• Journal of Korean Society on Water Environment
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• v.38 no.5
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• pp.231-239
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• 2022

In this study, we applied ENERWATER to evaluate the energy consumption labeling of wastewater treatment plants in Korea using the Korea sewerage statistics data. The results showed that the energy label status was excellent in the SBR process for small and medium-scale wastewater treatment plants and the A2O process for large-scale wastewater treatment plants. The energy labeling of wastewater treatment plants of 50,000 tons capacity was excellent. The statuses of metropolitan cities and Jeollanam-do province were excellent. We analyzed the effects of renewable energy on wastewater treatment plants' energy consumption and found out that digestion gas for large-scale plants and photovoltaic energy for small-scale plants were effective in improving energy labeling. In addition, we compared the energy labels of four wastewater treatment plants in "Z" city and wastewater treatment plant "X" had the best energy label, and the wastewater treatment plants "V" and "Y" had to be selected as priorities for the energy diagnosis and improvement project. In a comprehensive conclusion, the applicability of ENERWATER was confirmed based on sewage statistics data and labeling can be used to set priorities for the energy diagnosis and improvement project.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.6
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• pp.766-772
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• 2007

As XML is widely used, many researches on the XML storage and query processing have been done. But, previous works on path query processing have mainly focused on the storage and retrieval methods for a large XML document or XML documents had a same DTD. Those researches did not efficiently process partial match queries on the differently-structured document set. To resolve the problem, we suggested a new index structure using relational table. The method constructs the $B^+$-tree index using backward label paths instead of forward label paths used in previous researches for storing path information and allows for finding the label paths that match the partial match queries efficiently using it when process the queries.

• Journal of the Korean Society of Clothing and Textiles
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• v.31 no.5 s.164
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• pp.680-691
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• 2007

The increased diversity in designs, colors, and materials of children's clothing these days call for extra caution in care of these garments; however, the lack of customer's trust and efforts in complying with the care label combined with the enterprises's inadequate label attachments have led to various problems and disputes. This research attempts to examine customer's recognition, perception, and attitude towards the care labels on children's clothing. This research used the data collected from a total of 292 housewives raising children less than 7 year old. Descriptive statistics such as means, standard deviations, frequencies were calculated and ANOVAS followed by Duncan tests were carried out using SPSS 10.0. The results are as follows: First, 84.3% of the housewives admitted that they know about care labels; individuals with higher education level reported higher recognition. Second, as for the perception/attitude toward care labels, 46.9% perceived that care labels 'require additional knowledge for washing clothes' and 30.2% answered that they trust care labels. Third, 51.7% answered that they 'check the symbol instruction'; this tendency was higher among those with higher education levels. Fourth, 31.5% answered they comply with the instructions on care labels. Fifth, as for the reasons for not complying, 60.3% answered they neglect care labels because 'based on my experience, no major problems would occur'; this tendency was higher for those with greater personal income. Sixth, when asked whether any information on the care label kept them from buying a particular garment, 59.2% responded they did not purchase a garment because 'laundry costs appeared to outweigh the product price'; this response was higher among individuals with a higher level of income or education.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.37-62
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• 2018

This study examined the factors affecting the performance of automatic classification based on machine learning for domestic journal articles in the field of LIS. In particular, In view of the classification performance that assigning automatically the class labels to the articles in "Journal of the Korean Society for Information Management", I investigated the characteristics of the key factors(weighting schemes, training set size, classification algorithms, label assigning methods) through the diversified experiments. Consequently, It is effective to apply each element appropriately according to the classification environment and the characteristics of the document set, and a fairly good performance can be obtained by using a simpler model. In addition, the classification of domestic journals can be considered as a multi-label classification that assigns more than one category to a specific article. Therefore, I proposed an optimal classification model using simple and fast classification algorithm and small learning set considering this environment.

• Journal of KIISE:Information Networking
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• v.28 no.4
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• pp.602-610
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• 2001

In the MPLS(Multiprotocol Label Switching) forwarding paradigm, once a packet is assigned to a FEC(Forwarding Equivalence Class), no further header analysis is done by subsequent routers; all forwarding is driven by the labels. This has a number of advantages over conventional network layer forwarding. The MPLS LER(Label Edge Router) is located at the boundary of MPLS domain and plays a role in connecting with the existing Internet as an ingress or an egress router. That is, the MPLS LER as an ingress router assigns a label to a packet which enters the MPLS network from the Internet by analyzing its header and forwards to a corresponding next router in MPLS domain. As an egress router, the MPLS LER turns the packets out of the MPLS network by performing the reverse operation. In this paper, we analyze the traffic performance of an MPLS LER system and estimate the IP(Internet Protocol) packet processing capacity of the system using queueing model and simulation. It is found that the maximum IP packet processing capacity of the system is estimated by 420,000 through 460,000 packets/sec.

