• Journal of KIISE:Computer Systems and Theory
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• v.36 no.1
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• pp.1-8
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• 2009

Oligonucleotide design is known as a time-consuming work in Bioinformatics. In order to accelerate the oligonucleotide design process, one of the most widely used approaches is the prescreening unreliable regions using hashing(or seeding) method represented by BLAST. Since the seeding is originally proposed to increase the sensitivity for local alignment, the specificity should be considered as well as the sensitivity for the oligonucleotide design problem. However, a measure of evaluating the seeds regarding how adequate and efficient they are in the oligo design is not yet proposed. we propose a novel measure of evaluating the seeding algorithms based on the discriminability and the efficiency. By the proposed measure, five well-known seeding algorithms are examined. The spaced seed is recorded as the best efficient discriminative seed for oligo design.

• Dementia and Neurocognitive Disorders
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• v.17 no.3
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• pp.100-109
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• 2018

Background and Purpose: Although the clock drawing test (CDT) is a widely used cognitive screening instrument, there have been inconsistent findings regarding its utility with various scoring systems in patients with mild cognitive impairment (MCI) or dementia. The present study aimed to identify whether patients with MCI or dementia exhibited impairment on the CDT using three different scoring systems, and to determine which scoring system is more useful for detecting MCI and mild dementia. Methods: Patients with amnestic mild cognitive impairment (aMCI), vascular mild cognitive impairment (VaMCI), mild Alzheimer's disease (AD), mild vascular dementia (VaD), and cognitively normal older adults (CN) were included. All participants were administered the CDT, the Korean-Mini Mental State Examination (K-MMSE), and the Clinical Dementia Rating scale. The CDT was scored using the 3-, 5-, and 15-point scoring systems. Results: On all three scoring systems, all patient groups demonstrated significantly lower scores than the CN. However, while there were no significant differences among patients with aMCI, VaMCI, and AD, those with VaD exhibited the lowest scores. Area under the Receiver Operating Characteristic curves revealed that the three CDT scoring systems were comparable with the K-MMSE in differentiating aMCI, VaMCI, and VaD from CN. In differentiating AD from CN, however, the CDT using the 15-point scoring system demonstrated the most comparable discriminability with K-MMSE. Conclusions: The results demonstrated that the CDT is a useful cognitive screening tool that is comparable with the Mini-Mental State Examination, and that simple CDT scoring systems are sufficient for differentiating patients with MCI and mild dementia from CN.

• The Korea Journal of Herbology
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• v.37 no.4
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• pp.9-16
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• 2022

Objectives : In the Korean Pharmacopoeia 12th edition (KP 12) and the Korean Herbal Pharmacopoeia (KHP), two authentic herbal medicines are described, namely Bang-gi (Cheong-pung-deung) and Mok-bang-gi, respectively. In China, Bun-bang-gi is also used as herbal medicine. This study was conducted to develop a molecular authentication tool for distinguishing the three herbal medicine used as Bang-gi, which are Sinomeni Caulis et Rhizoma (Rhizome of Sinomenium acutum), Stephaniae Tetrandrae Radix (Root of Stephania terandra), and Cocculi Radix (Root of Cocculus trilobus). Methods : Twelve samples of three species (four samples of S. acutum, five samples of S. tetrandra, and three samples of C. trilobus) were collected from different habitats. The sequences of internal transcribed spacer (ITS) regions were obtained and comparatively analyzed to design the species-specific sequence characterized amplified region (SCAR) primers. The specificity of each pair of SCAR primers that amplified species-specific amplicon was evaluated for establishing the singleplex and multiplex PCR assay tools. Results : The singleplex SCAR markers show discriminability in C. acutum, S. tetrandra, and C. trilobus. These SCAR markers were also efficiently authenticated three species in the multiplex SCAR amplification using single PCR reaction. Furthermore, these PCR assay methods were applicable to authenticate dried herbal medicines distributed in the markets. Conclusions : The SCAR markers and PCR assay tools help discriminate the three herbal medicines used as Bang-gi at the species levels and provide a reliable genetic method to prevent the inauthentic distribution of these herbal medicines.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.942-943
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• 2021

The present work proposes a classification system for the HEp-2 cell images using an unsupervised deep feature learning method. Unlike most of the state-of-the-art methods in the literature that utilize deep learning in a strictly supervised way, we propose here the use of the deep convolutional autoencoder (DCAE) as the principal feature extractor for classifying the different types of the HEp-2 cell images. The network takes the original cell images as the inputs and learns to reconstruct them in order to capture the features related to the global shape of the cells. A final feature vector is constructed by using the latent representations extracted from the DCAE, giving a highly discriminative feature representation. The created features will be fed to a nonlinear classifier whose output will represent the final type of the cell image. We have tested the discriminability of the proposed features on one of the most popular HEp-2 cell classification datasets, the SNPHEp-2 dataset and the results show that the proposed features manage to capture the distinctive characteristics of the different cell types while performing at least as well as the actual deep learning based state-of-the-art methods.

