• The Journal of the Korea Contents Association
• /
• v.5 no.3
• /
• pp.193-199
• /
• 2005

One of the important fields for heuristics algorithm is how to balance between Intensificationand Diversification. Ant Colony System(ACS) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem(TSP). In this paper, we propose Multi Colony Interaction Ant Model that achieves positive negative interaction through elite strategy divided by intensification strategy and diversification strategy to improve the performance of original ACS. And, we apply multi colony interaction ant model by this proposed elite strategy to TSP and compares with original ACS method for the performance.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.2
• /
• pp.277-287
• /
• 2013

It is important to detect the gene-gene interaction in GWAS (genome-wide association study). There have been many studies on detecting gene-gene interaction. The one is D-MDR (dummy multifoactor dimensionality reduction) method. The goal of this study is to evaluate the power of D-MDR for identifying gene-gene interaction by simulation. Also we applied the method on the identify interaction effects of single nucleotide polymorphisms (SNPs) responsible for economic traits in a Korean cattle population (real data).

• Bulletin of the Korean Chemical Society
• /
• v.34 no.8
• /
• pp.2466-2472
• /
• 2013

Human immunodeficiency virus type-1 (HIV-1) is a causative agent of Acquired immunodeficiency syndrome (AIDS), which has affected a large population of the world. Viral envelope glycoprotein (gp120) is an intrinsic protein for HIV-1 to enter into human host cells. Molecular docking guided molecular dynamics (MD) simulation was performed to explore the interaction mechanism of heterobiaryl derivative with gp120. MD simulation result of inhibitor-gp120 complex demonstrated stability. Our MD simulation results are consistent with most of the previous mutational and modeling studies. Inhibitor has an interaction with the CD4 binding region. Van der Waals interaction between inhibitor and Val255, Thr257, Asn425, Met426 and Trp427 were important. This preliminary MD model could be useful in exploiting heterobiaryl-gp120 interaction in greater detail, and will likely to shed lights for further utilization in the development of more potent inhibitors.

• Journal of the Korean Data and Information Science Society
• /
• v.23 no.3
• /
• pp.467-474
• /
• 2012

Human diseases and livestock economic traits are not typically the result of variation of a single genetic locus, but are rather the result of interplay between interactions among multiple genes and a variety of environmental exposures. We have used linear regression model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. Of course, we use 5 SNPs (single uncleotide polymorphism) which were studied recently by Oh et al. (2011). We apply the MDR (multifactor demensionality reduction) method on the identify major interaction effects of single nucleotide polymorphisms responsible for economic traits in a Korean cattle population.

• Genomics & Informatics
• /
• v.18 no.4
• /
• pp.38.1-38.9
• /
• 2020

Chronotype is an important moderator of psychiatric illnesses, which seems to be controlled in some part by genetic factors. Clock genes are the most relevant genes for chronotype. In addition to the roles of individual genes, gene-gene interactions of clock genes substantially contribute to chronotype. We investigated genetic associations and gene-gene interactions of the clock genes BHLHB2, CLOCK, CSNK1E, NR1D1, PER1, PER2, PER3, and TIMELESS for chronotype in 1,293 healthy Korean individuals. Regression analysis was conducted to find associations between single nucleotide polymorphism (SNP) and chronotype. For gene-gene interaction analyses, the quantitative multifactor dimensionality reduction (QMDR) method, a nonparametric model-free method for quantitative phenotypes, were performed. No individual SNP or haplotype showed a significant association with chronotype by both regression analysis and single-locus model of QMDR. QMDR analysis identified NR1D1 rs2314339 and TIMELESS rs4630333 as the best SNP pairs among two-locus interaction models associated with chronotype (cross-validation consistency [CVC] = 8/10, p = 0.041). For the three-locus interaction model, the SNP combination of NR1D1 rs2314339, TIMELESS rs4630333, and PER3 rs228669 showed the best results (CVC = 4/10, p < 0.001). However, because the mean differences between genotype combinations were minor, the clinical roles of clock gene interactions are unlikely to be critical.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.95-102
• /
• 2023

This study aims to empirically verify the moderating effect of population drop on the relationship between demographic changes and crime decline in local cities facing population decline in Korea. The study employs changes in the population of young adults, men, elderly, foreign residents, and population movement as factors of demographic changes, including types of the city as a control variable in the research model. The rate of change in population drop is used as a moderator variable and the rate of change in crime decline as a dependent variable. Data are collected from 155 cities with declining populations from 2010 to 2022 through KOSIS, the National Statistics Portal, and information disclosure requests. Data collected are analyzed using moderated regression analysis. In the first and second stages of the analysis, they show that changes in the population of young adults, population movement, foreign people, population drop, and the type of city affect the change in crime. Moderated regression analysis shows that only the interaction terms among changes in the population of young adults, changes in population movement, and changes in the population of foreigners and the population drop affects change in crime significantly.

