• Science of Emotion and Sensibility
• /
• v.21 no.3
• /
• pp.83-102
• /
• 2018

The process model of emotion regulation suggests that cognitive reappraisal and expressive suppression engage at different time points in the regulation process. Although multiple brain regions and networks have been identified for each strategy, no articles have explored changes in network characteristics or network connectivity over time. The present study examined (a) the whole-brain network and six other resting-state networks, (b) their modularity and global efficiency, which is an index of the efficiency of information exchange across the network, (c) the degree and betweenness centrality for 160 brain regions to identify the hub nodes with the most control over the entire network, and (d) the intra-network and inter-network functional connectivity (FC). Such investigations were performed using a traditional large-scale FC analysis and a relatively recent sliding window correlation analysis. The results showed that the right inferior orbitofrontal cortex was the hub region of the whole-brain network for both strategies. The present findings of temporally altering functional activity of the networks revealed that the default mode network (DMN) activated at the early stage of reappraisal, followed by the task-positive networks (cingulo-opercular network and fronto-parietal network), emotion-processing networks (the cerebellar network and DMN), and sensorimotor network (SMN) that activated at the early stage of suppression, followed by the greater recruitment of task-positive networks and their functional connection with the emotional response-related networks (SMN and occipital network). This is the first study that provides neuroimaging evidence supporting the process model of emotion regulation by revealing the temporally varying network efficiency and intra- and inter-network functional connections of reappraisal and suppression.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.29 no.7B
• /
• pp.675-684
• /
• 2004

There have been several efforts to avoid unnecessary retransmission timeouts (RTOs), which is the main cause for TCP throughput degradation. Unnecessary RTOs can be classified into three groups according to their cause. RTOs due to multiple packet losses in the same window for TCP Reno, the most prevalent TCP version, can be avoided by TCP NewReno or using selective acknowledgement (SACK) option. RTOs occurring when a packet is lost in a window that is not large enough to trigger fast retransmit can be avoided by using the Limited Transmit algorithm. In this Paper, we comparatively analyze these schemes to cope with unnecessary RTOs by numerical analysis and simulations. On the basis of the results in this paper, TCP performance can be quantitatively predicted from the aspect of loss recovery probability. Considering that overall performance of TCP is largely dependent upon the loss recovery performance, the results shown in this paper are of great importance.

• KIEAE Journal
• /
• v.8 no.4
• /
• pp.19-27
• /
• 2008

The carbon dioxide is brought from the energy consumption and regarded as a criteria material to estimate the Global Warming Potential. Building shares about 30% in national energy consumption and affects to environment as much as the energy consumption. But there is not enough data to forecast the amount of the carbon dioxide during the maintenance stage. Various factors are related with the energy consumption and carbon dioxide emission such as the physical area, the building exterior area, the maintenance type and location. Among these factors, the building carbon-dioxide emission can be estimated by the overall building characteristics such as the maintenance area, the number of household, the heating type, etc., The physical amount such as the thickness of the insulation and window infiltration could explained the limited scope and might not be use to estimate the total carbon-dioxide emission energy because the each value could not include or represent the overall building. In this paper, it provided the estimation model of the carbon-dioxide emission, explained by the overall building characteristics. These factors are shown as the maintenance area, no. of household, the heating type, the volume of the building, the ratio of the window to wall area etc., For providing the estimation model of th carbon-dioxide emission, it conducted the corelation analysis to filter the variables and suggested the estimation model with the power model and multiple regression model. Most of the model have a good statistics and fitted in the curve line.

• Journal of the Korea Convergence Society
• /
• v.10 no.12
• /
• pp.271-280
• /
• 2019

Smart factory, a critical part of digital transformation, enables data-driven decision making using monitoring, analysis and prediction. Predictive maintenance is a key element of smart factory and the need is increasing. The purpose of this study is to analyze the degradation characteristics of a galvanizing kettle for the steel plating process and to predict the remaining useful life(RUL) for predictive maintenance. Correlation analysis, multiple regression, principal component regression were used for analyzing factors of the process. To identify the trend of degradation, a proposed rolling window was used. It was observed the degradation trend was dependent on environmental temperature as well as production factors. It is expected that the proposed method in this study will be an example to identify the trend of degradation of the facility and enable more consistent predictive maintenance.

• Journal of Chest Surgery
• /
• v.41 no.4
• /
• pp.499-503
• /
• 2008

Berry syndrome (a distal aortopulmonary window and a right pulmonary artery originating from the ascending aorta, an intact ventricular septum, a patent ductus arteriosus and an interrupted aortic arch) is a rare complex congenital cardiac malformation. We describe a case of one stage repair with using an autologous arterial flap in a 19-day-old neonate who was suffering with this malformation, and we report on the development of postoperative right pulmonary artery stenosis and its successful management with performing multiple balloon angioplasties.