• Korean Journal of Health Psychology
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• v.19 no.1
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• pp.407-420
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• 2014

In this study, a Korean abbreviation scale to measure love and compassion toward other person was developed based on a critical review on Compassionate Love Scale(CLS; Sprecher, & Fehr, 2005). In the study 1, 12 items were selected from the original version of 21 item CLS by surveying a sample of 207 college students on the basis of several psychometric characteristics (i.e., discriminability, coefficient of factor loading, and contribution to internal consistency). In the study 2, the validity of 12 item version, ACLS (Ajou Compassionate Love Scale), was confirmed by examining the factor structure, reliability, and correlations with other related scales. The results clearly showed that ACLS not only had a sufficient psychometric properties as the CLS, but also superior to the CLS in terms of parsimoniousness. Limitations and implications for future research of ACLS were discussed.

• Journal of the Korea Society of Computer and Information
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• v.29 no.2
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• pp.79-86
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• 2024

In this paper, a novel visual tracking method which can utilize the context of object regions is presented. Conventional methods have the inherent problem of treating all candidate regions independently, where the tracker could not successfully discriminate regions with similar appearances. This was due to lack of contextual modeling in a given scene, where all candidate object regions should be taken into consideration when choosing a single region. The goal of the proposed method is to encourage feature exchange between candidate regions to improve the discriminability between similar regions. It improves upon conventional methods that only consider a single region, and is implemented by employing the MLP-Mixer model for enhanced feature exchange between regions. By implementing channel-wise, inter-region interaction operation between candidate features, contextual information of regions can be embedded into the individual feature representations. To evaluate the performance of the proposed tracker, the large-scale LaSOT dataset is used, and the experimental results show a competitive AUC performance of 0.560 while running at a real-time speed of 65 fps.

• The Journal of Society for e-Business Studies
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• v.21 no.1
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• pp.65-77
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• 2016

As respecting one's privacy becomes an important issue in mobile device data analysis, on-device analysis is getting attention, in which the data analysis is conducted inside a mobile device without sending data from the device to outside. One possible application of the on-device analysis is gender prediction using text data in mobile devices, such as text messages, search keyword, website bookmarks, and contact, which are highly private, and the limited computing power of mobile devices can be addressed by utilizing the word comparison method, where words are selected beforehand and delivered to a mobile device of a user to determine the user's gender by matching mobile text data and the selected words. Moreover, it is known that performing prediction after filtering instances using definite evidences increases accuracy and reduces computational complexity. In this regard, we propose a two-phase approach to on-device gender prediction, where both discriminability and popularity of a word are sequentially considered. The proposed method performs predictions using a few highly discriminative words for all instances and popular words for unclassified instances from the previous prediction. From the experiments conducted on real-world dataset, the proposed method outperformed the compared methods.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.4
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• pp.107-115
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• 2011

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.2
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• pp.113-121
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• 2012

In this paper, we proposed fast and efficient algorithm for detecting near-duplication based on content based retrieval in large scale video database. For handling large amounts of video easily, we split the video into small segment using scene change detection. In case of video services and copyright related business models, it is need to technology that detect near-duplicates, that longer matched video than to search video containing short part or a frame of original. To detect near-duplicate video, we proposed motion distribution and frame descriptor in a video segment. The motion distribution descriptor is constructed by obtaining motion vector from macro blocks during the video decoding process. When matching between descriptors, we use the motion distribution descriptor as filtering to improving matching speed. However, motion distribution has low discriminability. To improve discrimination, we decide to identification using frame descriptor extracted from selected representative frames within a scene segmentation. The proposed algorithm shows high success rate and low false alarm rate. In addition, the matching speed of this descriptor is very fast, we confirm this algorithm can be useful to practical application.

• Journal of Preventive Medicine and Public Health
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• v.32 no.3
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• pp.361-373
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• 1999

Objectives: Receive Operating Characteristic(ROC) curve with the area under the ROC curve(AUC) is one of the most popular indicator to evaluate the criterion validity of the measurement tool. This study was conducted to develop a standardized questionnaire to discriminate workers at high-risk of work-related musculoskeletal disorders using ROC analysis. Methods: The diagnostic results determined by rehabilitation medicine specialists in 370 persons(89 shipyard CAD workers, 113 telephone directory assistant operators, 79 women with occupation, and 89 housewives) were compared with participant's own replies to 'the questionnair on the worker's subjective physical symptoms'(Kwon, 1996). The AUC's from four models with different methods in item selection and weighting were compared with each other. These 4 models were applied to 225 persons, working in an assembly line of motor vehicle, for the purpose of AUC reliability test. Results: In a weighted model with 11 items, the AUC was 0.8155 in the primary study population, and 0.8026 in the secondary study population(p=0.3780). It was superior in the aspects of discriminability, reliability and convenience. A new questionnaire of musculoskeletal disorder could be constructed by this model. Conclusion: A more valid questionnaire with a small number of items and the quantitative weight scores useful for the relative comparisons are the main results of this study. While the absolute reference value applicable to the wide range of populations was not estimated, the basic intent of this study, developing a surveillance fool through quantitative validation of the measures, would serve for the systematic disease prevention activities.