• Title/Summary/Keyword: process and object

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The Effects on Problem Solving of Linear Function Using Excel (엑셀의 활용이 일차함수 문제해결에 미치는 효과)

  • Lee, Kwang-Sang;Cho, Min-Shik;Lew, Hee-Chan
    • School Mathematics
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    • v.8 no.3
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    • pp.265-290
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    • 2006
  • The purpose of this study is to search an effective teaching & learning program by examining how much does Excel affect on problem solving of linear function. This study was based on qualitative case study. Teaching experiment was performed for seven periods with five students in 8th graders. Pre and posts tests were attempted to analyze the changes of student's ability on problem solving of linear function. The analysis of tests were performed in category with correct process-object perspective, near process-object perspective, incorrect process-object perspective. According to this study, the subjects showed an improvement on problem solving perspective of linear function. This meant that lessons using Excel had influenced on the problem solving of linear function. We noticed that exploring the learning environment with Excel could supplement paper-and-pencil environment. We believed that Excel with an intuitive dynamic and explorative skills can play a role in scaffolding to support problem solving of linear function.

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A Study on the Application of Object-Oriented Methodologies to Process Modeling : Cognitive Integration Process of Multiple Models (객체지향방법론을 이용한 프로세스모델링에 대한 연구 - 복수 모형의 인지적 통합과정을 중심으로 -)

  • Kim, Jin-U;Han, Hyeong-Mi
    • Asia pacific journal of information systems
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    • v.6 no.2
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    • pp.19-52
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    • 1996
  • It has been argued theoretically and empirically that the analysis of business processes requires the decomposition of an integrated system. However, in order to innovate a business process, cognitive integration activities that try to understand the decomposed features of the business process as an integrated system are essential. This research aims at 1) empirically investigating the cognitive process of integrating multiple diagrams while using object-oriented methodologies in process modeling ; 2) identifying a cognitive integration strategy that supports the successful comprehension of business processes with the use of multiple diagrams ; and 3) proposing guidelines for developing supporting tools for effective business process engineering by using object-oriented process modeling.

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Object Recognition using Comparison of External Boundary

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.7 no.3
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    • pp.134-142
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    • 2019
  • As the 4th industry has been widely distributed, there is a need for a process of real-time image recognition in various fields such as identification of company employees, security maintenance, and development of military weapons. Therefore, in this paper, we will propose an algorithm that effectively recognizes a test object by comparing it with the DB model. The proposed object recognition system first expresses the outline of the test object as a set of vertices with the distances of predefined length or more. Then, the degree of matching of the structures of the two objects is calculated by examining the distances to the outline of the DB model from the vertices constituting the test object. Because the proposed recognition algorithm uses the outline of the object, the recognition process is easy to understand, simple to implement, and a satisfactory recognition result is obtained.

Brain Dynamics and Interactions for Object Detection and Basic-level Categorization (물체 탐지와 범주화에서의 뇌의 동적 움직임 추적)

  • Kim, Ji-Hyun;Kwon, Hyuk-Chan;Lee, Yong-Ho
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2009.05a
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    • pp.219-222
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    • 2009
  • Rapid object recognition is one of the main stream research themes focusing to reveal how human recognizes object and interacts with environment in natural world. This field of study is of consequence in that it is highly important in evolutionary perspective to quickly see the external objects and judge their characteristics to plan future reactions. In this study, we investigated how human detect natural scene objects and categorize them in a limited time frame. We applied Magnetoencepahlogram (MEG) while participants were performing detection (e.g. object vs. texture) or basic-level categorization (e.g. cars vs. dogs) tasks to track the dynamic interaction in human brain for rapid object recognition process. The results revealed that detection and categorization involves different temporal and functional connections that correlated for the successful recognition process as a whole. These results imply that dynamics in the brain are important for our interaction with environment. The implication from this study can be further extended to investigate the effect of subconscious emotional factors on the dynamics of brain interactions during the rapid recognition process.

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A Study on the Dimensions of Object-oriented Systems Modeling : Theory and an Exploratory Evaluation (객체지향 시스템 모델링 차원 : 이론 및 탐색적 평가)

  • 안준모
    • The Journal of Information Technology and Database
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    • v.8 no.1
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    • pp.41-65
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    • 2001
  • This study proposes evaluation dimensions of object-oriented systems modelling tools and activities available in object-oriented systems development practices. The dimensions ale developed based on previous research in cognitive psychology, information systems modeling study, and object-oriented systems analysis arid design areas. The proposed dimension is composed of two dimensions. The one dimension includes abstraction levels of modelling and the other includes process and representation in modeling activities. Experts on object-oriented modeling were selected to evaluate the practical validity of the proposed dimensions and applications of major object-oriented modeling tools during systems development project. Most of the tools were observed to be used for representing objects rather than for modeling the process of related objects. The proposed modeling dimension will be evaluated for acquiring general validity in future empirical research.

