• Asian-Australasian Journal of Animal Sciences
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• v.33 no.10
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• pp.1544-1557
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• 2020

Objective: Genomic selection (GS) is becoming popular in animals' genetic development. We, therefore, investigated the single-step genomic best linear unbiased prediction (ssGBLUP) as tool for GS, and compared its efficacy with the traditional pedigree BLUP (pedBLUP) method. Methods: A total of 9,952 males born between 1997 and 2018 under Hanwoo proven-bull selection program was studied. We analyzed body weight at 12 months and carcass weight (kg), backfat thickness, eye muscle area, and marbling score traits. About 7,387 bulls were genotyped using Illumina 50K BeadChip Arrays. Multiple-trait animal model analyses were performed using BLUPF90 software programs. Breeding value accuracy was calculated using two methods: i) Pearson's correlation of genomic estimated breeding value (GEBV) with EBV of all animals (r_M1) and ii) correlation using inverse of coefficient matrix from the mixed-model equations (r_M2). Then, we compared these accuracies by overall population, info-type (PHEN, phenotyped-only; GEN, genotyped-only; and PH+GEN, phenotyped and genotyped), and bull-types (YBULL, young male calves; CBULL, young candidate bulls; and PBULL, proven bulls). Results: The r_M1 estimates in the study were between 0.90 and 0.96 among five traits. The r_M1 estimates varied slightly by population and info-type, but noticeably by bull-type for traits. Generally average r_M2 estimates were much smaller than r_M1 (pedBLUP, 0.40 to0.44; ssGBLUP, 0.41 to 0.45) at population level. However, r_M2 from both BLUP models varied noticeably across info-types and bull-types. The ssGBLUP estimates of r_M2 in PHEN, GEN, and PH+ GEN ranged between 0.51 and 0.63, 0.66 and 0.70, and 0.68 and 0.73, respectively. In YBULL, CBULL, and PBULL, the r_M2 estimates ranged between 0.54 and 0.57, 0.55 and 0.62, and 0.70 and 0.74, respectively. The pedBLUP based r_M2 estimates were also relatively lower than ssGBLUP estimates. At the population level, we found an increase in accuracy by 2.0% to 4.5% among traits. Traits in PHEN were least influenced by ssGBLUP (0% to 2.0%), whereas the highest positive changes were in GEN (8.1% to 10.7%). PH+GEN also showed 6.5% to 8.5% increase in accuracy by ssGBLUP. However, the highest improvements were found in bull-types (YBULL, 21% to 35.7%; CBULL, 3.3% to 9.3%; PBULL, 2.8% to 6.1%). Conclusion: A noticeable improvement by ssGBLUP was observed in this study. Findings of differential responses to ssGBLUP by various bulls could assist in better selection decision making as well. We, therefore, suggest that ssGBLUP could be used for GS in Hanwoo proven-bull evaluation program.

• Journal of Korea Spatial Information System Society
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• v.2 no.2 s.4
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• pp.5-23
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• 2000

Since 1995, national and local governments have competitively initiated many and large GIS projects and audit for the projects becomes an important issue. So far, the audit in the Information Technology(IT) area has tried to deal with the issue but ineffectiveness has been found for the successful GIS project management. Effective auditing is a critical element for the project management. In order to establish a proper audit model for the GIS projects and to promote auditing activities in the projects, this study constructs two hypotheses and tries to prove them. The hypotheses are as follows : 1) For a good audits model for GIS, unique characteristics of a GIS project audit items and the scope of the audit need to be identified. 2) The scope of audit needs to be classified according to the requests from tasks in the projects. To prove the hypotheses, this study analyzes positive aspects of audit in IT and construction projects, clarifies the audit items in GIS projects by comparing with them, and classifies the scope of the GIS audit based on various types of GIS projects. As a results, 5 types of the GIS audit are identified : (1) audit for project management, (2) audit focused on IT, (3) audit characterized by GIS technologies, (4) GIS database audit and (5) consulting services for critical problems in the projects. In addition, 4 criteria in classifying the GIS projects are suggested for the GIS audit. The 4 criteria are domain, scope, duration, and GIS applications technologies. Especially, GIS technology considered in this study includes GIS software, methodologies for GIS development, GIS database and quality control of GIS data, which are not usually reflected in the existing studies about in GIS audit. Because the GIS audit depends on a type of GIS projects, scopes of the audit can be flexibly reconstructed in accordance with the types of GIS projects. This is a key to effective and realistic audit for the future GIS projects. Strategies for effective GIS audit are also proposed in terms of the following: GIS project management, goal establishment in each audit stage, documentation from GIS audit, timing strategies for intensive GIS audit, and designing team structure.