• The Journal of the Korea Contents Association
• /
• v.19 no.11
• /
• pp.474-481
• /
• 2019

Korea entered the aged society in 2018 with the elderly population accounting for 14.4% of the total population, and it is expected to enter the super-aged society in 2026. In particular, it is predicted that by 2050, the elderly population will be 38% of the total population, making it one of the countries with the highest number of elderly people in the world. The increase in the elderly population is naturally leading to an increase in the number of traffic accidents among elderly drivers, in 2017, there were 26,713 elderly driver accidents over 65 years of age, with 848 people dying and 38,627 injured. Compared with 2011, the number of accidents and injuries has doubled and the number of deaths has increased 1.4 times. This study determined that the main factors of the increase in traffic accidents were the characteristics of elderly drivers, such as a decrease in visual/hearing ability, cognitive and information processing ability, and muscle strength. Therefore, it raised the necessity of autonomous vehicle(level 2) for elderly driver who can minimize the burden of driving and aimed to study the function of autonomous vehicle for elderly driver who is not familiar with new technology. Based on this, four functions of autonomous vehicles for elderly drivers were derived, such as providing clear information according to the road environment, considering physical characteristics of drivers, simplifying interface, and reinforcing in-vehicle safety devices.

• Journal of Service Research and Studies
• /
• v.10 no.2
• /
• pp.1-15
• /
• 2020

As big data become more important socially and economically in recent years, many problems have been derived from the indiscriminate application of big data. Big data are valuable because it can figure out the meaning of informative information hidden within the data. In particular, to predict customer behavior patterns and experiences, structured data that were extracted from Customer Relationship Management (CRM) or unstructured data that were extracted from Social Network Service(SNS) can be defined as a population to interpret the data, during which many errors can occur. However, those errors are usually overlooked. In addition to data analysis techniques, some data, which should be considered in the analysis, are not included in the population and thus do not show any meaningful patterns. Therefore, this study presents the measurement and interpretation of the data generated when the cause of error in the population setting is strong relationship and interaction between people or a person and an object. In other words, it will be shown that if the relationship and interaction are strong, it is important to include data collected from the perspective of user experience and ethnography in the population by comparing various cases of big data application, through which the meaning will be derived and the best direction will be suggested.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.26 no.4
• /
• pp.173-187
• /
• 2023

In an era of population decline, depopulated regions facing challenges in attracting inbound population migration must enhance urban vitality through the attraction of living populations. This study focuses on Busan, a city experiencing population decline, comparing the spatiotemporal distribution characteristics of registered residents and living populations in various administrative districts (Eup-Myeon-Dong) using mobile communication big data. Administrative districts are typified based on population change patterns, and regional characteristics are analyzed using indicators related to urban decline and vitality. Spatiotemporal distribution analysis reveals generally similar density patterns between registered residents and living populations; however, a distinctive feature is observed in the city center areas where the density of registered residents is low, while the density of living populations is high. Divergent trends in spatial patterns of change between registered residents and living populations show clusters of registered population decline in low-density areas and clusters of living population decline in high-density areas. Areas adjacent to declining living populations exhibit large clusters of population changes, indicating a spillover effect from high-density to neighboring areas. Typification results reveal that, even in areas with a decline in registered residents, there is active population influx due to commuting or visiting. These areas sustain an increase in the number of businesses, confirming the presence of industrial and economic growth. However, approximately 47% of administrative districts in Busan are experiencing a decline in both registered residents and living populations, indicating ongoing regional decline. Urgent measures are needed for enhancing urban vitality. The study emphasizes the necessity of utilizing living population data as an urban planning indicator, considering the increasing limit distance of urban activities and growing interregional interaction due to advancements in transportation and communication.

• Advances in nano research
• /
• v.10 no.4
• /
• pp.359-371
• /
• 2021

A tumor immune interaction is a main topic of interest in the last couple of decades because majority of human population suffered by tumor, formed by the abnormal growth of cells and is continuously interacted with the immune system. Because of its wide range of applications, many researchers have modeled this tumor immune interaction in the form of ordinary, delay and fractional order differential equations as the majority of biological models have a long range temporal memory. So in the present work, tumor immune interaction in fractional form provides an excellent tool for the description of memory and hereditary properties of inter and intra cells. So the interaction between effector-cells, tumor cells and interleukin-2 (IL-2) are modeled by using the definition of Caputo fractional order derivative that provides the system with long-time memory and gives extra degree of freedom. Moreover, in order to achieve more efficient computational results of fractional-order system, a discretization process is performed to obtain its discrete counterpart. Furthermore, existence and local stability of fixed points are investigated for discrete model. Moreover, it is proved that two types of bifurcations such as Neimark-Sacker and flip bifurcations are studied. Finally, numerical examples are presented to support our analytical results.