• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.120-126
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• 2020

Studies are being conducted regarding falling recognition using sensors on smartphonesto recognize falling in human daily life. These studies use a number of sensors, mostly acceleration sensors, gyro sensors, motion sensors, etc. Falling recognition system processes the values of sensor data by using a falling recognition algorithm and classifies behavior based on thresholds. If the threshold is ambiguous, the accuracy will be reduced. To solve this problem, Deep learning was introduced in the behavioral recognition system. Deep learning is a kind of machine learning technique that computers process and categorize input data rather than processing it by man-made algorithms. Thus, in this paper, we propose a falling recognition application system using deep learning based on smartphones. The proposed system is powered by apps on smartphones. It also consists of three layers and uses DataBase as a Service (DBaaS) to handle big data and address data heterogeneity. The proposed system uses deep learning to recognize the user's behavior, it can expect higher accuracy compared to the system in the general rule base.

• International Journal of Contents
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• v.8 no.4
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• pp.42-49
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• 2012

Recently the unprecedented progress of Android platform and Google Play has brought more opportunities for individual mobile game developers. When playing an Android 3D game, users can accidentally hit HOME Key or BACK Key or receive an incoming message. Subsequently, another screen will appear on top and make the game application lose focus, or the operating system pause that game. These interruption events may also lead to the loss of game information or the game runs out of user control if that game cannot catch interruption events itself and resume at the exact time. As same as other mobile platforms, Android platform also provides Activity Lifecycle methods to help the game application control interruption problems. However, these methods are not adequate to solve all the interruption events. By implementing ANDCube game, we examine most of the possible interruption cases and propose some solutions to help Android game developers avoid some common interruption cases. Concurrently, we show the ways how a game application can catch all unavoidable interruption events and effectively resume from interruption to obtain a high quality game.

• The KIPS Transactions:PartA
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• v.13A no.5 s.102
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• pp.445-454
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• 2006

We introduce a family of simulators for I/O-intensive distributed or parallel applications, and a methodology that permits selecting the most efficient simulator meeting a given user-defined accuracy requirement. This methodology consists of a series of tests to choose an appropriate simulation based on the attributes of the application. In addition, each simulator provides two estimates of application execution time: the minimum expected time and the maximum. We present the results of applying our methodology to existing applications, and show that we can accurately simulate applications tens to hundreds of tunes faster than the application execution times.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.313-322
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• 2005

In order to access digital items in a server via ubiquitous devices, the digital items should be adapted according to the system environment, device characteristics and user preferences. In ubiquitous environment, those device-dependent adaptation requirements are not statically determined and not predictable. Therefore an application specific adaptation mechanism can not be applied to a general digital item adaptation engine. In this paper, we propose an application independent digital item adaptation architecture which has a set of minimal transcoders, transcoding path generator for a required adaptation requirement, and adaptation scheduler. And a CFG based method of finding a sequence of multiple unit transcoders called a transcoding path Is described in detail followed by experimental results.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.8-12
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• 1996

In many fields, the human sensibility ergonomics has applied to the product development for user's satisfaction. Also, it may use to lots of products and environments related to human convenient life. If the measurement and the validation of human sensibility are accomplished subjectively and qualitatively, then a good result is expected. Under the very competitive products development, designers applying with human sensibility ergonomics has faced with lots of problems including lack of experience, time, cost, and knowledge. In this study, a method of design for human sensibility application system is presented. In this study, a method of design for human sensibility application system is presented. Information element database such as adjectives, sensitivities, functions, and design factors is conducted, and design of system development including product development mechanism is produced. Also, the requirements and the specifications of this development model are discussed to develop the qualified implementation system.

• Journal of Fashion Business
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• v.22 no.6
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• pp.83-93
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• 2018

The purpose of this research is to investigate the characteristics of big data-based fashion shopping (BDFS) application, perceived usefulness, and expectation confirmation that influence the continuous usage intention of BDFS application users based on the expectation-confirmation model. A survey was conducted with female consumers in their 20s, who are living in Seoul and Incheon area and have used BDFS applications, A total of 182 responses were used for the data analysis. Five hypotheses were proposed, and regression analyses were conducted to test those hypotheses. The results indicated that the users' perceived usefulness increased with the increase of accuracy and personalization characteristics of the app and the expectation confirmation. The result suggested that it is essential to provide accurate information for users to feel useful and to develop the personalized offerings and services which can be the biggest strength of the big-data based mobile fashion store. It was also found that continuous usage intention increases with increased perceived usefulness and expectation confirmation. This result suggests that expectations can play a critical role in perceiving the usefulness of BDFS applications and the user's expectation confirmation also significantly affected the users' continuous usage intention.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.13-26
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• 2023

