정성원 교수

The evaluation of building energy consumption is heavily based on building characteristics and thus often deviates from the true consumption. Consequently, user-based estimation of building energy consumption is necessary because the actual consumption is greatly affected by user characteristics and activities. This work aims to examine the variation in energy consumption as a function of user activities within the same building, and to employ an artificial neural network (ANN) to predict user-b

There has been a great deal of research on the relationship between the built environment and walking activity, but many studies have produced inconclusive or conflicting results. In this research we aim to enrich the association of the built environment with walking activity by examining its impact in Seoul, a Korean megacity characterized by high-density development and a well-equipped public transportation system. The results show that neighborhoods with a relatively higher land-use mix and r

When researching the energy consumption of residential buildings, it is becoming increasingly important to consider how residents use energy. With the advancement of computing power and data analysis techniques, it is now possible to analyze user information using big data techniques. Here, we endeavored to integrate user information with the physical characteristics of residential buildings to analyze how these elements impact energy consumption. Regression analysis was conducted to accurately

Previous crime prediction research focusing on regional characteristics is lacking in terms of the examination of physical characteristics of individual crime scenes. This study, therefore, presents a street crime prediction model by analysing streetscape features within an actual field of vision for a low-rise housing area in South Korea, which serves as a gauge for potential offenders to carry out crime. First, we performed logistic regression to analyse the correlation between street crime op

Identifying differential features between conditions is a popular approach to understanding molecular features and their mechanisms underlying a biological process of particular interest. Although many tests for identifying differential expression of gene or gene sets have been proposed, there was limited success in developing methods for differential interactions of genes between conditions because of its computational complexity. We present a method for Evaluation of Dependency DifferentialitY

Residential energy consumption accounts for the majority of building energy consumption. Physical factors and technological developments to address this problem have been researched continuously. However, physical improvements have limitations, and there is a paradigm shift towards energy research based on occupant behavior. Furthermore, the rapid increase in the number of single-person households around the world is decreasing residential energy efficiency, which is an urgent problem that needs

BACKGROUND: Clinical decision support (CDS) can improve health care with respect to the quality of care, patient safety, efficiency, and effectiveness. Establishing a CDS system in a health care setting remains a challenge. A few hospitals have used self-developed in-house CDS systems or commercial CDS solutions. Since these in-house CDS systems tend to be tightly coupled with a specific electronic health record system, the functionality and knowledge base are not easily shareable. A shared inte

The treatment has been improved on the accurate reduction of blow-out fracture for many decades. But still, it has been limited to reduce completely when surgeons are approaching by conventional technique. The authors analyzed the postoperative results using computed tomography (CT) scans after conventional open reduction of isolated medial wall fracture. Thirty-seven patients with isolated medial wall fracture were reviewed. All patients underwent preoperative, immediate, and postoperative CT s

Nasal bone fracture is the most common facial fracture; however, surgery does not guarantee reduction and complications, such as undercorrection, overcorrection, and deviation, may occur. By analyzing findings of computed tomography (CT) immediately and at 3 months postoperatively, we evaluated the accuracy of reduction and long-term changes to the nasal bone.Patients with pure nasal bone fracture were evaluated from January 1, 2010 to December 31, 2011. First, we categorized fracture types acco

There is a lack of quantitative data regarding how offenders make decisions about committing a crime or how situational factors influence such decisions. Detailed crime data on decision-making among criminals are required to improve the accuracy of research. Demonstrating a new methodology for assessing the factors impacting criminal decision-making among street robbery offenders, this study identifies visual data that influence criminal decision-making, and verifies the significance of the meas

Previous studies have shown that when a crime occurs, the risk of crime in adjacent areas increases. To reflect this, previous grid-based crime prediction studies combined all the cells surrounding the event location to be predicted for use in model training. However, the actual land is continuous rather than a set of independent cells as in a geographic information system. Because the patterns that occur according to the detailed method of crime vary, it is necessary to reflect the spatial char

Crime prediction research using AI has been actively conducted to predict potential crimes—generally, crime locations or time series flows. It is possible to predict these potential crimes in detail if crime characteristics, such as detailed techniques, targets, and environmental factors affecting the crime’s occurrence, are considered simultaneously. Therefore, this study aims to categorize theft by performing k-modes clustering using crime-related characteristics as variables and to propose an