• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.23-46
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• 2021

Collaborative filtering, which is often used in personalization recommendations, is recognized as a very useful technique to find similar customers and recommend products to them based on their purchase history. However, the traditional collaborative filtering technique has raised the question of having difficulty calculating the similarity for new customers or products due to the method of calculating similaritiesbased on direct connections and common features among customers. For this reason, a hybrid technique was designed to use content-based filtering techniques together. On the one hand, efforts have been made to solve these problems by applying the structural characteristics of social networks. This applies a method of indirectly calculating similarities through their similar customers placed between them. This means creating a customer's network based on purchasing data and calculating the similarity between the two based on the features of the network that indirectly connects the two customers within this network. Such similarity can be used as a measure to predict whether the target customer accepts recommendations. The centrality metrics of networks can be utilized for the calculation of these similarities. Different centrality metrics have important implications in that they may have different effects on recommended performance. In this study, furthermore, the effect of these centrality metrics on the performance of recommendation may vary depending on recommender algorithms. In addition, recommendation techniques using network analysis can be expected to contribute to increasing recommendation performance even if they apply not only to new customers or products but also to entire customers or products. By considering a customer's purchase of an item as a link generated between the customer and the item on the network, the prediction of user acceptance of recommendation is solved as a prediction of whether a new link will be created between them. As the classification models fit the purpose of solving the binary problem of whether the link is engaged or not, decision tree, k-nearest neighbors (KNN), logistic regression, artificial neural network, and support vector machine (SVM) are selected in the research. The data for performance evaluation used order data collected from an online shopping mall over four years and two months. Among them, the previous three years and eight months constitute social networks composed of and the experiment was conducted by organizing the data collected into the social network. The next four months' records were used to train and evaluate recommender models. Experiments with the centrality metrics applied to each model show that the recommendation acceptance rates of the centrality metrics are different for each algorithm at a meaningful level. In this work, we analyzed only four commonly used centrality metrics: degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality. Eigenvector centrality records the lowest performance in all models except support vector machines. Closeness centrality and betweenness centrality show similar performance across all models. Degree centrality ranking moderate across overall models while betweenness centrality always ranking higher than degree centrality. Finally, closeness centrality is characterized by distinct differences in performance according to the model. It ranks first in logistic regression, artificial neural network, and decision tree withnumerically high performance. However, it only records very low rankings in support vector machine and K-neighborhood with low-performance levels. As the experiment results reveal, in a classification model, network centrality metrics over a subnetwork that connects the two nodes can effectively predict the connectivity between two nodes in a social network. Furthermore, each metric has a different performance depending on the classification model type. This result implies that choosing appropriate metrics for each algorithm can lead to achieving higher recommendation performance. In general, betweenness centrality can guarantee a high level of performance in any model. It would be possible to consider the introduction of proximity centrality to obtain higher performance for certain models.

• Journal of Bio-Environment Control
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• v.18 no.4
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• pp.309-315
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• 2009

Maintenance of adequate soil water content during the period of crop growth is necessary to support optimum plant growth and yields. A better understanding of soil water movement for precision irrigation would allow efficient supply of water to crops, thereby resulting in minimization of water drainage and contamination of ground water. This research reports on the characterization of spatial and temporal variations in water contents through three different textured soils, such as loam, sandy loam, and loamy sand, when water is applied on the soil surface using an one-line drip irrigation system and the soils are dried after the irrigation stops, respectively. Water contents through each soil profile were continuously monitored using three Sentek probes, each consisting of three capacitance sensors at 10, 20, and 30cm depths. Spatial variability in water content for each soil type was strongly influenced by soil textural class. There were big differences in wetting pattern and the rate of downward movement between loam and sandy loam soils, showing that the loam soil had a wider wetting pattern and a slower rate of downward movement than did the sandy loam soil. The wetting pattern in loamy sand soil was not apparent due to a low variability in water content (< 10%) by a lower-water holding capacity as compared to those measured in the loam and sandy loam soils, implying that the rate of water drainage below a depth of 30cm was high. When soils were dried, there were highly exponential relationships between water content and time elapsed after irrigation stops ($r^2$${\geq}$0.98). It was estimated that equilibrium moisture contents for loam, sandy loam, and loamy sand soils would be 17.6%, 6.2%, and 4.2%, respectively.

