Mobile Devices, which are developed with the fast growing of the Internet, have flexible internet accessibility and can access the network anywere so that they can execute software applications. However, it is very challenging to deploy highly complex applications on mobile devices since they have limited resources. To overcome the limitation, researches on applying a concept of services to mobile applications have been proposed. Android is one of the popular mobile platforms and is designed to effectively execute mobile applications on the mobile devices having limited resources. Since service-based Android applications, which adopt a concept of services and Android platform, invoke remote services and are built with Android-specific components, they are much different from traditional software applications. Consequently, it is not straightforward to apply object-oriented (OO) analysis and design methods to developing service-based Android applications, although they have been frequently applied to developing traditional applications. In this paper, we present a process to develop service-based Android mobile applications, which extends a traditional OO development process. First, we raise design issues to be considered in developing service-based Android applications. Then, to solve the issues, we present detailed guidelines for essential phases of OO-based development process that are customized to service-based Android applications. Finally, to show applicability of the process, we perform a case study. The proposed design process is effectively utilized as a set of guidelines to develop service-based Android applications more systematically and effectively.
As tourists travel to other regions, they encounter numerous facts that conflict with their views. At that time, we change our view of coping with life. In this respect, tourism is a new way of learning. As a new learning method, tourism experience research is a new approach. In this study, the relationship between experience and learning experienced in tourist destinations was analyzed by applying the activity theory. The analysis units applied in the activity theory were set as subjects, goals, communities, roles, methods and rules, outcomes, and relevance to local communities. Based on this, in-depth interviews were conducted with commentators and guides who had a great influence on the tourism experience to analyze the learning process of tourists. As a result of the analysis, the experiences of tourists during the tour were interactive in various forms within the unit as well as the unit of the activity system of the commentator and guide. This interaction induces changes in the tourism experience activity system, enabling tourists to learn. The content is that the value of learning increases as the role of guide and commentator increases, that the social and cultural dimension of tourism experience is included in the learning effect, and the contradictions that arise from interactions within or between activity systems. The fact that they find the solution process themselves, and that tourism activity is not an isolated unit, but exists at the intersection of hierarchies and networks, is affected by the activities and environments of others.
For high school students in Jeonbuk, this study aims to identify the problems caused by outflow of local youth population and their preference factors to enter university in Seoul-metropolitan area, and to draw out the direction of local human resources program, through questionnaire investigation and focused group interview. The main findings are as follows: First, 68.8% of high school students, especially the top grade students prefer to enter university in metropolitan area. The metropolitan cultural characteristics, such as reputation of universities and ranking, openness and anonymity, and urban infrastructure attract students. Second, there is a close relationship between the individual background, growth area - enrollment area - employment area, and the location dependency without return migration is very strong. Third, local human resources program was evaluated as a meaningful activity for high school students, in order to understand the further education and career, and have an interest in local universities. Therefore, it is necessary to discover industries consistent with local identity, create networks, develop and implement programs considering the actual educational conditions. The gender-free program, supplement program for the integrated curriculum, and contents that to supplement science subjects should be developed. Additionally, this issue could be resolved expanding the perspective of balanced national development and improve the local environment to enhance the urban attraction points.
Joonho Kim;Geonju Chae;Jaemin Park;Kyeong-Won Park
Journal of Intelligence and Information Systems
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v.29
no.1
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pp.107-119
/
2023
The technology that recognizes a soldier's motion and movement status has recently attracted large attention as a combination of wearable technology and artificial intelligence, which is expected to upend the paradigm of troop management. The accuracy of state determination should be maintained at a high-end level to make sure of the expected vital functions both in a training situation; an evaluation and solution provision for each individual's motion, and in a combat situation; overall enhancement in managing troops. However, when input data is given as a timer series or sequence, existing feedforward networks would show overt limitations in maximizing classification performance. Since human behavior data (3-axis accelerations and 3-axis angular velocities) handled for military motion recognition requires the process of analyzing its time-dependent characteristics, this study proposes a high-performance data-driven classifier which utilizes the long-short term memory to identify the order dependence of acquired data, learning to classify eight representative military operations (Sitting, Standing, Walking, Running, Ascending, Descending, Low Crawl, and High Crawl). Since the accuracy is highly dependent on a network's learning conditions and variables, manual adjustment may neither be cost-effective nor guarantee optimal results during learning. Therefore, in this study, we optimized hyperparameters using Bayesian optimization for maximized generalization performance. As a result, the final architecture could reduce the error rate by 62.56% compared to the existing network with a similar number of learnable parameters, with the final accuracy of 98.39% for various military operations.
With the rapid development of live streaming commerce, online host as an information source plays a critical role in affecting live streaming performance. However, the impact of different product types on the relationship between online hosts and live streaming has been less studied. Based on the elaboration likelihood model (ELM) and information source theory, this study aims to empirically investigate what factors influence the sales of live streaming commerce and how product type moderates the relationship between them. The analysis of 11,422 live streaming commerce data collected for four months from October 10, 2021 to February 10, 2022 shows that, among the factors related to source credibility and attractiveness, multi-channel networks (MCN) and the number of followers positively affect the sales volume of live streaming commerce, whereas the reputation score harms the sales. Moreover, the moderating effect of the product type (i.e., ratio of involvement products) on the relationships is confirmed. The findings enrich the literature on live streaming commerce performance. The limitations and future research directions are also discussed.
