This research was conducted to examine the antecedents of perceived service quality (PSQ) factors in Airbnb by using Big Data and Artificial Intelligence. The findings include that the SERVQUAL model requires adjustment in this context, and it is well-enhanced by cognitive and attitudinal factors, including intimacy, authenticity, privacy, and security.

This study utilized data to classify and characterize the body types of plus-size adult men aged in their 30s and 40s. Diversity is an important factor in the era of inclusive design, and discussion about size diversity to include the plus size should be accommodated. Data from 493 adult men classified as obese (with a World Health Organization criterion ≥25 BMI) were used for the analysis. The results of the study are as follows. Six independent factors were extracted using factor analysis for cluster analysis, which were then classified into five types. Type 1 (29.01%) was identified as body type I with the smallest degree of obesity. Type 2 (15.4%) was identified as body type Y with wide shoulders and a thin waist. Type 3 (14.2%) was the largest body volume (body type O), while the fourth (19.27%) identified as body type H has a large height and upper body. Lastly, type 5 (22.11%) has a long lower body and a slim abdomen, referred to as body type X. This study presents a basis for the development of various clothing sizes utilizing the body shape characteristics of plus-size men in their 30s and 40s. Follow-up research is needed to develop patterns for plus size men and to design various products.

PURPOSES : Despite the availability of larger traffic data and more advanced data collection methods, the problem of missing data is yet to be solved. Imputing missing data to ensure data quality and reliability of statistics has always been challenging. Missing data are imputed via several existing methods, such as autoregressive integrated moving average, exponential smoothing, and interpolation. However, these methods are complicated and results in significant errors. METHODS : A deep-learning method was applied in this study to impute traffic volume data of the South Korean national highway. Traffic data were trained using the long short-term memory method, which is a suitable deep-learning method for time series analysis. RESULTS : Three cases were proposed to estimate the traffic volume. In the first case, which represented the general conditions, the mean absolute percentage error (MAPE) was 12.7%. The second estimation case, which was based on the opposite traffic flow, exhibited a MAPE of 17%~18%. The third case, which was estimated using adjacent-section data, had a MAPE of 18.2%. CONCLUSIONS : Deep learning may be a suitable alternative data imputation method based on the limited site and data. However, its application depends on the specific situation. Furthermore, deep-learning models can be improved using an ensemble method, batch-size, or through model-structure optimization.

염분은 해양의 밀도를 결정하는 중요한 변수이자 전지구 물의 순환을 나타내는 주요 인자 중 하나이다. 해상 염분 관측은 선박을 이용한 현장조사, Argo 플로트, 부이를 통한 조사가 주로 수행되어 왔다. 2009년 염분관측 인공위 성이 발사한 이래로, 위성 염분자료를 이용하여 전 지구 해역에서 표층 염분 관측이 가능해졌다. 그러나 위성 염분자료는 다양한 오차를 포함하기 때문에 연구 자료로 활용하기에 앞서 정확도 검증과정이 필요하다. 따라서 본 연구에서는 2015년 4월부터 2020년 8월까지 Soil Moisture Active Passive (SMAP) 위성 염분자료와 이어도 해양과학기지에서 제공하는 실측 염분자료 간의 정확도 및 오차특성을 비교 분석하였다. 총 314개의 일치점을 생산하였으며, 염분의 평균제 곱근오차 및 평균편차는 각각 1.79, 0.91 psu로 제시되었다. 전반적으로 위성 염분이 실측 염분보다 과대추정 되는 것으로 나타났다. 위성 염분의 오차는 계절, 표층 수온, 풍속과 같은 다양한 해양 환경적 요인에 의존성을 보였다. 여름철 위성 염분과 실측 염분의 차이는 0.18 psu 이하로 저수온보다는 고수온에서 위성 염분의 정확도가 증가하였다. 이는 센서의 민감도에 따른 결과였다. 마찬가지로 5 m s−1 이상 풍속 조건에서 오차가 줄어들었다. 본 연구결과는 연안에서 위성 염분자료를 활용할 경우에는 특정한 연구 목적에 적합한지 확인하여 제한적으로 사용하여야 함을 제시한다.

본 연구에서는 2016-2017년 봄철(3-5월) 동안 보성 지역에서의 해풍 발생 시 연직 기상 특성을 분석하기 위해, 해풍 발생에 대한 선정 기준을 마련하였다. 이를 위해 지상에서 측정된 강수량, 운량, 풍향과 지상과 해상 기온의 차이, 1km 고도에서의 윈드프로파일러 및 수치모델 자료를 이용한 풍속 값이 사용되었다. 선정 기준에 따라 보성지역에서의 해풍일을 분류하였고, 해풍 발생 시간 및 고도와 풍속의 크기 분석을 통해 해풍의 시공간적 특성을 파악하였다. 해풍의 발생일은 총 183일 중 23일(12%)로서, 보성지역의 경우 봄철 10일 중 최소 1.2일은 해풍이 나타났다. 해풍은 1200 LST부터 1800 LST로 낮 시간에 지상에서부터 700 m 고도까지 주로 발생하였다. 또한, 최대 풍속은 평균 4.9 m s−1로 1600 LST에 40 m 고도에서 나타나, 선행연구보다 비교적 낮은 값을 보였다. 이는 해안지형이 복잡하여 지형 효과에 따른 풍속 감소로 인한 것으로 보인다.

