• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.31-37
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• 2019

Citation-based article summarization is to create a shortened text for an academic article, reflecting the content of citing sentences which contain other's thoughts about the target article to be summarized. To deal with the problem, this study introduces an extractive summarization method based on calculating a linear combination of various sentence salience scores, which represent the degrees to which a candidate sentence reflects the content of author's abstract text, reader's citing text, and the target article to be summarized. In the current study, salience scores are obtained by computing surface-level textual similarities. Experiments using CL-SciSumm datasets show that the proposed method parallels or outperforms the previous approaches in ROUGE evaluations against SciSumm-2017 human summaries and SciSumm-2016/2017 community summaries.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.239-250
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• 2019

An individual's health data is very sensitive and private. Such data are usually stored on a private or community owned cloud, where access is not restricted to the owners of that cloud. Anyone within the cloud can access this data. This data may not be read only and multiple parties can make to it. Thus, any unauthorized modification of health-related data will lead to incorrect diagnosis and mistreatment. However, we cannot restrict semipublic access to this data. Existing security mechanisms in e-health systems are competent in dealing with the issues associated with these systems but only up to a certain extent. The indigenous technologies need to be complemented with current and future technologies. We have put forward a method to complement such technologies by incorporating the concept of blockchain to ensure the integrity of data as well as its provenance.

• Korea Information Processing Society Review
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• v.11 no.6
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• pp.8-24
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• 2004

OO RT programming is a technology expected to flourish in this quarter of the 21st century. Currently, its youthfulness is indicated by the insufficient availability of the support middleware and the associated API, let alone language compilers. The middleware providing fault-tolerant execution support is in its infancy. The advances in OO RT distributed programming will also enable large-scale RT simulations. The research community dealing with this technology area is expected to grow continuously for foreseeable future and consequent accelerations of the technology advances will in turn accelerate the development of many new types of sophisticated RT DC applications as well as realization of advanced types of ubiquitous computing societies.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.1-18
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• 2011

Context-aware computing aims to enable the on-line applications and services to be executed in a timely and automated manner. Many of such applications and services involve group-level interactions. For more smoothing communication within a community, specific group-level issues such as group dynamics must be considered. To do so, obtaining group-level contexts such as the role, conflict resolution and norms, are key ingredients to improve group performance. Since group context is not the same as a simple summation of individual context, as group is not just a simple set of individuals, awaring individual context is not sufficient for group-level communication support. However, context-aware computing research still has stressed more on individual context. This leads us to the motivation of searching for group context aware method. Hence, the of this paper is to propose a novel methodology which automatically recognizes group context. Especially, we focus on group conhesiveness in this paper just because group cohosiveness is one of the important variables to control the performance of group interaction. To verify the applicability of the proposed method, an empirical test has been conducted to compare the performance of the proposed methodology with that of conventional methods.

• The Journal of the Korea Contents Association
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• v.8 no.12
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• pp.53-62
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• 2008

The Election paradigm can be used as a building block in many practical problems such as group communication, atomic commit and replicated data management where a protocol coordinator might be useful. The problem has been widely studied in the research community since one reason for this wide interest is that many distributed protocols need an election protocol. However, despite its usefulness, to our knowledge there is no work that has been devoted to this problem in a mobile ad hoc computing environment. Mobile ad hoc systems are more prone to failures than conventional distributed systems. Solving election in such an environment requires from a set of mobile nodes to choose a unique node as a leader based on its priority despite failures or disconnections of mobile nodes. In this paper, we describe a solution to the election problem from mobile ad hoc computing systems. This solution is based on the Group Membership Detection algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.1
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• pp.86-90
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• 2008

Ubiquitous Smart pace connects many kinds of smart object to satisfy user's demands. Thus, not only excessive loads but also resource collisions occur among service objects while configurating services to fulfill the user's request. After all, as malfunction occurs between service objects, it offers wrong service to user or does not respond to service request. To solve these problems, Ubiquitous Smart Space is observed by monitoring system of function, performance, and status of objects. Therefore, optimized function, performance and duality of service of smart space service for user should be improved by recording log and analyzing recorded the log. In this paper, we suggest a novel monitoring system to optimize performance according to pattern of diverse services and execute self-recovery on system down and malfunction.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.131-140
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• 2009

