• Journal of the Korea Fashion and Costume Design Association
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• v.25 no.3
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• pp.17-29
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• 2023

This study collected and analyzed reference information on the size labeling method and size of clothing products in 13 online shopping malls for plus size women in their 20s and 30s, and compared the size specification information focusing on jeans. First, in the results of examining the method of clothing size designation, clothing sizes indicated by 1, 2, 3 or physique designation (M, L, XL) differed between shopping malls, and even in the same shopping mall, even if the same size notation was used. Most the clothing sizes were different depending on the type of clothing. For bottoms, it was found that one company used seven size designation methods at the same time, two shopping malls used four size designation methods, and five shopping malls used three size designation methods. In the meantime, in the results of comparing the size specifications of jeans XL (size 88, 32 inches) by product part, for waist and hip circumferences, each of the eight companies showed that the size was smaller than the body size suggested by KS adult women's wear.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.731-734
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• 1998

A scalable parallel algorithm is proposed for efficient image component labeling with local operatos on a mesh connected SIMD computer. In contrast to the conventional parallel labeling algorithms, where a single pixel is assigned to each PE, the algorithm presented here is scalable and can assign m$\times$m pixel set to each PE according to the input image size. The assigned pixel set is converted to a single pixel that has representative value, and the amount of the required memory and processing time can be highly reduced. For N$\times$N image, if m$\times$m pixel set is assigned to each PE of P$\times$P mesh, where P=N/m, the time complexity due to the communication of each PE and the computation complexity are reduced to O(PlogP) bit operations and O(P) bit operations, respectively, which is 1/m of each of the conventional method. This method also diminishes the amount of memory in each PE to O(P), and can decrease the number of PE to O(P2) =Θ(N2/m2) as compared to O(N2) of conventional method. Because the proposed parallel labeling algorithm is scalable, we can adapt to the increase of image size without the hardware change of the given mesh connected SIMD computer.

• ETRI Journal
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• v.36 no.3
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• pp.429-438
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• 2014

Semantic role labeling (SRL) is a task in natural-language processing with the aim of detecting predicates in the text, choosing their correct senses, identifying their associated arguments, and predicting the semantic roles of the arguments. Developing a high-performance SRL system for a domain requires manually annotated training data of large size in the same domain. However, such SRL training data of sufficient size is available only for a few domains. Constructing SRL training data for a new domain is very expensive. Therefore, domain adaptation in SRL can be regarded as an important problem. In this paper, we show that domain adaptation for SRL systems can achieve state-of-the-art performance when based on structural learning and exploiting a prior model approach. We provide experimental results with three different target domains showing that our method is effective even if training data of small size is available for the target domains. According to experimentations, our proposed method outperforms those of other research works by about 2% to 5% in F-score.

• Journal of the Korea Society of Computer and Information
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• v.13 no.6
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• pp.243-251
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• 2008

This study is to suggest the extraction algorithms of fingerprint corepoint and region separation using the labeling for gate security in order that it might be applied to the fingerprint recognition effectively. The gate security technology is entrance control, attendance management, computer security, electronic commerce authentication, information protection and so on. This study is to extract the directional image by dividing the original image in $128{\times}128$ size into the size of $4{\times}4$ pixel. This study is to separate the region of directional smoothing image extracted by each directional by using the labeling, and extract the block that appeared more than three sorts of change in different directions to the corepoint. This researcher is to increase the recognition rate and matching rate by extracting the corepoint through the separation of region by direction using the maximum direction and labeling, not search the zone of feasibility of corepoint or candidate region of corepoint used in the existing method. According to the result of experimenting with 300 fingerprints, the poincare index method is 94.05%, the proposed method is 97.11%.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.10
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• pp.421-426
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• 2013

As a greater amount of traffic have been generated on the Internet, it becomes more important to know the size of each flow. Many research studies have been conducted on the traffic measurement, and mostly they have focused on how to increase the measurement accuracy with a limited amount of memory. In this paper, we propose an explicit flow labeling technique that can be used to find out the names of the top flows and to increase the counting upper bound of the existing scheme. The labeling technique is applied to CSM (Counter Sharing Method), the most recent traffic measurement algorithm, and the performance is evaluated using the CAIDA dataset.