• Journal of Dental Rehabilitation and Applied Science
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• v.26 no.2
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• pp.121-143
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• 2010

To investigate the effect of implant types and bone resorption on the fracture characteristics. 4 types of Osstem$^{(R)}$Implant were chosen and classified into external parallel, internal parallel, external taper, internal taper groups. Finite elements analysis was conducted with ANSYS Multi Physics software. Fatigue fracture test was performed by connecting the mold to the dynamic load fatigue testing machine with maximum load of 600N and minimum load of 60N. The entire fatigue test was performed with frequency of 14Hz and fractured specimens were observed with Hitachi S-3000 H scanning electron microscope. The results were as follows: 1. In the fatigue test of 2 mm exposed implants group, Tapered type and external connected type had higher fatigue life. 2. In the fatigue test of 4 mm exposed implants group, Parallel type and external connected types had higher fatigue life. 3. The fracture patterns of all 4 mm exposed implant system appeared transversely near the dead space of the fixture. With a exposing level of 2 mm, all internally connected implant systems were fractured transversely at the platform of fixture facing the abutment. but externally connected ones were fractured at the fillet of abutment body and hexa of fixture or near the dead space of the fixture. 4. Many fatigue striations were observed near the crack initiation and propagation sites. The cleavage with facet or dimple fractures appeared at the final fracture sites. 5. Effective stress of buccal site with compressive stress is higher than that of lingual site with tensile stress, and effective stress acting on the fixture is higher than that of the abutment screw. Also, maximum effective stress acting on the parallel type fixtures is higher. It is careful to use the internal type implant system in posterior area.

• The Korean Journal of Archival Studies
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• no.39
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• pp.193-228
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• 2014

In recent years, as well as management of public records, interest in the private archive of large and small is growing. Dedicated archive has various types. In addition, lack of personnel and budget, personnel records management professional because the absence, that help you maintain these records in a systematic manner is not easy. Request to the system have continued to rise, but the budget and professionals in order to solve this problem are missing. As breakthrough of the burden to the system with archive dedicated, it introduces the trends and meaning of public recording system, and was examined in detail AtoM function. AtoM is public land can be made by a method that requires a Web service, the database server. Without restrictions, including the advantage of being available free of charge, by the application or operating system specific, installation and operation is convenient. In addition, compatibility, and is highly scalable, AtoM use and convenient archive of private experiencing a shortage of personnel and budget. Because in terms of data management, and excellent interoperability and search share, and use, it is possible in the future, it favors also documentary use through a network of inter-agency archives and private. In addition, Enhancements exhibition services through cooperation with Omeka, long-term storage through Archivematica, many discussion is needed. Public centered around the private area of the recording management spilling expanded, open-source software allows to balance the recording system will be able to play an important role. In addition, the efforts of academia and in the field, close collaboration between the open source recording system through a user study should be continued. Furthermore, co-operation and sharing of private archives expect come true.

