• Journal of Information Processing Systems
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• v.15 no.4
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• pp.986-1016
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• 2019

Mobile user interface pattern (MUIP) is a kind of structured representation of interaction design knowledge. Several studies have suggested that MUIPs are a proven solution for recurring mobile interface design problems. To facilitate MUIP selection, an effective clustering method is required to discover hidden knowledge of pattern data set. In this paper, we employ the semi-supervised kernel fuzzy c-means clustering (SSKFCM) method to cluster MUIP data. In order to improve the performance of clustering, clustering parameters are optimized by utilizing the global optimization capability of particle swarm optimization (PSO) algorithm. Since the PSO algorithm is easily trapped in local optima, a novel PSO algorithm is presented in this paper. It combines an improved intuitionistic fuzzy entropy measure and a new population search strategy to enhance the population search capability and accelerate the convergence speed. Experimental results show the effectiveness and superiority of the proposed clustering method.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.259-265
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• 2020

The study aims to define the career competency of HRD practitioners based on an intelligent career framework. This intelligent career framework has been described as having been achieved by the accumulation of career capital through the three ways of knowing, including knowing why, knowing how, and knowing with whom. The data were collected from the interviews with 15 HRD practitioners. Semi-structured interviews were used to collect data from the HRD practitioners. For the orientation about the interview, the researcher explained the importance of gathering data about the personal experiences of the respondents on their work and career. After that explanation, the researcher asked several questions based on the pre-structured interview guide. The data collected were qualitatively analyzed on the basis of the intelligent career framework. Based on the analysis of the interviews, the subcategories of each way of knowing competency were identified. For the knowing why, identity, credibility, and career clarity were identified. The subcategories of knowing how are remaining updates, hard skills, and soft skills, while the subcategories of knowing with whom are personal networking and professional networking. The interdependency among the three career competencies was found. The findings provide theoretical implications of applying an intelligent career framework.

• Journal of Distribution Science
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• v.22 no.1
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• pp.25-36
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• 2024

Purpose: The study attempts to explore the operational performance of the existing Malaysian logistics companies and the extent of their adoption of digitalization. The role of digitalization in enhancing the performance of companies in the logistics industry in Malaysia, for value creation, is the topic of study. Research design, data and methodology: A qualitative research method with a semi-structured interview approach was applied and judgmental sampling was used as the sampling technique to collect data. The research has chosen nine companies in the logistics industry in Peninsular Malaysia, with the interviews aimed at eleven members of top and middle-level management. Data analysis was performed using logical system techniques to examine and evaluate data, reorganizing feedback, comparing it with literature, and transforming it into structured, valuable information after interviews. Results: The study revealed mixed opinions on digitalization in logistics, despite its potential benefits such as improved operational efficiency, real-time information, and customer service. However, high costs may hinder financial performance and require revisions due to stakeholder involvement. Conclusions: The Malaysian logistics industry's adoption of digitalization is gaining traction, with most companies satisfied with their status. However, challenges like cost and inefficiency persist, prompting calls for government support to improve efficiency and reduce costs while ensuring sustainable transportation.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.572-574
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• 2003

XML은 반 구조 데이터(semi-structured data)의 일종으로 데이터들이 정형화된 구조를 가지고 있지 않다는 것이 특징이다. 기존의 데이터베이스 시스템은 고정된 스키마를 통해 데이터를 저장 관리하기 때문에 정형화된 구조를 가지지 않는 XML 문서를 저장하기에는 한계가 있다. 본 논문에서는 정형화된 구조를 가지지 못하는 XML문서를 효과적으로 저장하고 관리할 수 있는 저장장치를 구현하고 구현 사항에 대해 설명한다. 본 논문의 저장 장치는 XML을 DOM트리로 표현한 후 DOM트리의 각 노드를 객체로 만들어 저장한다. 본 논문의 저장 장치는 다중 사용자를 지원하기 위해 클라이언트 서버 구조로 구성되어 있으며 각 객체는 전용 파일, 관계형 시스템의 LDB등 다양한 하부 구조에 저장될 수 있다.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.3
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• pp.1-9
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• 2016

The current meaning of "Big Data" refers to all the techniques for value eduction and actionable analytics as well management tools. Particularly, with the advances of wireless sensor networks, they yield diverse patterns of digital records. The records are mostly semi-structured and unstructured data which are usually beyond of capabilities of the management tools. Such data are rapidly growing due to their complex data structures. The complex type effectively supports data exchangeability and heterogeneity and that is the main reason their volumes are getting bigger in the sensor networks. However, there are many errors and problems in applications because the managing solutions for the complex data model are rarely presented in current big data environments. To solve such problems and show our differentiation, we aim to provide the solution of actionable analytics and semantic reusability in the sensor web based streaming big data with new data structure, and to empower the competitiveness.

