• Journal of Distribution Science
• /
• v.18 no.4
• /
• pp.87-96
• /
• 2020

Purpose: In this paper, we provide an illustration of Indonesian youth Social Networking Service (SNS) behavior and its relation to their culinary activity. Specifically, their behavior of culinary activity preferences and also the factors affecting their action of spending their money. Data and methodology: We gathered primary data from stratified random questionnaire survey (406 youth). The gathered data was analyzed using text data mining and statistics using R statistical computing language. Results: 1) We found out why our respondents are interested in following the accounts of SNS food influencers: i.e. visually attracted to the posts, as their reference to find places to dine out, as their reference to try new food menu and to get nostalgic feeling about the food. 2) The respondents decide to actually go to the recommended culinary places because of several factors, specifically, its description (visual and text), location, word of mouth (WoM), the experience of being to that place and price. 3) Important factors affecting culinary spent are income, number of following food influencer account, SNS usage time and their interest when looking at WoM. Conclusions: SNS behavior influences Indonesian youth culinary activity preferences and spent.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.6
• /
• pp.2470-2491
• /
• 2018

Web-scale open information extraction (Open IE) plays an important role in NLP tasks like acquiring common-sense knowledge, learning selectional preferences and automatic text understanding. A large number of Open IE approaches have been proposed in the last decade, and the majority of these approaches are based on supervised learning or dependency parsing. In this paper, we present a novel method for web scale open information extraction, which employs cosine distance based on Google word vector as the confidence score of the extraction. The proposed method is a purely unsupervised learning algorithm without requiring any hand-labeled training data or dependency parse features. We also present the mathematically rigorous proof for the new method with Bayes Inference and Artificial Neural Network theory. It turns out that the proposed algorithm is equivalent to Maximum Likelihood Estimation of the joint probability distribution over the elements of the candidate extraction. The proof itself also theoretically suggests a typical usage of word vector for other NLP tasks. Experiments show that the distance-based method leads to further improvements over the newly presented Open IE systems on three benchmark datasets, in terms of effectiveness and efficiency.

• Journal of the Korean Home Economics Association
• /
• v.49 no.1
• /
• pp.55-65
• /
• 2011

This study explored how a 5th grade girl from a divorced family recovered her femininity through the sandplay therapy. The client was referred by a social worker in her school because of maladjustments such as passivity in school work, poor peer relations, especially with girls, the usage of bad language and a lack of concern about her appearance. There were 41 sessions of the therapy. The first part of the therapy included 1-7 sessions, the middle part 8-35, and the final part 36-41. The client expressed her situation by showing guardians and a peeing boy and by seeking love in the first part. During the middle part she put copper ballerinas and needed to make them alive. In the final part she set figures facing each other who seemed to have mutual understandings and placed cars running well. The client recovered her femininity through the sandplay therapy in a free and protected space.

• The Mathematical Education
• /
• v.51 no.2
• /
• pp.131-144
• /
• 2012

The purpose of this study is to investigate the change of mathematics pre-service teachers' teaching behaviors in microteaching. This study is organized along the following lines: 1) mathematics pre-service teachers conduct twice microteachings, 2) the microteaching recordings and lesson observation reports written by pre-service teachers are analyzed. Through reviewing the first microteaching, pre-service teacher have reviewed and found out improvements of their teaching. In the second microteaching, pre-service teachers' teaching behaviors have been positively and effectively changed with respect to teaching methods, proposal of learning objectives, prior knowledge usage, presenting lesson's content, concise descriptions, brief language usages, multimedia, and appropriate questions. However, they frequently used inappropriate expressions from their unconscious habits. Therefore, the educational institutions should provide opportunities involved in well-structured microteaching training program with pre-service teachers, which in turn, help pre-service teachers to have more positive teaching competence.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.36 no.5
• /
• pp.319-333
• /
• 2018

As human beings spend more time indoors, and with the growing complexity of indoor spaces, more focus is given to indoor spatial applications and services. 3D topological networks are used for various spatial applications that involve navigation indoors such as emergency evacuation, indoor positioning, and visualization. Manually generating indoor network data is impractical and prone to errors, yet current methods in automation need expensive sensors or datasets that are difficult and expensive to obtain and process. In this research, a methodology for semi-automatically generating a 3D indoor topological model based on IndoorGML (Indoor Geographic Markup Language) is proposed. The concept of Shooting Point is defined to accommodate the usage of omnidirectional images in generating IndoorGML data. Omnidirectional images were captured at selected Shooting Points in the building using a fisheye camera lens and rotator and indoor spaces are then identified using image processing implemented in Python. Relative positions of spaces obtained from CAD (Computer-Assisted Drawing) were used to generate 3D node-relation graphs representing adjacency, connectivity, and accessibility in the study area. Subspacing is performed to more accurately depict large indoor spaces and actual pedestrian movement. Since the images provide very realistic visualization, the topological relationships were used to link them to produce an indoor virtual tour.

