• Journal of Digital Contents Society
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• v.18 no.3
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• pp.457-463
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• 2017

VOD service provides an additional revenue model for digital broadcasting companies in addition to the existing subscription fees and advertisement-based revenue models. Therefore, each digital broadcasting company develops its own VOD service and performs frequent improvement work. In this circumstance, the developer is seeking to improve the efficiency of the VOD service development. To address the needs of such developers, this study conducted a basic study to apply the feature-oriented analysis model to the development of VOD services. The feature-oriented analysis model is recognized (through a number of case studies) as an effective tool for analyzing the requirements of softwares with the functions that are interconnected organically. In this paper, we developed a feature model of VOD service and designed the primary functions of each feature and the test-cases that can test the these functions, laying the foundation for developing VOD services based on feature-oriented analysis model.

• Journal of KIISE:Software and Applications
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• v.32 no.2
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• pp.119-127
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• 2005

Product line analysis is an activity for analyzing requirements, their relationships, and constraints in a product line before engineering product line assets (e.g., architectures and components). A feature-oriented commonality and variability analysis (called feature modeling) has been considered an essential part of product line analysis. Commonality and variability analysis, although critical, is not sufficient to develop reusable and adaptable product line assets. Dependencies among features and feature binding time also have significant influences on the design of product line assets. In this paper. we propose a feature-oriented product line analysis model that extends the existing feature model in terms of three aspects (i.e., feature commonality and variability, feature dependency, and feature binding time). To validate the consistency among the three aspects we formally define the feature-oriented product line analysis model and provide rules for checking consistency.

• Convergence Security Journal
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• v.17 no.3
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• pp.51-57
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• 2017

VOD service provides an additional revenue for broadcasting companies in addition to the existing subscription fees and advertisement-based revenue. Therefore, each broadcasting company develops its own VOD service and performs frequent improvement work. This leads to the development of new VOD services, so developers are considering ways to effectively handle the frequent development needs. In this background, we conducted an underlying research to apply the feature-oriented analysis model to the development of VOD service. The feature-oriented analysis model used in this study is the Feature-Oriented Domain Analysis (FODA) developed by SEI of Carnegie Mellon University. FODA provides a tool for specifying a feature model of a software domain, based on which developers determine the configuration of a software with customers. This study developed a feature model of the VOD service domain and devised the functionalities and testcases in an integrated manner with the feature model. Additionally, we proposed a VOD service development process utilizing the feature model, function specification, and testcases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.26-32
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• 2017

VOD (Video-On Demand) Services are considered to be one of the most successful data broadcasting services, along with Electronic Program Guides (EPGs). In particular, VOD services provide supplementary revenue for broadcasting companies in addition to the existing subscription fees and advertisement-based revenue. Therefore, each broadcasting company has developed its own VOD service and constantly seeks to improve it. This leads to the development of new VOD services, so developers are considering ways to effectively handle the frequent development needs. In this background, we conducted underlying research to apply the feature-oriented analysis model to the development of VOD services. The feature-oriented analysis model used in this study is the Feature-Oriented Domain Analysis (FODA) one developed by SEI of Carnegie Mellon University. FODA provides a tool for specifying the feature model of a software domain, based on which the developers can determine the configuration of the software with the customers. This study developed a feature model of the VOD service domain and devised the functionalities and test cases in an integrated manner with the feature model. Additionally, we proposed a VOD service development process utilizing the feature model, function specification, and test cases.

• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.232-240
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• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.147-154
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• 2003

Microarray information system is a complex system to manage, analyze and interpretate microarray gene expression data. Establishment of well-defined development process is very essential for understanding the complexity and organization of the system. We performed object-oriented analysis using Unified Modeling Language (UML) in specifying, visualizing and documenting microarray information system. The object-oriented analysis consists of three major steps: (i) use case modeling to describe various functionalities from the user's perspective (ii) dynamic modeling to illustrate behavioral aspects of the system (iii) object modeling to represent structural aspects of the system. As a result of our modeling activities we provide the UML diagrams showing various views of the microarray information system. We believe that the object-oriented analysis ensures effective documentations and communication of information system requirements. Another useful feature of object-oriented technique is structural continuity to standard microarray data model MAGE-OM (Microarray Gene Expression Object Model). The proposed modeling e(forts can be applicable for integration of biomedical information system.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.05a
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• pp.486-489
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• 2006

This paper presents a newly proposed object-oriented finite element framework and its applications on dynamic analysis of plate girder bridge. The developed framework supports various types of finite elements, materials, constraints, loads, and solution methods. One major feature different from other object-oriented finite element programs is that static model and dynamic state can be easily read from or written to a file. In addition, the framework supports efficient DOF pattern handling for a node connecting elements with different DOF patterns, new multi-point constraint handling, and various scripting languages for easy use of the library. In order to show the applicability to dynamic analysis, dynamic moving load analysis on plate girder bridge is performed.