• Journal of the Korean Society of Radiology
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• v.12 no.1
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• pp.23-30
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• 2018

To evaluate the effect of patient size on effective dose and image quality for Digital Chest Tomosynthesis(DTS) using additional 0.3 mm copper filtration. Eighty artificial nodules were placed in the thorax phantom("Lungman," Kyoto Kagaku, Japan), and Digital Chest Tomosynthesis(DTS) images of the phantom were acquired both with and without added 0.3 mm Cu filtration. To simulate patients of three sizes: small, average size and oversize, one or two 20-mm-thick layer of PMMA(polymethyl methacrylatek) blocks were placed on the phantom. The Effective dose was calculated using Monte Carlo simulations. Two evaluations of image quality methods have been employed. Three readers counted the number of nodules detected in the lung, and the measured contrast-to-noise ratios(CNRs) were used. Data were analyzed statistically. The ED reduced $26{\mu}Sv$ in a phantom, $33{\mu}Sv$ in one 20-mm-thick layer of PMMA block placed on the phantom, and $48{\mu}Sv$ in two 20-mm-thick layer of PMMA blocks placed on the phantom. The Effective dose(ED) differences between DTS with and without filtration were significant(p<0.05). In particular, when we used two 20-mm-thick layer of PMMA blocks placed on the phantom, the ED was significantly reduced by 36% compared with those without additional filtration. Nodule detection sensitivities were not different between with and without added filtration. Differences of CNRs were statistically insignificant(p>0.05). Use of additional filtration allows a considerable dose reduction during Digital Chest Tomosynthesis(DTS) without loss of image quality. In particular, additional filtration showed outstanding result for effective dose reduction on two 20-mm-thick layer of PMMA blocks placed on the phantom. It applies to overweight patients.

• 한국지구물리탐사학회:학술대회논문집
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• 1999.08a
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• pp.137-155
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• 1999

Recently, Televiewer(Borehole Acoustic Scanner(Televiewer)) has come to be widely used specially for the general engineering construction design. The Televiewer tool using a focussed acoustic beam is to detect the amplitude and traveltime of each reflected acoustic signal at the wall, resulting in the amplitude- and traveltime image respectively. Fractures can be well detected, because they easily scatter the acoustic energy due to the highly narrow beam. In addition, the drilling work will rough the borehole wall so that the acoustic energy can be scattered simply due to the roughness of the wall. Thus, the amplitude level can be directed associated with the elastic properties(impedance) and the hardness of the rock as well. Meanwhile, the traveltime image provides an information about the borehole shape and can be converted to a high precision 3D caliper log(max. 288 arms). In this paper, based on the high resolution of Televiewer images, general evaluation methods are illustrated to derive very reliable rock parameters.

• Journal of Dental Rehabilitation and Applied Science
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• v.36 no.3
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• pp.183-195
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• 2020

Purpose: The purpose of this study is to compare the flexural strength of CAD/CAM denture base resins with conventional denture base resins based on their thicknesses. Materials and Methods: For the conventional denture base resins, Lucitone 199^® (C-LC) was used. DIOnavi - Denture (P-DO) and DENTCA Denture Base II (P-DC) were taken for the 3D printing denture base resins. For the prepolymerized PMMA resins, Vipi Block Gum (M-VP) and M-IVoBase^® CAD (M-IV) were used. The final dimensions of the specimens were 65.0 mm x 12.7 mm x 1.6 mm / 2.0 mm / 2.5 mm. The 3-point bend test was implemented to measure the flexural strength and flexural modulus. Microscopic evaluation of surface of fractured specimen was conducted by using a scanning electron microscope (SEM). After testing the normality of the data, one-way ANOVA was adopted to evaluate the differences among sample groups with a significance level of P = 0.05. The Tukey HSD test was performed for post hoc analysis. Results: Under the same thicknesses, there are significant differences in flexural strength between CAD/CAM denture base resins and conventional denture base resins except for P-DO and C-LC. M-VP showed higher flexural strength than conventional denture base resins, P-DC and M-IV displayed lower flexural strength than conventional denture base resins. Flexural modulus was highest in M-VP, followed by C-LC, P-DO, P-DC, M-IV, significant differences were found between all materials. In the comparison of flexural strength according to thickness, flexural strength of 2.5 mm was significantly higher than that of 1.6 mm in C-LC. Flexural strength of 2.5 mm and 2.0 mm was significantly higher than that of 1.6 mm in P-DC and M-VP. In M-IV, as the thickness increases, significant increase in flexural strength appeared. SEM analysis illustrates different fracture surfaces of the specimens. Conclusion: The flexural strength of different CAD/CAM denture base resins used in this study varied according to the composition and properties of each material. The flexural strength of CAD/CAM denture base resins was higher than the standard suggested by ISO 20795-1:2013 at a thickness of 1.6 mm or more though the thickness decreased. However, for clinical use of dentures with lower thickness, further researches should be done regarding other properties at lower thickness of denture base resins.