• Management & Information Systems Review
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• v.33 no.1
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• pp.191-217
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• 2014

The Purpose of this study is to find the effect factors of R&D investment in SMEs which plays an important role in the national economy, and the differences of the effect factors by the type of SMEs. The subject of this study is about 3,400 SMEs mentioned in "The survey of technical statistics on SMEs in 2007" by Korea Federation of Small and Medium Business. The effect factors are related with the size of business, the infrastructure of R&D and the activities of R&D which have been studied by many researchers. The methods of analysis are regression analysis, moderating effect analysis and the software package used is SPSS 12.0. The results of the study are as fallow. First, it was found that unlike in previous studies which show the effect of the elements of business's size, research infrastructure, research activities on R&D investment, one element alone can't be considered for meaningful result but the various elements have effect on R&D investment at the same time. In other words, the number of employees and the sales as the elements of business's size, the ratio of researchers, the technical ability, the ratio of equipment possession and the intellectual properties as the elements of R&D infrastructure, the activity of ideas and joint research as the elements of R&D activities have positive(+) effect, whereas the participation of CEO in the activity of R&D as the elements of R&D activities activity has negative(-) one. The number of employees, the ratio of researchers, and the sales had relatively high influence whereas equipment possession, technical ability, intellectual properties, the participation of CEO in the research, the activity of idea, joint research had relatively low influence. Next, it was also found that there are differences of the effect factors over the types of SMEs. SMEs were classified into 19 types by eight criteria such as start-ups and existing business by business age; small business and medium business by size; manufacturing business and service business by product type;independent business and subcontractor business by dealing type; businesses in the entering, growing, maturing and restructuring stage by growth stage; businesses with low, medium and high technology by technological level; pioneering business and non-pioneering business by industrial type; and businesses with state-of-the-art technology and non-advanced business by the level of business activities. The meaning of this study lies in the fact that it found the various effect factors should be considered at the same time when conducting study on SMEs' R&D investment, and the differences by the type should be acknowledged. This study surpassed the limitations of the previous studies which focused on a couple of factors and types. This study result can also be considered for other studies on achievement, organization, marketing and others. Moreover, it shows that a differential policy by business type is needed when formulating SME policy.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.1-17
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• 2017

The deep learning framework is software designed to help develop deep learning models. Some of its important functions include "automatic differentiation" and "utilization of GPU". The list of popular deep learning framework includes Caffe (BVLC) and Theano (University of Montreal). And recently, Microsoft's deep learning framework, Microsoft Cognitive Toolkit, was released as open-source license, following Google's Tensorflow a year earlier. The early deep learning frameworks have been developed mainly for research at universities. Beginning with the inception of Tensorflow, however, it seems that companies such as Microsoft and Facebook have started to join the competition of framework development. Given the trend, Google and other companies are expected to continue investing in the deep learning framework to bring forward the initiative in the artificial intelligence business. From this point of view, we think it is a good time to compare some of deep learning frameworks. So we compare three deep learning frameworks which can be used as a Python library. Those are Google's Tensorflow, Microsoft's CNTK, and Theano which is sort of a predecessor of the preceding two. The most common and important function of deep learning frameworks is the ability to perform automatic differentiation. Basically all the mathematical expressions of deep learning models can be represented as computational graphs, which consist of nodes and edges. Partial derivatives on each edge of a computational graph can then be obtained. With the partial derivatives, we can let software compute differentiation of any node with respect to any variable by utilizing chain rule of Calculus. First of all, the convenience of coding is in the order of CNTK, Tensorflow, and Theano. The criterion is simply based on the lengths of the codes and the learning curve and the ease of coding are not the main concern. According to the criteria, Theano was the most difficult to implement with, and CNTK and Tensorflow were somewhat easier. With Tensorflow, we need to define weight variables and biases explicitly. The reason that CNTK and Tensorflow are easier to implement with is that those frameworks provide us with more abstraction than Theano. We, however, need to mention that low-level coding is not always bad. It gives us flexibility of coding. With the low-level coding such as in Theano, we can implement and test any new deep learning models or any new search methods that we can think of. The assessment of the execution speed of each framework is that there is not meaningful difference. According to the experiment, execution speeds of Theano and Tensorflow are very similar, although the experiment was limited to a CNN model. In the case of CNTK, the experimental environment was not maintained as the same. The code written in CNTK has to be run in PC environment without GPU where codes execute as much as 50 times slower than with GPU. But we concluded that the difference of execution speed was within the range of variation caused by the different hardware setup. In this study, we compared three types of deep learning framework: Theano, Tensorflow, and CNTK. According to Wikipedia, there are 12 available deep learning frameworks. And 15 different attributes differentiate each framework. Some of the important attributes would include interface language (Python, C ++, Java, etc.) and the availability of libraries on various deep learning models such as CNN, RNN, DBN, and etc. And if a user implements a large scale deep learning model, it will also be important to support multiple GPU or multiple servers. Also, if you are learning the deep learning model, it would also be important if there are enough examples and references.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.39-70
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• 2017

Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

• Archives of design research
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• v.17 no.2
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• pp.77-86
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• 2004

User-Centered Design Approach plays important role in dealing with usability issues for developing modern technology products. Yet it is still questionable whether the User-Centered approach is enough for the development of successful consumer contents since the User-Centered Design is originated from the software engineering field where meeting customers' functional requirement is the most critical aspect in developing a software. However, modern consumer market is already saturated and in order to meet ever increasing consumer requirements, the User-Centered Design approach needs to be expanded. As a way of incorporating the User-Centered Approach into the consumer product development, Jordan suggested the 'Pleasure-based Approach' in industrial design field, which usually generates multi-dimensional user requirements: 1)physical, 2)cognitive, 3)identity and 4) social. It is the current tendency that many portal and community service providers focus on fulfilling both functional and emotional needs for users when developing new items, contents and services. Previously fulfilling consumers' emotional needs solely depend on visual designer's graphical sense and capability. However, taking the customer-centered approach on withdrawing consumers' unknown needs is getting critical in the competitive market environment. This paper reviews different types of user research techniques and categorized into 6 ways based on Kano(1992)'s product quality model. Based on his theory, only performance factors, such as suability, can be identified through the user-centered design approach. The user-centered design approach has to be expanded to include factors include personality, sociability, pleasure, and so on. In order to identify performance as well as excellent factors through user research, a user-research framework was established and tested through the case study, which is ' the development of new online service for teens '. The results of the user research were summarized at the end of the paper and the pros and cons of each research techniques were analyzed.

• The Journal of Korean Academy of Prosthodontics
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• v.57 no.2
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• pp.110-117
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• 2019

Purpose: This study was to evaluate the wear resistance of 3D printed, milled, and conventionally cured provisional resin materials. Materials and methods: Four types of resin materials made with different methods were examined: Stereolithography apparatus (SLA) 3D printed resin (S3P), digital light processing (DLP) 3D printed resin (D3P), milled resin (MIL), conventionally self-cured resin (CON). In the 3D printed resin specimens, the build orientation and layer thickness were set to $0^{\circ}$ and $100{\mu}m$, respectively. The specimens were tested in a 2-axis chewing simulator with the steatite as the antagonist under thermocycling condition (5 kg, 30,000 cycles, 0.8 Hz, $5^{\circ}C/55^{\circ}C$). Wear losses of the specimens were calculated using CAD software and scanning electron microscope (SEM) was used to investigate wear surface of the specimens. Statistical significance was determined using One-way ANOVA and Dunnett T3 analysis (${\alpha}=.05$). Results: Wear losses of the S3P, D3P, and MIL groups significantly smaller than those of the CON group (P < .05). There was no significant difference among S3P, D3P, and MIL group (P > .05). In the SEM observations, in the S3P and D3P groups, vertical cracks were observed in the sliding direction of the antagonist. In the MIL group, there was an overall uniform wear surface, whereas in the CON group, a distinct wear track and numerous bubbles were observed. Conclusion: Within the limits of this study, provisional resin materials made with 3D printing show adequate wear resistance for applications in dentistry.