• The Journal of Information Systems
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• v.20 no.3
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• pp.41-61
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• 2011

In order to buy products through the Internet, consumers dissipate much time and efforts in collecting and comparing product information from various online shopping malls. Consumers can save their efforts by using price comparison sites, but there are some shortcomings in comparison shopping. Firstly, comparison sites do not show the lowest price of some products that are selling in shopping malls. Secondly, the product information provided by comparison sites is sometimes wrong. Thirdly, there are too many results. In order to overcome the shortcomings, we suggested a comparison shopping system based on RSS by using ontology matching. We used the current RSS standard for syntactic interoperability instead of suggesting new standards. Moreover, we used ontology matching for semantic interoperability to compare product information with different ontologies. The suggested ontology matching consists of three steps. The first step is finding exact sense from WordNet for a given product category, and the second step is searching for matching product category candidates from the products of RSS feeds. The final step is calculating similarities of the candidates with the target product category. From the experiments, we could get better recall rates that are suitable for e-commerce environments and the results show that our system is effective in product comparison.

• Journal of Digital Convergence
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• v.12 no.12
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• pp.365-370
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• 2014

The existing system consumes a considerable amount time and cost for extracting the patterns from whole sequences or misaligned sequences. In this paper, We propose the classification system, which creates the partition sequence sections using multiple sequence alignment method and extracts the sequential patterns from these section. These extracted patterns are accumulated motif candidate sets and then used the training sets of SVM classifier. This proposed system predicts a HPV-type(high/low) using the learned knowledges from known/unknown protein sequences and shows more improved precision, recall than previous system in 30% minimum support.

• Journal of The Korean Astronomical Society
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• v.47 no.6
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• pp.209-214
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• 2014

In this study we develop a set of solar proton event (SPE) forecast models with NOAA scales by Multi Layer Perceptron (MLP), one of neural network methods, using GOES solar X-ray flare data from 1976 to 2011. Our MLP models are the first attempt to forecast the SPE scales by the neural network method. The combinations of X-ray flare class, impulsive time, and location are used for input data. For this study we make a number of trials by changing the number of layers and nodes as well as combinations of the input data. To find the best model, we use the summation of F-scores weighted by SPE scales, where F-score is the harmonic mean of PODy (recall) and precision (positive predictive value), in order to minimize both misses and false alarms. We find that the MLP models are much better than the multiple linear regression model and one layer MLP model gives the best result.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.sup3
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• pp.213-218
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• 2016

Cancer is a major health problem in the Arab region including Iraq. An adequate database is essential for effective cancer control strategies. Such a database may be provided through cancer registration but supportive household surveys may be useful. This article reports selected results on the feasibility of household surveys to support and validate cancer registration in Basrah governorate - southern Iraq. A large scale multi-stage cluster sample household survey was carried out in Basrah during 2013. It covered 6,999 households and involved gathering data on demographic characteristics and both incident cancer cases and cancer-related deaths among members of these households during a three-year recall period (2010-2012). The data obtained yielded an average annual incidence rate of 91 per 100,000 population (age-standardized incidence rate of 148.8 /100,000) and cancer specific mortality rate of 68 per 100,000 population (age-standardized mortality rate of 126.3/100,000). The results showed an overall pattern of cancer similar to that reported according to cancer registration but the household survey results were consistently higher than those of the cancer registration by a margin of approximately 20- 30% with respect to incident cancer and about 70 % with respect to cancer-specific mortality. Household surveys on cancer, while costly and time consuming, are a very useful additional source of information on cancer at the population level. They can be performed for specific purposes with effective resource mobilization.

• Journal of Information Processing Systems
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• v.16 no.2
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• pp.435-446
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• 2020

With the ability to learn rules from training data, the machine learning model can classify unknown objects. At the same time, the dimension of hyperspectral data is usually large, which may cause an over-fitting problem. In this research, an identification methodology of tea diseases was proposed based on spectral reflectance and machine learning, including the feature selector based on the decision tree and the tea disease recognizer based on random forest. The proposed identification methodology was evaluated through experiments. The experimental results showed that the recall rate and the F1 score were significantly improved by the proposed methodology in the identification accuracy of tea disease, with average values of 15%, 7%, and 11%, respectively. Therefore, the proposed identification methodology could make relatively better feature selection and learn from high dimensional data so as to achieve the non-destructive and efficient identification of different tea diseases. This research provides a new idea for the feature selection of high dimensional data and the non-destructive identification of crop diseases.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.1
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• pp.73-79
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• 2000

