• Educational Technology International
• /
• v.10 no.1
• /
• pp.25-40
• /
• 2009

The purpose of this study was to explore procedures and modalities on collaborative visualization processing of text information for developing e-Learning contents. In order to investigate, two research questions were explored: 1) what are procedures on collaborative visualization processing of text information, 2) what kinds of patterns and modalities can be found in each procedure of collaborative visualization of text information. This research method was employed a qualitative research approaches by means of grounded theory. As a result of this research, collaborative visualization processing of text information were emerged six steps: identifying text, analyzing text, exploring visual clues, creating visuals, discussing visuals, elaborating visuals, and creating visuals. Collaborative visualization processing of text information came out the characteristic of systemic and systematic system like spiral sequencing. Also, another result of this study, modalities in collaborative visualization processing of text information was divided two dimensions: individual processing by internal representation, social processing by external representation. This case study suggested that collaborative visualization strategy has full possibility of providing ideal methods for sharing cognitive system or thinking system as using human visual intelligence.

• Asian-Australasian Journal of Animal Sciences
• /
• v.30 no.4
• /
• pp.569-575
• /
• 2017

Objective: The objective of this research was to study the electrical properties and quality of frozen-thawed chicken breast meat and to investigate the relationship between these parameters at different times of frozen storage. Methods: Thawed samples of chicken breast muscles were evaluated after being kept in frozen storage at $-18^{\circ}C$ for different periods of time (1, 2, 3, 4, 5, 6, 7, and 8 months). Results: The results showed that water-holding capacity (WHC) and protein solubility decreased while thiobarbituric acid-reactive substances content increased with increasing storage time. The impedance module of samples decreased during 8-month frozen storage. Pearson correlation coefficients showed that the impedance change ratio (Q value) was significantly (p<0.05) related to pH, color, WHC, lipid oxidation and protein solubility, indicating a good relationship between the electrical properties and qualities of frozen-thawed chicken breast meat. Conclusion: Impedance measurement has a potential to assess the quality of frozen chicken meat combining with quality indices.

• Asian-Australasian Journal of Animal Sciences
• /
• v.30 no.2
• /
• pp.236-245
• /
• 2017

Objective: The study was to investigate the effects of alanyl-glutamine (Ala-Gln) and glutamine (Gln) supplementation on the intestinal mucosa barrier in piglets. Methods: A total of 180 barrows with initial weight $10.01{\pm}0.03kg$ were randomly allocated to three treatments, and each treatment consisted of three pens and twenty pigs per pen. The piglets of three groups were fed with control diet [0.62% alanine (Ala)], Ala-Gln diet (0.5% Ala-Gln), Gln diet (0.34% Gln and 0.21% Ala), respectively. Results: The results showed that in comparison with control diet, dietary Ala-Gln supplementation increased the height of villi in duodenum and jejunum (p<0.05), Gln supplementation increased the villi height of jejunum (p<0.05), Ala-Gln supplementation up-regulated the mRNA expressions of epidermal growth factor receptor and insulin-like growth factor 1 receptor in jejunal mucosa (p<0.05), raised the mRNA expressions of Claudin-1, Occludin, zonula occludens protein-1 (ZO-1) and the protein levels of Occludin, ZO-1 in jejunal mucosa (p<0.05), Ala-Gln supplementation enlarged the number of goblet cells in duodenal and ileal epithelium (p<0.05), Gln increased the number of goblet cells in duodenal epithelium (p<0.05) and Ala-Gln supplementation improved the concentrations of secretory immunoglobulin A and immunoglobulin G in the jejunal mucosa (p<0.05). Conclusion: These results demonstrated that dietary Ala-Gln supplementation could maintain the integrity of small intestine and promote the functions of intestinal mucosa barriers in piglets.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.14-15
• /
• 2007

Now-a-days, data and task migration in collaborative work provides enormous facilities to users. Here, we propose an ontology-based information management scheme to facilitate data and task migration in collaborative work. This ontologybased model will help us to organize huge information (e.g. device status, runtime state etc.) efficiently.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.6
• /
• pp.2310-2332
• /
• 2020

In recent years, deep learning techniques have achieved tremendous successes in natural language processing, speech recognition and image processing. Collaborative filtering(CF) recommendation is one of widely used methods and has significant effects in implementing the new recommendation function, but it also has limitations in dealing with the problem of poor scalability, cold start and data sparsity, etc. Combining the traditional recommendation algorithm with the deep learning model has brought great opportunity for the construction of a new recommender system. In this paper, we propose a novel collaborative recommendation model based on auxiliary stacked denoising autoencoder(ASDAE), the model learns effective the preferences of users from auxiliary information. Firstly, we integrate auxiliary information with rating information. Then, we design a stacked denoising autoencoder based collaborative recommendation model to learn the preferences of users from auxiliary information and rating information. Finally, we conduct comprehensive experiments on three real datasets to compare our proposed model with state-of-the-art methods. Experimental results demonstrate that our proposed model is superior to other recommendation methods.

