• Journal of Preventive Medicine and Public Health
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• v.45 no.2
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• pp.90-97
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• 2012

Objectives: While there have been many quantitative studies on the public's attitude towards mental illnesses, it is hard to find quantitative study which focused on the contextual effect on the public's attitude. The purpose of this study was to identify factors that affect the public's beliefs and attitudes including contextual effects. Methods: We analyzed survey on the public's beliefs and attitudes towards mental illness in Korea with multi-level analysis. We analyzed the public's beliefs and attitudes in terms of prejudice as an intermediate outcome and social distance as a final outcome. Then, we focused on the associations of factors, which were individual and regional socioeconomic factors, familiarity, and knowledge based on the comparison of the intermediate and final outcomes. Results: Prejudice was not explained by regional variables but was only correlated with individual factors. Prejudice increased with age and decreased by high education level. However, social distance controlling for prejudice increased in females, in people with a high education level, and in regions with a high education level and a high proportion of the old. Therefore, social distance without controlling for prejudice increased in females, in the elderly, in highly educated people, and in regions with a high education and aged community. Conclusions: The result of the multi-level analysis for the regional variables suggests that social distance for mental illness are not only determined by individual factors but also influenced by the surroundings so that it could be tackled sufficiently with appropriate considering of the relevant regional context with individual characteristics.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.2914-2935
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• 2016

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.1
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• pp.42-50
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• 2006

The multi-criteria group decision making (MCGDM) problem is to determine the best compromise solution in a set of competing alternatives that are evaluated under conflicting criteria by decision maker (DM)s. In this paper, we propose a mixed-integer programming (MIP) model to solve MCGDM. The existing method based on minimizing a distance measure such as Median Approach can not guarantee the best compromise solution because the element of median point vector is defined with respect to each criteria separately. However, by considering all criteria simultaneously, we generate median point that is better for locating the best compromise solution. We also utilize the concept of spatial dispersion index (SDI) to produce a threshold value, which is used as a guideline to choose either the Utopian Approach or the Median Approach. And we suggest using CBITP (Convex hull of individual maxima Based Interactive Tchebycheff Procedure) to provide DMs with various Pareto-optimal solutions so that DMs have broad range of selection.

• The KIPS Transactions:PartD
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• v.12D no.5 s.101
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• pp.673-682
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• 2005

Distance browsing queries, namely k-nearest neighbor queries, are the most important queries in spatial database applications, e.g., Geographic Information Systems(GISs). Recently, GIS applications trends to extend themselves toward wide multi-user environments such as the Web. Since many techniques for such queries, where Hjaltason and Samet's algorithm is the most efficient one, were optimized for only one query, we need to complement them suitable for multi-user environments. It can be a good approach that we store many individual query results in a cache, i.e., query result caching and reuse them in evaluating incoming queries, j.e., query result matching. In this paper, we propose a complementary Hjaltason and Samet's algerian capable of reusing previous query results in a cache for answering distance browsing queries in multi-user GIS environments. Our experimental results conform the efficiency of our approach.

• Ocean and Polar Research
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• v.36 no.4
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• pp.465-473
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• 2014

This paper proposes a formation control method by which multi-mining robots maintain a specified formation and follow a path. To secure the path tracking performance, a pure-pursuit algorithm is considered for each individual robot, and to minimize the deviation from the reference path, speed reduction in the steering motion is added. For the formation, in which two robots are parallel in a lateral direction, the robots track the specified path at a constant distance. In this way, the Leader-Follower method is adopted and the following robot knows the position and heading angle of the leader robot. Through the experimental test using two ground vehicle models, the performance is verified.

• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.445-455
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• 2007

We present a new biometric identification system based on multi-view features of teeth using principal components analysis(PCA). The multi-view features of teeth consist of the frontal view, the left side view and the right side view. In this paper, we try to stan the foundations of a dental biometrics for secure access in real life environment. We took the pictures of the three views teeth in the experimental environment designed specially and 42 principal components as the features for individual identification were developed. The classification for individual identification based on the nearest neighbor(NN) algorithm is created with the distance between the multi-view teeth and the multi-view teeth rotated. The identification performance after rotating two degree of test data is 95.2% on the left side view teeth and 91.3% on the right side view teeth as the average values.