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.165-170
• /
• 1999

Previous technology of remote sensing was focused on analyzing raster image and gaining information through image processing. But now it has extended to diverse fields like automatic map generation, material exploitation or monitoring environmental changes with effort to utilizing practical usage. And with rapid expansion of information exchange on Internet and high-speed network, the demand of public which want to utilize remotely sensed image has been increased. This makes growth of service on acquisition and processing remotely sensed image. GeoNet is a Java-based remotely sensed image processing system. It is based on Java object-oriented paradigm and features cross-platform, web-based execution and extensibility to client/server remotely sensed image processing model. Remotely sensed image processing software made by Java programming language can suggest alternatives to meet readily demand on remotely sensed image processing in proportion to increase of remotely sensed data. In this paper, we introduce GeoNet and explain its architecture.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1993.04a
• /
• pp.62-71
• /
• 1993

Recently, the computer software technology is not keeping pace with the increasing demand of application software development and rapid changes in business environment. To overcome this "software crisis", many researchers have studied the methodologies to improve the productivity in software development and the flexibility of software usage. Among these methodologies, the most promising and intensively studied methodology is the Object-Oriented Approach The purpose of this study is, therefore, to examine the applicability of the Object-Oriented Approach for improving productivity and flexibility in Management Information Systems development. For an application, we selected a financial planning model, especially focusing on the budgeted income statement. In this thesis, we identified relevent objects in the budgeted income statement, and represented them in the object models. By implementing these object models using C++ language, we evaluated their adaptability in the budget-making process, and showed, by comparing them with the existing Planning '||'&'||' Modeling Languages such as IFPS(Interactive Financial Planning Saystem), their practicability in Management Information Systems. The results of this study are as follows: First, the same object models can be used in making the budgeted income statement both in the department level and in the corporate level. Second, the object models provide the flexibility and extensibility of an application program in case of the changes in business environment. Third, the Object-Oriented Approach is a practical methodology to improve the productivity and cut down the maintenance cost of application software development.t.

• CELLMED
• /
• v.4 no.2
• /
• pp.8.1-8.6
• /
• 2014

Despite the remarkable advancements of the modern medicine, the traditional system of medicine (TSM) still serves as a potential primary health care modality in the in low- and middle-income countries. The recent reports suggest that there is a renewed interest has been observed towards TSM in the developed countries too, because of the adverse side-effect of modern medicines. Medicinal plants have been widely serving as a rich source of therapeutic agent. Ethiopia is one of the most reserves rich countries in the world. It is renowned for well-diversified and natural resources in terms of its unique flora and fauna. Ethiopian deep-rooted tradition and culture largely depends on the usage of plants for their religious ceremonies, impressive festivals, traditional medicinal uses and other basic necessities. The present scrutiny is an attempt to understand the omnipotent nature of an Ethiopian Ethnomedicinal plant called Tinjute [vernacular name (local native language, Amharic); Otostegia integrifolia]. There are several studies suggest that Tinjute can be used as a natural medicine or health-promoting agents for various disorders and ailments. Nevertheless, in Ethiopia, it is renowned as an insect repellent to drive-away insect vector of diseases, particularly mosquitoes in the early evening. However, there are many more issues and challenges which must be urgently addressed to scientifically formulate various potent, efficacious, safe and highly selective phytotherapeutic agents and insects' repellent from the Tinjute plant in the near future.

• Journal of Information Technology Services
• /
• v.17 no.2
• /
• pp.111-128
• /
• 2018

About 3.9 million apps and 24 primary categories can be approved on Apple iTunes Store. Making accurate categorization can potentially receive many benefits for developers, app stores, and users, such as improving discoverability and receiving long-term revenue. However, current categorization problems may cause usage inefficiency and confusion, especially for cross-attribution, etc. This study focused on evaluating the reliability of app categorization on Apple iTunes Store by using several rounds of inter-rater reliability statistics, locating categorization problems based on Machine Learning, and making more accurate suggestions about representative functionality stems for each primary category. A mixed methods research was performed and total 4905 popular apps were observed. The original categorization was proved to be substantial reliable but need further improvement. The representative functionality stems for each category were identified. This paper may provide some fusion research experience and methodological suggestions in categorization research field and improve app store's categorization in discoverability.

• Journal of KIISE:Software and Applications
• /
• v.33 no.5
• /
• pp.470-480
• /
• 2006

The longer the input sentences, the worse the parsing results. To improve the parsing performance, many methods about long sentence segmentation have been reserarched. As an isolating language, Chinese sentence has fewer cues for sentence segmentation. However, the average frequency of comma usage in Chinese is higher than that of other languages. The syntactic information that the comma conveys can play an important role in long sentence segmentation of Chinese languages. This paper proposes a method for classifying commas in Chinese sentences according to the context where the comma occurs. Then, sentences are segmented using the classification result. The experimental results show that the accuracy of the comma classification reaches 87.1%, and with our segmentation model, the dependency parsing accuracy of our parser is improved by 5.6%.