Recently, the information visualization research community has given significant attention to graph visualization, especially visualization of social networks. However, visualization of information flows in a very large social network has not been studied in depth. However, information flows are tightly related to the structure of social networks and it shows dynamic behavior of interactions between members of social networks. Thus, we can get much useful information about social networks from information flows. In this paper, we present our research result that enables users to navigate a very large social network in Google Maps' method and to take a look at information flows on the network. To this end, we devise three techniques; (i) mapping a very large social network to a 2-dimensional graph layout, (ii) exploring the graph to all directions with zooming it in/out, and (iii) building an efficient query processing framework. With these methods, we can visualize very large social networks and information flows in a limited display area with a limited computing resources.

• Journal of Internet Computing and Services
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• v.21 no.1
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• pp.103-110
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• 2020

The EDISON is a platform that supports numerical analysis for problem solving in computational science and engineering. We provide a cloud service for users, and provide an environment to access and execution of the simulation service on the web. For now, the EDISON platform provides simulation services for eight applied field on computational science engineering. Users can check the numerical analysis result by web in the computational science and engineering platform. In addition, various services such as community activity with other researchers, and the configuration of simulation environment by user 's needs can be provided. A representative service of the EDISON platform is a web-based simulation service that performs numerical analysis for problem solving of various computational science and engineering. Currently, EDISON platform provides workbench simulation service. It is the web-based simulation execution environment, and result analysis to provide simulation regardless of various personal computing resource or environment in each numerical analysis. In this paper, we build an interface for pre and post processor that can be used in conjunction with the workbench-based simulation service provided by EDISON platform. We provide a development environment with interface that is implemented by applying a pre and post processor optimized for the simulation service. According to simulation and execution are performed by linking the new workbench-based simulation service to the pre and post processor.

• Computers and Concrete
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• v.9 no.4
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• pp.275-291
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• 2012

The service loads are often decisive in the design of concrete structures. The evaluation of the cracking moment, $M_{cr}$, is an important issue to predict the performance of the structure, such as, the deflections of the reinforced concrete beams and slabs. To neglect the steel bars of the section is a simplification that is normally used in the computation of the cracking moment. Such simplification leads to small errors in the value of this moment (typically less than 20%). However, these small errors can conduce to significant errors when the values of deflections need to be computed from $M_{cr}$. The article shows that an error of 10% on the evaluation of $M_{cr}$ can lead to errors over 100% in the deformation values. When the deformation of the structure is the decisive design parameter, the exact computing of the cracking moment is obviously very important. Such rigorous computing might lead to important savings in the cost of the structure. With this article the authors wish to draw the attention of the technical community to this fact. A simple equation to evaluate the cracking moment, $M_{cr}$, is proposed for a rectangular cross-section. This equation leads to cracking moments higher than those obtained by neglecting the reinforcement bars and is a simple rule that can be included in Eurocode 2. To verify the accuracy of the developed model, the results of the proposed equation was compared with a rigorous computational procedure. The proposed equation corresponds to a good agreement when compared with the previous approach and, therefore, this model can be used as a practical aid for calculating an accurate value of the cracking moment.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.6
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• pp.7-14
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• 2019

The automatic monitoring and detection of crowd behavior in the surveillance videos has obtained significant attention in the field of computer vision due to its vast applications such as security, safety and protection of assets etc. Also, the field of crowd analysis is growing upwards in the research community. For this purpose, it is very necessary to detect and analyze the crowd behavior. In this paper, we proposed a deep learning-based method which detects abnormal activities in surveillance cameras installed in a smart city. A fine-tuned VGG-16 model is trained on publicly available benchmark crowd dataset and is tested on real-time streaming. The CCTV camera captures the video stream, when abnormal activity is detected, an alert is generated and is sent to the nearest police station to take immediate action before further loss. We experimentally have proven that the proposed method outperforms over the existing state-of-the-art techniques.