• Korean Journal of Acupuncture
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• v.28 no.4
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• pp.41-48
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• 2011

Objectives : This study aimed to explore the passive multi-channel time series analysis method by measuring bio-potentials of acupuncture point and the peripheral region Methods : Bio-potential was measured at ST36 and the peripherical region of ST36 of 5 healthy volunteers at three times. The diagram of the potential changes over time were smoothed by moving average method and similarities of ST36 and the other points were calculated. Results : In the normal weight group, bio-potential similarity tended to decrease in proportion to the distance from the acupuncture point. In the obesity group, bio-potential similarity appeared in a very wide area. Bio-potential similarity had positive correlation with BMI value. Conclusions : The passive multi-channel time series analysis method showed the possibility be appropriate for the electrical characteristics study of meridians.

• The Journal of Industrial Distribution & Business
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• v.9 no.1
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• pp.67-76
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• 2018

Purpose - With the worldwide aging problem and the development of globalization, customers prefer to seek affordable medical services with the higher quality overseas. This new trend has urged some destination countries to improve their services for the more competitive advantages over other countries. Literature research indicate that medical quality and cost may be the key factors influencing global patients' decisions. In the international environment, however, medical tourism destinations are selected due to cultural similarity between the hosting country and the customers' own country. The more similarity perceived between the two countries leads foreign patients to choose the considering country as the destination for medical tourism. However, little research has been conducted on this topic. Thus, we empirically investigate how cultural similarity influences Chinese medical customers' choice of the destinations. We also consider the factors related to medical competency and travel attribute which might affect customers' decisions along with some moderating roles of disease types. Research design, data, and methodology - We proposed a research model in order to confirm the relations among different variables of cultural similarity, medical competency, travel attractiveness, disease types, and destination choice. The questionnaire survey is processed in the more economically developed regions of China such as Beijing, Shanghai, and Jiangsu. Conditional logit regression is applied to analyze the data of 881. Results - Results indicate that cultural similarity is the important predictor of Chinese customers' decision to select a medical country. However, the effects of cultural similarity vary according to the disease types. We also find that medical competency and travel attractiveness influence their decisions with the moderating role of disease types. Conclusions - Cultural similarity is the important factor that influences Chinese potential medical tourists' decisions to select a destination. Marketing managers should consider the effects of cultural similarity when developing strategies for attracting Chinese medical tourists. Since medical competency and travel attractiveness are still the critical key elements for them to evaluate the destination countries, it is necessary to continuously improve medical service quality and facilities. The results also recommend that medical managers should sharpen their marketing strategies by segmenting Chinese potential customers in terms of disease types.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.778-790
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• 2023

Although density peak clustering can often easily yield excellent results, there is still room for improvement when dealing with complex, high-dimensional datasets. One of the main limitations of this algorithm is its reliance on geometric distance as the sole similarity measurement. To address this limitation, we draw inspiration from the information bottleneck theory, and propose a novel density peak clustering algorithm that incorporates this theory as a similarity measure. Specifically, our algorithm utilizes the joint probability distribution between data objects and feature information, and employs the loss of mutual information as the measurement standard. This approach not only eliminates the potential for subjective error in selecting similarity method, but also enhances performance on datasets with multiple centers and high dimensionality. To evaluate the effectiveness of our algorithm, we conducted experiments using ten carefully selected datasets and compared the results with three other algorithms. The experimental results demonstrate that our information bottleneck-based density peaks clustering (IBDPC) algorithm consistently achieves high levels of accuracy, highlighting its potential as a valuable tool for data clustering tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.3
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• pp.522-538
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• 2013

Content based image retrieval has become an increasingly important research topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The retrieval systems rely on a key component, the predefined or learned similarity measures over images. We note that, the similarity measures can be potential improved if the data distribution information is exploited using a more sophisticated way. In this paper, we propose a similarity measure learning approach for image retrieval. The similarity measure, so called Fisher kernel, is derived from the probabilistic distribution of images and is the function over observed data, hidden variable and model parameters, where the hidden variables encode high level information which are powerful in discrimination and are failed to be exploited in previous methods. We further propose a discriminative learning method for the similarity measure, i.e., encouraging the learned similarity to take a large value for a pair of images with the same label and to take a small value for a pair of images with distinct labels. The learned similarity measure, fully exploiting the data distribution, is well adapted to dataset and would improve the retrieval system. We evaluate the proposed method on Corel-1000, Corel5k, Caltech101 and MIRFlickr 25,000 databases. The results show the competitive performance of the proposed method.

• Design & Manufacturing
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• v.17 no.3
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• pp.34-40
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• 2023

In this study, real-time collection of mold vibration signals during injection molding processes was achieved through IoT devices installed on the mold surface. To analyze changes in the collected vibration signals, injection molding was performed under six different process conditions. Analysis of the mold vibration signals according to process conditions revealed distinct trends and patterns. Based on this result, cosine similarity was applied to compare pattern changes in the mold vibration signals. The similarity in time and acceleration vector space between the collected data was analyzed. The results showed that under identical conditions for all six process settings, the cosine similarity remained around 0.92±0.07. However, when different process conditions were applied, the cosine similarity decreased to the range of 0.47±0.07. Based on these results, a cosine similarity threshold of 0.60~0.70 was established. When applied to the analysis of mold vibration signals, it was possible to determine whether the molding process was stable or whether variations had occurred due to changes in process conditions. This establishes the potential use of cosine similarity based on mold vibration signals in future applications for real-time monitoring of molding process changes and anomaly detection.