• The Journal of Information Systems
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• v.14 no.3
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• pp.37-47
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• 2005

Mining of association rules is to find associations among data items that appear together in some transactions or business activities. As of today, algorithms for association rule mining, as well as for other data mining tasks, are mostly applied to relational databases. As XML being adopted as the universal format for data storage and exchange, mining associations from XML data becomes an area of attention for researchers and developers. The challenge is that the semi-structured data format in XML is not directly suitable for traditional data mining algorithms and tools. In this paper we present an encoding method to encode XML tree-nodes. This method is used to store the XML data in Value Table and Transaction Table that can be easily accessed via indexing. The hierarchical relationship in the original XML tree structure is embedded in the encoding. We applied this method to association rules mining of XML data that may have missing data.

• Journal of Society of Preventive Korean Medicine
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• v.25 no.3
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• pp.73-88
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• 2021

Objectives : The purpose of this study is to explore the experiences of traditional korean medical doctors (TKMD) who have treated victims of sexual violence by collecting their qualitative data that cannot be obtained with statistical data. Methods : In-depth interviews were conducted with semi-structured questionnaires for each of 5 TKMDs who had experiences in treating sexual violence victims. For analysis, the interviews were recorded along with their facial expressions and actions during the interview process, and all collected data were analyzed by colaizzi's method. In each process, a 'phenomenological reduction' was applied. Results : The identity of TKMD's experience of treating sexual violence victims was structured into 25 themes, 9 theme clusters, and 4 categories. The 4 categories included 'Professionalism and sense of efficacy', 'Personal life experiences and mental trauma treatment experiences that are mutually influencing each other', 'Factors needed to increase TKMD's participation in treatment of sexual violence victims', 'Deriving the future strategy of traditional korean medicine'. Conclusions : This study derived the essence and meaning of TKMDs' experiences in treating sexual violence victims, and presented future directions of traditional korean medicine in this field. It is expected that the results of this study would be used as the basis for establishing the traditional korean medical support system for sexual violence victims in the context of the korean medical system.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4395-4407
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• 2023

Bubble columns are widely encountered in several industries, especially in the field of nuclear safety. The Eulerian-Eulerian and the Eulerian-Lagrangian methods are commonly used to investigate bubble columns. Eulerian approaches require additional tasks such as strict volume conservation at the interface and a predefined well-structured grid. In contrast, the Lagrangian approach can be easily implemented. Hence, we introduce a fully Lagrangian approach for the simulation of bubble columns using the discrete bubble model (DBM) and moving particle semi-implicit (MPS) methods. Additionally, we propose a rigorous method to estimate the volume fraction accurately, and verified it through experimental data and analytical results. The MPS method was compared with the experimental data of Dambreak. The DBM was verified by analyzing the terminal velocity of a single bubble for each bubble size. It agreed with the analytical results for each of the four drag correlations. Additionally, the improved method for calculating the volume fraction showed agreement with the Ergun equation for the pressure drop in a packed bed. The implemented MPS-DBM was used to simulate the bubble column, and the results were compared with the experimental results. We demonstrated that the MPS-DBM was in quantitative agreement with the experimental data.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.12
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• pp.5969-5973
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• 2012

Introduction: Andhra Pradesh (AP) is one of the largest tobacco producing states in India. About 29% of adults in AP currently use tobacco in some form. Almost 24% of males and 4% of females are smokers. The prevalence of tobacco use in the state is higher than the national average of 15% for male and 2% for female smokers. However, few attempts have been made to understand the current situation of tobacco control resources, activities and strategies in the context of such a high tobacco prevalence state. The present study aimed to identify the gaps in existing tobacco control program and areas where tobacco control efforts can be integrated. Methods: Data were collected using both quantitative and qualitative methods. Semi-structured interviews were undertaken with a total of 95 key officials of state health departments, program managers, and project directors in six districts to understand ongoing tobacco control efforts. To facilitate the interviews, semi-structured guides were developed. Simple descriptive statistical analysis was conducted on the quantitative data using SPSS version 17. Results: The results of the situational analysis suggest that a sufficient health workforce and infrastructure with the potential to integrate tobacco control activities is available in the surveyed districts. However, lack of integration of the tobacco control program intothe tuberculosis control program and the National Rural Health Mission was observed. Information, education and communication activities were lacking at block level health facilities. Conclusions: Our findings indicate that lack of trained health professionals, paucity of dedicated funds, lack of information, education and communication materials and low priority given to tobacco control activities are some of the factors which impede integration of tobacco control into existing health and developmental programmes in the districts of Andhra Pradesh, India.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.503-508
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• 2005

In the modern, distributed and dynamic construction environment it is important to exchange information from different sources and in different data formats in order to improve the processes supported by these systems. Previous research has demonstrated that (i) a significant percentage of construction data is stored in semi-structured or unstructured data formats (ii) locating and identifying such data that are needed for the important decision making processes is a very hard and time-consuming task. In this paper, an automated methodology for the classification and retrieval of construction images in AEC/FM model based systems will be presented. Specifically, a combination of techniques from the areas of image processing, computer vision, and content-based image retrieval have been deployed to develop a method that can retrieve related construction site image data from components of a project model.