• Management & Information Systems Review
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• v.32 no.2
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• pp.1-19
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• 2013

The purpose of this study is to provide the model for goal planning system and explore the affecting factors in suitability of goal planning system and possibility of goal attainment. The findings in a factor analysis of the sample of Korean firms indicate that the factors suggested by theories and previous studies can be summarized to 40 implications and then 7 groups including attachment of top managers, systemicity, participation system, motivation, alignment of top-down & bottom-up. adjustment for environmental changes, goal content. In addition, the findings in multiple regression analyses show that goal content, alignment of top-down & bottom-up, and adjustment for environmental changes are positively, significantly influence the recognition level of employees on the suitability of goal planning system. On the other hand, goal content, attachment of top managers, and motivation are significantly influence the recognition level of employees on the possibility of goal attainment. This study provides the checklist for the suitability of goal planning system and various implications for practitioners.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.172-183
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• 1994

In the multidatabase systems(MDBS), local autonomy and global consistency are important issues. Global consistency could be maintained by a global concurrency control algorithm and a global recovery algorithm. In this thesis, we propose a global concurrency control algorithm to ensure local autonomy and to guarantee global serializability, and a global recovery algorithm which is possible to recover the multudatabase from any failures. The proposed global concurrency control algorithm uses bottom-up approach, based on three-level transaction processing model. It can produce a local history that the execution order of subtransactions is identical to their serialization order by using dummy-operations in the server when an indirect conflict is caused between subtransactions due to local transactions. At the global module, it can efficiently validate global serializability of global transactions by checking global serializability only for the global transactions which conflict with each other.

• Journal of Agricultural Extension & Community Development
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• v.10 no.1
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• pp.15-29
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• 2003

The study uses agricultural knowledge system theory to explore how traditional knowledge applies to the linkage system of agricultural research and extension in rural Korea. By agricultural knowledge system we emphasize the dynamic networks of actors, processes of negotiation, and the diverse ways in which knowledge is constructed and performed. The knowledge systems reflect the idea that the boundaries between knowledge groups are not closed and that there could be considerable overlap between knowledge system. The results of this study are the following : First, we should know that some extension agents clearly value farmer knowledge and try to facilitate farmer-to-farmer communication. Extension plays a significant role in the knowledge-creation process and shaping communities because knowledge processes are embedded in social processes that involve aspects of power, authority, and legitimization. Third, the constructions of agricultural knowledge systems thus include social interactions, communication, and the diverse processes individuals employ create, use, and evaluate multiple types and sources of information through the linkage between agricultural colleges and Rural Development Administration (RDA), establishing the research institution of research and extension linkage, exchange research agent with extension agent, and bottom-up approach. Second, we should know that the focus of traditional knowledge development is rural community development as a community process. Nowadays the sessions of the Intergovernmental Committee of World Intellectual Property Organization (WIPO) cover two lines of inquiry, which are the use of existing standards of intellectual property for the protection of traditional knowledge and that of new legal standards, eventually in the from of sui generis mechanisms of protection.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.378-391
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• 2011

In this paper, we suggest a novel method of selecting visual information based on bottom-up visual attention of human. We propose a new model that improve accuracy of detecting attention region by using depth information in addition to low-level spatial features such as color, lightness, orientation, form and temporal feature such as motion. Motion is important cue when we derive temporal saliency. But noise obtained during the input and computation process deteriorates accuracy of temporal saliency Our system exploited the result of psychological studies in order to remove the noise from motion information. Although typical systems get problems in determining the saliency if several salient regions are partially occluded and/or have almost equal saliency, our system is able to separate the regions with high accuracy. Spatiotemporally separated prominent regions in the first stage are prioritized using depth value one by one in the second stage. Experiment result shows that our system can describe the salient regions with higher accuracy than the previous approaches do.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3567-3582
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• 2020

