• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.751-770
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• 2019

Action recognition is an essential task in computer vision due to the variety of prospective applications, such as security surveillance, machine learning, and human-computer interaction. The availability of more video data than ever before and the lofty performance of deep convolutional neural networks also make it essential for action recognition in video. Unfortunately, limited crafted video features and the scarcity of benchmark datasets make it challenging to address the multi-person action recognition task in video data. In this work, we propose a deep convolutional neural network-based Effective Hybrid Learning (EHL) framework for two-person interaction classification in video data. Our approach exploits a pre-trained network model (the VGG16 from the University of Oxford Visual Geometry Group) and extends the Faster R-CNN (region-based convolutional neural network a state-of-the-art detector for image classification). We broaden a semi-supervised learning method combined with an active learning method to improve overall performance. Numerous types of two-person interactions exist in the real world, which makes this a challenging task. In our experiment, we consider a limited number of actions, such as hugging, fighting, linking arms, talking, and kidnapping in two environment such simple and complex. We show that our trained model with an active semi-supervised learning architecture gradually improves the performance. In a simple environment using an Intelligent Technology Laboratory (ITLab) dataset from Inha University, performance increased to 95.6% accuracy, and in a complex environment, performance reached 81% accuracy. Our method reduces data-labeling time, compared to supervised learning methods, for the ITLab dataset. We also conduct extensive experiment on Human Action Recognition benchmarks such as UT-Interaction dataset, HMDB51 dataset and obtain better performance than state-of-the-art approaches.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.171-180
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• 2022

In the knowledge development of online assessment in learning management systems (LMSs), many assessments are evaluated weekly in the summer training course for undergraduate students in the Faculty of Computing and Information Technology at King Abdul-Aziz University in Saudi Arabia. The number of performance assessments in the summer training course reaches 15 weeks. Many of them, however, are sent or done informally or through unreliable ways and cannot be verified by third parties. Therefore, applying the concept of digital transformation is essential. This research study reported herein used the action design research (ADR) method to build a new information technology system that could assist in the digital transformation. An electronic platform was designed, developed, implemented, and evaluated using the ADR method so that the main people involved in the summer training process (i.e., students, academic supervisors, and administrators) would have a high level of satisfaction with it. The study was conducted on 452 students, 105 academic supervisors, and 15 administrative staff and was conducted during the summer semester of 2020. All the training processes were digitally transformed and automated to control and raise the level and reliability of the training. All involved people were satisfied, thus, shifting the process to be in a digital form assist in achieving the high-level goal.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.591-596
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• 2011

There are quite a number of business processes in the urban regeneration project. Managers and participants who involved in the project make and use information for the best way to perform in the particular business process. The information can be also reused and produced for data at the next stage. Accordingly, the information sometimes goes out of existence and work data up into new information when the urban regeneration project has been accomplished. But in that case some of changes happen occasionally, the business for urban regeneration has suffered a loss of profit and time as result of confusions about decisions and inappropriate action. For that reason, the information should be analyzed to achieve its aim at the business process under the influence of changes. Then, even though detail processes and management method change, the Core Information, which are important factors for accomplishing the project, help that the project can be operated to solve the problem about confusion and loss of the business. In conclusion, the Core Information is main effective factors for successful urban regeneration projects on the change management. The purpose of this study is to research the information according to the Information-flow and changes, and to find out the influence factors and the Core Information to manage efficiently at the process of urban regeneration projects.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.373-378
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• 2021

The study is a user experience design study on the function of action cams used for leisure activities that have been on the rise recently. Along with the video platforms that are developing in a user-friendly way, the size of the action cam market is also growing. However, there is a lack of research on the quality of a function that enhances the user experience. Thus, this study classified action cam functions according to user experience elements by using Kano Model's analysis method and in-depth interview, and analyzed how the quality of action cam functions affects the user experience by conducting a satisfaction survey by function. The results of the study have shown which functions should be improved first and which functions should be continuously researched and invested. I hope this study will contribute useful information to developing user-centered action cams.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.1126-1131
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• 2008