• Journal of Information Processing Systems
• /
• v.15 no.3
• /
• pp.616-631
• /
• 2019

With the rapid increase of information on the World Wide Web, finding useful information on the internet has become a major problem. The recommendation system helps users make decisions in complex data areas where the amount of data available is large. There are many methods that have been proposed in the recommender system. Collaborative filtering is a popular method widely used in the recommendation system. However, collaborative filtering methods still have some problems, namely cold-start problem. In this paper, we propose a movie recommendation system by using social network analysis and collaborative filtering to solve this problem associated with collaborative filtering methods. We applied personal propensity of users such as age, gender, and occupation to make relationship matrix between users, and the relationship matrix is applied to cluster user by using community detection based on edge betweenness centrality. Then the recommended system will suggest movies which were previously interested by users in the group to new users. We show shown that the proposed method is a very efficient method using mean absolute error.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2013.11a
• /
• pp.1156-1157
• /
• 2013

The mobile application market has been growing extensively in recent years. Currently, Apple's App Store has more than 400,000 applications and Google's Android Market has above 150,000 applications. Such growth in volumes of mobile applications has created a need to develop a recommender system that assists the users to take the right choice, when searching for a mobile application. In this paper, we study the recommendation system building tools based on collaborative filtering. Specifically, we present a study on comparison analysis of collaborative filtering in Java and R statistical software. We implement the collaborative filtering using Java's Apache Mahout and R's recommenderlab package. We evaluate both methods and describe the advantages and disadvantages of using them in order to implement collaborative filtering.

• International Journal of Advanced Culture Technology
• /
• v.8 no.3
• /
• pp.223-230
• /
• 2020

Companies have made an investment of cost and time to optimize processing of a new business model in a cloud environment, applying collaboration technology utilizing business processes in a social network. The collaborative processing method changed from traditional BPM to the cloud and a mobile cloud environment. We proposed a collaborative system for operating processes in social networks using MOXMDR-DAI+ (eXtended Metadata Registry-Data Access & Integration based multimedia ontology). The system operating cloud-based collaborative processes in application of MOXMDR-DAI+, which was suitable for data interoperation. MOXMDR-DAI+ applied to this system was an agent effectively supporting access and integration between multimedia content metadata schema and instance, which were necessary for data interoperation, of individual local system in the cloud environment, operating collaborative processes in the social network. In operating the social network-based collaborative processes, there occurred heterogeneousness such as schema structure and semantic collision due to queries in the processes and unit conversion between instances. It aimed to solve the occurrence of heterogeneousness in the process of metadata mapping using MOXMDR-DAI+ in the system. The system proposed in this study can visualize business processes. And it makes it easier to operate the collaboration process through mobile support. Real-time status monitoring of the operation process is possible through the dashboard, and it is possible to perform a collaborative process through expert search using a community in a social network environment.

• Journal of Information Processing Systems
• /
• v.9 no.1
• /
• pp.157-172
• /
• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.2
• /
• pp.355-364
• /
• 2000

Application sharing for collaborative works make multiple participants to be capable of collaborative developments through sharing development tools and applications which is distributed to various system without spatial restriction. However, applying legacy application sharing to CSCW based virtual environment has a problem because it dont consider 3D space and it disturbs the harmonic interaction of participants. In this study, we designed application sharing system for collaborative works in 3D virtual environment to share application effectively on collaborative virtual environment. The designed application sharing system for collaborative works in 3D virtual environment consist of application sharing manager, group manager and communication manager. This system is able to perceive event of 3D space about application of participant on 3D virtual environment by agent which moves to participant sites and get an ordered events and conflict among participants through scheduling. Therefore, designed application sharing system for collaborative work in 3D virtual environment can support efficient collaborative works and improve reusability of legacy application through using easily legacy application in 3D virtual environment when CSCW application development for virtual environments.