• International Journal of Highway Engineering
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• v.10 no.2
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• pp.159-166
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• 2008

Video image processing systems (VIPS) offer numerous benefits to transportation models and applications, due to their ability to monitor traffic in real time. VIPS based on a wide-area detection algorithm provide traffic parameters such as flow and velocity as well as occupancy and density. However, most current commercial VIPS utilize a tripwire detection algorithm that examines image intensity changes in the detection regions to indicate vehicle presence and passage, i.e., they do not identify individual vehicles as unique targets. If VIPS are developed to track individual vehicles and thus trace vehicle trajectories, many existing transportation models will benefit from more detailed information of individual vehicles. Furthermore, additional information obtained from the vehicle trajectories will improve incident detection by identifying lane change maneuvers and acceleration/deceleration patterns. However, unlike human vision, VIPS cameras have difficulty in recognizing vehicle movements over a detection zone longer than 100 meters. Over such a distance, the camera operators need to zoom in to recognize objects. As a result, vehicle tracking with a single camera is limited to detection zones under 100m. This paper develops a methodology capable of monitoring individual vehicle trajectories based on image processing. To improve traffic flow surveillance, a long distance tracking algorithm for use over 200m is developed with multi-closed circuit television (CCTV) cameras. The algorithm is capable of recognizing individual vehicle maneuvers and increasing the effectiveness of incident detection.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.3
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• pp.226-235
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• 2006

Telematics is expected to be one of the fastest growing businesses in information technology area. It may create a new emerging market in industry related to automotive, telecommunications, and information services. Especially vehicle navigation service is considered as a killer application among telematics service applications. The current vehicle navigation service typically recommends a single path that is based on the traveling time or distance from the origin to the destination. The system provides two options for users to choose either via highway or via any road. Since the traffics and road conditions of big cities are very complicated and dynamic, the demand of multi-path guidance system is increasing in telematics market. The multi-path guidance system should allow drivers to choose a path based on their individual preferences such as traveling time, distance, or route familiarity. Using the Lawler's algorithm, it is possible to find multiple paths; however, due to the lengthy computational time, it is not suitable for the real-time services. This study suggests a computationally feasible and efficient heuristic multiple paths finding algorithm that is reliable for the real-time vehicle navigation services.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.10
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• pp.129-136
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• 2015

We propose a hybrid face recognition to deal with illumination variation. For this, we extract discriminant features by using the different illumination invariant feature extraction methods. In order to utilize both advantages of each method, we evaluate the discriminant power of each feature by using the discriminant distance and then construct a composite feature with only the features that contain a large amount of discriminative information. The experimental results for the Multi-PIE, Yale B, AR and yale databases show that the proposed method outperforms an individual illumination invariant feature extraction method for all the databases.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.70.1-70.1
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• 2012

We investigate 53 late-type galaxies in Virgo to get better understanding galaxy evolution driven by environmental effects in the cluster. The goal is to study how galaxies are strongly affected gravitationally by their surroundings and/or how interstellar medium (ISM) of galaxies changes through the interaction with intracluster medium (ICM). To quantify these, a variety of diagnostic methods have been introduced. Our diagnostics have two different perspectives. First, we have carefully examined the morphological and kinematical properties of individual galaxies using high resolution HI images and compared with multi-wavelength data. Based on the visual inspection, we have identified signatures of the interactions with other galaxies or the ICM. Second, we have quantified influence of local environments of individual galaxies using X-ray data and optical catalog of the cluster. By combining all the diagnostics, we have identified the environmental effect(s) at work on individual galaxies. We also probe the environmental processes as a function of the cluster centric distance. Various gravitational interactions are found throughout the cluster, while the ICM-ISM interaction is mainly dominant near the cluster center. However, we find some evidence that galaxies start losing their gas already in the low density outskirts of the cluster.