, CHA2DS2-VASc). Then we compared proposed model with the statistical models for various hyperparameters. Accuracy and area under the receiver operating characteristic (AUROC) were mainly used as indicators for performance evaluation. As a result, the model using batch normalization showed the highest performance, which recorded better performance than the statistical model.

• Journal of Aerospace System Engineering
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• v.16 no.6
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• pp.106-113
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• 2022

The structural safety of the basic design model of the linear actuator for the individual blade pitch control of eVTOL personal aircraft was investigated. Stress analysis based on the finite element method was conducted, and the margin of safety was calculated to examine the structural safety under stall load conditions. Additionally, fatigue analysis was conducted to evaluate the fatigue life of the linear actuators under operating conditions. The load history with the blade pitch angle was calculated using multi-body dynamics analysis, and the static load analysis was used to obtain the stress distribution for the rated load. As a result, it was confirmed that the safety margins exceeded zero, and the fatigue lives of all linear actuator components exceeded 107 cycles, indicating a safe structural range.