Recently, the development of wireless network technologies has been advancing in several directions: increasing data transmission speed, enhancing user mobility, expanding the range of services offered, improving the utilization of the radio frequency spectrum, and enhancing the intelligence of network and subscriber equipment. In this research, a series of contradictions has emerged in the field of wireless network technologies, with the most acute being the contradiction between the growing demand for wireless communication services (on operational frequencies) and natural limitations of frequency resources, in addition to the contradiction between the expansions of the spectrum of services offered by wireless networks, increased quality requirements, and the use of traditional (outdated) management technologies. One effective method for resolving these contradictions is the application of artificial intelligence elements in wireless telecommunication systems. Thus, the development of technologies for building intelligent (cognitive) radio and cognitive wireless networks is a technological imperative of our time. The functions of artificial intelligence in prospective wireless systems and networks can be implemented in various ways. One of the modern approaches to implementing artificial intelligence functions in cognitive wireless network systems is the application of fuzzy logic and fuzzy processors. In this regard, the work focused on exploring the application of fuzzy logic in prospective cognitive wireless systems is considered relevant.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.5
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• pp.49-58
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• 2005

There has been an increase in the interest of applications that use a combination of both pervasive computing technology and context-aware technology. This application based on the development environment along with the support of developing context-aware applications is now being researched thoroughly and by many. The service management system provides services that are needed for context-aware applications. This system is an integral part of the developmental environment of context-aware applications. But there is a restrictive matching based on ontology that uses simple syntactic matching or a plain type of service used in previous researches. And there is also no consideration for context-aware information. Also, if the user is unable to find a service that is satisfactory, or is a service which a user does not desire, they may use a service which is composed of other existing services. This paper proposes a service management system based on context-aware information. The proposed system enables the accurate finding of services by considering semantic matching methods based on ontology and context-aware information. If the user does not find a service that is helpful in the service registry, it can provide the service list to enable other existing service compositions, by providing the functionality of these service compositions. As a result, the experiment of the system proposed has shown that the system properly supported the service discovery based on context-aware information and service composition.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.67-86
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• 2020

Recommender Systems have been huge influence users and business more and more. Recently the importance of E-commerce has been reached rapid growth greatly in world-wide COVID-19 pandemic. Recommender system is the center of E-commerce lively. Top ranked E-commerce managers mentioned that recommender systems have a major influence on customer's purchase such as about 50% of Netflix, Amazon sales from their recommender systems. Most algorithms have been focused on improving accuracy of recommender system regardless of novelty, diversity, serendipity etc. Recommender systems with only high accuracy cannot satisfy business long-term profit because of generating sales polarization. In addition, customers do not experience enjoyment of shopping from only focusing accuracy recommender system because customer's preference is changed constantly. Therefore, recommender systems with various values need to be developed for user's high satisfaction. Reranking is the most useful methodology to realize diversity of recommender system. In this paper, diversity of recommender system is represented through constructing high similarity with users who have different preference using each user's purchased item's category algorithm. It is distinguished from past research approach which is changing the algorithm of recommender system without user's diversity preference level. We tried to discover user's diversity preference level and observed the results how the effect was different according to user's diversity preference level. In addition, graph-based recommender system was used to show diversity through user's network, not collaborative filtering. In this paper, Amazon Grocery and Gourmet Food data was used because the low-involvement product, such as habitual product, foods, low-priced goods etc., had high probability to show customer's diversity. First, a bipartite graph with users and items simultaneously is constructed to make graph-based recommender system. However, each users and items unipartite graph also need to be established to show diversity of recommender system. The weight of each unipartite graph has played crucial role changing Jaccard Distance of item's category. We can observe two important results from the user's unipartite network. First, the user's diversity preference level is observed from the network and second, dissimilar users can be discovered in the user's network. Through the research process, diversity of recommender system is presented highly with small accuracy loss and optimalization for higher accuracy is possible controlling diversity ratio. This paper has three important theoretical points. First, this research expands recommender system research for user's satisfaction with various values. Second, the graph-based recommender system is developed newly. Third, the evaluation indicator of diversity is made for diversity. In addition, recommender systems are useful for corporate profit practically and this paper has contribution on business closely. Above all, business long-term profit can be improved using recommender system with diversity and the recommender system can provide right service according to user's diversity level. Lastly, the corporate selling low-involvement products have great effect based on the results.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.656-659
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• 2015

Recently, due to the standard of a new browser developed by the Google and Mozilla "Service Worker", future users is expected to be able to make use of favorite Web sites offline. Google's is, Web sites have developed a standard of a new browser so as to always respond to user requests. Service Worker, websites that provide space capable of offline work to the user's browser to store various document information, to provide the necessary resources. Then, in order to greatly reduce the data exchange operations between the browser and the server, the speed of the Web page increases. Not only cooks as native app that can use the Web application offline, in that us to also further enhance the characteristics of an existing Web application that is running without installing destructive high technology. Service worker specifications, use experience of Web application is very can be improved, is an innovative technology indicates the version of the web evolve as the future of the platform. Service Worker is not included in HTML5 standard final, is currently being continued standardization. Future Service Worker technology I expect what kind of thing unfolds when applied to the Web browser.