• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.71-88
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• 2017

Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Life Science
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• v.22 no.7
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• pp.871-879
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• 2012

Polyploids are a potentially important germplasm source in seedless citrus breeding program. Seedlessness is one of the most promising traits of commercial mandarin breeds that mandarin triploid hybrids possess permanently. The formation of new constant triploid hybrids can be recovered through diploid species hybridization from the fusion of divalent gametes at low frequencyor intra-and inter-ploidy crosses. However, extensive breeding work based on small $F_1$ hybrid seeds developed is impossible without a very effective aseptic methodology and ploidy event. In this study, in vitro embryo culture was employed to recover natural hybrids from monoembryonic diploid, open-pollinated mandarin. Flow cytometry was used to determine ploidy level. A total of 10,289 seeds were extracted from 792 fruits having approximately 13 seeds per fruit. Average frequency of small seeds developed was 7.1%, while the average frequency of small seeds per fruit were: 8.9% for 'Clementine' 10.2% for 'Harehime' 2.6% for 'Kamja' 3.1% for 'Pyunkyool' 2.8% for 'Sadookam' and 7.0% for 'Wilking' mandarin. Average size of a perfect seed was $49.52{\pm}0.07mm^2$ ('Clementine') while the small seed measured $7.95{\pm}0.04mm^2$ ('Clementine'), which was about 1/6 smaller than the perfect seed. In total, 731 small seeds were obtained and all of them contained only one embryo per seed. The efficiency of 'Clementine' was 14 times higher than 'Wilking' and more than 109 times higher than 'Pyunkyool'. The basic information on spontaneous polyploidy provides for the hybridization of constant triploids and increases the efficiency of conventional cross.

• The korean journal of orthodontics
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• v.27 no.5 s.64
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• pp.815-824
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• 1997

The purpose of this study is to develop the basic algorithm for the finite element method modeling of individual malocclusions. Usually, a great deal of time is spent in preprocessing. To reduce the time required, we developed a standardized procedure for measuring the position of each tooth and a program to automatically preprocess. The following procedures were carried to complete this study. 1. Twenty-eight teeth morphologies were constructed three-dimensionally for the finite element analysis and saved as separate files. 2. Standard brackets were attached so that the FA points coincide with the center of the brackets. 3. The study model of a patient was made. 4. Using the study model, the crown inclination, angulation, and the vertical distance from the tip of a tooth was measured by using specially designed tools. 5. The arch form was determined from a picture of the model with an image processing technique. 6. The measured data were input as a rotational matrix. 7. The program provides an output file containing the necessary information about the three-dimensional position of teeth, which is applicable to several finite element programs commonly used. The program for a basic algorithm was made with Turbo-C and the subsequent outfile was applied to ANSYS. This standardized model measuring procedure and the program reduce the time required, especially for preprocessing and can be applied to other malocclusions easily.

• Korean Journal of Environment and Ecology
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• v.34 no.1
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• pp.9-17
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• 2020

Domestic cats (Felis catus) introduced to insular environments can be invasive predators that often threaten endemic species and cause biodiversity loss or local extinction on the island. This study was conducted from March to July 2018 to understand the population size, home range, and spatial use of cats introduced to Mara Islet (N 33° 07', E 126° 16') in Jeju Special Governing Province, the Republic of Korea. Observation records based on their natural marks revealed that there were 20 adult cats on Mara Islet. A capture-recapture method also estimated 20 adult individuals (95% confidence interval: 20-24 individuals). According to our telemetry study on ten adults deployed with GPS-based telemetry units, the home range size was 12.05±6.99 ha (95% KDE: kernel density estimation), and the core habitat size was 1.60±0.77 ha (50% KDE). There were no significant differences in the home range and core habitat sizes by sex. The home range of domestic cats overlapped with the human residential area, where they might secure easy foods. Five of ten tracked cats were active at potential breeding colonies for the Crested Murrlet (Synthliboramphus wumizusume), and six approached potential breeding areas of the Styan's Grasshopper Warbler (Locustella pleskei), suggesting the predation risk of the two endangered species by cats. This study provides novel information on the population size and home range of introduced cats on Mara Islet which is an important stopover site of migratory birds as well as a breeding habitat of the two endangered avian species. Reducing the potential negative impacts of the introduced cats on migratory birds and the endangered species on Mara Islet requires monitoring of the predation rate of birds by cats, the population trends of cats and endangered breeding birds as well as the effective cat population control and management.

• Journal of Food Hygiene and Safety
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• v.20 no.1
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• pp.22-35
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• 2005

A survey was conducted to investigate the perception of food sanitation officers toward the Genetically Modified Foods. They were mainly from Regional Agencies of KFDA, City/Province office, and National quarantine station. Some of them were professors of university and researchers of research institute. Most of respondents had experiences of hearing or reading GM foods (over $95\%$) and over $90\%$ of respondents much needed the label of GM foods. Although some of officers of city/province office and national quarantine station showed less knowledge than other respondent groups, most of respondents had basic knowledge about biology. The frequency of respondents worked over 20 years and worked in the general administration was higher than that of other groups in the question of unsafe of GM foods. The answer frequency of careless treatment of foods was highest in the question of risk factor, and the frequency of GM foods was lowest ($4.4\%$). It was concluded that food sanitation officers had positive opinion about GM foods, but there were some differences in the knowledge among agencies. Therefore, it is necessary more educations and informations are needed for food sanitation officers.

