• Spatial Information Research
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• v.13 no.3 s.34
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• pp.221-237
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• 2005

This study attempts at building a GIS computing environment that incorporates object-relational spatio-temporal database for the time geography model with space-time path, space-time prism and space-time accessibility. The proposed computing environment is composed of ( i ) mobile GIS application for collecting spatio-temporal trajectory data of an individual, ( ii ) spatio-temporal database server that includes time geography model, and (iii) geovisualization client that performs time geographic queries to the spatio-temporal database. The spatio-temporal trajectory data collected by GPS-PDA client is automatically processed and sent to server through data management middleware. The spatio-temporal database implemented by extending a generic DBMS provides spatio-temporal objects, functions, and SQL. The geovisualization client illustrates 3D visual results of the queries about space-time path, space-time prism, and space-time accessibility. This study confirms the possibility of integrating mobile GIS and DBMS for time geography model, and it presents the appropriate database model with spatio-temporal objects and functions that may handle very large data for time geography application.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.51-76
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• 2014

As the smart phone devices gain popularity, companies no longer consider mobile application marketing as an auxiliary marketing tactic. The branded mobile application (branded app) becomes an important part of marketing strategies. This study is an attempt to investigate antecedents of the use intention of the branded app from the perspective of TAM (Technology Acceptance Model). This study takes a macro perspective in explaining the adoption process by incorporating a set of new, yet promising additional variables into the TAM model such as flow experience, benefits, innovation inclination, and customization features. Data were collected by using a survey research. A total of 270 responses were collected. Questionnaires from 25 individuals were removed from the data set due to the insincere responses, leaving the final sample size of 245. Findings support all but one hypotheses of the study. Both perceived utilitarian benefits and customization features of the branded app were found to have positive influences on the perceived usefulness of the branded app. Also, the innovation inclination and perceived entertainment of branded app users showed positive influences on the perceived ease of use of branded app. In addition, it was shown that the perceived usefulness about the use of the branded app influenced positively the flow experience and the users' attitudes toward branded app. Also, the ease of use perceived by branded app users had positive influences on the perceived usefulness and the user's attitude toward branded app. However, the ease of use of branded app did not have a significant influence on the flow experience among users. Moreover, the flow experience from the use of branded app users influenced positively the user's attitude toward branded app. Finally, the users' attitudes toward branded app had positive influences on their intention to use the branded app. Implications for practitioners and academicians are provided.

• International Journal of Knowledge Content Development & Technology
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• v.9 no.4
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• pp.95-114
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• 2019

The digitization of traditional medical knowledge in Tanzania will greatly enhance its preservation and dissemination. This is especially important given the challenges facing the current methods of preserving and managing such knowledge. This study presents the requirements engineering approaches and requirements for a web-mobile application that would successfully digitize indigenous knowledge of phytomedicine and relevant practitioners licensing and registration processes. To establish the requirements of such a digital system application, the study sought the opinion of 224 stakeholders whose suggestions were used to analyze and model the requirements for designing such a web-mobile tool. The study was carried out in Arusha, Kagera and Dar es Salaam regions of Tanzania which involved ethnobotanical researchers, herb practitioners, curators from herbaria and registrar officers from Traditional and Alternatives Health Practice Council. Structured interview, survey, observation and document review were employed to find out the basic functional and non-functional requirements for possible designing and implementation a web-mobile application that would digitize indigenous knowledge of medicinal plants. The requirements were modelled using the use case and context diagrams. Finally, the study came up with a list of items for both functional and non-functional requirements that can be used as guidelines to develop a web-mobile application that will capture and document traditional medical knowledge of medicinal plants in Tanzania and, enabling relevant authorities to regulate and manage stakeholders.

• Korea Trade Review
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• v.45 no.6
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• pp.77-97
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• 2020

This study investigates the effects of O2O-based mobile shopping application (O2O MSA)'s information and service quality on the user's perceived privacy protection, satisfaction and loyalty. In this study, 969 questionnaire reponses were collected, out of which 555 were used to estimate the structural paths using PLS-SEM (partial least square structural equation model) for the hypothesis test. Our empirical findings are drawn from Chinese respondents that live in a 1-line city in China and use O2O MSAs serviced by China's leading companies. This study examines and confirms that qualified information and service of O2O MSA positively affect both perceived privacy protection and customer satisfaction, which finally leads to customer behavioral loyalty through the perceived privacy protection. Further, this study presents effective practical implications for application development strategy suitable for users in the O2O-based mobile shopping industry.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2849-2865
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• 2012

In order to block mobile junk messages automatically, many studies on spam filters have applied machine learning algorithms. Most previous research focused only on the accuracy rate of spam filters from the view point of the algorithm used, not on individual user's preferences. In terms of individual taste, the spam filters implemented on a mobile device have the advantage over spam filters on a network node, because it deals with only incoming messages on the users' phone and generates no additional traffic during the filtering process. However, a spam filter on a mobile phone has to consider the consumption of resources, because energy, memory and computing ability are limited. Moreover, as time passes an increasing number of feature words are likely to exhaust mobile resources. In this paper we propose a spam filter model distributed between a users' computer and smart phone. We expect the model to follow personal decision boundaries and use the uniform resources of smart phones. An authorized user's computer takes on the more complex and time consuming jobs, such as feature selection and training, while the smart phone performs only the minimum amount of work for filtering and utilizes the results of the information calculated on the desktop. Our experiments show that the accuracy of our method is more than 95% with Na$\ddot{i}$ve Bayes and Support Vector Machine, and our model that uses uniform memory does not affect other applications that run on the smart phone.

