• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.744-751
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• 2022

Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.

• 한국군사과학기술학회지
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• 제16권3호
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• pp.348-357
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• 2013

This work describes an approach that contributes to derive from mission to critical functions of the attack helicopter under future battle space environment. An existing mission of the attack helicopter is limited to the only shooter oriented functions. In the future environment, mission and its functions of the helicopter might be much expanded. The functions should be derived by the top down approach based on systems engineering approach. In this point of view, this work describes network based future battle environment. From this environment, the missions of the attack helicopter are identified and optimized functions are derived through sequential procedures like from missions to tasks, tasks to activities, and activities to functions. The selected activities are obtained from the tasks using QFD. The weighting scores of the QFD are calculated by the AHP computational procedure. Finally the critical functions are presented through the similar procedure.

• 천문학회보
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• 제42권2호
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• pp.59.3-59.3
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• 2017

We will present the activities of East Asian VLBI Network, EAVN, which consists of around 20 radio telescopes in Japan, Korea, and China with 6,500 km extend. It is a most sensitive and highest VLBI array in the world. We have conducted science verification observations at mainly 8 and 22 GHz. And Japanese VLBI array, VERA, and Korean VLBI array, KVN have combined as KaVA, Korean and VERA Array, and started science observations with open use at 22 and 43 GHz. We will presents some commissioning and science results based on it. Moreover Taiwan is constructing the Greenland telescope to be a millimeter and submillimeter VLBI station, which will be a very powerful station in Global millimeter and submillimeter VLBI array. These activities will be introduced as well.

• International Journal of Computer Science & Network Security
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• 제21권4호
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• pp.47-51
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• 2021

The article analyzes and studies that pedagogical design of the educational process using information and communication technologies in educational institutions of higher education based on the development of a model and methodology personalization of training will improve the quality of the educational process at the university and solve the identified contradiction. A qualitative analysis of foreign countries in the possibility of using information and communication technologies in educational institutions of higher education is carried out.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.275-279
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• 2022

The growth of technology nowadays has made many things easy for humans. These things are from everyday small task to more complex tasks. Such growth also comes with the illegal activities that are perform by using technology. These illegal activities can simple as displaying annoying message to big frauds. The easiest way for the attacker to perform such activities is to convenience user to click on the malicious link. It has been a great concern since a decay to classify URLs as malicious or benign. The blacklist has been used initially for that purpose and is it being used nowadays. It is efficient but has a drawback to update blacklist automatically. So, this method is replace by classification of URLs based on machine learning algorithms. In this paper we have use four machine learning classification algorithms to classify URLs as malicious or benign. These algorithms are support vector machine, random forest, n-nearest neighbor, and decision tree. The dataset that is used in this research has 36694 instances. A comparison of precision accuracy and recall values are shown for dataset with and without preprocessing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.5023-5038
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• 2017

Big data is an emerging technology which deals with wide range of data sets with sizes beyond the ability to work with software tools which is commonly used for processing of data. When we consider a huge network, we have to process a large amount of network information generated, which consists of both normal and abnormal activity logs in large volume of multi-dimensional data. Intrusion Detection System (IDS) is required to monitor the network and to detect the malicious nodes and activities in the network. Massive amount of data makes it difficult to detect threats and attacks. Sequential Pattern mining may be used to identify the patterns of malicious activities which have been an emerging popular trend due to the consideration of quantities, profits and time orders of item. Here we propose a sequential pattern mining algorithm with fuzzy logic feature selection and fuzzy weighted support for huge volumes of network logs to be implemented in Apache Hadoop YARN, which solves the problem of speed and time constraints. Fuzzy logic feature selection selects important features from the feature set. Fuzzy weighted supports provide weights to the inputs and avoid multiple scans. In our simulation we use the attack log from NS-2 MANET environment and compare the proposed algorithm with the state-of-the-art sequential Pattern Mining algorithm, SPADE and Support Vector Machine with Hadoop environment.

• 경영과학
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• 제34권2호
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• pp.15-33
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• 2017

This paper considers a Bayesian Network analysis for understanding the heterogeneous cross-category effects of different promotion activities and developing an efficient overall promotion strategy for a large retail store. More specifically we differentiate price reduction promotion and floor promotion and study their heterogeneous effect on consumer purchase behavior under a market basket setting. We then utilize Bayesian networks in identifying complex association structure in market basket dataset by analyzing the effects of different promotional activities and also include the effects of time, family income and size. We find from our Bayesian network analysis that the dominant cross-category promotion effect of price promotion is the indirect effect whereas the dominant cross-category promotion effect of floor promotion is the direct effect. Also, among the demographic variables we find that family size of the household is linked with more product categories compared to income and see that there are differences in the extent of the effects by product category. Finally, we also show the existence of products acting as a network hub and how they can be utilized by retailers faced with a limited marketing budget and suggest a more efficient promotion strategy.

• Journal of Information Technology Applications and Management
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• 제24권1호
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• pp.11-24
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• 2017

Due to development of smart and network technologies, social network service (SNS) has become popular in daily life. With increasing use of SNS, the scope of communication has been widened. Lots of activities can be easily shared daily on SNS. Differing with opinions about more activated communication on SNSs, some people have viewpoints that, in some cases, communications may be decreased among SNS users. This research is to investigate whether there may be the differences among generations in the social network age. Major concerns of study are as follows. First, there may be differences in age related to the decrease of communication activities. On the other hand, there may be differences among generations related to the increase of communication. Two research steps have been adopted that the FGI (focus group interview) was to understand. Defining actual communication status was the first step, and an empirical approach, a survey to verify hypotheses, was performed as the second step. Key findings of the study were that older generations perceived communication has been decreased. Research results can provide implications regarding characteristics of SNS communication.

• 한국건설관리학회논문집
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• 제1권3호
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• pp.75-80
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• 2000

공간의 분할이 많은 건축공사에서는 반복적 특성으로 인해 공정계획상에 다수의 대안이 존재한다. 공사기간은 각 액티비티의 기간뿐 아니라 반복되는 액티비티의 배열방법에 의해서도 많은 영향을 받는다. 본 연구는 각 액티비티에 적정한 선행 액티비티를 할당함으로써 여유시간을 최소화하는 공정계획기법을 제시하는 것을 목적으로 진행되었다. Line of Balance 기법을 기본으로 하는 기존연구와는 달리 본 연구에서는 AON방식의 네트워크 기법을 기본으로 하여 공간과 자원의 두 축 사이에 액티비티를 배열하였다. 각 액티비티별로 자원과 공간의 양방향으로 가장 적절한 선행 액티비티를 검색하여 여유시간을 최소화한다. 본 연구에서 제시한 액티비티 배열방법을 공동주택공사 건설공사를 대상으로 적용한 결과, 액티비티 배열을 달리함에 따라서 다수의 대안이 존재함을 확인할 수 있었으며 그중 적정대안을 찾아낼 수 있었다. 본 기법은 공동주택공사와 같은 다수의 유사공간으로 구성된 건설공사의 공정 계획에 도움을 줄 수 있을 것으로 판단된다.

• 경영과정보연구
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• 제14권
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• pp.67-77
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• 2004

Although project management for new product development is a very important issue, only a few approach from project scheduling has been made. The traditional project scheduling research has focused on the project network with certainty, but the new product development project has some uncertainties in network; Some activities may not need to be peformed, and/or some precedent relationships between activities may not need to be kept. In this paper, a simulation model is introduced in order to reflect uncertainties in project network for new product development. This simulation model can be used as a project scheduling technique for product development. By repeating the simulation, the degree of the risk and the feasibility of the project can be assessed.