• PNF and Movement
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• v.21 no.1
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• pp.129-137
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• 2023

Purpose: The physical therapy diagnosis process requires high-level background knowledge, the ability to obtain added information from patients, accurate examination skills, and a framework for transforming thoughts into a diagnostic decision. Thus, the physical therapy diagnostic process is highly complicated and difficult work. To function as autonomous professionals, physical therapists must develop effective clinical diagnosis skills. As such, mobile application aids can help with accurate and scientific diagnoses. Therefore, this study aims to develop and evaluate the usability of a mobile application for physical therapy diagnoses. Methods: In this study, a diagnostic application was developed using App Inventor, the development environment was the Chrome web browser for Windows 10, and the mobile application was run on a Google Pixel 5. The developed application was evaluated for usability by 20 physical therapists with more than 5 years of clinical experience in the musculoskeletal physical therapy field, and a usability evaluation was conducted using a 5-point Likert scale for accuracy, convenience, satisfaction, and usability. The collected Likert scores were converted into percentages and analyzed as descriptive statistics. Results: The graphical user interface consisted of an initial screen with program guidance, 18 screens presenting the algorithm, and 12 screens presenting the estimated diagnosis based on the algorithm. As such, the usability evaluation of the developed application was as follows: accuracy 100%, convenience 90%, satisfaction 91%, and usability 88%. Conclusion: The newly developed mobile application for physical therapeutic diagnoses has a high accuracy, and it will aid in building an easy and reliable physical therapy diagnosis system.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.445-454
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• 2014

In recent days, trend technologies for cloud, bigdata, or mobile, as the important marketable keywords or paradigm in Information Communication Technology (ICT), are widely used and interrelated each other in the various types of platforms and web-based services. Especially, the combination of cloud and mobile is recognized as one of a profitable business models, holding benefits of their own. Despite these challenging aspects, there are a few application cases of this model dealing with geo-based data sets or imageries. Among many considering points for geo-based cloud application on mobile, this study focused on a performance test of mobile cloud of Bayesian image fusion algorithm with satellite images. Two kinds of cloud platform of Amazon and OpenStack were built for performance test by CPU time stamp. In fact, the scheme for performance test of mobile cloud is not established yet, so experiment conditions applied in this study are to check time stamp. As the result, it is revealed that performance in two platforms is almost same level. It is implied that open source mobile cloud services based on OpenStack are enough to apply further applications dealing with geo-based data sets.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.44.1-44
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• 2001

This paper discusses the interacting mobile robots for tele-operation system using the world wide web. In multi-agent and web-based teleoperation environment the problem of communication delay must be solved for the efficient and robust control of the system. The standard graphic user interface(GUI)is implemented using Java Programing language. The web browser is used to integrate the virtual environment and the standard GUI(Java applet) in a single user interface. Users can access a dedicated WWWserver and download the user interface. Reinforcement learning is applied to indirect control in order to autonomously operate without the need of human intervention. Java application has been developed to communicate and control multi robots using WWW. The effectiveness of our multi robots system is verified by simulation and experiments ...

• Proceedings of the Korea Contents Association Conference
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• 2004.05a
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• pp.323-329
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• 2004

New business model for mobile internet has been developed using multifunction mobile terminal. Multifunction terminal provides mobile multimedia service such as VOD and AOD and personal area network(PAN) service using bluetooth and W-LAN. In this paper, we develop home network WEI application interworking with home network gateway This application controls home appliances and provides still image for home secuirt using the web camera. We further develop the home networking PAN services using multifunction terminal having GigBee and RFID.

• Journal of the Korea Society of Computer and Information
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• v.15 no.7
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• pp.117-124
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• 2010

Recently, according to development of wired and wireless networks, contents production of user-defined changes a environment producing contents that it get out of manufactured contents offered by mobile telecommunication company. This paper propose a system proposing and registering a contents service provider of mobile telecommunication company for user-defined mobile contents production and transmission. We propose a system using web hosting service for user-defined mobile contents production and solution for system and transmission for contents production of a person and enterprises.