• Journal of Korean Library and Information Science Society
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• v.42 no.2
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• pp.299-322
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• 2011

The study aims to develop a mobile library model for universities that can be adapted to offer suitable library information and services to smart phone users. To do this, we conducted a case study using four foreign and domestic mobile libraries as well as a user study with 212 participants and questionnaires. In addition, we also administered a survey with 160 librarians. Based on the results of case and user/librarian studies, we proposed a mobile library model in which an access and navigation methods are described and nine key information and services including catalog search, code reader and SNS services are proposed.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.276-282
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• 2018

Objectives: Due to the uncontrolled increase of the mobile health applications and their scarce use by elderly for reason of absence credibility of measurements by lack scientific support, the aim of this study was to evaluate the differences between the biophysical measurements based on standard instrument against a mobile application using controlled experiments with elderly to propose an effective validation model of the developed apps. Methods: The subjects of the study (50 people) were elderly people who wanted to check their weight and cardiac status. For this purpose, two mobile applications were used to measure energy expenditure based on physical activity (Activ) and heart rate (SMCa) during controlled walking at specific speeds. Minute-by-minute measurements were recorded to evaluate the average error and the accuracy of the data acquired through confidence intervals by means of statistical analysis of the data. Results: The experimental results obtained by the Activ/SMCa apps showed a consistent statistical similarity with those obtained by specialized equipment with confidence intervals of 95%. All the subjects were advised and trained on the use of the applications, and the initial registration of data to characterize them served to significantly affect the perceived ease of use. Conclusions: This is the first model to validate a health-app with elderly people allowed to demonstrate the anthropometric and body movement differences of subjects with equal body mass index (BMI) but younger. Future studies should consider not only BMI data but also other variables, such as age and usability perception factors.

• Journal of Information Processing Systems
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• v.15 no.5
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• pp.1082-1095
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• 2019

Camera calibration is an important part of machine vision and close-range photogrammetry. Since current calibration methods fail to obtain ideal internal and external camera parameters with limited computing resources on mobile terminals efficiently, this paper proposes an improved fast camera calibration method for mobile terminals. Based on traditional camera calibration method, the new method introduces two-order radial distortion and tangential distortion models to establish the camera model with nonlinear distortion items. Meanwhile, the nonlinear least square L-M algorithm is used to optimize parameters iteration, the new method can quickly obtain high-precise internal and external camera parameters. The experimental results show that the new method improves the efficiency and precision of camera calibration. Terminals simulation experiment on PC indicates that the time consuming of parameter iteration reduced from 0.220 seconds to 0.063 seconds (0.234 seconds on mobile terminals) and the average reprojection error reduced from 0.25 pixel to 0.15 pixel. Therefore, the new method is an ideal mobile terminals camera calibration method which can expand the application range of 3D reconstruction and close-range photogrammetry technology on mobile terminals.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.1
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• pp.65-71
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• 2006

There has been equipped wireless network infrastructure making possible to contact mobile computing at buildings, university, airport etc. Due to increase of mobile user dramatically, it raises interest about application and importance of LBS. The purpose of this study is to develop an indoor positioning system which is position of mobile users using Wireless LAN signal strength. We present Euclidean distance model and Bayesian inference model for analyzing position determination. The experimental results showed that the positioning of Bayesian inference model is more accurate than that of Euclidean distance model. In case of static target, the positioning accuracy of Bayesian inference model is within 2 m and increases when the number of cumulative tracking points increase. We suppose, however, Bayesian inference model using 5- cumulative tracking points is the most optimized thing, to decrease operation rate of mobile instruments and distance error of tracking points by movement of mobile user.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.25-34
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• 2024

This paper presents the development of a mobile application that detects and identifies canine skin diseases by training a deep learning-based U-Net model to infer the presence and location of skin lesions from images. U-Net, primarily used in medical imaging for image segmentation, is effective in distinguishing specific regions of an image in a polygonal form, making it suitable for identifying lesion areas in dogs. In this study, six major canine skin diseases were defined as classes, and the U-Net model was trained to differentiate among them. The model was then implemented in a mobile app, allowing users to perform lesion analysis and prediction through simple camera shots, with the results provided directly to the user. This enables pet owners to monitor the health of their pets and obtain information that aids in early diagnosis. By providing a quick and accurate diagnostic tool for pet health management through deep learning, this study emphasizes the significance of developing an easily accessible service for home use.