• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.11
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• pp.9-18
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• 2020

Recently, studies of integrated management platform and performance-based maintenance decision-marking systems have proceeded to the efficient management of port facilities. The purpose of this study was to manage and operate port facilities based on performance and to provide long-term durability and budgetary execution. Thus, it is essential to secure basic data to be analyzed in an integrated platform and decision-marking system. This study derived the data linkage measures to secure port facility design and management information. The target of deriving the data linkage was the POMS (Port Facility Management System) currently in operation by the MOF (Ministry of Oceans and Fisheries). To derive data linkage, analyze the database of POMS and select the data required for the operation-integrated platform and decision-marking system. The final data linkage target was determined by compiling the requirements of the relevant experts and selecting the final target of three groups (port and facility information, management information, and user information). As a result, the API interface design was prepared for detailed linked data and data linkage framework between the linkage data of POMS. The provision of real-time data linkage between POMS and integrated platform is expected to improve the operational efficiency of the integrated platform.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.575-584
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• 2013

Data types used for big-data analysis are very widely, such as news, blog, SNS, papers, patents, sensed data, and etc. Particularly, the utilization of web documents offering reliable data in real time is increasing gradually. And web crawlers that collect web documents automatically have grown in importance because big-data is being used in many different fields and web data are growing exponentially every year. However, existing web crawlers can't collect whole web documents in a web site because existing web crawlers collect web documents with only URLs included in web documents collected in some web sites. Also, existing web crawlers can collect web documents collected by other web crawlers already because information about web documents collected in each web crawler isn't efficiently managed between web crawlers. Therefore, this paper proposed a distributed web crawler. To resolve the problems of existing web crawler, the proposed web crawler collects web documents by RSS of each web site and Google search API. And the web crawler provides fast crawling performance by a client-server model based on RMI and NIO that minimize network traffic. Furthermore, the web crawler extracts core content from a web document by a keyword similarity comparison on tags included in a web documents. Finally, to verify the superiority of our web crawler, we compare our web crawler with existing web crawlers in various experiments.

• KIISE Transactions on Computing Practices
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• v.23 no.9
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• pp.517-534
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• 2017

This paper proposes an Internet of Things (IoT) middleware called Middleware for Cooperative Interaction of Things (MinT). MinT supports a fully distributed IoT environment in which IoT devices directly connect to peripheral devices, easily constructing a local or global network and sharing their data in an energy efficient manner. MinT provides a sensor abstract layer, a system layer and an interaction layer. These layers enable integrated sensing device operations, efficient resource management, and interconnection between peripheral IoT devices. In addition, MinT provides a high-level API, allowing easy development of IoT devices by developers. We aim to enhance the energy efficiency and performance of IoT devices through the performance improvements offered by MinT resource management and request processing. The experimental results show that the average request rate increased by 25% compared to existing middlewares, average response times decreased by 90% when resource management was used, and power consumption decreased by up to 68%. Finally, the proposed platform can reduce the latency and power consumption of IoT devices.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.1-9
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• 2007

Cellular operators develop high speed mobile internet and multi-function cellular phones to activate new business model based on mobile internet services. Domestic cellular operators evolve their mobile networks from cdma2000-1x and EvDo to HSDPA to activate high speed mobile internet services. They also develop mobile internet platforms such as WIPI, BREW, and J2ME on multi-function cellular phones having multimedia solutions such as camera, MP3, MPEG, 3D game engine, DMB, PAN such as bluetooth, IrDA, W-LAN, and location information using GPS. But, content providers have problems of redevelopment of the same mobile internet application on different mobile internet platforms provided by cellular operators. In this paper, we develop conversion solutions for interoperability of mobile internet applications on WIPI and BREW using an one-pass compiler. We confirm the performance the proposed conversion solutions for the API conversion rate, the converted file size, and the full conversion time using the popular mobile games which are the killer applications on WiPI and BREW.

• The Journal of the Korea Contents Association
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• v.20 no.10
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• pp.89-99
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• 2020

In this study, we tried to produce moving-image works through sentiment analysis of music. First, Google natural language API was used for the sentiment analysis of lyrics, then the result was applied to the image visualization rules. In prior engineering researches, text-based sentiment analysis has been conducted to understand users' emotions and attitudes by analyzing users' comments and reviews in social media. In this study, the data was used as a material for the creation of artworks so that it could be used for aesthetic expressions. From the machine's point of view, emotions are substituted with numbers, so there is a limit to normalization and standardization. Therefore, we tried to overcome these limitations by linking the results of sentiment analysis of lyrics data with the rules of formative elements in visual arts. This study aims to transform existing traditional art works such as literature, music, painting, and dance to a new form of arts based on the viewpoint of the machine, while reflecting the current era in which artificial intelligence even attempts to create artworks that are advanced mental products of human beings. In addition, it is expected that it will be expanded to an educational platform that facilitates creative activities, psychological analysis, and communication for people with developmental disabilities who have difficulty expressing emotions.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.169-186
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• 2020

