• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.125-133
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So intuitive fuzzy c-means(IFCM) clustering algorithm is applied to improve KNN, which is the KNN/IFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of IFCM based on signal to noise ratio(SNR). Then, the k RPs are classified into different clusters through IFCM based on SNR. Experimental results indicate that the proposed KNN/IFCM hybrid algorithm generally outperforms KNN, KNN/FCM, KNN/PFCM algorithm when the locations error is less than 2m.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.109-115
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• 2011

As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So artificial neural network(ANN) clustering algorithm is applied to improve KNN, which is the KNN/ANN hybrid algorithm presented in this paper. For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of ANN based on SNR. Then, the k RPs are classified into different clusters through ANN based on SNR. Experimental results indicate that the proposed KNN/ANN hybrid algorithm generally outperforms KNN algorithm when the locations error is less than 2m.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.20
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• pp.8667-8671
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• 2014

Background: Survival rates after resection of advanced gastric cancer are extremely poor. An increasing number of patients with gastric carcinomas (GC) are therefore being treated with preoperative chemotherapy. We evaluated 36 month survival rate of GC patients that were treated by adding a neoadjuvant chemoradiotherapy before gastrostomy.Materials and Methods: Patients with stage II or III gastric adenocarcinomas were enrolled. The patients divided into two groups: (A) Neoadjuvant group that received concurrent chemoradiation before surgery (4500cGy of radiation at 180cGy per day plus chemotherapy with cisplatin and 5-fluorouracil, in the first and the end four days of radiotherapy). Resection was attempted 5 to 6 weeks after end of chemoradiotherapy. (B) Adjuvant group that received concurrent chemo-radiation after surgical resection. Results: Two (16.7%) patients out of 12 patients treated with neoadjuvant chemo-radiotherapy and 5 (38.5%) out of 13 in the surgery group survived after 36 months. These rates were not significantly different with per protocol and intention-to-treat analysis. The median survival time of patients in group A and B were 13.4 and 21.6 months, respectively, again not significantly different. Survival was significantly greater in patients with well differentiated adenocarcinoma in group B than in group A (p<0.004). Conclusions: According to this study we suggest surgery then chemoradiotherapy for patients with well differentiated gastric adenocarcinoma rather than other approaches. Additional studies with greater sample size and accurate matching relying on cancer molecular behavior are recommended.

• Journal of the Korea Computer Industry Society
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• v.2 no.9
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• pp.1175-1182
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• 2001

One to one Marketing (a.k.a. database marketing or relationship marketing) is one of the many fields that will benefit from the electronic revolution and shifts in consumer sales and advertising. As a component of intelligent customer services on Internet storefront, this paper describes technology of providing personalized advertisement using the market basket analysis, a well-Known data mining technique. The underlining theories of recommendation techniques are statistics, data mining, artificial intelligence, and/or rule-based matching. In the rule-based approach for personalized recommendation, marketing rules for personalization are usually collected from marketing experts and are used to inference with customer's data. However, it is difficult to extract marketing rules from marketing experts, and also difficult to validate and to maintain the constructed Knowledge base. In this paper, using marketing basket analysis technique, marketing rules for cross sales are extracted, and are used to provide personalized advertisement selection when a customer visits in an Internet store.

• Journal of the Korea Fashion and Costume Design Association
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• v.21 no.4
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• pp.139-152
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• 2019

This study aims to find out the influence of brand awareness and preference of collaboration products created by SPA and luxury brands using specific examples of collaborations, which are now becoming prevelent in the fashion industry. For this study, data collection was carried out through a distribution of 350 copies of the questionnaire, 333 responses were used for data analysis. Using a statistical package program with SPSS, a frequency analysis, a factor analysis, and a multiple regression analysis were conducted. The results of this study are summarized as follows. Awareness and preferences of the SPA and luxury brands lead collaboration products to be preferred. In addition, consumers happen to have more favorable attitudes regarding the purchase of collaboration products. This means that matching brands with high preference is a very important factor to create profits from the collaboration products as awareness and the preference are important factors for the success of projects. In particular, the recognition and preference of luxury brands was found to have greater impact on the preference and recognition of collaboration the SPA brands. Accordingly, brands should expand and actively collaborate through a variety of methods and support proper collaborations that fit their image.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.6
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• pp.1294-1310
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• 2010

User authentication using fingerprint information provides convenience as well as strong security. However, serious problems may occur if fingerprint information stored for user authentication is used illegally by a different person since it cannot be changed freely as a password due to a limited number of fingers. Recently, research in fuzzy fingerprint vault system has been carried out actively to safely protect fingerprint information in a fingerprint authentication system. In addition, research to solve the fingerprint alignment problem by applying a geometric hashing technique has also been carried out. In this paper, we propose the hardware architecture for a geometric hashing based fuzzy fingerprint vault system that consists of the software module and hardware module. The hardware module performs the matching for the transformed minutiae in the enrollment hash table and verification hash table. On the other hand, the software module is responsible for hardware feature extraction. We also propose the hardware architecture which parallel processing technique is applied for high speed processing. Based on the experimental results, we confirmed that execution time for the proposed hardware architecture was 0.24 second when number of real minutiae was 36 and number of chaff minutiae was 200, whereas that of the software solution was 1.13 second. For the same condition, execution time of the hardware architecture which parallel processing technique was applied was 0.01 second. Note that the proposed hardware architecture can achieve a speed-up of close to 100 times compared to a software based solution.

