• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.185-205
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• 2023

As the tourism industry recovers post the COVID-19 pandemic, an increasing number of tourists are utilizing various platforms to leave reviews. However, amidst the vast amount of data, finding useful information remains challenging, often leading to time and cost inefficiencies in selecting travel destinations. Despite ongoing research, there are limitations due to the absence of ratings or the presence of different rating formats across platforms. Moreover, inconsistencies between ratings and the content of reviews pose challenges in developing recommendation models. To address these issues, this study utilized 7,104 reviews of tourist spots in Jeju Island to develop a specialized satisfaction index for Jeju tourist attractions and employed this index to construct a 'Rating Prediction Model.' To validate the model's performance, we predicted the ratings of 700 experimental data points using both the developed model and an LSTM approach. The proposed model demonstrated superior performance with a weighted accuracy of 73.87%, which is approximately 4.67% higher than that of the LSTM. The results of this study are expected to resolve the discrepancies between ratings and review contents, standardize ratings in reviews without ratings or in various formats, and provide reliable rating indicators applicable across all areas of travel in different domains.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.6
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• pp.499-506
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• 2019

NDSM (Normalized Digital Surface Model) is key information for the detailed analysis of remote sensing data. Although NDSM can be simply obtained by subtracting a DTM (Digital Terrain Model) from a DSM (Digital Surface Model), in case of UAV (Unmanned Aerial Vehicle) data, it is difficult to get an accurate DTM due to high resolution characteristics of UAV data containing a large number of complex objects on the ground such as vegetation and urban structures. In this study, RGB-based UAV vegetation index, ExG (Excess Green) was used to extract initial seed points having low ExG values for region growing such that a DTM can be generated cost-effectively based on high resolution UAV data. For this process, local window analysis was applied to resolve the problem of erroneous seed point extraction from local low ExG points. Using the DSM values of seed points, region growing was applied to merge neighboring terrain pixels. Slope criteria were adopted for the region growing process and the seed points were determined as terrain points in case the size of segments is larger than 0.25 ㎡. Various slope criteria were tested to derive the optimized value for UAV data-based NDSM generation. Finally, the extracted terrain points were evaluated and interpolation was performed using the terrain points to generate an NDSM. The proposed method was applied to agricultural area in order to extract the above ground heights of crops and check feasibility of agricultural monitoring.

• Journal of Digital Convergence
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• v.19 no.6
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• pp.113-132
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• 2021

This study is a new evaluation using the Arrhenius equation, which is known as the chemical reaction rate estimation equation, to evaluate the intrinsic and extrinsic value elements of patents as a model. The performance of the evaluation model was superior to the SVM, Logistic reg. and ANN models that were used as patent evaluation models in prior studies. In addition, there was a strong correlation between the predicted lifespan of the patent and the actual lifespan of the patent. These evaluation models may be used for evaluation purposes only, or if an evaluation is required, including a commercialization entity or technical characteristics.

• Journal of Korea Port Economic Association
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• v.29 no.3
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• pp.159-174
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• 2013

This paper mainly deals with the appropriation of ship voyage allocation, using a heuristic regression model, in order to reduce total costs incurred in port, yard and at sea under the specific port condition. Because of different behavior of costs incurred in port, yard and at sea, an effort to minimize these costs by adjusting the number of voyages for three ship classes(50,000, 100,000, and 150,000-ton) should be made. For instance, if the port managers attempt to reduce the sea transport cost by increasing the annual allocated number of ship voyages classed 150,000-ton for economies of scale, they have no choice but to suffer a significant increase in queueing cost due to port congestion. To put it differently, there are trade-off relationships among the costs incurred in port, yard, and at sea. We utilized a computer simulation result to perform a couple of regression analyses in order to figure out the appropriate range of allocated number of voyages of each ship class using a heuristic approach. The detailed analytical results will be shown at the main paper. We also suggested a net present value(NPV) model to make a proper investment decision for an additional berth of 200,000-ton class that alleviates port congestion and reduces transport cost incurred both in port and at sea.

• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.179-184
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• 2020

본 연구는 확장된 합리적 행동이론(ETRA)을 이용하여 주식투자 시 자본시장심리지수를 기반으로 한 어플리케이션의 선택행동에 영향을 끼치는 요인들과 투자자의 휴리스틱과의 관계를 알아보는데 있다. 연구자는 개별 투자자의 휴리스틱이 선택행동에 영향을 미칠 것으로 추정하고 대표성 휴리스틱, 가용성 휴리스틱, 감정 휴리스틱을 측정하여 선택행동에 영향을 미치는 매개변수로 분석을 하였다. 연구모델의 경로계수 분석결과는 다음과 같다. 첫째, 독립변수인 투자기회확장 그리고 매개변수인 휴리스틱 중 대표성 휴리스틱이 행동의도에 영향을 미치는 것으로 나타났다. 둘째, 행동의도가 종속변수인 선택행동에 영향을 미치고 매개변수인 가용성 휴리스틱이 선택행동에 영향을 미치는 것으로 나타났다. 연구모형에서 대표성 휴리스틱에 영향을 주는 독립변수는 혁신적 성향, 투자기회확장, 사용비용, 그리고 인지된 효익이며 반면에 가용성 휴리스틱에 영향을 주는 독립변수는 혁신적 성향과 투자기회확장으로 밝혀졌다. 매개효과 검증결과에 의하면 서비스다양성은 선택행동에 영향을 미치는데 휴리스틱의 매개효과가 없고 직접효과만 있는 것으로 밝혀졌다. 반면에 투자기회확장은 선택행동에 미치는 직접효과는 통계적으로 유의하지 않고 매개변수 휴리스틱의 간접효과 값이 0.217이고 통계적으로 유의하여 매개효과가 있는 것으로 밝혀졌다. 휴리스틱의 매개효과를 개별적으로 확인한 결과 첫째, 대표성 휴리스틱은 매개효과를 통한 간접효과가 없는 것으로 확인되었다. 둘째, 가용성 휴리스틱은 매개효과의 크기가 0.1360이고 경로계수가 통계적으로 유의하게 나타나 매개효과를 통한 간접효과가 있다는 것을 확인하였다. 따라서 독립변수 투자기회확장은 시장 심리지수를 기반으로 한 어플리케이션에 대한 선택행동에 영향을 미치는데 직접적으로 영향을 미치지 않고 투자자의 가용성 휴리스틱이 매개가 되어 간접적으로 선택행동에 영향을 나타내는 것을 실증적으로 확인하였다.