Human activities are often affected by weather conditions. Automatic weather recognition is meaningful to traffic alerting, driving assistance, and intelligent traffic. With the boost of deep learning and AI, deep convolutional neural networks (CNN) are utilized to identify weather situations. In this paper, a three-channel convolutional neural network (3C-CNN) model is proposed on the basis of ResNet50.The model extracts global weather features from the whole image through the ResNet50 branch, and extracts the sky and ground features from the top and bottom regions by two CNN5 branches. Then the global features and the local features are merged by the Concat function. Finally, the weather image is classified by Softmax classifier and the identification result is output. In addition, a medium-scale dataset containing 6,185 outdoor weather images named WeatherDataset-6 is established. 3C-CNN is used to train and test both on the Two-class Weather Images and WeatherDataset-6. The experimental results show that 3C-CNN achieves best on both datasets, with the average recognition accuracy up to 94.35% and 95.81% respectively, which is superior to other classic convolutional neural networks such as AlexNet, VGG16, and ResNet50. It is prospected that our method can also work well for images taken at night with further improvement.

• Journal of Internet Computing and Services
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• v.6 no.2
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• pp.141-152
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• 2005

Many organizations have been recognizing the necessity of workflow automation technologies according to the rapid expansion of business process oriented applications, such as enterprise resource pianning, customer relationship management, electronic approval management, and so on, Thus, they have started adopting workflow management systems as an essential technological solution for their workflow processes, However, we need some technological extensions and improvements on them in order to accommodate a new type of workflow processes, which is called cross-organizational global workflow processes that require a certain level of collaborations between the organizations engaged in the global workflow processes, Fragment-driven workflow modeling methodology is a Bottom-Up methodology composing a global workflow by defining each organization's own activities, which is called a fragment through a realtime cooperative system. The approach is able to not only simplify the modeling work but also keep each organization's independence in modeling a global workflow, In this paper, we describe the fragment-driven workflow modeling methodology and realize the methodology through the implementation of a cooperative swimlane workflow modeling system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.119-128
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• 2016

Use of ICT in Government has ability to improve service delivery to its citizens, and yet many developing countries have lagged behind in the implementation of e-Government. Many e-Government initiatives also failed to achieve their objectives in developing countries. This paper therefore aims to identify critical failure or success factors in Kenya, using Heeks' Factor Model. A survey questionnaire was developed and data were collected and analyzed from officials and interested citizens. The analysis results enabled to highlight seven specific success and failure factors, and their constituent elements in Kenya. The Kenyan overall e-Government implementation score belongs to the Zone of Improvement (3.52 of total 5.0), which means partial success or failure. The enablers of e-Government projects are good strategy formulation, and internal and external drive, whereas main failures of e-Government are weak ICT infrastructure. The areas for improvement are project management, design, competencies and funding. Data analysis highlights both strengths and weaknesses for each factor or variable. In particular, Kenyan government excels at the drive for change by top to bottom government officers as well as external stakeholders, while the government officers who are using e-Government are satisfied with the availability of vision, strategy and plan of e-Government implementation. Both technologies and e-transactions laws were the worst of all the variables in e-Government implementation. Two areas should be improved using immediate corrective action. In-depth study reveals that government officers and citizens can't fully use their laptop and mobile devices due to the lack of both ICT network and its operating technology, and legal system associated with the transaction of business information. Finally, the study ends up with recommendations for policy makers to shape the future of e-Government system in both developing and developed countries.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.1
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• pp.1-12
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• 2023

It is very time-intensive to obtain data with labels on anomaly detection tasks for multivariate time series. Therefore, several studies have been conducted on unsupervised learning that does not require any labels. However, a well-done integrative survey has not been conducted on in-depth discussion of learning architecture and property for multivariate time series anomaly detection. This study aims to explore the characteristic of well-known architectures in anomaly detection of multivariate time series. Additionally, architecture was categorized by using top-down and bottom-up approaches. In order toconsider real-world anomaly detection situation, we trained models with dataset such as power grids or Cyber Physical Systems that contains realistic anomalies. From experimental results, we compared and analyzed the comprehensive performance of each architecture. Quantitative performance were measured using precision, recall, and F1 scores.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.495-500
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• 2006

