• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.12
• /
• pp.5782-5799
• /
• 2018

With the development of GPS and the popularity of mobile devices with positioning capability, collecting massive amounts of trajectory data is feasible and easy. The daily trajectories of moving objects convey a concise overview of their behaviors. Different social roles have different trajectory patterns. Therefore, we can identify users or groups based on similar trajectory patterns by mining implicit life patterns. However, most existing daily trajectories mining studies mainly focus on the spatial and temporal analysis of raw trajectory data but missing the essential semantic information or behaviors. In this paper, we propose a novel trajectory semantics calculation method to identify groups that have similar behaviors. In our model, we first propose a fast and efficient approach for stay regions extraction from daily trajectories, then generate semantic trajectories by enriching the stay regions with semantic labels. To measure the similarity between semantic trajectories, we design a semantic similarity measure model based on spatial and temporal similarity factor. Furthermore, a pruning strategy is proposed to lighten tedious calculations and comparisons. We have conducted extensive experiments on real trajectory dataset of Geolife project, and the experimental results show our proposed method is both effective and efficient.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.4
• /
• pp.1409-1425
• /
• 2021

In wide-ranging information society, fast and easy access to information in language of one's choice is indispensable, which may be provided by using various multilingual Natural Language Processing (NLP) applications. Natural language text contains references among different language elements, called anaphoric links. Resolving anaphoric links is a key problem in NLP. Anaphora resolution is an essential part of NLP applications. Anaphoric links need to be properly interpreted for clear understanding of natural languages. For this purpose, a mechanism is desirable for the identification and resolution of these naturally occurring anaphoric links. In this paper, a framework based on Hobbs syntactic approach and a system developed by Lappin & Leass is proposed for resolution of reflexive anaphoric links, present in Urdu text documents. Generally, anaphora resolution process takes three main steps: identification of the anaphor, location of the candidate antecedent(s) and selection of the appropriate antecedent. The proposed framework is based on exploring the syntactic structure of reflexive anaphors to find out various features for constructing heuristic rules to develop an algorithm for resolving these anaphoric references. System takes Urdu text containing reflexive anaphors as input, and outputs Urdu text with resolved reflexive anaphoric links. Despite having scarcity of Urdu resources, our results are encouraging. The proposed framework can be utilized in multilingual NLP (m-NLP) applications.

• Nuclear Engineering and Technology
• /
• v.54 no.12
• /
• pp.4751-4758
• /
• 2022

Two-phase flow may almost exist in every branch of the energy industry. For the corresponding engineering design, it is very essential and crucial to monitor flow patterns and their transitions accurately. With the high-speed development and success of deep learning based on convolutional neural network (CNN), the study of flow pattern identification recently almost focused on this methodology. Additionally, the photographing technique has attractive implementation features as well, since it is normally considerably less expensive than other techniques. The development of such a two-phase flow pattern online monitoring system is the objective of this work, which seldom studied before. The ongoing preliminary engineering design (including hardware and software) of the system are introduced. The flow pattern identification method based on CNNs and transfer learning was discussed in detail. Several potential CNN candidates such as ALexNet, VggNet16 and ResNets were introduced and compared with each other based on a flow pattern dataset. According to the results, ResNet50 is the most promising CNN network for the system owing to its high precision, fast classification and strong robustness. This work can be a reference for the online monitoring system design in the energy system.