• Proceedings of the KIEE Conference
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• 2006.04a
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• pp.159-161
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• 2006

The peer-to-peer (P2P) systems have Brown significantly over last few years due to their hish potential of sharing various resources. Super-peer based P2P systems have been found very effective by dividing the peers into two layers, SP (Super-Peer) and OP (Ordinary-Peer). In this paper, we present ISP2P (Intelligent Super-peer based P2P system), which allows us to choose the best SP. Through analyzing capacity and similarity between SP and OP, we can help OPs to select the most appropriate SP respectively. Proposed system can improve the performance of the average response time by superior SP, reduce the bandwidth cost by small path length due to content similarity and solve frequent SP replacement problem by considering similarity of user behavior.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.269-284
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• 2022

Exploring research similarity of researchers offers insight on research communities and potential interactions among scholars. While co-authorship is a popular measure for studying research similarity of researchers, it cannot provide insight on authors who have not collaborated yet. In this work, we present novel approach to capture research similarity of authors using citation information. Extensive study is conducted on DATA & KNOWLEDGE ENGINEERING (DKE) publications to demonstrate and compare suggested approach with co-authorship based approach. Analysis result shows that proposed approach distinguishes author relationships that is not shown in co-authorship network.

• Journal of Crop Science and Biotechnology
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• v.10 no.4
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• pp.231-236
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• 2007

Differentially expressed genes(DEG) were identified in a rice variety, Sathi, an indica type showing high allelopathic potential against barnyardgrass(Echinochloa crus-galli(L.) Beauv. var. frumentaceae). Rice plants were grown with and without barnyardgrass and total RNA was extracted from rice leaves at 45 days after seeding. DEG full-screening was performed by $GeneFishing^{TM}$ method. The differentially expressed bands were re-amplified and sequenced, then analyzed by Basic Local Alignment Search Tool(BLAST) searching for homology sequence identification. Gel electrophoresis showed nine possible genes associated with allelopathic potential in Sathi, six genes(namely DEG-1, 4, 5, 7, 8, and 9) showed higher expression, and three genes(DEG-2, 3 and 6) showed lower expression as compared to the control. cDNA sequence analysis showed that DEG-7 and DEG-9 had the same sequence. From RT PCR results, DEG-6 and DEG-7 were considered as true DEG, whereas DEG-1, 2, 3, 4, 5, and 8 were considered as putative DEG. Results from blast-n and blast-x search suggested that DEG-1 is homologous to a gene for S-adenosylmethionine synthetase, DEG-2 is homologous to a chloroplast gene for ribulose 1,5-bisphosphate carboxylase large subunit, DEG-8 is homologous to oxysterol-binding protein with an 85.7% sequence similarity, DEG-5 is homologous to histone 2B protein with a 47.9% sequence similarity, DEG-6 is homologous to nicotineamine aminotransferase with a 33.1% sequence similarity, DEG-3 has 98.8% similarity with nucleotides sequence that has 33.1% similarity with oxygen evolving complex protein in photosystem II, DEG-7 is homologous to nucleotides sequence that may relate with putative serin/threonine protein kinase and putative transposable element, and DEG-4 has 98.8% similarity with nucleotides sequence for an unknown protein.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.71-74
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• 2000

The equi-potential lines designed in the electric field are introduced to find the preform shape in axisymmetric hot forging. The equi-potential lines generated between two conductors of different voltages show similar trends of the minimum work paths between the undeformed shape and the deformed shape. Base on this similarity the equi-potential lines obtained by arrangement of the initial and final shapes are utilized for the design of preform and then the artificial neural network is used to find the range of initial volume and potential value of the electric field.

• Journal of Pharmacopuncture
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• v.27 no.3
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• pp.223-233
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• 2024

Objectives: The phytochemicals in the aerial parts of Euphorbia paralias (also known as Sea Spurge) and their anti-inflammatory and antimicrobial activities were investigated. Methods: The methanolic extract was characterized using GC-MS and HPLC techniques. The anti-inflammatory feature was estimated through a Human Red Blood Cell (HRBC) membrane stabilization technique, while the antimicrobial feature was evaluated by the disc diffusion agar technique, minimum bactericidal concentration, and minimum inhibitory concentration (MIC) via micro-broth dilution method. Results: The GC/MS results demonstrated the existence of various phytochemicals, such as n-hexadecenoic acid, cis-11-eicosenoic acid, and methyl stearate, recognized for their anti-inflammatory and antibacterial features. The similarity of the phytochemical composition with other Euphorbia species emphasizes the genus-wide similarity. The anti-inflammatory activity exhibited a noteworthy inhibitory effect comparable to the reference drug indomethacin. The extract's antimicrobial potential was tested against a range of microorganisms, demonstrating significant action against Gram-positive bacteria and Candida albicans. The quantification of total phenolics and flavonoids further supported the therapeutic potential of the extract. Conclusion: The methanolic extract from E. paralias emerges as a successful natural source of important active constituents with potential applications as anti-inflammatory and antimicrobial agents. This research provides a first step to valorize Euphorbia paralias insights as a source of worthwhile phytochemicals that have potential applications in the pharmaceutical industry.