• The Korean Journal of Pain
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• v.35 no.4
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• pp.458-467
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• 2022

Background: Few studies have investigated unspecified or idiopathic pain associated with COIVD-19. This study aimed to provide the incidence rates of unspecified pain and idiopathic pain in patients with COVID-19 for 90 days after COVID-19 diagnosis. Methods: A propensity score matched cohort was used, including all patients with COVID-19 in South Korea, and analyzed their electronic medical records. The control group consisted of those who had not had tests for COVID-19 at all. Unspecified pain diagnoses consisted of diagnoses related to pain included in the ICD-10 Chapter XVIII. Idiopathic pain disorders included fibromyalgia, temporomandibular joint disorders, headaches, chronic prostatitis, complex regional pain syndrome, atypical facial pain, irritable bowel syndrome, and interstitial cystitis. Results: After matching, the number of participants in each group was 7,911. For most unspecified pain, the incidences were higher in the COVID-19 group (11.7%; 95% confidence interval [CI], 11.0-12.5) than in the control group (6.5%; 95% CI, 6.0-7.1). For idiopathic pain, only the headaches had a significantly higher incidence in the COVID-19 group (6.6%; 95% CI, 6.1-7.2) than in the control group (3.7%; 95% CI, 3.3-4.1). However, using a different control group that included only patients who visited a hospital at least once for any reasons, the incidences of most unspecified and idiopathic pain were higher in the control group than in the COVID-19 group. Conclusions: Patients with COVID-19 might be at a higher risk of experiencing unspecified pain in the acute phase or after recovery compared with individuals who had not had tests for COVID-19.

• Journal of the Korean Society of Physical Medicine
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• v.18 no.1
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• pp.99-110
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• 2023

PURPOSE: This study was conducted to suggest a way to easily understand and utilize the International Classification of Functioning, Disability and Health (ICF) or Korean Standard Classification of Functioning, Disability and Health (KCF), a common and standard language related to health information. METHODS: The tools used by physical therapists to evaluate the functioning of neurological patients were collected from 10 domestic hospitals. By applying the ICF linking rule, two experts compared, analyzed, and linked the concepts in the items of the collected tools and the ICF/KCF codes. The frequency of use of the selected tool, the matching rate of the liking results of two experts, and the number of the codes linked were treated as descriptive statistics and the code set was presented as a list. RESULTS: The berg balance scale, trunk impairment scale, timed up and go test, functional ambulation category, 6 Minute walk test, manual muscle test, and range of motion measurements were the most commonly used tools for evaluating the functioning. The total number of items of the seven tools was 33, and the codes linked to the ICF/KCF were 69. Twenty-two codes were mapped, excluding duplicate codes. Ten codes in the body function, 11 codes in the activity, and one code in the environmental factor were included. CONCLUSION: The information on the development process of the code set will increase the understanding of ICF/KCF and the developed code set can conveniently be used for collecting patients' functioning information.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.48 no.6
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• pp.348-355
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• 2022

Objectives: To compare the vital sign stability and cost of two commonly used sedatives, midazolam (MDZ) and dexmedetomidine (DEX). Patients and Methods: This retrospective study targeted patients who underwent mandibular third molar extractions under intravenous sedation using MDZ or DEX. The predictor variable was the type of sedative used. The primary outcome variables were vital signs (heart rate and blood pressure), vital sign outliers, and cost of the sedatives. A vital sign outlier was defined as a 30% or more change in vital signs during sedation; the fewer changes, the higher the vital sign stability. The secondary outcome variables included the observer's assessment of alertness/sedation scale, level of amnesia, patient satisfaction, and bispectral index score. Covariates were sex, age, body mass index, sleeping time, dental anxiety score, and Pederson scale. Descriptive statistics were computed including propensity score matching (PSM). The P-value was set at 0.05. Results: The study enrolled 185 patients, 103 in the MDZ group and 82 in the DEX group. Based on the data after PSM, the two samples had similar baseline covariates. The sedative effect of both agents was satisfactory. Heart rate outliers were more common with MDZ than with DEX (49.3% vs 22.7%, P=0.001). Heart rate was higher with MDZ (P=0.000). The cost was higher for DEX than for MDZ (29.27±0.00 USD vs 0.37±0.04 USD, P=0.000). Conclusion: DEX showed more vital sign stability, while MDZ was more economical. These results could be used as a reference to guide clinicians during sedative selection.

• Journal of Technologic Dentistry
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• v.46 no.2
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• pp.36-41
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• 2024

Purpose: This study aimed to generate virtual mandibular left first molar teeth using deep convolutional generative adversarial networks (DCGANs) and analyze their matching accuracy with actual tooth morphology to propose a new paradigm for using medical data. Methods: Occlusal surface images of the mandibular left first molar scanned using a dental model scanner were analyzed using DCGANs. Overall, 100 training sets comprising 50 original and 50 background-removed images were created, thus generating 1,000 virtual teeth. These virtual teeth were classified based on the number of cusps and occlusal surface ratio, and subsequently, were analyzed for consistency by expert dental technicians over three rounds of examination. Statistical analysis was conducted using IBM SPSS Statistics ver. 23.0 (IBM), including intraclass correlation coefficient for intrarater reliability, one-way ANOVA, and Tukey's post-hoc analysis. Results: Virtual mandibular left first molars exhibited high consistency in the occlusal surface ratio but varied in other criteria. Moreover, consistency was the highest in the occlusal buccal lingual criteria at 91.9%, whereas discrepancies were observed most in the occusal buccal cusp criteria at 85.5%. Significant differences were observed among all groups (p<0.05). Conclusion: Based on the classification of the virtually generated left mandibular first molar according to several criteria, DCGANs can generate virtual data highly similar to real data. Thus, subsequent research in the dental field, including the development of improved neural network structures, is necessary.