본 연구에서는 태백산국립공원 주요 탐방로 입구에 설치된 탐방객 자동 계수기 데이터를 이용하여 탐방로별 일간 탐방객수에 영향을 미치는 요인을 분석하고, 이를 바탕으로 탐방로를 유형화하였다. 일일 탐방객수를 종속변수로 다중회귀분석 실시한 결과, 개천절이나 눈축제 등 행사는 모든 탐방로의 탐방객수에 영향을 미쳐, 태백산국립공원의 일일 탐방객수를 결정하는 가장 큰 요인인 것으로 분석되었다. 3일 이상 휴일이 연속되는 연휴와 일반 공휴일도 대부분의 탐방로의 일일 탐방객수에 영향을 미쳤다. 강수량은 비산행 목적의 탐방객이 많은 탐방로의 탐방객수에는 부(-)의 영향을 미쳤으나, 산행 목적의 탐방객이 많은 탐방로의 탐방객수에는 유의미한 영향을 미치지 않아, 산행 목적 탐방객들은 날씨가 궂더라도 산행을 강행하는 것으로 나타났다. 기온은 산행 목적의 탐방객이 많은 탐방로의 탐방객수에는 정(+)의 영향을 미쳤으나, 눈축제가 열리는 당골광장 인근의 탐방로의 탐방객수에는 부(-)의 영향을 미쳐, 눈축제의 영향권인지 여부가 탐방로 관리에 결정적 요인이었다. K-mean clustering을 이용하여 18개 탐방로를 유형 분류한 결과, 태백산국립공원의 탐방로는 눈축제에 영향을 받는 유형(유형 1)과, 가까운 거리에 볼거리가 많아 비산행 탐방객이 많은 유형(유형 2), 그리고 산행을 목적으로 온 탐방객들이 대부분인 유형(유형 3)의 3개 유형을 분류할 수 있었다. 탐방로 유형별 탐방객 행태와 불법 행위 유형이 다르므로, 유형별 특성에 맞춰 탐방로 관리방안을 마련하여야 할 것이다.

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.

Game development costs a lot of money. Thus, in terms of cost-saving, game companies produce prototypes and undergo several tests and modifications during the development period. In this paper, we proposed a brainwave signal analysis system and linked it with the game to measure the player's emotion through brainwave analysis experiment and tried to solve these problems. The brainwave signal analysis system proposed in this paper is capable of various applications according to various development situations, such as the progress of the game, events, etc. in obtaining simple figures over time by linking games, and collecting the tester's responses according to development intentions, so there will have to be continuous additional research.

The purpose of this study was to analyze six English as a Foreign Language (EFL) learners’ trajectories of discriminating near-synonyms in a data-driven learning task. Since the learners find it considerably difficult to learn subtle meaning differences of near-synonyms, corpuscorpuscorpuscorpuscorpuscorpus-based data-driven learning may provide an opportunity for them to tackle their difficulties. The study materials guided the learners to identify the differences between the four pairs of near-synonyms, categorize the concordance lines based on their findings, and generalize the findings. The six participants had notably different trajectories of discriminating near-synonyms. The qualitative analysis of the trajectories showed a tendency that the intermediate learners focused on the meanings and found the correct answer without knowing the core meaning, and the advanced learners moved further to attend to structural differences and sometimes tested their previous knowledge on the concordance data. This study implies the need for careful guidance, collaborative group works, and strategy teaching in data-driven learning tasks.

This study analyzed the distribution characteristics of invasive alien plants on the islands of the Korean Peninsula. Ten species, Rumex acetosella, Sicyos angulatus, Solanum carolinense, Ambrosia artemisiaefolia var. elatior, Ambrosia trifida, Aster pilosus, Eupatorium rugosum, Hypochaeris radicata, Lactuca scariola, and Paspalum distichum were present on 68 islands. These ecosystem-disturbing invasive alien plants appeared extensively on the islands of Gyeonggi province and Jeollanam province. The proportion of the plants on the inhabited islands (41 places, 2.15 species on average) was higher than that on the uninhabited islands (27 places, 1.07 species on average). This means that the distribution of invasive alien plants was closely related to human activity. The distribution of Ambrosia artemisiaefolia var. elatior (32 islands) and Rumex acetosella (31 islands) was the widest, and there were distinct distribution differences according to species. In the island area, the physical environment is poor compared to the mainland, and the native space is limited. Therefore, when invasive alien species enter and settle on the island, the native island plants can be damaged more than those on the mainland. In this regard, the discussion of the distribution of invasive alien plants in the island region can contribute to the conservation of biodiversity in the region.