• Journal of Korean Society of Forest Science
• /
• v.96 no.3
• /
• pp.251-258
• /
• 2007

Airborne Lidar (light detection and ranging) can be an effective alternative in forest inventory to overcome the limitations of conventional field survey and aerial photo interpretation. In this study, we attempt to develop methodologies to identify individual trees and to estimate tree height from airborne Lidar data. Initially, digital elevation model (DEM) data representing the exact ground surface were generated by removing non-ground returns from the multiple-return laser point clouds, obtained over the coniferous forest site of rugged terrain. Based on the canopy height model (CHM) data representing non-ground layer, individual tree heights are extracted through pseudo-grid method and moving window filtering algorithm. Comparing with field survey data and aerial photo interpretation on sample plots, the number of trees extracted from Lidar data show over 90% accuracy and tree heights were underestimated within 1.1m in average at two plantation stands of pine (Pinus koraiensis) and larch (Larix leptolepis).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.10C
• /
• pp.990-999
• /
• 2007

In this paper, we propose the region-based image retrieval method using JSEG which is a method for unsupervised segmentation of color-texture regions. JSEG is an algorithm that discretizes an image by color classification, makes the J-image by applying a region to window mask, and then segments the image by using a region growing and merging. The segmented image from JSEG is given to a user as the query image, and a user can select a few segmented regions as the query region. After finding the MBR of regions selected by user query and generating the multiple window masks based on the center point of MBR, we extract the feature vectors from selected regions. We use the accumulated histogram as the global descriptor for performance comparison of extracted feature vectors in each method. Our approach fast and accurately supplies the relevant images for the given query, as the feature vectors extracted from specific regions and global regions are simultaneously applied to image retrieval. Experimental evidence suggests that our algorithm outperforms the recent image-based methods for image indexing and retrieval.

• Journal of Communications and Networks
• /
• v.11 no.5
• /
• pp.518-528
• /
• 2009

IEEE 802.11 wireless local area network (WLAN) has become the prevailing solution for wireless Internet access while transport control protocol (TCP) is the dominant transport-layer protocol in the Internet. It is known that, in an infrastructure-based WLAN with multiple stations carrying long-lived TCP flows, the number of TCP stations that are actively contending to access the wireless channel remains very small. Hence, the aggregate TCP throughput is basically independent of the total number of TCP stations. This phenomenon is due to the closed-loop nature of TCP flow control and the bottleneck downlink (i.e., access point-to-station) transmissions in infrastructure-based WLANs. In this paper, we develop a comprehensive analytical model to study TCP dynamics in infrastructure-based 802.11 WLANs. We calculate the average number of active TCP stations and the aggregate TCP throughput using our model for given total number of TCP stations and the maximum TCP receive window size. We find out that the default minimum contention window sizes specified in the standards (i.e., 31 and 15 for 802.11b and 802.11a, respectively) are not optimal in terms of TCP throughput maximization. Via ns-2 simulation, we verify the correctness of our analytical model and study the effects of some of the simplifying assumptions employed in the model. Simulation results show that our model is reasonably accurate, particularly when the wireline delay is small and/or the packet loss rate is low.

• Journal of IKEEE
• /
• v.17 no.2
• /
• pp.96-103
• /
• 2013

Since multimedia data takes large part of realtime transmission in wireless communication environments such as IEEE 802.11, QoS issues became one of the important problems with network performance. 802.11e MAC provides differentiated services based on priority schemes to solve existing 802.11 MAC problems. The TXOP is an important factor with the priority to improve network performance and QoS because it defines the time duration in which multiple frames can be transferred at one time for each station. In this paper, therefore frame sizes, TXOP Limit, and Priority values in accordance with the number of stations are experimented and derived for best network performance and QoS. Using 802.11e standard parameters, simulation results show the best throughput when the number of stations is 5 and TXOP Limit value is 6.016ms. For fairness, the best result is achieved at 3.008ms of TXOP Limit value and 15-31 of CW(Contention Window) that is lower priority than CW 7-15.

• Journal of the Korean Society of Clothing and Textiles
• /
• v.33 no.5
• /
• pp.721-731
• /
• 2009

The purpose of this study was to investigate the effects of VMD consciousness on importance of VMD components and clothing purchasing behaviors of university students. The research method was survey and subjects were 545 male and female university students in Chungnam province. The questionnaire consisted of 4 measuring instruments; VMD consciousness, importance of VMD components, clothing purchasing behaviors, and demographic attribution. The data were analyzed by factor analysis, $X^2$ test, t-test, cluster analysis, ANOVA and Duncan's multiple range test, using SPSS program. The results were as follows. First, university students had high VMD consciousness and attended to fashion trend, brand image, product information, and enjoyment of shopping, and felt appetite to purchase. Second, university students considered store arrangement and show window display as the important VMD components to purchase clothing. Third, university students were categorized into 3 consumer types(shopping/brand pursuit type, utilitarian information pursuit type, and trend/information pursuit type) by VMD consciousness. Forth, the consumer types by VMD consciousness showed many differences in importance of VMD components and clothing purchasing behaviors. Shopping/brand type considered show window display, cleanness and lighting/music/properties/color as more important VMD components, and used more money to purchase clothing and shopped more often than other consumer types.