• The KIPS Transactions:PartD
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• v.15D no.6
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• pp.803-814
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• 2008

Product line architectures include variable parts to be selected according to product specific requirements. In order to derive architectures that are valid for a particular product from product line architectures, variabilities of product line architectures must be systematically managed. In this paper, we adopt an approach to variability management of product line architectures through an explicit mapping between a feature model and product line architecture models. If this mapping is incorrect or there exists inconsistency among product line architectural elements, variabilities of product line architectures cannot be managed correctly. Therefore, this paper formally defines product line architectural models in terms of conceptual, process, deployment, and module views, and mapping relationships between the feature model and the architectural models. Consistency rules for correct variability management of product line architectures are defined in terms of consistency in each of product line architecture model, consistency between different architectural view models, and consistency between a feature model and product line architectural models. These consistency rules provide a theoretical foundation for deriving valid product architecture from product line architectures.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.2
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• pp.115-125
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• 2012

Application of the Object-oriented Programming (OOP) method to the Finite Element Model (FEM) program has various strengths including the features of encapsulation, polymorphism and inheritance. However, this technique should be based upon a premise that the independency of the object method and data to be used is guaranteed. By attempting to apply the OOP to the FEM, existing researches go against the independency of the OOP which is an essential feature of the method. The reason is this: existing researches apply the OOP to modules in accordance with analysis procedures, although the data to be used is classified as an element unit in the FEM. Therefore, the required independency cannot be maintained as whole stiffness matrices and boundary conditions are combined together. Also, solutions are sought from analysis module after data is regrouped at the pre-processor, and their results are analyzed during the post-processor. As this is similar to a batch processing, it cannot use data at analysis, and recalculation should be done from the beginning if any condition is changed after the analysis is complete, which are limitations of the existing researches. This research implemented the Object-orientation of elements so that the three features of the OOP (i.e. encapsulation, polymorphism and inheritance) can be guaranteed and their independency maintained as a result. For this purpose, a model called 'Object-oriented Finite element Model ensuring the Independency of Elements (OFMIE)', which enables the analysis of targets through mutual data exchanges within instance, was developed. In conclusion, the required independency was achieved in the instance of the objected elements and the analysis results of previous conditions could be used for the analysis after changes. The number of repetitive calculations was reduced by 75 per cent through this gradual analysis processes.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.667-674
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• 2007

Facial expressions provide significant clues about one's emotional state; however, it always has been a great challenge for machine to recognize facial expressions effectively and reliably. In this paper, we report a method of feature-based adaptive motion energy analysis for recognizing facial expression. Our method optimizes the information gain heuristics of ID3 tree and introduces new approaches on (1) facial feature representation, (2) facial feature extraction, and (3) facial feature classification. We use minimal reasonable facial features, suggested by the information gain heuristics of ID3 tree, to represent the geometric face model. For the feature extraction, our method proceeds as follows. Features are first detected and then carefully "selected." Feature "selection" is finding the features with high variability for differentiating features with high variability from the ones with low variability, to effectively estimate the feature's motion pattern. For each facial feature, motion analysis is performed adaptively. That is, each facial feature's motion pattern (from the neutral face to the expressed face) is estimated based on its variability. After the feature extraction is done, the facial expression is classified using the ID3 tree (which is built from the 1728 possible facial expressions) and the test images from the JAFFE database. The proposed method excels and overcomes the problems aroused by previous methods. First of all, it is simple but effective. Our method effectively and reliably estimates the expressive facial features by differentiating features with high variability from the ones with low variability. Second, it is fast by avoiding complicated or time-consuming computations. Rather, it exploits few selected expressive features' motion energy values (acquired from intensity-based threshold). Lastly, our method gives reliable recognition rates with overall recognition rate of 77%. The effectiveness of the proposed method will be demonstrated from the experimental results.