• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.580-588
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• 1999

The reuse of software components from existing software system enhances productivity and reliability, decreases the cost of production in software development. The extraction of software components with high reusability from existing software system is very important in software reuse. The reuse of a class is classified into white-box reuse to reuse with modification and black-box reuse to reuse without modification. A class has the property of procedural language and object-oriented language. Therefore, it must measure reusability in consideration of two properties. In black-box reuse, independence of class is important quality. It can quantify through information hiding, coupling between objects, cohesion, etc. In white-box reuse, modification is the best important quality. It can quality through class complexity, coupling, cohesion, documentation, etc. We propose a new model for measurement of class reusability and the measure criteria in object-oriented program. A class that is measured by proposed model can judge whether the reuse with modification has the advantage or the reuse without modification has the advantage.

• Journal of Internet Computing and Services
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• v.19 no.5
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• pp.107-113
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• 2018

Object-oriented databases (OODBs) canbe used for many non-traditional database application areas such as computer-aided design, etc. Usually those application areas require advanced modeling power for expressing complicated relationships among data sets. OODBs have more distinguished features than the traditional relational database systems. One of the distinguished characteristics of OODBs is class hierarchy (also called inheritance hierarchy). A class hierarchy in an OODB means that a class can hand down the definitions of the class to the subclass of the class. In other words, a class is allowed to inherit the definitions of the class from the superclass. In this paper, we present performance evaluation metrics for class hierarchy in OODBs from a concurrency control perspective. The proposed performance metrics are developed to determine which concurrency control scheme in OODBs can be used for a given class hierarchy. In this study, in order to develop performance metrics, we use class hierarchy structure (both of single inheritance and multiple inheritance), and data access frequency for each class. The proposed performance metrics will be also used to compare performance evaluation for various concurrency control techniques.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.115-122
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• 2024

Multi-object tracking (MOT) is a vital component in understanding the surrounding environments. Previous research has demonstrated that MOT can successfully detect and track surrounding objects. Nonetheless, inaccurate classification of the tracking objects remains a challenge that needs to be solved. When an object approaching from a distance is recognized, not only detection and tracking but also classification to determine the level of risk must be performed. However, considering the erroneous classification results obtained from the detection as the track class can lead to performance degradation problems. In this paper, we discuss the limitations of classification in tracking under the classification uncertainty of the detector. To address this problem, a class update module is proposed, which leverages the class uncertainty estimation of the detector to mitigate the classification error of the tracker. We evaluated our approach on the VisDrone-MOT2021 dataset,which includes multi-class and uncertain far-distance object tracking. We show that our method has low certainty at a distant object, and quickly classifies the class as the object approaches and the level of certainty increases.In this manner, our method outperforms previous approaches across different detectors. In particular, the You Only Look Once (YOLO)v8 detector shows a notable enhancement of 4.33 multi-object tracking accuracy (MOTA) in comparison to the previous state-of-the-art method. This intuitive insight improves MOT to track approaching objects from a distance and quickly classify them.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.1-13
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• 2008

Gestwicki et. al. proposed the technique that detects and predicts the structure of object diagrams from class diagrams to get the improved drawing of object graphs. Their approach finds two predictable structures - recursive clusters and leaf clusters from class diagrams. Their approach is not practical to be applied to real programs, because the starting point is class diagram. In this work, we improve and implement their technique to apply to Java classes. We obtain the structure and relationships of classes and clusters extracted from class files. This information can be provided and used as a template of object graphs for Java execution visualization tools like JIVE.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.2
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• pp.215-224
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• 1997

This paper addresses the vertical class fragmentation in distributed object-oriented databases. In the proposed vertical fragmentation, after producing the attribute fragment by partitioning attributes, then the method fragment is produced by gathering methods referring the attribute in each fragment. For partitioning attributes, we define query access matrix(QAM) and method access matrix(MAM) to express attributes that method refers, and extend QAM, MAM and attribute usage matrix(AUM) to universal class environment for representing relationship among other classes through class hierarchy and class composite hierarchy.