In this paper we introduce an applicable RCM(Reliability centered maintenance) method for Track circuit equipment of AREX's Signalling System. AREX computerize all the process of FRACAS(Failure Reporting, Analysis and Corrective Action System)) by the Facility Management System of Integrated Information System. These datum were analysed and reproduced as the RAMS index value which can be used by maintenance staff for optimizing the maintenance method of the System.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.929-944
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• 2019

Many critical applications require accurate real-time human action recognition. However, there are many hurdles associated with capturing and pre-processing image data, calculating features, and classification because they consume significant resources for both storage and computation. To circumvent these hurdles, this paper presents a recognition machine learning (ML) based system model which uses reduced data structure features by projecting real 3D skeleton modality on virtual 2D space. The MMU VAAC dataset is used to test the proposed ML model. The results show a high accuracy rate of 97.88% which is only slightly lower than the accuracy when using the original 3D modality-based features but with a 75% reduction ratio from using RGB modality. These results motivate implementing the proposed recognition model on an embedded system platform in the future.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.279-289
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• 1998

This study deals with the schemes of design, plan and operate maintenance management support systems and with the engineering approach for the solutions to build the maintenance management for the production efficiency. Maintenance Management Information System(MMIS) is the task that must focus on machinery historical data and planned maintenance action. Also the efficient supporting system in a maintenance management is achieved by database which is based on process of machinery's failure history. Designing method of maintenance management information system, maintenance modules are consisted of six factors ; machinery's historical data, lubrication control, check sheet, repair work, availability report, and performance report(control board and detailed reports), and then operators can rapidly utilize data in work place. In the implementation of designed model, program coding has been developed by Visual Basic 3.0. Data insertion, deletion and updating which perform menu screen is implemented by reading data from database. Implementation model based on LAN environment and related data is stored in Microsoft DBMS.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.133-139
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• 2011

In this paper, we propose a hybrid filter for noise reduction. The proposed method adjusts rational filtering direction according to an edge in the image using median filtered data. Rational filter modulates the coefficients of a linear lowpass filter to limit its action in presence of image details. By the ratio of polynomials in the input variables, rational filter reduces noise adaptively. Median filter is widely used to reduce impulse noise, but removes some details for highly corrupted images. Also, desirable details are removed when the window size is large. Our proposed algorithm combines rational filter and median filter. Thus, proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing median and rational filtering methods.

• Journal of Korean Society for Quality Management
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• v.11 no.2
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• pp.25-31
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• 1983

Often arrangement for effective product assessment and audit have not been completely satisfactory. The underlying reasons are: (a) The lack of early evidence of new unit quality. (b) The collection and processing of data. (c) Ineffective data analysis techniques. (d) The variability of information on which decision making is based. Because of the nature of the product the essential outputs from an affective QA organization would be: (a) Confirmation of new unit quality. (b) Detection of failures which are either epidemic or slowly degradatory. (c) Identification of failure cases. (d) Provision of management information at the right time to effect the necessary corrective action. The heart of an effective QA scheme is the acquisition and processing of data. With the advent of data processing for quality monitoring becomes feasible in an automotive testing environment. This paper shows how the method enables us to use Automotive Testing data for the cost benefits of QA management.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.1
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• pp.58-67
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• 2000

Todays enterprise networks are composed of multiple types of interconnected networks.Enterprise Networks interoperability between these technologies is needed. To enable interworking, it is necessary to be able to map between the relevant object models and to build on this to provide a mechanism to handle protocol conversion on the domain boundaries.In this paper, we describe a gateway between management application in the CORBA domain and agent in the SNMP domain and various integration methods. The main function of the gateway is to dynamically convert the method invocations on object reference in CORBA domain to SNMP messages for MIB entries at remote agents, We also present translation methods from SNMP MIB to CORBA IDL using Direct translation and Abstract translation. JIDM algorithm has no notion of containment and inheritance relationships between object classes and is difficult to understanding between management attribute and SNMP Action attribute. Abstract translation over come these problems.New superclasses define for common attributes and define explicit CORBA method for SNMP Action.It is a methodology for obtaining the CORBA-compliant management agents from already existing SNMP agents.