• Journal of Information Processing Systems
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• v.10 no.4
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• pp.503-522
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• 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

• Women's Health Nursing
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• v.29 no.2
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• pp.128-136
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• 2023

Purpose: Topic modeling is a text mining technique that extracts concepts from textual data and uncovers semantic structures and potential knowledge frameworks within context. This study aimed to identify major keywords and network structures for each major topic to discern research trends in women's health nursing published in the Korean Journal of Women Health Nursing (KJWHN) using text network analysis and topic modeling. Methods: The study targeted papers with English abstracts among 373 articles published in KJWHN from January 2011 to December 2021. Text network analysis and topic modeling were employed, and the analysis consisted of five steps: (1) data collection, (2) word extraction and refinement, (3) extraction of keywords and creation of networks, (4) network centrality analysis and key topic selection, and (5) topic modeling. Results: Six major keywords, each corresponding to a topic, were extracted through topic modeling analysis: "gynecologic neoplasms," "menopausal health," "health behavior," "infertility," "women's health in transition," and "nursing education for women." Conclusion: The latent topics from the target studies primarily focused on the health of women across all age groups. Research related to women's health is evolving with changing times and warrants further progress in the future. Future research on women's health nursing should explore various topics that reflect changes in social trends, and research methods should be diversified accordingly.

• Journal of the HCI Society of Korea
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• v.3 no.1
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• pp.33-38
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• 2008

The major users of children's library are children and housewives. Recent increasing frequency of their visit to the library expands the function of it from the place where they borrow and read books further to the cultural space where each family unit can enjoy leisure activities. Though the children's library basically is a quiet place for reading books, peers' establishing friendship and emotional bond with the parents, and such plays as small scale muscular movements take place in addition to reading activities because the major users are infants under six or children in the lower grades in elementary school. Thus, in order to study the features and requirements that are inherent in the various behaviors of the children who use furniture, understanding of the particular factors in the physical environment of the children's library and the user context must precede. In reality, though the fixed form of the desks and chairs in the library was made by a small number of designers, a large number of children are using them in tremendously various ways beyond the ways that the designers had intended, adapting themselves to the environmental context. Therefore, the purpose of this study is to find out the children's using way of seats when they do reading and playing activities based on the way of interaction between children and parents, and, after modeling of the children's behavior data, to understand the demands inherent inside the various behaviors of children who use furniture.

• Archives of design research
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• v.19 no.5 s.67
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• pp.75-84
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• 2006

The aims of this study are to examine the conceptual contents of space diagram, and to find its elements and practical applications by analyzing the UN Studio. The Findings of this study are as follows: firstly, the conceptual contents represented in space diagram are classified into four elements - motif, flow, relationship, and distribution. Secondly, space diagram is used in program development, schematic design, and preliminary design of design process phases. Thirdly, the elements based on the case diagrams include five elements: context analysis, object analysis, time-behavior analysis, modeling analysis, and space analysis. Fourthly, in practical use, diagrams with motif concept is usually used in modeling analysis, and diagram with flow concept is commonly used in the analysis of time-behavior and object. Diagrams with relationship concept is mostly used in space analysis, secondly in analysis of context and modeling. Further, diagrams with distribution concept is usually used in space analysis. If one uses these findings for design projects in practical business or education, it would be helpful in design conception and development as well as of design information structuralization.

• Journal of Advanced Navigation Technology
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• v.14 no.1
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• pp.108-118
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• 2010

In this paper, we propose Context-based Music Recommendation (COMUS) ontology for modeling user's musical preferences and context and for supporting reasoning about the user's desired emotion and preferences. The COMUS provides an upper Music Ontology that captures concepts about the general properties of music such as title, artists and genre and also provides extensibility for adding domain-specific ontologies, such as Mood and Situation, in a hierarchical manner. The COMUS is music dedicated ontology in OWL constructed by incorporating domain specific classes for music recommendation into the Music Ontology. Using this context ontology, we believe that the use of logical reasoning by checking the consistency of context information, and reasoning over the high-level, implicit context from the low-level, explicit information. As a novelty, our ontology can express detailed and complicated relations among the music, moods and situations, enabling users to find appropriate music for the application. We present some of the experiments we performed as a case-study for music recommendation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2839-2852
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• 2013