• Journal of Korean Society of Environmental Engineers
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• v.32 no.1
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• pp.97-104
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• 2010

At present, the biological nutrient removal (BNR) process for removal of nitrogen and phosphorus is being constructing to keep pace with the reinforced standard of effluent quality and the traditional activated sludge process of preexistence is being promoting to retrofit. At the most case of retrofitting, processes are subjected to be under consideration as alternative BNR process for retrofitting. However, process evaluation methods are restricted to compare only treatment efficiency. Therefore, when BNR process apply, process evaluation was needed various method for treatment efficiency as well as sludge production and aeration cost, and all. In this study, the evaluation method of alternative process was suggested for the case for retrofitting S wastewater treatment plant which has been operated the standard activated sludge process. Three BNR processes for evaluation of proper alternatative process were selected and evaluated with suggested method. The selected $A^2$/O, VIP and DNR processes were evaluated using the mathematical model which is time and cost effective as well as gathered objective evaluation criteria. The evaluation between 5 individual criteria was possible including sludge production and energy efficiency as well as treatment performance. The objective final decision method for selection of optimal process was established through the fuzzy inference.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Information Systems Review
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• v.6 no.2
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• pp.195-208
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• 2004

In this paper we propose a new software project development management model incorporating quality management to schedule management. Though many efficient techniques such as code review and inspection are used to remove defects, the effect of defect removal time on project schedule hasn't been studied much. However, poor quality management has an important effect upon overall schedule and sometimes software projects fails due to it. Thus, quality management and schedule management should be considered together and we need to reflect the time to maintain software quality into the schedule management. For the proposed model we introduced "Quality Value" representing the needed time to remove software defects. We assume PSP/TSP to gather the needed data for quality value. The proposed model can be used to predict the effect of software defects on schedule in advance and to prevent schedule lag.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1059-1062
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• 2021

투자에 대한 관심 증가에 따라 적은 비용과 시간으로 객관적인 정보 제공의 필요성 증가와 함께 인공지능 기술을 활용한 로보어드바이저 서비스가 확대되었다. 또한, 최근 ETF 를 통한 안정적인 투자에 대한 선호도가 증가함에 따라 ETF 중심의 AI 로보어드바이저 추천 서비스가 필요할 것으로 보인다. 하지만, 기존의 투자 어플리케이션에서는 뉴스 기반의 감성적인 요인이 반영되지 않은 추천 방식으로 주가에 영향을 미치는 다양한 요인들을 고려하지 못하는 문제점이 있다. 이에 본 연구에서는 뉴스의 감성분석을 통한 감성지수를 기반으로 새로운 주가 예측 모델을 제안하고, 사용자의 투자 성향 분석을 통한 맞춤 추천 서비스를 통해 개인화된 ETF 서비스를 제공한다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.04a
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• pp.562-567
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• 2003

최근 고해상도 위성영상정보의 민간 사용이 활발해지면서 기존에 널리 알려진 위성영상정보 응용분야 뿐만 아니라 새로운 응용 분야에 대한 적용 가능성이 국제적으로 여러 가지 방향으로 모색되고 있다. 본 연구는 이러한 추세를 반영하여 교통 또는 도시교통 환경분야에서의 위성영상정보의 활용 가능성 및 기존 방법론과의 연계를 분석하고, 시험적으로 프로토타입 프로그램을 소개하고자 한다. 일반적으로 교통문제에서의 접근성 분석은 일종의 중력모델로 설명이 가능하며, 교통계획 수립시에 대안 도로 계획선정이나 대중교통 노선결정시에 많이 이용되고 있다. 접근성 분석에 대한 개념은 비교적 간단하여, 교통분석대상구역의 임의 지역에서 유인 요인과 거리를 변수로 하여 적용 목적에 부합되는 대상 지점까지의 정량적 지수정보를 얻도록 하여 몇 가지 결과로부터 출발지점에서 목적지점 또는 대상 지점까지의 손익비용산출에 대한 정보를 얻는 방식이다. 최근에 GIS를 통하여 구축된 교통 데이터베이스정보와 공간분석 기법을 통하여 수행하는 경우가 많으나 현재까지 위성영상정보가 이용된 경우는 거의 보고된 바가 없다. 따라서 본 연구에서는 정사위성 실제 교통시설물이나 교통 대상 객체의 육안 식별이 가능한 고 해상도 위성영상정보는 이러한 출발지-목적지 선정에 적용될 수 있다는 점에 착안하여 기존에 교통분야에서 개발된 몇 가지의 교통 접근성 산출 알고리듬에 위성영상정보가 연계되어 적용될 수 있는 가능성을 검토하였다.