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A Technique of Deriving Concrete Object Model for C++ Programming (C++ 프로그래밍을 위한 구체적 객체 모델의 작성법)

  • Kim, Tae-Gyun;Im, Chae-Deok;Song, Yeong-Gi;In, So-Ran
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.3
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    • pp.731-746
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    • 1997
  • The usage of object models for the development of software has been frowung due to the prevalence of the ob-ject oriented paradigm.The object moedels produced as results of requirments analysis and design activities are vety veneficial to the implementation phase.It is even possible for source code to be genrated automatically if object models are concrete enough.Therefore system analyzers and desingners should make an dffort to refine theabstrace ogject model defined at.an early stage in order to achieve a more conrete object model.In general,re-fining an abstrace object model into a concrete model depends too much on the desigver's infromal experience.In this paper,we persent the refinement techniques required for concreting an abstract object model bassed on OMT(Object Modeling Technique)'s notation,We will discuss the definition of the abstraction level of an object model and the transformational rules of refinement.These transformational rules are currently applied to the design of a software tool,named Process Modeler,which is a major component of the software development process modeling system for ICS(Information Communication Service). Finally we can achieve a concrete object model which can easily be translated into C++ source code.

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LSTM Network with Tracking Association for Multi-Object Tracking

  • Farhodov, Xurshedjon;Moon, Kwang-Seok;Lee, Suk-Hwan;Kwon, Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.23 no.10
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    • pp.1236-1249
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    • 2020
  • In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

Joint Template Matching Algorithm for Associated Multi-object Detection

  • Xie, Jianbin;Liu, Tong;Chen, Zhangyong;Zhuang, Zhaowen
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.1
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    • pp.395-405
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    • 2012
  • A joint template matching algorithm is proposed in this paper to reduce the high rate of miss-detection and false-alarm caused by the traditional template matching algorithm during the process of multi-object detection. The proposed algorithm can reduce the influence on each object by matching all objects together according to the correlation information among different objects. Moreover, the rate of miss-detection and false-alarm in the process of single-template matching is also reduced based on the algorithm. In this paper, firstly, joint template is created from the information of relative positions among different objects. Then, matching criterion according to normalized cross correlation is generated for multi-object matching. Finally, the proposed algorithm is applied to the detection of watermarks in bill. The experiments show that the proposed algorithm has lower miss-detection and false-alarm rate comparing to the traditional NCC algorithm during the process of multi-object detection.

OOPT: An Object-Oriented Development Methodology for Software Engineering Education (OOPT: 소프트웨어공학 교육을 위한 객체지향 소프트웨어 개발 방법론)

  • Jung, Sejin;Lee, Dong-Ah;Kim, Eui-Sub;Chang, Chun-Hyon;Yoo, Junbeom
    • Journal of KIISE
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    • v.44 no.5
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    • pp.510-521
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    • 2017
  • The software development process (SDP) plays an important basic role in software engineering education. Every software is developed in accordance with a specific SDP which contains all phases of software development. SDP education helps students to understand the overall techniques and the process of software engineering. This paper introduces a software development methodology (i.e., process) - 'OOPT (Object Oriented Process with Traceability),' which was proposed for use in university software engineering classes. The OOPT is based on object-oriented software development, and it defines concrete requirements as well as outputs of each process/phases. It also contains the unit/system testing and a traceability analysis. We have used the OOPT in software engineering classes at Konkuk university for eight years. This paper conveys our experience as well as future extension and improvement plans.

ASM Algorithm Applid to Image Object spFACS Study on Face Recognition (영상객체 spFACS ASM 알고리즘을 적용한 얼굴인식에 관한 연구)

  • Choi, Byungkwan
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.12 no.4
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    • pp.1-12
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    • 2016
  • Digital imaging technology has developed into a state-of-the-art IT convergence, composite industry beyond the limits of the multimedia industry, especially in the field of smart object recognition, face - Application developed various techniques have been actively studied in conjunction with the phone. Recently, face recognition technology through the object recognition technology and evolved into intelligent video detection recognition technology, image recognition technology object detection recognition process applies to skills through is applied to the IP camera, the image object recognition technology with face recognition and active research have. In this paper, we first propose the necessary technical elements of the human factor technology trends and look at the human object recognition based spFACS (Smile Progress Facial Action Coding System) for detecting smiles study plan of the image recognition technology recognizes objects. Study scheme 1). ASM algorithm. By suggesting ways to effectively evaluate psychological research skills through the image object 2). By applying the result via the face recognition object to the tooth area it is detected in accordance with the recognized facial expression recognition of a person demonstrated the effect of extracting the feature points.