Context-awareness is an essential part of ubiquitous computing, and over the past decade video based activity recognition (VAR) has emerged as an important component to identify user's context for automatic service delivery in context-aware applications. The accuracy of VAR significantly depends on the performance of the employed human body segmentation algorithm. Previous human body segmentation algorithms often engage modeling of the human body that normally requires bulky amount of training data and cannot competently handle changes over time. Recently, active contours have emerged as a successful segmentation technique in still images. In this paper, an active contour model with the integration of Chan Vese (CV) energy and Bhattacharya distance functions are adapted for automatic human body segmentation using depth cameras for VAR. The proposed technique not only outperforms existing segmentation methods in normal scenarios but it is also more robust to noise. Moreover, it is unsupervised, i.e., no prior human body model is needed. The performance of the proposed segmentation technique is compared against conventional CV Active Contour (AC) model using a depth-camera and obtained much better performance over it.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.4
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• pp.736-739
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• 2009

In this paper, an efficient lossless compression algorithm using motion adaptation is proposed. It is divided into two parts: a motion adaptation based nonlinear predictor part and a residual data coding part. The proposed nonlinear predictor can reduce prediction error by learning from its past prediction errors using motion adaption. The predictor decides the proper selection of the intra and inter prediction values according to the past prediction error. The reduced error is coded by existing context adaptive coding method. Experimental results show that the proposed algorithm has the higher compression ratio than context modeling methods, such as FELICS, CALIC, and JPEG-LS.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.3-8
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• 1999

Previous variable vocabulary speech recognition systems with context-independent acoustic modeling, could not represent the effect of neighboring phonemes. To solve this problem, we use allophone-based context-dependent acoustic model. This paper describes the method to improve acoustic model of the system effectively. Acoustic model is improved by using allophone clustering technique that uses entropy as a similarity measure and the optimal allophone model is generated by changing the number of allophones. We evaluate performance of the improved system by using Phonetically Optimized Words(POW) DB and PC commands(PC) DB. As a result, the allophone model composed of six hundreds allophones improved the recognition rate by 13% from the original context independent model m POW test DB.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.915-925
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• 2020

The purpose of the research is to analyze the behavioral intention to adopt social media in SMEs affected by the COVID-19 crisis, based on the TOE Model. This study uses the TOE framework as a theoretical basis. This research is important because COVID-19 has destroyed most of the SMEs, and SMEs are exposed to social media technology to market their products. The success of social media adoption has helped SMEs to be able to rise from adversity. Respondents in this study were 250 SMEs in the Special Region of Yogyakarta, Indonesia. The data analysis technique used is structural equation modeling with AMOS. The results of this study indicate that SMEs affected by the COVID-19 crisis have a high awareness of social media and have a high intention to adopt social media as a way to market their products and connect with customers. The intention to adopt social media is significantly influenced by the technological context, organizational context, environmental context, and social media awareness. The findings of this study suggest that in times of crisis due to the COVID-19 pandemic, the Government support is needed. The Government needs to open services for SMEs whose businesses are affected by the pandemic.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.7
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• pp.333-339
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• 2021

The study seeks to identify the determinants of the adoption of e-commerce by small and medium-sized enterprises (SMEs) in developing countries, in our case, in Indonesia. The aim of this study is to examine the factors influencing e-commerce adoption. This study uses the method of quantitative data collection based on a questionnaire survey of SMEs in Indonesia. The research relies on Regional Project stipulations regarding Business Development in Indonesia, to capture businesses with a range of 5 to 100 employees that are classified as SMEs. This study randomly chose 100 SMEs in Indonesia from the IndoNetwork database. Partial least square (PLS) structural model data processing was used for path coefficients analysis. Structural equation modeling is applied in this study to analyze the determinant factors on the e-commerce adoption. The study findings reveal that four factors, namely, perceived benefits, compatibility, technology readiness, and government support, significantly influence the adoption of e-commerce, whereas customer/supplier pressure does not have influence. So, this study concludes that perceived benefits, compatibility, technology readiness, and government support had a significant and positive relationship with e-commerce adoption. Meanwhile, customer/supplier pressure had no effect on the e-commerce adoption of by Indonesia SMEs.