• Journal of The Korean Association For Science Education
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• v.38 no.6
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• pp.765-780
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• 2018

The purpose of this study is to synthesize the theoretical perspectives, research methods, and research results of teachers' professional vision by reviewing and analyzing previous research papers and to suggest implications for science teacher education and research. Three databases were used to search peer reviewed journal articles published between 1997-2017, which include 'teachers' and 'professional vision' explicitly in abstracts and empirical studies only. 21 articles in total were analyzed and review results are as follows. First, researchers regarded professional vision as a new concept of teacher professionalism. Previous research viewed professional vision as integrated structure of teachers' knowledge or ability activated at specific moment. Second, the analytical framework of professional vision included two aspects; 'selective attention' and 'reasoning'. Several aspects of lessons or the desirable teaching and learning factors are suggested as the subcategories of selective attention. Hierarchical levels or independent reasoning ability factors are suggested as the subcategories of reasoning process. Third, research on teachers' professional vision focused more on middle school teachers than elementary teachers and on various subject areas. Most studies used video clips and more cases of using videos of non-participants were found. In case of measurement of professional vision, most quantitative scoring methods were whether the responses of experts and teachers on video clips were consistent. Last, most studies examined or assessed teachers' professional vision. It is reported that in-service teachers' professional vision was evaluated higher than novice teachers' and using video clips were effective to examine and improve teachers' professional vision.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.31-39
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• 2023

The purpose of this study is to propose a scientific performance evaluation framework for measuring and managing the overall outcome of complex types of projects that are linked to public demand-based commercialization, such as information system projects and public procurement, in integrated national R&D projects. In the case of integrated national R&D projects that involve multiple research institutes to form a single final product, and in the case of demand-based demonstration and commercialization of the project results, the existing evaluation system that evaluates performance based on the short-term outputs of the detailed tasks comprising the R&D project has limitations in evaluating the mid- and long-term effects and practicality of the integrated research products. (Moreover, as the paradigm of national R&D projects is changing to a mission-oriented one that emphasizes efficiency, there is a need to change the performance evaluation of national R&D projects to focus on the effectiveness and practicality of the results.) In this study, we propose a performance evaluation framework from a structural perspective to evaluate the completeness of each national R&D project from a practical perspective, such as its effectiveness, beyond simple short-term output, by utilizing the Hourglass model. In particular, it presents an integrated performance evaluation framework that links the top-down and bottom-up approaches leading to Tool-System-Service-Effect according to the structure of R&D projects. By applying the proposed detailed evaluation indicators and performance evaluation frame to actual national R&D projects, the validity of the indicators and the effectiveness of the proposed performance evaluation frame were verified, and these results are expected to provide academic, policy, and industrial implications for the performance evaluation system of national R&D projects that emphasize efficiency in the future.

• Korean Journal of Heritage: History & Science
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• v.41 no.1
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• pp.5-19
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• 2008

Thirty six samples of Western asia glass vessel shards which were excavated from South Mound of Hwangnamdaechong were each measured for thickness, pore size and specific gravity and analyzed for ten major compositions and thirteen trace elements. The glass samples with colorless, greenish blue and dark purple blue were well classified by principal component analysis(PCA). All glass shards of Hwangnamdaechong belonged to Soda glass system ($Na_2O-CaO-SiO_2$) which have the range of 14~17% $Na_2O$ and 5~6% CaO. The corelation coefficients of (MgO, $K_2O$) and (MnO, CuO) showed above 0.90. The concentrations of thirteen trace elements apparently differentiated from colorless, greenish blue and dark blue glasses. We found that thirteen trace elements were very important indices for studying raw material of glass and the origin of glass making. Colorless glass : The specific gravity is $1.50{\pm}0.04$. Circle or oval circle pores are observed with regular direction in internal zone and the longest one is about 0.35 mm. The raw material of sodium must be the plant ash because sodium glasses contain HCLA(High CaO, Low $Al_2O_3$) and HMK(high MgO, high $K_2O$) and suggested to Sasanian glass. The total amount of coloring agent of colorless glass is below 1 % which is too small to attribute to the color. Greenish blue glass : The specific gravity is $1.58{\pm}0.04$. The fine pores which are 0.1~0.2mm are dispersed in internal zone. Sodium glasses are distributed to HCLA and HMK. Therefore the greenish blue glass also have used plant ash for raw material of sodium with the same as colorless glass. It was also suggested to the glass of Sasanian. The total amount of coloring agent of greenish blue glass is about 4% under the influence of working MnO, $Fe_2O_3$ and CuO. Dark purple blue glass : The specific gravity is $1.48{\pm}0.19$. There are rarely pores in internal zone. They are distributed to HCLA and LMK(Low MgO, Low $K_2O$) and suggested to Roman glass. The raw material of sodium is estimated to natron. The total amount of coloring agents of greenish blue is about 3% by $Fe_2O_3$ and CuO. These studies for western asia glass shards from South Mound of Hwangnamdaechong could be used in the future as the standard data which could be compared with those of other several graves in Korea and dispersed in foreign areas.