• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• KIISE Transactions on Computing Practices
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• v.22 no.7
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• pp.338-343
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• 2016

Today, opinion reviews on the Web are often used as a means of information exchange. As the importance of opinion reviews continues to grow, the number of issues for opinion spam also increases. Even though many research studies on detecting spam reviews have been conducted, some limitations of gold-standard datasets hinder research. Therefore, we introduce a new dataset called "Paraphrased Opinion Spam (POS)" that contains a new type of review spam that imitates truthful reviews. We have noticed that spammers refer to existing truthful reviews to fabricate spam reviews. To create such a seemingly truthful review spam dataset, we asked task participants to paraphrase truthful reviews to create a new deceptive review. The experiment results show that classifying our POS dataset is more difficult than classifying the existing spam datasets since the reviews in our dataset more linguistically look like truthful reviews. Also, training volume has been found to be an important factor for classification model performance.

• Journal of the Korean Society for Library and Information Science
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• v.42 no.2
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• pp.87-108
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• 2008

The purpose of standards and guidelines of library service for people with disability is to provide libraries, governments and other stakeholders with a framework for developing library services for people with disability. This Paper is to Identify the constituents of standards and guidelines of library service for people with disability. These constituents are developed by analysis and investigation of foreign standards and are based on many people's advice such as members of the advisory committee. Extracted constituents of standards and guidelines of library service for people with disability are as follows: physical accessibility to library building and facilities, construction of alternative formats, access to services and programs. assistance engineering devices, web accessibility and universal design, training and staff development, cooperation and networking etc. Finally, we clarified main contents of each element to be included in standard.

• Journal of Gifted/Talented Education
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• v.25 no.2
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• pp.261-277
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• 2015

The purposes of this study were to find out what attitude teachers have toward adopting ICT education to educational programs for gifted students, and how ready they are for carrying out ICT education for gifted students. For these purposes, this study surveyed 191 teachers that are currently working for gifted students in various school levels, from elementary schools to junior high and high schools. The major results of this study were as follow: (1) most teachers recognized that enhancing ICT-related capabilites of gifted students is very important, and (2) ICT-related activities in current education programs for gifted students are limited to the basic level, such as web searching for collecting information and making visual presentations using well-known commercial software. Based on the common recognition on the importance of ICT-related capabilites for gifted students, this study suggests that training teachers, as well as employing well-trained teachers, should be the first and most important step for ICT education for gifted students.

• Health Policy and Management
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• v.23 no.1
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• pp.52-58
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• 2013

This study was conducted to investigate the responsiveness and its related factors of public health center for novel influenza A (H1N1) epidemic. The data was collected through a web-based survey conducted during February to April 2011. The 182 respondents were team leaders or persons who were responsible for H1N1-related work at public health centers during the H1N1 prevalence. The related factors affecting the responsiveness were different by urban or rural area. In the level of gu (urban) area, cooperation with the public organizations, preparing its own response plan were the significant factors. But, in the level of si or gun (rural) area, cooperation with private organizations (clinic or pharmacy), physical (facilities, equipments, and medicines), and human infrastructures (public health professions, education and knowledge, and motivation) were more important factors. Therefore, how to cope with H1N1 prevalence in the future should be different by local characteristics. As a result, there are several challenges that public health centers should prepare for the further emerging infectious diseases. First, it is needed to make standard manuals which could strengthen education and training in order to respond appropriately, as well as to prepare enough physical infrastructures for the crisis. Next, the public health center should prepare correct media response and cooperation system with public and private organizations.

• Journal of Korean Library and Information Science Society
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• v.30 no.2
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• pp.1-28
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• 1999

This study aims to provide some rosie material for the libraries to improve its role for supporting the virtual university by recognizing the changing roles to have to support the distance education which is becoming a growing area in the coming new century due to the necessity of continuing renewal and the retaining of the information related workers. Through the study, a few conclusions were derived. (1) To support the virtual university, the library services should be directed toward the operation of the full access - philosophy and should reflect the information needs of the off-campus students. The librarians should be equipped with the ability to make use of networked resources and to provide the document delivery services together with the ability to develop the web-based user training programs. The department of library and Information Science should educate the future librarian for the purpose of supporting the virtual university. (2) A written and agreed guidelines should be established to specify the philosophy, management, facilities, resources and services to support the virtual university. And it is desirable that in the near future the department and a librarian responsible for the supporting the distance education should be established.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.113-121
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• 2005

Since documents on the Web are naturally partitioned into many document databases, the efficient information retrieval (IR) process requires identifying the document databases that are most likely to provide relevant documents to the query and then querying the identified document databases. We first introduce a neural net agent for such an efficient IR, and then propose the hierarchically organized multi-agent IR system in order to scale our agent with the large number of document databases. In this system, the hierarchical organization of neural net agents reduced the total training cost at an acceptable level without degrading the IR effectiveness in terms of precision and recall. In the experiment, we introduce two neural net IR systems based on single agent approach and multi-agent approach respectively, and evaluate the performance of those systems by comparing their experimental results to those of the conventional statistical systems.

• Journal of radiological science and technology
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• v.27 no.4
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• pp.61-66
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• 2004

In order to improve an efficiency of education and acquisition of PACS administor in Radiological technologist, we implement an e-Learing databank system providing more efficiently provide medical questions set for the integrated education and PACS administor without the limitation of time and space based on XML that is the standard of exchange and transmission of Web documents via Internet. The proposed system is composed of administration module and user module. The former supports some functions: a creation, classification, and management of Radiological question set. Our system can elevate ability of learning and interchange of information among Radiological technologist making preparation of PACS administor for Radiological technologist examination. Finally, our system can maximize an effectiveness of education by evaluating and training users individually with various level according to the user's ability of learning and realization.

• The Journal of Korean Society for School & Community Health Education
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• v.12 no.1
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• pp.91-102
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• 2011

Objectives: The purpose of this study is to identify the extent of the health behaviors of juveniles with experience in drug and the extent of their oral health behaviors. Then the impact of such factors on the oral health was analyzed. Methods: The analysis in this study used the raw data from 'The Fifth Korea Youth Risk Behavior Web-based Survey' after getting approval for use from the Center for Disease Control. The research subjects of this study were juveniles with experience in drug. Analysis was done by using 8 socio-demographic variables, 6 health behaviors related variables, 4 oral-health behaviors related variables and 1 oral health related variable. All survey data were analyzed by SPSS WIN 17.0 program. as frequency analysis and logistic regression. Results: The factors that give impact on the oral health of juveniles with drug experience were found as: gender, academic year, study grade, school type, school class, city scale, economic status, residential type, experience in alcohol, experience in smoking, obesity, frequency of medium-level physical exercise, eating breakfast frequency, hours of sleeping, number of tooth-brushing in one day, brushing teeth after lunch frequency, experience in dental treatment and experience in oral health training. Conclusions: In order to improve the oral health of juveniles with drug experience, health behaviors such as stop-smoking, stop-drinking and regular physical exercise are recommended. In addition, they should stop using drugs that threats their oral health. The development of nursing intervention to maintain the continuous enhancement of their oral health is also required.