• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.12
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• pp.2329-2334
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• 2006

In this paper, we proposed a method complementing failure of combining DNA fragments, defect of conventional contig assembly programs. In the proposed method, very long DNA sequence data are made into a prototype of fragment of about 700 bases that can be analyzed by automatic sequence analyzer at one time, and then matching ratio is calculated by comparing a standard prototype with 3 fragmented clones of about 700 bases generated by the PCR method. In this process, the time for calculation of matching ratio is reduced by Compute Agreement algorithm. Two candidates of combined fragments of every prototype are extracted by the degree of overlapping of calculated fragment pairs, and then degree of combination is decided using a fuzzy reasoning method that utilizes the matching ratios of each extracted fragment, and A, C, G, T membership degrees of each DNA sequence, and previous frequencies of each A, C, G, T. In this paper. DNA sequence combination is completed by the iteration of the process to combine decided optimal test fragments until no fragment remains. For the experiments, fragments or about 700 bases were generated from each sequence of 10,000 bases and 100,000 bases extracted from 'PCC6803', complete protein genome. From the experiments by applying random notations on these fragments, we could see that the proposed method was faster than FAP program, and combination failure, defect of conventional contig assembly programs, did not occur.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.273-282
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• 2016

There has been growing social interest recently in the movement rights of people with reduced mobility. However, it simply eliminates the temporary inconvenience of walking of people with reduced mobility because it focuses only on supply of institutional facilities. Therefore, we look forward to improving movement welfare by proposing an optimized path finding algorithm for people with reduced mobility that takes into consideration physical elements affecting their movement, such as slope, steps etc. We selected Walking barrier factor by analyzing previous studies and calculated the relative importance of Walking barrier factors using an Analytic Hierarchy Process(AHP). Next, through the fuzzy system, the Walking disturbance level of link, which integrates the weights of Walking barrier factors and the attributes of each link, is derived. Then, Walking path cost that takes into consideration the ‘length’ factors is calculated and an optimized path for people with reduced mobility is searched using Dijkstra’s Algorithm. Nineteen different paths were searched and we confirmed that the derived paths are meaningful in terms of improving the mobility of people with reduced mobility by conducting a field test. We look forward to improving movement welfare by providing a navigation service using the path finding algorithm proposed in this study.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.5
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• pp.466-473
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• 2020

A marine air drone is a new device that can be used to respond to and prevent marine casualties. Determining the districts where marine air drones can be deployed helps the government decision makers identify efficient policy. The aim of this study is to develop a model using the fuzzy-analytic hierarchy process (F-AHP) and additive ratio assessment (ARAS) method to evaluate appropriate districts for deploying marine air drones. To verify the applicability of the proposed model, a case study was performed with respect to the Korea coast guard (KCG) districts. Since the deployed marine air drones are characterized by a high degree of overlap between the evaluation attributes. the F-AHP is used to determine the weights of identified criteria. The results of this study, show that missing people from the shore was the most important criterion for deployment of the drone. For ranking the local districts of the KCG, the ARAS is applied in the case study with the single goal of 50% reduction in marine casualties. Consequently, the highest priority district was identified as Mokpo, followed by Incheon, Seogwipo, Taean, Wando, Yeosu, Pohang, Tongyeong, Gunsan, Bolyeong, Jeju, Buan, Donghae, Sokcho, Ulsan, Uljin, Busan, Changwon, and Pyeongtaeg.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.218-225
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• 2020

This study analyzed the priorities of the cross-compliance items of public-benefit direct payment using an Analytic Hierarchy Process and Fuzzy Decision Making Analysis. The valuation criteria are policy efficiency, farm acceptability, and feasibility, and the valuation targets are the basic and additional cross-compliance items. The survey was performed by targeting 50 experts from each class, and conducted for about a month starting from the beginning of July 2019. The results show that the weight of the valuation criteria is higher in the order of farm acceptability, feasibility, and policy efficiency. Compliance with PLS standards, compliance with disposal standards of waste vinyl and pesticides, soil testing, compliance with toxic substance standards, education, etc. are comparatively evaluated to be higher cross-compliance items in basic cross-compliance. Disposing of an abandoned well, jointly collecting and disposing of agricultural by-products, common area care and cleaning, maintenance of empty houses and poor facilities, growing green manure crops during the fallow period, etc. are comparatively evaluated to be higher cross-compliance items for the additional cross-compliance. The results of this study are expected to contribute to the government's policy related to the cross-compliance of public-benefit direct payment.

