• Journal of Korean Society on Water Environment
• /
• v.26 no.5
• /
• pp.860-870
• /
• 2010

Long term monthly monitoring data showed that the water quality of streams flowing into Lake Paldang has been improved by various strategy for water. However, the effect of quality on Lake Paldang is still insufficient because of nonpoint source from watershed. In order to evaluate quantifying methods for pollution source and make a suggestion on improvements, Storm Water Management Model (SWMM) was constructed by using data set from the water quality and streamflow monitoring network in the Kyoungan watershed for Total Maximum Daily Loads (TMDLs). Load duration curve (LDC) based on the result of the Kyoungan watershed SWMM indicated that the water quality criterion on $BOD_5$ was often exceeded in up-stream than down-stream. From flowrate-load correlation curve, SS load significantly increased as streamflow increases. 75.3% of streamflow and 62.1% of $BOD_5$ loads is discharged especially in the zone of high flows, but monitoring data set didn't provide proper information about the conditions and the patterns associated with storm events. Therefore, it is necessary to acquire representative data set for comparing hydrograph and pollutograph through monitoring experimental watershed and to establish methods for quantifying point and nonpoint source pollutant loads.

• The Korean Journal of Applied Statistics
• /
• v.23 no.6
• /
• pp.1169-1178
• /
• 2010

This article consider a performance model selection based on AIC under unbalanced deign in linear mixed effect models. Vaida and Balanchard (2005) proposed conditional AIC for model selection in linear mixed effect models when the prediction of random effects is of primary interest. Theoretical properties of cAIC and related criteria have been investigated by Liang et al. (2008) and Greven and Kneib (2010). However, all of the simulation studies were performed under a balanced design. Even though functional form of AIC remain same even under the unbalanced deign, it is worthwhile to investigate performance of AIC based model selection criteria under the unbalanced design. The simulation study in this article shows how unbalancedness affects model selection in linear mixed effect models.

• The KIPS Transactions:PartB
• /
• v.11B no.4
• /
• pp.485-490
• /
• 2004

In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.

• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.17 no.1
• /
• pp.31-38
• /
• 2004

Mechanical design process is generally accomplished by design, analysis, and test. Designers use programs fitting purpose, and obtain repeatedly a response of a simulation program, a sub-program for optimization. In this paper, shape optimization using approximate optimization technique is carried out with sequential design domain(SDD). In addition, algorithm executing Pro/Engineer and ANSYS automatically are adopted in the approximate optimization program by SDD. It is difficult for design problem to be approximated accurately for the whole range of design space. However, more or less accurate approximation is constructed if SDD is applied to that case. SDD starts with a certain range which is off-seted from midpoint of an initial design domain and then SDD of the next step is determined by a move limited. Convergence criterion is defined such that optimal point must be located within SDD during the two steps. Also, the PLBA(Pshenichny-Lim-Belegundu-Arora) algorithm is used to solve approximate optimization problems. This algorithm uses the second-order information and the active set strategy, in order to seek the direction of design variables.

• Journal of Advanced Navigation Technology
• /
• v.20 no.2
• /
• pp.161-166
• /
• 2016

In high capacity and long haul optical communication systems, signal distortion is induced by chromatic dispersion and nonlinear effects of optical fibers. Dispersion management (DM) combining with mid-spans spectral inversion (MSSI) is one of the various techniques for overcoming this drawback. The most simple configuration of DM link is obtained by uniformly distributing the lengths of single mode fiber (SMF) and residual dispersion per span (RDPS) over whole fiber spans consisted of optical link. In this paper, the system performances in the uniformly distributed DM link combined with MSSI are assessed as a function of the number of fiber spans, because the system performances in this configuration are used as the significant performance criterion in other link configurations, such as the artificial distribution or the random distribution of SMF lengths and RDPS.

• Korean Journal of Artificial Intelligence
• /
• v.5 no.1
• /
• pp.10-17
• /
• 2017

This study is the first attempt to raise face recognition ability through machine learning algorithm and apply to CRM's information gathering, analysis and application. In other words, through face recognition of VIP customer in distribution field, we can proceed more prompt and subdivided customized services. The interest in machine learning, which is used to implement artificial intelligence, has increased, and it has become an age to automate it by using machine learning beyond the way that a person directly models an object recognition process. Among them, Deep Learning is evaluated as an advanced technology that shows amazing performance in various fields, and is applied to various fields of image recognition. Face recognition, which is widely used in real life, has been developed to recognize criminals' faces and catch criminals. In this study, two image analysis models, TF-SLIM and Inception-V3, which are likely to be used for criminal face recognition, were selected, analyzed, and implemented. As an evaluation criterion, the image recognition model was evaluated based on the accuracy of the face recognition program which is already being commercialized. In this experiment, it was evaluated that the recognition accuracy was good when the accuracy of the image classification was more than 90%. A limit of our study which is a way to raise face recognition is left as a further research subjects.