• Journal of the Korean Society for Library and Information Science
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• v.48 no.1
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• pp.415-439
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• 2014

The purpose of this study is to analyze mobile web accessibility of public libraries. To achieve this, accessibility checklists were driven from mobile web and application guidelines. The study also conducted automatic and manual evaluations. As results, the study found that text alternatives for resource image, main menu, image for text contents were mainly missing. In addition, focus for retrieval, operating system accessibility for retrieval, and id & password label, color difference for library calendar and seat reservation, brightness difference for main manu and resource display, and space between controls for retrieval were mainly missing. The study also suggested focal missing areas for main library services. It will be utilized as checklists for development of mobile services.

• Journal of Korean Institute of Industrial Engineers
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• v.33 no.4
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• pp.402-409
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• 2007

Markov Chains has proven to be effective in predicting human behaviors in the areas of web site assess, multimedia educational system, and driving environment. In order to extend an application area of predicting human behaviors using Markov Chains, this study was conducted to investigate whether Markov Chains could be used to predict human behavior in selecting mobile phone menu item. Compared to the aforementioned application areas, this study has different aspects in using Markov Chains : m-order 1-step Markov Model and the concept of Power Law of Learning. The results showed that human behaviors in predicting mobile phone menu selection were well fitted into with m-order 1-step Markov Model and Power Law of Learning in allocating history path vector weights. In other words, prediction of mobile phone menu selection with Markov Chains was capable of user's actual menu selection.

• Spatial Information Research
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• v.22 no.2
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• pp.63-71
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• 2014

Ocean leisure sports have recently emerged as one of so-called blue ocean industries. They are sensitive to diverse environmental conditions such as current, temperature, and salinity, which can increase needs of forecasting data as well as in-situ observations for the ocean. In this context, a Web-based geovisualization system for coastal information produced by model forecasts was implemented for use in supporting various ocean activities. First, FVCOM(Finite Volume Coastal Ocean Model) was selected as a forecasting model, and its data was preprocessed by a spatial interpolation and sampling library. The interpolated raster data for water surface elevation, temperature, and salinity were stored in image files, and the vector data for currents including speed and direction were imported into a distributed DBMS(Database Management System). Web services in REST(Representational State Transfer) API(Application Programming Interface) were composed using Spring Framework and integrated with desktop and mobile applications developed on the basis of hybrid structure, which can realize a cross-platform environment for geovisualization.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.155-162
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• 2021

With the global COVID-19 pandemic, the tourism sector and all consumption have contracted with the untact era. Wine will also be sold and developed in various ways non-face-to-face in the future. Therefore, it is necessary to develop apps and web servers that focus on health in the era of single-person households and non-face-to-face. This study used facial recognition data based on photos of adult men and women in their 40s and 50s to analyze the Sasang constitution through a mobile app and web server, and suggested wine recommendations suitable for their constitution. First, the user's body information is entered. And through the facial recognition mobile app, recommend the right wine after analyzing the body type. if it's not like the first recommended wine, it is configured to receive another wine recommendation. In the future, the number of single-person households will increase further, and in the age of well-being, wine recommendations that fit my body will be useful. Wine recommendation suitable for Sasang constitution will be a useful mobile application to manage personal healt

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.3
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• pp.245-251
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• 2023

Facial expression recognition plays a significant role in understanding human emotional states. With the advancement of AI and computer vision technologies, extensive research has been conducted in various fields, including improving customer service, medical diagnosis, and assessing learners' understanding in education. In this study, we develop a model that can infer emotions in real-time from a webcam using transfer learning with TensorFlow.js and MobileNet. While existing studies focus on achieving high accuracy using deep learning models, these models often require substantial resources due to their complex structure and computational demands. Consequently, there is a growing interest in developing lightweight deep learning models and transfer learning methods for restricted environments such as web browsers and edge devices. By employing MobileNet as the base model and performing transfer learning, our study develops a deep learning transfer model utilizing JavaScript-based TensorFlow.js, which can predict emotions in real-time using facial input from a webcam. This transfer model provides a foundation for implementing facial expression recognition in resource-constrained environments such as web and mobile applications, enabling its application in various industries.