• The Korean Journal of Nuclear Medicine Technology
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• v.22 no.1
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• pp.23-27
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• 2018

Purpose The introduction of bone scan has been reported as a useful tool in the diagnosis, treatment, and treatment response of skeletal disease. The purpose of this study is to improve the anatomical information and tolerance of the bone by combining bone scan and pelvic X-ray without additional radiation exposure. Materials and Methods From November 2015 to August 2016, 236 patients(64 men and 172 women, average age $50.96{\pm}15.39years$) take Bone scan and Pelvis AP(Anteroposterior) X-ray scan at the National Cancer Center. The scan equipment was a gamma camera, Symbia Ecam (SIEMENS, Germany), and a digital x-ray, DRS-800 (Listem, Korea). Osirix version 3.8.1 (Osirix, USA) and Stata/SE version 14.0 (StataCorp, USA) were used for image combination and analysis. The patient was intravenously injected with $^{99m}Tc-DPD$ (740 MBq), and the scan was performed 2 to 4 hours later. Gamma camera image acquisition were Matrix size $256{\times}1024$, Zoom 1.00, and scan speed 17 cm/min. The digital X-ray was made with a collimator size of $14^{{\prime}{\prime}}{\times}17^{{\prime}{\prime}}$, 77 kVp (60 to 97 kVp) and an average of 30 mAs (20 to 48). ASIS and pubic symphysis Select virtual points then Combine three virtual points and pelvic contour lines. The acquired images were evaluated by three radiologists who worked for more than 5 years in the nuclear medicine department. Results Of the total 236 patients, 216 (91.53%) were matched. The median and range (min~max) of the age were 67 (46~81) years old in the unmatched group and 52 (22~87) years old in the matched group, The Wilcoxon rank-sum test was performed to determine whether age was different between the two groups. As a result, the age difference between the two groups was statistically significant at p < 0.0001. Of the 64 men, 60 (93.75%) were match and of the 172 women, 156 (93.75%) were match. There was no statistically significant difference according to gender(p = 0.4542). Of the 54 patients without pelvic lesions, 54 (100.00%) were match, and 162 (89.01%) of 182 patients with pelvic lesions were match. There was a statistically significant difference according to the presence of pelvic lesions. Conclusion There are many variables in the combination of bone scan and pelvic X-ray imaging, and the patient's age and pelvic lesion may have some effect on the image combination. This study is expected to be useful for the diagnosis of pelvic osteosarcoma of children without radiation exposure. It is expected that this combination of images will help to develop the nuclear medicine image.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.10-25
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• 2011

Since 1950, the city of Yokohama has been demanding the return of US. military base sites in Yokohama. Yokohama has established a systematic utilization plan for these relocation sites. The Fukaya communication site is one of former US. military bases verified for return in 2004. The Fukaya communication site is distinctively circular in shape and is entirely national land. Yokohama took an idea competition to its citizens to create a new park at the relocation of the Fukaya communication site, involving lots of citizen opinion in its utilization goals. This study determined the process of the idea competition at the Fukaya communication site in encouraging civic participation and analyzing citizen demands for the utilization of the relocation site. Through the idea competition, Yokohama city was able to obtain several ideas on the new park from various angles such as the function and shape of the urban open spaces. Citizens showed great interest in creating a park as green infrastructure on the Fukaya communication site. In addition, beyond utilization as an urban open space, many ideas suggested new lifestyles for the region in connection with the natural environment in the vicinity. Yokohama city tried to share the process and results of the idea competition with as many citizens as it could through a variety of means such as Participation, Judging, Support, Observation and Understanding. The case study on the idea competition at the Fukaya communication site is a good example of community design practice in public projects, and is full of suggestions for military bases in Korea, which has just established the plan of utilizing relocation sites as parks. Based on this case study, it can be concluded that it is important to make a systemic form for utilization planning with a clear process, open information and partnership in a variety of participatory design processes in order to ensure maximum civic utilization of relocation sites.

• Korean Journal of Cognitive Science
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• v.27 no.2
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• pp.159-219
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• 2016

Mathematical ability is important for academic achievement and technological renovations in the STEM disciplines. This study concentrated on the relationship between neural basis of mathematical cognition and its mechanisms. These cognitive functions include domain specific abilities such as numerical skills and visuospatial abilities, as well as domain general abilities which include language, long term memory, and working memory capacity. Individuals can perform higher cognitive functions such as abstract thinking and reasoning based on these basic cognitive functions. The next topic covered in this study is about individual differences in mathematical abilities. Neural efficiency theory was incorporated in this study to view mathematical talent. According to the theory, a person with mathematical talent uses his or her brain more efficiently than the effortful endeavour of the average human being. Mathematically gifted students show different brain activities when compared to average students. Interhemispheric and intrahemispheric connectivities are enhanced in those students, particularly in the right brain along fronto-parietal longitudinal fasciculus. The third topic deals with growth and development in mathematical capacity. As individuals mature, practice mathematical skills, and gain knowledge, such changes are reflected in cortical activation, which include changes in the activation level, redistribution, and reorganization in the supporting cortex. Among these, reorganization can be related to neural plasticity. Neural plasticity was observed in professional mathematicians and children with mathematical learning disabilities. Last topic is about mathematical creativity viewed from Neural Darwinism. When the brain is faced with a novel problem, it needs to collect all of the necessary concepts(knowledge) from long term memory, make multitudes of connections, and test which ones have the highest probability in helping solve the unusual problem. Having followed the above brain modifying steps, once the brain finally finds the correct response to the novel problem, the final response comes as a form of inspiration. For a novice, the first step of acquisition of knowledge structure is the most important. However, as expertise increases, the latter two stages of making connections and selection become more important.