Satellite systems for objects positioning appeared indispensable for performing basic tasks of maritime navigation. Navigation, understood as safe and effective conducting a vehicle from one point to another, within a specific physical-geographical environment. [Kopacz, $Urba{\acute{n}}ski$, 1998]. However, the systems have not solved the problem of accessibility to reliable and highly accurate information about a position of an object, especially if surveyed toward on-shore navigational signs or in sea depth. And it's of considerable significance for many navigational tasks, carried out within the frameworks of special works performance and submarine navigation. In addition, positioning precisely the objects other than vessels, while executing hydrographical works, is not always possible with a use of any satellite system. Difficulties with GPS application show up also while positioning such off-lying dangers as wrecks, underwater and aquatic rocks also other naturaland artificial obstacles. It is caused by impossibility of surveyors approaching directly any such object while its positioning. Moreover, determination of vessels positions mutually (mutual geometrical relations) by teams carrying out one common tasks at sea, demands applying the navigational techniques other than the satellite ones. Vessels'staying precisely on specified positions is of special importance in, among the others, the cases as follows: - surveying vessels while carrying out bathymetric works, wire dragging; - special tasks watercraft in course of carrying out scientific research, sea bottom exploration etc. The problems are essential for maritime economy and the Country defence readiness. Resolving them requires applying not only the satellite navigation methods, but also the terrestrial ones. The condition for implementation of the geo-navigation methods is at present the methods development both: in aspects of their techniques and technologies as well as survey data evaluation. Now, the classical geo-navigation comprises procedures, which meet out-of-date accuracy standards. To enable meeting the present-day requirements, the methods should refer to well-recognised and still developed methods of contemporary geodesy. Moreover, in a time of computerization and automation of calculating, it is feasible to create also such software, which could be applied in the integrated navigational systems, allowing carrying out navigation, provided with combinatory systems as well as with the new positioning methods. Whereas, as regards data evaluation, there should be applied the most advanced achievements in that subject; first of all the newest, although theoretically well-recognised estimation methods, including estimation [Hampel et al. 1986; $Wi{\acute{s}}niewski$ 2005; Yang 1997; Yang et al. 1999]. Such approach to the problem consisting in positioning a vehicle in motion and solid objects under observation enables an opportunity of creating dynamic and interactive navigational structures. The main subject of the theoretical suggested in this paper is the Interactive Navigational Structure. In this paper, the Structure will stand for the existing navigational signs systems, any observed solid objects and also vehicles, carrying out navigation (submarines inclusive), which, owing to mutual dependencies, (geometrical and physical) allow to determine coordinates of this new Structure's elements and to correct the already known coordinates of other elements.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.459-468
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• 2019

Purpose: The cavity exploration of the lower part of the road is carried out to prevent ground-sinking. However, the detected communities cannot be identified by the cavity location and history information, such as repackaging the pavement. Therefore, the field applicability of RFID systems was evaluated in this study to enable anyone to accurately identify information. Method: During temporary recovery, tag recognition distance and recognition rate were measured according to underground burial materials and telecommunication tubes using RFID systems with electronic tag chips attached to the bottom of the rubber cap. Result: The perceived distance and perceived rate of depth for each position of the electron tag did not significantly affect the depth up to 15cm, but it did have some effect if the depth was 20cm. In addition, water effects from nearby underground facilities and rainfall are relatively small, and the effects of wind will need to be considered during the weather conditions of the road. Conclusion: The RFID tags for field application of the pavement management system store various information such as location and size of cavity, identification date, cause of occurrence, and surrounding underground facilities to maximize cavity management effect with a system that can be computerized and mobile utilization.