• The KIPS Transactions:PartC
• /
• v.17C no.6
• /
• pp.491-498
• /
• 2010

Wi-Fi based vehicle-to-infrastructure (V2I) communication is an emerging solution to improve the safety, traffic efficiency, and comfort of passengers. However, due to the high mobility of vehicles and the limited coverage of Wi-Fi APs, the V2I system may suffer from frequent handoffs although roadside APs can support cost effective Internet connectivity. Such problem of V2I systems can be overcome with Mobile AP (MAP) platform. The MAPs yield longer service duration by moving along with vehicles, yet they provide a lower link capacities than the roadside APs. In this paper, we propose a new association control mechanism that effectively determines whether the vehicle will select a fixed roadside-AP or a nearby MAP in mobile vehicular network environments. We consider both the achievable link bandwidth and available connection duration as a selection criterion and provide their run-time estimation method. Extensive simulation using real traces show significant performance improvements.

• The Journal of Korean Physical Therapy
• /
• v.19 no.5
• /
• pp.29-41
• /
• 2007

Purpose: The aim of this study was to examine the validity and reliability on Psychometric Arthritis Impact Measurement Scale-Short Form (AIMS-SF) in patients with knee osteoarthritis(OA). Methods: The sample consisted of 62 patients who had received physical therapy at the physical therapy units of the Andong Medical Center, Sungso Hospital, Ahn Orthopedic Surgery Clinic, and St. Luke Clinic in Andong city in June 2006. Questionnaire on the AIMS-SF was recruited by 5 physical therapists. The internal structure and reliability of the scales were evaluated by means of item-internal consistency(Cronbach's alpha coefficient: ${\alpha}$), item-discriminant validity, Pearson's relation coefficient. To explore construct validity we conducted a principal component factor analysis with varimax rotation analysis. The criterion for factor extraction was an eigenvalue >1.0. Results: 62 OA patients's an average $age{\pm}standard$ deviation was $53.8{\pm}14.4$ years (range: $40{\sim}81$ yr). The internal consistency reliability of 11 items, as estimated by Cronbach's ${\alpha}$ coefficient, was high ranging $0.60{\sim}0.78$ (except for 0.40 for mobility level and -0.48 for mood). The internal consistency reliability of item-each scale was also high $0.82{\sim}0.93$ (except for 0.48 for mood). Of 11 items, the item-discriminant validity on 6 items was high (${\alpha}$ coefficient range: $0.11{\sim}0.25$), however, others (0.57 for tension level, 0.48 for arthritis pain, 0.41 for walking and bending, and 0.40 for work) were a little low. The construct validity by factor analysis was a little low. Conclusion: In conclusion, the results reported here confirm the validity and reliability of the AIMS-SF in patients with OA of the knee. The Collection of information on health status using this instrument was acceptable to patients. A further prospective multi-center study will be necessary to prove the construct validity.

• Journal of Korean Society for Atmospheric Environment
• /
• v.24 no.6
• /
• pp.662-673
• /
• 2008

Two hybrid receptor models, potential source contribution function (PSCF) and concentration weighted tracjectory (CWT), were compared for locating $PM_{2.5}$ sources contributing to the atmospheric $PM_{2.5}$ concentrations in Seoul. The source contribution estimates by chemical receptor model (CMB) receptor model were used to identify better source areas, Among the sources, soil, agricultural burning, marine aerosol, coal-fired power plant and Chinese aerosol were only considered for the study because these sources were more likely to be associated with the long-range transport of air pollutant. Both methods are based on combining chemical data with calculated air parcel backward trajectories. However, the PSCF analyses were performed with trajectories above the $75^{th}$ percentile criterion values, while the CWT analyses used all trajectories. This difference resulted in locating of different sources, which might be helpful to interpret locating of $PM_{2.5}$ sources, High possible source areas in source contribution of soil and agricultural burning contributing to the Seoul $PM_{2.5}$ were inland areas of Heibei and Shandong provinces (highest density areas of agricultural production and population) in China. The "Chinese aerosol" was used as a representative source for the $PM_{2.5}$ originated from urban area in China. High possible source areas for the aerosol were the cities in China where are relatively close to the receptor. This result suggests that Chinese aerosol is likely to be a useful tool in studies on source apportionment and identification in Korea.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.29 no.2
• /
• pp.113-121
• /
• 2011

In this paper, we proposed the method automatically to match areal feature based on similarity using spatial information. For this, we extracted candidate matching pairs intersected between two different spatial datasets, and then measured a shape similarity, which is calculated by an weight sum method of each matching criterion automatically derived from CRITIC method. In this time, matching pairs were selected when similarity is more than a threshold determined by outliers detection of adjusted boxplot from training data. After applying this method to two distinct spatial datasets: a digital topographic map and street-name address base map, we conformed that buildings were matched, that shape is similar and a large area is overlaid in visual evaluation, and F-Measure is highly 0.932 in statistical evaluation.