• Journal of KIISE
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• v.41 no.9
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• pp.699-706
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• 2014

As XML documents are getting bigger and more complex, a keyword-based search method that does not require structural information is needed to search these large XML documents. In order to use this method, not only all keywords expressed as nodes in the XML document must be labeled for indexing but also structural information should be well represented. However, the existing labeling methods either have very simple information of XML documents for index or represent the structural information which is difficult to deal with the increase of XML documents' size. As the size of XML documents is getting larger, it causes either the poor performance of keyword search or the exponential increase of space usage. In this paper, we present the Repetitive Prime Labeling Scheme (RPLS) in order to improve the problem of the existing labeling methods for keyword-based search of large XML documents. This method is based on the existing prime number labeling method and allows a parent's prime number to be used at a lower level repeatedly so that the number of prime numbers being generated can be reduced. Then, we show an experimental result of the comparison between our methods and the existing methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.12
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• pp.1997-2003
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• 2004

This paper presents a new method and an associated device, capable of detecting protein presence and size from the shift of the mechanical stiffness changing points due to the presence and size of proteins in a nano-gap actuator. Compared to the conventional resonant detection method, the present nanomechanical stiffness detection method shows higher precision for protein detection. The present method also offers simple and inexpensive protein detection devices by removing labeling process and optical components. We design and fabricate the nanomechanical protein detector using an electrothermal actuator with a nano-gap. In the experimental study, we measure the stiffness changing points and their coordinate shift from the devices with and without target proteins. The fabricated device detects the protein presence and the protein size of 14.0$\pm$7.4nm based on the coordinate shift of stiffness changing points. We experimentally verify the protein presence and size detection capability of the nanomechanical protein detector for applications to high-precision biomolecule detection.

• Parasites, Hosts and Diseases
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• v.29 no.1
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• pp.31-42
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• 1991

In order to observe the antigenic localization in the tissues of the young adult Paragenimus westermani, immunogold labeling method was applied using serum immunoglobulins (IgG) of the dog which infected with isolated metacercariae from Cambaroides similis. The sectioned worm tissue was embedded in Lowicryl HM 20 medium and stained with infected serum IgG and protein A gold complex(particle size; 12 nm) It was observed by electron microscopy at each tissues of the worm. The gold particles were not observed on the basal lamina of the tegument, interstitial matrix of the parenchyma, the muscle tissue and mitochondria of the tegument. The gold particles were specifically labeled in the secretory granules in the vitelline cells. They were predominantly labeling on the epithelial lamela and lumen of caecum. The above finding showed that antigenic materials in young adult worm tissue were specifically concentrated on the tegumental syncytium as well as cytoplasm of tegumental cells.

• Applied Microscopy
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• v.51
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• pp.2.1-2.7
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• 2021

Synaptic vesicles, which are endogenous to neurotransmitters, are involved in exocytosis by active potentials and release neurotransmitters. Synaptic vesicles used in neurotransmitter release are reused via endocytosis to maintain a pool of synaptic vesicles. Synaptic vesicles show different types of exo- and endocytosis depending on animal species, type of nerve cell, and electrical activity. To accurately understand the dynamics of synaptic vesicles, direct observation of synaptic vesicles is required; however, it was difficult to observe synaptic vesicles of size 40-50 nm in living neurons. The exo-and endocytosis of synaptic vesicles was confirmed by labeling the vesicles with a fluorescent agent and measuring the changes in fluorescence intensity. To date, various methods of labeling synaptic vesicles have been proposed, and each method has its own characteristics, strength, and drawbacks. In this study, we introduce methods that can measure presynaptic activity and describe the characteristics of each technique.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.721-723
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• 2007

Recently, the size and location of the acquired container image while the container is loading and unloading in Harbors is not fixed. And it is difficult to get a good image for recognition because of the variation of external environment as those the size of container and where the yard-tractor stop is. In this paper, we estimate where the container ISO-code set is using Top-hat transform from realtime images and get an image to recognize container ISO-code using PAN/TILT/ZOOM camera. We extract the container ISO-code using Top-hat transform and Histogram projection. After binarization, we extract each character from complex background using labeling. We use BP(Backpropagation Network) to recognize extracted characters.