Sang-Gyoon Kim;Jong-Seok Won;Yong-Beom Pyeon;Min-Kyung Cho
Journal of the Society of Disaster Information
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v.20
no.2
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pp.339-350
/
2024
Purpose: This study analyzes accessibility of 10 hydrogen charging stations in Seoul and identifies areas that were difficult to access. The purpose is to re-analyze accessibility by adding a new location in terms of equity and safety of location placement, and then draw implications by comparing the improvement effects. Method: By applying the location-allocation model and the service area model based on network analysis of the ArcGIS program, areas with weak access were identified. The location selection method applied the 'Minimize Facilities' method in consideration of the need for rapid arrival to insufficient hydrogen charging stations. The limit distance for arrival within a specific time was analyzed by applying the average vehicle traffic speed(23.1km/h, Seoul Open Data Square) in 2022 to three categories: 3,850m(10minutes), 5,775m(15minutes), 7,700m(20minutes). In order to minimize conflicts over the installation of hydrogen charging stations, special standards of the Ministry of Trade, Industry and Energy applied to derive candidate sites for additional installation of hydrogen charging stations among existing gas stations and LPG/CNG charging stations. Result: As a result of the analysis, it was confirmed that accessibility was significantly improved by installing 5 new hydrogen charging stations at relatively safe gas stations and LPG/CNG charging stations in areas where access to the existing 10 hydrogen charging stations is weak within 20 minutes. Nevertheless, it was found that there are still areas where access remains difficult. Conclusion: The location allocation model is used to identify areas where access to hydrogen charging stations is difficult and prioritize installation, decision-making to select locations for hydrogen charging stations based on scientific evidence can be supported.
The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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v.27
no.3
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pp.127-143
/
2022
Recently, many attempts to run numerical ocean models in cloud computing environments have been tried actively. A cloud computing environment can be an effective means to implement numerical ocean models requiring a large-scale resource or quickly preparing modeling environment for global or large-scale grids. Many commercial and private cloud computing systems provide technologies such as virtualization, high-performance CPUs and instances, ether-net based high-performance-networking, and remote direct memory access for High Performance Computing (HPC). These new features facilitate ocean modeling experimentation on commercial cloud computing systems. Many scientists and engineers expect cloud computing to become mainstream in the near future. Analysis of the performance and features of commercial cloud services for numerical modeling is essential in order to select appropriate systems as this can help to minimize execution time and the amount of resources utilized. The effect of cache memory is large in the processing structure of the ocean numerical model, which processes input/output of data in a multidimensional array structure, and the speed of the network is important due to the communication characteristics through which a large amount of data moves. In this study, the performance of the Regional Ocean Modeling System (ROMS), the High Performance Linpack (HPL) benchmarking software package, and STREAM, the memory benchmark were evaluated and compared on commercial cloud systems to provide information for the transition of other ocean models into cloud computing. Through analysis of actual performance data and configuration settings obtained from virtualization-based commercial clouds, we evaluated the efficiency of the computer resources for the various model grid sizes in the virtualization-based cloud systems. We found that cache hierarchy and capacity are crucial in the performance of ROMS using huge memory. The memory latency time is also important in the performance. Increasing the number of cores to reduce the running time for numerical modeling is more effective with large grid sizes than with small grid sizes. Our analysis results will be helpful as a reference for constructing the best computing system in the cloud to minimize time and cost for numerical ocean modeling.
WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.
The controversy of the risk perception related to particulate matters becomes significant. Therefore, in order to understand the nature of the particulate matters, we gathered articles and comments in on-line community related to bicycling which is affected by exposure of the particulate matters. As a result, firstly, the government - led particulate matter policy was strengthened and segmented every period, butthe risk perception related to particulate matters in the bicycle community has become active and serious. Second, as a result of analyzing the perception change of outdoor activities related to particulate matters, bicycle users in community showed a tendency of outdoor activity depending on the degree of particulate matters ratherthan the weather. In addition, the level of the risk perception related to particulate matters has been moved from fears of serious threat in daily life and health, combined with the disregard of domestic particulate matter levels or mask performance. Ultimately, these risk perception related to particulate matters have led some of the bicycling that were mainly enjoyed outdoors to the indoor space. However, in comparison with outdoor bicycling enjoyed by various factors such as scenery, people, and weather, the monotonous indoor bicycling was converted into another type of indoor exercise such as fitness and yoga. In summary, it was derived from mistrust of excessive information or policy provided by the government or local governments. It is considered that environmental policy should be implemented after discussion of risk communication that can reduce the gap between public anxiety and concern so as to cope with the risk perception related to particulate matters. Therefore,this study should be provided as an academic basis for the effective communication direction when decision makers establish the policy related to particulate matters.
In this paper, we developed DNL(Dynamic Network Loading) model based on Moving cell theory to analyze the dynamic characteristics of traffic flow in congested network. In this paper vehicles entered into link at same interval would construct one cell, and the cells moved according to Cell following rule. In the past researches relating to DNL model a continuous single link is separated into two sections such as running section and queuing section to describe physical queue so that various dynamic states generated in real link are only simplified by running and queuing state. However, the approach has some difficulties in simulating various dynamic flow characteristics. To overcome these problems, we present Moving cell theory which is developed by combining Car following theory and Lagrangian method mainly using for the analysis of air pollutants dispersion. In Moving cell theory platoons are represented by cells and each cell is processed by Cell following theory. This type of simulation model is firstly presented by Cremer et al(1999). However they did not develop merging and diverging model because their model was applied to basic freeway section. Moreover they set the number of vehicles which can be included in one cell in one interval so this formulation cant apply to signalized intersection in urban network. To solve these difficulties we develop new approach using Moving cell theory and simulate traffic flow dynamics continuously by movement and state transition of the cells. The developed model are played on simple network including merging and diverging section and it shows improved abilities to describe flow dynamics comparing past DNL models.
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