• Journal of the Korean Society for information Management
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• v.33 no.2
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• pp.33-59
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• 2016

This study examined the factors affecting the performance of automatic classification for the domestic conference papers based on machine learning techniques. In particular, In view of the classification performance that assigning automatically the class labels to the papers in Proceedings of the Conference of Korean Society for Information Management using Rocchio algorithm, I investigated the characteristics of the key factors (classifier formation methods, training set size, weighting schemes, label assigning methods) through the diversified experiments. Consequently, It is more effective that apply proper parameters (${\beta}$, ${\lambda}$) and training set size (more than 5 years) according to the classification environments and properties of the document set. and If the performance is equivalent, I discovered that the use of the more simple methods (single weighting schemes) is very efficient. Also, because the classification of domestic papers is corresponding with multi-label classification which assigning more than one label to an article, it is necessary to develop the optimum classification model based on the characteristics of the key factors in consideration of this environment.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.493-500
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• 2020

The purpose of this study is to analyze the effect of the visual element of the label design image of premium lunch boxes and general lunch boxes on purchasing intention. As a method of research, the label design images and purchase intentions of premium lunch boxes and general lunch boxes from the nation's leading convenience store brands, Seven Eleven, GS25, and CU, were investigated through a survey, T-verification was conducted based on the measured average value and standard deviation was completed after analysis with SPSS 21. The results of the study showed that the label design of premium lunch boxes was recognized by consumers as a premium image that was a point of differentiation from general lunch boxes, and that the proportion of "quality" and "menu composition" was high, This indicates that convenience store premium lunch boxes could also offer consumers a competitive edge in value that is considered premium other than "price."

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.12
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• pp.1801-1810
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• 2009

This study was carried out to investigate food-nutrition labeling perception and utilization classified by age in Busan. The survey was conducted from March 26 to April 30, 2008 by questionnaires and data analyzed by SPSS program. The results are summarized as follows: reasons for purchase of the processed food was 'delicious' in elementary school children and middle & high school students, but was 'easy to eat and cook' in the adults groups (p<0.001). The criteria for choice of the processed foods was 'taste' in all of the subjects. Eighty seven point five percent of the over 60's do not know about food labeling and 70.1% of them did not check the food label. The first confirmed items for buying the processed foods was 'expiration date' in all of the subjects (71.1%). In elementary school children, middle & high school students, 20's & 30's group, the ratio of awareness of nutrition label was higher than the 40's & 50's and over 60's group. For reading of nutrition label, all of the subjects except elementary group replied 'often' (p<0.001). For the experience of education and publicity on food-nutrition labeling, 54.3% of the subjects replied 'often', and there was a significant difference by age. For the necessity of education and publicity on food-nutrition labeling, 49.5% of the subjects replied 'necessary'. There was significant positive correlation between degree of checking of nutrition label and degree of checking of food label, accuracy of knowledge of processed food, necessity of education and publicity. Therefore, education and publicity on food-nutrition labeling for the subjects are required to encourage them to choose more nutritious food and have healthier dietary pattern.

• Investigative Magnetic Resonance Imaging
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• v.24 no.3
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• pp.123-131
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• 2020

Purpose: Joint label fusion (JLF) is a popular multi-atlas-based segmentation algorithm, which compensates for dependent errors that may exist between atlases. However, in order to get good segmentation results, it is very important to set the several free parameters of the algorithm to optimal values. In this study, we first investigate the feasibility of a JLF algorithm for prostate segmentation in MR images, and then suggest the optimal set of parameters for the automatic prostate segmentation by validating the results of each parameter combination. Materials and Methods: We acquired T2-weighted prostate MR images from 20 normal heathy volunteers and did a series of cross validations for every set of parameters of JLF. In each case, the atlases were rigidly registered for the target image. Then, we calculated their voting weights for label fusion from each combination of JLF's parameters (r_pxy, r_pz, r_sxy, r_sz, β). We evaluated the segmentation performances by five validation metrics of the Prostate MR Image Segmentation challenge. Results: As the number of voxels participating in the voting weight calculation and the number of referenced atlases is increased, the overall segmentation performance is gradually improved. The JLF algorithm showed the best results for dice similarity coefficient, 0.8495 ± 0.0392; relative volume difference, 15.2353 ± 17.2350; absolute relative volume difference, 18.8710 ± 13.1546; 95% Hausdorff distance, 7.2366 ± 1.8502; and average boundary distance, 2.2107 ± 0.4972; in parameters of r_pxy = 10, r_pz = 1, r_sxy = 3, r_sz = 1, and β = 3. Conclusion: The evaluated results showed the feasibility of the JLF algorithm for automatic segmentation of prostate MRI. This empirical analysis of segmentation results by label fusion allows for the appropriate setting of parameters.

• Journal of KIISE:Information Networking
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• v.31 no.2
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• pp.233-241
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• 2004

In this paper, we propose a packet-lossless fast rerouting scheme at a link/node fault in MPLS (Multiprotocol Label Switching) network with minimized accumulated buffer delay problem at ingress node. The proposed scheme uses a predefined, alternative LSP (Label Switched Path) In order to restore user traffic. We propose two restoration approaches. In the first approach, an alternative LSP is initially allocated with more bandwidth than the protected working LSP during the failure recovery phase. After the failure recovery, the excessively allocated bandwidth of the alternative LSP is readjusted to the bandwidth of the working LSP. In the second approach, we reduce the length of protected working LSP by using segment-based restoration. The proposed approaches have merits of (ⅰ) no buffer delay problem after failure recovery at ingress node, and (ⅱ) the smaller required buffer size at the ingress node than the previous approach.