• Journal of information and communication convergence engineering
• /
• v.21 no.2
• /
• pp.117-129
• /
• 2023

High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-interest identification and recommendation systems that serve as frequent itemset identification tools, product or service recommendation systems, etc. Recently, it has gained widespread attention owing to its increasing role in business intelligence, top-N recommendation, and other enterprise solutions. Despite the increasing significance and the inability to provide swift and more accurate predictions, most at-hand solutions, including frequent itemset mining, HUIM, and high average- and fast high-utility itemset mining, are limited to coping with real-time enterprise demands. Moreover, complex computations and high memory exhaustion limit their scalability as enterprise solutions. To address these limitations, this study proposes a model to extract high-utility frequent closed itemsets based on an improved cumulative summary list structure (CSLFC-HUIM) to reduce an optimal set of candidate items in the search space. Moreover, it employs the lift score as the minimum threshold, called the cumulative utility threshold, to prune the search space optimal set of itemsets in a nested-list structure that improves computational time, costs, and memory exhaustion. Simulations over different datasets revealed that the proposed CSLFC-HUIM model outperforms other existing methods, such as closed- and frequent closed-HUIM variants, in terms of execution time and memory consumption, making it suitable for different mined items and allied intelligence of business goals.

• Korean Journal of Clinical Laboratory Science
• /
• v.47 no.2
• /
• pp.83-89
• /
• 2015

Although Mycobacterium tuberculosis complex strains remain responsible for the majority of diseases caused by mycobacterial infections worldwide, the increase in HIV (human immuno deficiency virus) infections has allowed for the emergence of other non-tuberculous mycobacteria as clinically significant pathogens. M. tuberculosis was detected by two-tube nested polymerase chain reaction (PCR) and non-tuberculous mycobacteria was detected by PCR-restriction fragment length polymorphism (RFLP) with Msp I. Result of niacin test is equal to result of two-tube nested PCR after culture for M. tuberculosis. In this study, acid fast bacilli stain (AFB. stain) >2+ case, Detection of Mycobacteria is similar to result before culture and after culture. AFB. stain <1+ case, result of mycobacteria is distinguished. Conclusionly, these results suggest that identification of mycobacteria must go side by side both culture and PCR for more fast and accuracy.

• Korean Journal of Clinical Laboratory Science
• /
• v.52 no.3
• /
• pp.229-236
• /
• 2020

Sixty-five molds isolated from clinical specimens were included in this study. All the isolates were molds that could be identified morphologically, strains that are difficult to identify because of morphological similarities, and strains that require species-level identification. PCR and direct sequencing were performed to target the internal transcribed spacer (ITS) region, the D1/D2 region, and the β-tubulin gene. Comparative sequence analysis using the GenBank database was performed using the basic local alignment search tool (BLAST) algorithm. The fungi identified morphologically to the genus level were 67%. Sequencing analysis was performed on 62 genera and species level of the 65 strains. Discrepancies were 14 (21.5%) of the 65 strains between the results of phenotypic and molecular identification. B. dermatitidis, T. marneffei, and G. argillacea were identified for the first time in Korea using the DNA sequencing method. Morphological identification is a very useful method in terms of the reporting time and costs in cases of frequently isolated and rapid growth, such as Aspergillus. When molecular methods are employed, the cost and clinical significance should be considered. On the other hand, the molecular identification of molds can provide fast and accurate results.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
• /
• 2001.06a
• /
• pp.3111-3111
• /
• 2001

The implementation of NIR and chemometrics in the Pharmaceutical industries is still in strong progress, both regarding qualitative and quantitative applications and beneficial results are seen. Looking at the development so far, NIR will change the pharmaceutical industry even more in the future. This presentation will address the experiences and progress achieved regarding the application and implementation of quantitative methods for determination of content uniformity and assay of tablets with less than 10% w/w of active, using Near Infrared transmittance spectroscopy in combination with PLS. Also qualitative methods for identification of the same tablets by Near Infrared reflectance spectroscopy will be discussed. Four commercial tablet strengths are formulated and produced from two different compositions by direct compression. Three different strengths are dose proportional, i.e. fixed concentration by varying in size. The aim was to replace the conventional primary methods for analysing content uniformity, assay and identification by NIR. Studies were performed on comparing transmittance versus reflectance spectroscopy for both applications on the dose proportional tablets. The model for determination of content uniformity and assay was developed to cover both coated and uncoated tablets, whereas the qualitative model was developed to identify coated tablets only. The impact of the tablet formulation, tablet size and coating, resulted in individual models far each composition The best calibration was achieved using diffuse reflectance for the identification purposes and diffuse transmittance for the quantitative determination of the active content within the tablets. As NIR in combination with other techniques opens up the possibility of total quality management within the production, the transfer of the above-mentioned models from a laboratory based approach to an at-line approach at H.Lundbeck will be addressed too.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.13 no.2
• /
• pp.88-95
• /
• 2008