This study aims to examine the characteristics of news content and users' reactions in local broadcasting Youtube news' channel, and explore how the local media should response in the new online video environment. YouTube Open API sampled 3,950 news-related videos uploaded over a month on 31 YouTube news channels nationwide. The content analysis was performed on the basis of the analysis of individual videos, such as characteristics of each content and users' reactions. As a result, a few news channels have produced digital-only content, but the ratio has been very low, most were broadcast replay videos with titles and formats uploaded as they were. In some cases, it still operates as a comprehensive channel, which failed to show its expertise as an independent digital news platform. This shows that theses YouTube channels lacks differentiation from TV or its own web page, and is still skewed to the auxiliary role or online archive function of TV platform. Nevertheless, digital-only content, which can be a national issue based on regional expertise, has led to a higher number of views and users reactions, suggesting that is a realistic and effective strategy with expandability in online space in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.54-62
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• 2018

As a part of realization of artificial intelligence signal(AI Signal), this study proposed an actuated signal algorithm based on vehicle queue length that estimates in real time by deep learning. In order to implement the algorithm, we built an API(COM Interface) to control the micro traffic simulator Vissim in the tensorflow that implements the deep learning model. In Vissim, when the link travel time and the traffic volume collected by signal cycle are transferred to the tensorflow, the vehicle queue length is estimated by the deep learning model. The signal time is calculated based on the vehicle queue length, and the simulation is performed by adjusting the signaling inside Vissim. The algorithm developed in this study is analyzed that the vehicle delay is reduced by about 5% compared to the current TOD mode. It is applied to only one intersection in the network and its effect is limited. Future study is proposed to expand the space such as corridor control or network control using this algorithm.

• The Journal of Bigdata
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• v.4 no.2
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• pp.23-34
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• 2019

Recently, the crime that utilizes the digital platform is continuously increasing. About 140,000 cases occurred in 2015 and about 150,000 cases occurred in 2016. Therefore, it is considered that there is a limit handling those online crimes by old-fashioned investigation techniques. Investigators' manual online search and cognitive investigation methods those are broadly used today are not enough to proactively cope with rapid changing civil crimes. In addition, the characteristics of the content that is posted to unspecified users of social media makes investigations more difficult. This study suggests the site-based collection and the Open API among the content web collection methods considering the characteristics of the online media where the infringement crimes occur. Since illegal content is published and deleted quickly, and new words and alterations are generated quickly and variously, it is difficult to recognize them quickly by dictionary-based morphological analysis registered manually. In order to solve this problem, we propose a tokenizing method in the existing dictionary-based morphological analysis through WPM (Word Piece Model), which is a data preprocessing method for quick recognizing and responding to illegal contents posting online infringement crimes. In the analysis of data, the optimal precision is verified through the Vote-based ensemble method by utilizing a classification learning model based on supervised learning for the investigation of illegal contents. This study utilizes a sorting algorithm model centering on illegal multilevel business cases to proactively recognize crimes invading the public economy, and presents an empirical study to effectively deal with social data collection and content investigation.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.1
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• pp.47-62
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• 2012

To propagate clinical disease management service, there should be built a ecosystem where service developers, service providers, device suppliers closely cooperate for u-Health platform. However, most u-Health platform is difficult to build an effective ecosystem due to the lack of secure and effective PHR(Personal Health Record) management, the lack of personalized and intelligent service, difficulties of N-screen service. To solve these problems we suggest the CDMP(Chronic Disease Management Platform) architecture. The CDMP is a software platform that provides the core functions to develop the chronic disease management services and performs a hub function for the link and integration rbetween various services and systems. CDMP is SOA based platform that enables a provision of reusability, expansibility and it provides open API where everybody can share information, contents and services easily. CDMP supports the multi platform system foN-screen service and the self management functions via SNS. In this paper, we design and implement the CDMP including PHR service based on hybrid data model for privacy preservation. Experiment results prove the effectiveness of hybrid model-based PHR service.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.6
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• pp.33-42
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• 2012

Rapid evolution of wired and wireless technologies results in various types of embedded systems, and the software to be embedded into those devices now needs the flexibility rather than the fixedness which was well-known property for the embedded software in the past. Mobile agent is one of the useful distributed technologies of reducing network load and latency because of its disconnected operations and high asynchrony. In this paper, a component-based mobile agent framework, called EmHUMAN, is designed and implemented for structural embedding into the devices showing different functions and resource constraints. It consists of 3 layers of components. Based on those components, a structural embedding, considering resource constraints of required functions, amount of storage space, computing power, network bandwidth, ${\ldots} $ etc can be performed. The components in each layer can be extended with addition of new components, removing some components and modifying components. EmHUMAN plays the role of a framework for developing mobile agent based distributed systems. It is also a mobile agent system by itself. EmHUMAN provides several utilities as built-in API's, and thus high effectiveness in programming mobile agents can be achieved.