• Korean Journal of Construction Engineering and Management
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• v.14 no.4
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• pp.140-151
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• 2013

In 2011 and 2012, Korean construction firms awarded around $ 64.5. Billion each year from the overseas market in 2011. This contract value accounted for overwhelming portion of total overseas construction contract values, and this growth is expected to continue for the next decade. However, contract scopes awarded to the Korean construction firms mainly involve detailed design and construction phases due to their competitiveness for the construction techniques. In other words, front-end-engineering-design and construction project management are not considered part of core business due to the lack of project management skills and experience. The researchers focused on development of construction sequence model required to improve construction planning and scheduling skills for the Korean construction firms. The model identifies critical work items and the sequence throughout project execution process. In addition, the researchers developed a risk evaluation method by applying fuzzy theory to the critical construction activities for the industrial plant construction projects. Developed methodology will help project practitioners to develop project schedule in a timely and effe ctive manner and evaluate project risks associated with scheduling process for the industrial plant construction projects.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2773-2784
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• 2023

It is essential to evaluate the blasting-enhanced permeability (BEP) feasibility of a low-permeability sandstone-type uranium deposit. In this work, the mineral composition, reservoir physical properties and rock mechanical properties of samples from sandstone-type uranium deposits were first measured. Then, the reformability evaluation method was established by the analytic hierarchy process-entropy weight method (AHP-EWM) and the fuzzy mathematics method. Finally, evaluation results were verified by the split Hopkinson Pressure Bar (SHPB) experiment and permeability test. Results show that medium sandstone, argillaceous sandstone and siltstone exhibit excellent reformability, followed by coarse sandstone and fine sandstone, while the reformability of sandy mudstone is poor and is not able to accept BEP reservoir stimulation. The permeability improvement and the distribution of damage fractures before and after the SHPB experiment confirm the correctness of evaluation results. This research provides a reformability evaluation method for the BEP of the low-permeability sandstone-type uranium deposit, which contributes to the selection of the appropriate regional and stratigraphic horizon of the BEP and the enhanced ISL of the low-permeability sandstone-type uranium deposit.

• Tunnel and Underground Space
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• v.18 no.6
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• pp.465-479
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• 2008

For the quantitative identification of rock behavior in shallow tunnels, we recommend using the rock behavior index (RBI) by the analytic hierarchy process (AHP) and the Rock Engineering Systems (RES). AHP and RES can aid engineers in effectively determining complex and un-structured rock behavior utilizing a structured pair-wise comparison matrix and an interaction matrix, respectively. Rock behavior types are categorized as rock fall, cave-in, and plastic deformation. Seven parameters influencing rock behavior for shallow depth rock tunnel are determined: uniaxial compressive strength, rock quality designation (RQD), joint surface condition, stress, pound water, earthquake, and tunnel span. They are classified into rock mass intrinsic, rock mass extrinsic, and design parameters. An advantage of this procedure is its ability to obtain each parameter's weight. We applied the proposed method to the basic design of Seoul Metro Line O and quantified the rock behavior into RBI on rock fall, cave-in, and plastic deformation. The study results demonstrate that AHP and RES can give engineers quantitative information on rock behavior.

• Journal of Biosystems Engineering
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• v.19 no.2
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• pp.124-137
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• 1994

Visual features of a mushroom(Lentinus Edodes, L.) are critical in grading and sorting as most agricultural products are. Because of its complex and various visual features, grading and sorting of mushrooms have been done manually by the human expert. To realize the automatic handling and grading of mushrooms in real time, the computer vision system should be utilized and the efficient and robust processing of the camera captured visual information be provided. Since visual features of a mushroom are distributed over the front and back sides, recognizing sides and states of the stalk including the stalk orientation from the captured image is a prime process in the automatic task processing. In this paper, the efficient and robust recognition process identifying the front and back side and the state of the stalk was developed and its performance was compared with other recognition trials. First, recognition was tried based on the rule set up with some experimental heuristics using the quantitative features such as geometry and texture extracted from the segmented mushroom image. And the neural net based learning recognition was done without extracting quantitative features. For network inputs the segmented binary image obtained from the combined type automatic thresholding was tested first. And then the gray valued raw camera image was directly utilized. The state of the stalk seriously affects the measured size of the mushroom cap. When its effect is serious, the stalk should be excluded in mushroom cap sizing. In this paper, the stalk removal process followed by the boundary regeneration of the cap image was also presented. The neural net based gray valued raw image processing showed the successful results for our recognition task. The developed technology through this research may open the new way of the quality inspection and sorting especially for the agricultural products whose visual features are fuzzy and not uniquely defined.