A material of 48 patients with 60 avulsed and replanted permanent teeth were followed retrospectively in the period of 1996. 1 to 1998. 12 (mean observation period=1year 7months). The age of the patients at the time of replantation ranged from 9 to 63 years (mean=24 years). Clinical records of patients were reviewed to obtain valid data concerning the extent of injury and treatment provided. Pulpal and periodontal healing states were examined with periapical x-rays and clinical examination procedures (i.e. percussion test and mobility test) at their recall visit. Root ankylosis was found in fifty-two teeth(87%) and root resorption in twenty-four(40%). Only two of the replanted teeth(3%) showed partial regeneration of the periodontal ligament. Six teeth(10%) resulted in tooth loss, but the remaining fifty-four were clinically well functioning. Most of teeth have mild marginal bone loss accompanied by gingival retraction without pathological periodontal pockets. The incidence of root resorption was much higher in younger age group. However, it was not affected by the interval between avulsion and replantation, the condition of supporting tissues, the degree of root formation and the type of splinting, indicating that multiple factors involved in determining the prognosis of replanted teeth. Based on these findings, avulsed teeth in unfavorable conditions (i.e. long extra-alveolar periods, etc.) should be preserved if possible.

• Journal of Periodontal and Implant Science
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• v.44 no.3
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• pp.118-125
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• 2014

Purpose: The present split mouth study evaluates the effect of nonsurgical periodontal treatment on the gingival crevicular fluid (GCF) leptin level in chronic periodontitis. Methods: Ninety sites from 30 nonobese chronic periodontitis patients were selected and divided as follows: group I, 30 healthy sites receiving no treatment; group II, 30 periodontitis sites receiving scaling and root planing (SRP); and group III, 30 periodontitis sites receiving SRP with tetracycline local drug delivery. At baseline, after GCF sampling and clinical parameter recording, the assigned treatment was performed for the study groups. During recall visits, GCF sampling followed by clinical parameter recording was done for groups II and III. Results: Reductions in the probing depth and the clinical attachment level (CAL) were highly significant at different time intervals (except between day 0 and 45) in both groups II and III. Upon comparison, group III showed significant gain in CAL between day 0 and 15 and between day 0 and 45. After treatment, the reduction in the GCF leptin level was more significant in group III than in group II at day 15 but re-elevated almost to the pretreatment levels at day 45. Conclusions: Nonsurgical periodontal therapies were not effective in maintaining stable reduction in the GCF leptin level during the study period.

• The Journal of Korean Association of Computer Education
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• v.10 no.5
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• pp.61-69
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• 2007

The subjective-type evaluation can estimate the high-recognition ability, but has the problem of the objectivity and reliability of the evaluation, and the difficulty of Korean language processing. To solve the problem, this paper designs and implements a subjective-type evaluation system using syntactic and case-role information. This system can reduce the time and endeavor for evaluation and provide the objectivity of the evaluation. The system results the 75% success rate to the instructor evaluation and gets the better precision and recall than the word extraction evaluation system. We expect that this system will become a basis of the research on the subjective-type evaluation.

• Journal of the Semiconductor & Display Technology
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• v.13 no.4
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• pp.91-96
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• 2014

Mobile image retrieval is one of the most exciting and fastest growing research fields in the area of multimedia technology. As the amount of digital contents continues to grow users are experiencing increasing difficulty in finding specific images in their image libraries. This paper proposes a new efficient and effective mobile image retrieval method that applies a weighted combination of color and texture utilizing spatial-color and second order statistics. The system for mobile image searches runs in real-time on an iPhone and can easily be used to find a specific image. To evaluate the performance of the new method, we assessed the iPhone simulations performance in terms of average precision and recall using several image databases and compare the results with those obtained using existing methods. Experimental trials revealed that the proposed descriptor exhibited a significant improvement of over 13% in retrieval effectiveness, compared to the best of the other descriptors.

• IE interfaces
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• v.18 no.2
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• pp.178-183
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• 2005

In this study, changes in memory performance, blood oxygen saturation and heart rate according to 30% concentration oxygen supply were observed. Ten healthy male and female college students (male:$25.8{\pm}0.8$ years, female: $24.2{\pm}1.9$ years) participated in the study. The experiment was performed as Rest (1min.), Control task (1min.), Word presentation (1min.), Reaction time task (1min.), Distractor (2min.), and Word recall (1min.) and the physiological signals such as blood oxygen saturation and heart rate were measured throughout the stages. Subjects who received 30% oxygen recalled more words than those who received 21% oxygen, which shows 30% oxygen supply has influenced positively on memory cognitive performance. When 30% concentration oxygen is supplied, the blood oxygen saturation in the task phases was increased and the heart rate decreased when comparing to 21%. It means that 30% oxygen can stimulate brain activation by increasing actual blood oxygen concentration in the process of cognitive performance, and the heart rate decreases because enough oxygen is supplied to process the cognitive performance.