• Journal of Korean Society for Geospatial Information Science
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• v.5 no.2 s.10
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• pp.87-97
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• 1997

For real-time data Process of digital images, all things that related to problem-domain are understood individual object and then it Is necessary to program using object oriented approach to grasp all problem as a objects operation by means of message transmission among objects. In this study, for digital photogrammetry class is designed using object oriented programming and class hierarchy is established Also, it is very useful to construct to digital photogrammetry system using class library when it is applied to close range photogrammetry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.12
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• pp.3668-3674
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• 2009

Use case diagram is used for defining inter-action between users and systems in object-oriented modeling. It is very important to defining users' requirements for efficient software development. In this paper, we propose a object-oriented modeling process using hierarchical use case analysis for designing class model. First, We define many use case diagrams by several hierarchical modeling level. And next, we can also design class model using the use case diagrams. Our proposed modeling process provides interaction between use case model and class model. That can make us to check the modeling process during the software development. Using the proposed object-oriented modeling we can develop software based on users' requirements. It is very useful for class modeling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2523-2538
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• 2017

In most of the existing literature, the definition of the class label has the following characteristics. First, the class label of the samples from the same object has an absolutely fixed value. Second, the difference between class labels of the samples from different objects should be maximized. However, the appearance of a face varies greatly due to the variations of the illumination, pose, and expression. Therefore, the previous definition of class label is not quite reasonable. Inspired by discriminative least squares regression algorithm (DLSR), a noisy label based discriminative least squares regression algorithm (NLDLSR) is presented in this paper. In our algorithm, the maximization difference between the class labels of the samples from different objects should be satisfied. Meanwhile, the class label of the different samples from the same object is allowed to have small difference, which is consistent with the fact that the different samples from the same object have some differences. In addition, the proposed NLDLSR is expanded to the kernel space, and we further propose a novel kernel noisy label based discriminative least squares regression algorithm (KNLDLSR). A large number of experiments show that our proposed algorithms can achieve very good performance.

• The KIPS Transactions:PartD
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• v.10D no.5
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• pp.859-872
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• 2003

Class hierarchies often constitute the backbone of object-oriented software. Their quality is therefore quite crucial. Building class hierarchies with good qualify is a very important and common tasks on the object oriented software development, but such hierarchies are not so easy to build. Moreover, the class hierarchy structure under construction is frequently restructured and refined until it becomes suitable for the requirement on the iterative and incremental development lifecycle. Therefore, there has been renewal of interest in all methodologies and tools to assist the object oriented developers in this task. In this paper, we define a set of quantitative metrics which provide a wav of capturing features of a rough estimation of complexity of class hierarchy structure. In addition to, we suggest a set of algorithms that transform a original class hierarchy structure into reorganized one based on the proposed metrics for class hierarchy structure. Furthermore, we also prove that each algorithm is "object-preserving". That is, we prove that the set of objects are never changed before and after applying the algorithm on a class hierarchy. The technique presented in this paper can be used as a guidelines of the construction, restructuring and refinement of class hierarchies. Moreover, the proposed set of algorithms based on metrics can be helpful for developers as an useful instrument for the object-oriented software development.velopment.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.164-172
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• 1996

The partitioning of related objects should be performed before clustering for an efficient access in object-oriented databases. In this paper, a horizontal partition of related objects in object-oriented databases is presented. All subclass nodes in a class inheritance hierarchy of a schema graph are shrunk to a class node in the graph that is called condensed schema graph because the aggregation hierarchy has more influence on the partition than the class inheritance hierarchy. A set function and an accessibility function are defined to find a maximal subset of related objects among the set of objects in a class. A set function maps a subset of the domain class objects to a subset of the range class objects. An accessibility function maps a subset of the objects of a class into a subset of the objects of the same class through a composition of set functions. The algorithm derived in this paper is to find the related objects of a condensed schema graph using accessibility functions and set functions. The existence of a maximal subset of the related objects in a class is proved to show the validity of the partition algorithm using the accessibility function.