This paper proposes a fast fault detection algorithm under open-circuit fault of a switch for a brushless DC(BLDC) motor drive system. This proposed method is configured without the additional devices for fault detection and identification. The fault detection and identification are achieved by a simple algorithm using the operating characteristic of the BLDC motor. After the fault identification, the drive system is reconfigured for continuous operation. This system is reconfigured by four-switch topology connecting a faulty leg to the middle point of DC-link bidirectional switches. This proposed method can also be embedded into existing BLDC motor drive systems as a subroutine without excessive computational effort. The feasibility of a the proposed fault detection algorithm is validated in simulation and experiment.

• Journal of Microbiology and Biotechnology
• /
• v.21 no.12
• /
• pp.1270-1279
• /
• 2011

Bealmijang is a short-term aged paste made from meju, which is a brick of fermented soybeans and other ingredients. Different types of bealmijang are available depending on the geographic region or ingredients used. However, no study has clarified the microbial diversity of these types. We identified 17 and 14 fungal species from black soybean meju (BSM) and buckwheat meju (BWM), respectively, on the basis of morphology, culture characteristics, and internal transcribed spacer and ${\beta}$-tubulin gene sequencing. In both meju, Aspergillus oryzae, Rhizopus oryzae, Penicillium polonicum, P. steckii, Cladosporium tenuissimum, C. cladosporioides, C. uredinicola, and yeast species Pichia burtonii were commonly found. Moreover, A. flavus, A. niger, P. crustosum, P. citrinum, Eurotium niveoglaucum, Absidia corymbifera, Setomelanomma holmii, Cladosporium spp. and unclassified species were identified from BSM. A. clavatus, Mucor circinelloides, M. racemosus, P. brevicompactum, Davidiella tassiana, and Cladosporium spp. were isolated from BWM. Fast growing Zygomycetous fungi is considered important for the early stage of meju fermentation, and A. oryae and A. niger might play a pivotal role in meju fermentation owing to their excellent enzyme productive activities. It is supposed that Penicillium sp. and Pichia burtonii could contribute to the flavor of the final food products. Identification of this fungal diversity will be useful for understanding the microbiota that participate in meju fermentation, and these fungal isolates can be utilized in the fermented foods and biotechnology industries.

• Journal of Microbiology and Biotechnology
• /
• v.24 no.9
• /
• pp.1189-1195
• /
• 2014

A strain-specific identification method is required to secure Chlorella strains with useful genetic traits, such as a fast growth rate or high lipid productivity, for application in biofuels, functional foods, and pharmaceuticals. Microsatellite markers based on simple sequence repeats can be a useful tool for this purpose. Therefore, this study developed five novel microsatellite markers (mChl-001, mChl-002, mChl-005, mChl-011, and mChl-012) using specific loci along the chloroplast genome of Chlorella vulgaris. The microsatellite markers were characterized based on their allelic diversities among nine strains of C. vulgaris with the same 18S rRNA sequence similarity. Each microsatellite marker exhibited 2~5 polymorphic allele types, and their combinations allowed discrimination between seven of the C. vulgaris strains. The two remaining strains were distinguished using one specific interspace region between the mChl-001 and mChl-005 loci, which was composed of about 27 single nucleotide polymorphisms, 13~15 specific sequence sites, and (T)n repeat sites. Thus, the polymorphic combination of the five microsatellite markers and one specific locus facilitated a clear distinction of C. vulgaris at the strain level, suggesting that the proposed microsatellite marker system can be useful for the accurate identification and classification of C. vulgaris.