• Title/Summary/Keyword: Computer Model

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Analysing Risk Factors of 5-Year Survival Colorectal Cancer Using the Network Model

  • Park, Won Jun;Lee, Young Ho;Kang, Un Gu
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.9
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    • pp.103-108
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    • 2019
  • The purpose of this study is to identify the factors that may affect the 5-year survival of colon cancer through network model and to use it as a clinical decision supporting system for colorectal cancer patients. This study was conducted using data from 2,540 patients who underwent colorectal cancer surgery from 1996 to 2018. Eleven factors related to survival of colorectal cancer were selected by consulting medical experts and previous studies. Analysis was proceeded from the data sorted out into 1,839 patients excluding missing values and outliers. Logistic regression analysis showed that age, BMI, and heart disease were statistically significant in order to identify factors affecting 5-year survival of colorectal cancer. Additionally, a correlation analysis was carried out age, BMI, heart disease, diabetes, and other diseases were correlated with 5-year survival of colorectal cancer. Sex was related with BMI, lung disease, and liver disease. Age was associated with heart disease, heart disease, hypertension, diabetes, and other diseases, and BMI with hypertension, diabetes, and other diseases. Heart disease was associated with hypertension, diabetes, hypertension, diabetes, and other diseases. In addition, diabetes and kidney disease were associated. In the correlation analysis, the network model was constructed with the Network Correlation Coefficient less than p <0.001 as the weight. The network model showed that factors directly affecting survival were age, BMI levels, heart disease, and indirectly influencing factors were diabetes, high blood pressure, liver disease and other diseases. If the network model is used as an assistant indicator for the treatment of colorectal cancer, it could contribute to increasing the survival rate of patients.

SKU-Net: Improved U-Net using Selective Kernel Convolution for Retinal Vessel Segmentation

  • Hwang, Dong-Hwan;Moon, Gwi-Seong;Kim, Yoon
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.4
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    • pp.29-37
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    • 2021
  • In this paper, we propose a deep learning-based retinal vessel segmentation model for handling multi-scale information of fundus images. we integrate the selective kernel convolution into U-Net-based convolutional neural network. The proposed model extracts and segment features information with various shapes and sizes of retinal blood vessels, which is important information for diagnosing eye-related diseases from fundus images. The proposed model consists of standard convolutions and selective kernel convolutions. While the standard convolutional layer extracts information through the same size kernel size, The selective kernel convolution extracts information from branches with various kernel sizes and combines them by adaptively adjusting them through split-attention. To evaluate the performance of the proposed model, we used the DRIVE and CHASE DB1 datasets and the proposed model showed F1 score of 82.91% and 81.71% on both datasets respectively, confirming that the proposed model is effective in segmenting retinal blood vessels.

An Investigation of the Effects of Model-Centered Instruction for Pre-service Teachers Majoring in Computer Education (모형 중심교수의 효과성에 관한 탐구- '컴퓨터 교육'교과를 수강하는 예비교사 대상으로)

  • Kim, Hye-Won;Han, Kyu-Jung
    • Journal of The Korean Association of Information Education
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    • v.11 no.3
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    • pp.359-369
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    • 2007
  • Model-centered instruction which presents expert mental model before or during learning can facilitate and help novice learners' problem solving process. During six phases of cognitive apprenticeship model which is a method for applying model centered instruction theory, collaborative learning strategy can maximize articulation and reflection of novice learners. This article presents results of a study that investigated the effects of model-centered instruction and collaborative learning on the learning of instructional design process for pre-service teachers attending a computer education class at an education university.

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Dynamic File Migration And Mathematical model in Distributed Computer Systems (분산 시스템에서 동적 파일 이전과 수학적 모델)

  • Moon, Won Sik
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.10 no.3
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    • pp.35-40
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    • 2014
  • Many researches have been conducted to achieve improvement in distributed system that connects multiple computer systems via communication lines. Among others, the load balancing and file migration are considered to have significant impact on the performance of distributed system. The dynamic file migration algorithm common in distributed processing system involved complex calculations of decision function necessary for file migration and required migration of control messages for the performance of decision function. However, the performance of this decision function puts significant computational strain on computer. As one single network is shared by all computers, more computers connected to network means migration of more control messages from file migration, causing the network to trigger bottleneck in distributed processing system. Therefore, it has become imperative to carry out the research that aims to reduce the number of control messages that will be migrated. In this study, the learning automata was used for file migration which would requires only the file reference-related information to determine whether file migration has been made or determine the time and site of file migration, depending on the file conditions, thus reflecting the status of current system well and eliminating the message transfer and additional calculation overhead for file migration. Moreover, mathematical model for file migration was described in order to verify the proposed model. The results from mathematical model and simulation model suggest that the proposed model is well-suited to the distributed system.

A Study on Development of Test Process Improvement Model (테스트 프로세스 개선 모델 개발에 관한 연구)

  • Yang, Ju-Mi;Bae, Wook;Han, Hyuk-Soo;Shin, Seok-Kyoo;Kim, Kyoung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2005.05a
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    • pp.251-254
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    • 2005
  • 소프트웨어 품질의 중요성이 커짐에 따라, 기업들은 품질을 높이기 위해 테스트에 많은 노력을 기울이고 있다. 최근에는 테스트 성과를 높이기 위한 방법중의 하나로 테스트 프로세스 개선이 주목 받고 있다. 이를 위해 기업들은 SW-CMM(Capability Maturity Model for Software), CMMI(Capability Maturity Model Integration)와 같은 일반적인 프로세스 개선 모델들이나, TMM (Test Maturity Model), TPI (Test Process Improvement Model), TCMM (Testing Capability Maturity Model)과 같은 테스트 프로세스 개선 모델들을 적용하고 있다. 그러나 일반적인 프로세스 개선 모델들은 테스트 관련 이슈를 충분히 다루고 있지 않고, 테스트 프로세스 개선 모델들은 구조가 불완전하거나 내용이 충분하지 않아 적용 시 많은 어려움이 있다. 이에 본 논문에서는 TMM 과 CMMI 를 기반으로 조직들의 테스트 프로세스 확립이나 개선을 지원할 수 있는 새로운 테스트 프로세스 성숙도 모델인 TPMM(Test Process Maturity Model)을 연구, 개발하였다. 개발된 TPMM 을 통해 조직에서 테스트 프로세스를 개선하고, 심사하는 것을 지원할 수 있을 것으로 기대된다.

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A Hybrid Rendering Model to support LOD(Level of Detail) (LOD(Level of Detail)를 지원하는 하이브리드 렌더링 모델)

  • Kim, Hak-Ran;Park, Hwa-Jin
    • Journal of Digital Contents Society
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    • v.9 no.3
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    • pp.509-516
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    • 2008
  • We propose the Hybrid Rendering model to support multi-resolution for computer graphics. LOD method for computer graphics system considering performance of device environment and end-user preference usually adopts mesh resolution, mipmap in texture rendering, or oct-tree data structure in ray tracing. The hybrid rendering model, as a local shading model combining Gouraud shading model and a flat shading model, applies a proper shading method to each of polygons consisting of an object. This method can be an effective alternative to reduce real-time rendering time so that it can be utilized in real time adaptive service of computer graphic contents among various device environments under ubiquitous environments.

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CCAJS: A Novel Connect Coverage Algorithm Based on Joint Sensing Model for Wireless Sensor Networks

  • Sun, Zeyu;Yun, Yali;Song, Houbing;Wang, Huihui
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.10
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    • pp.5014-5034
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    • 2016
  • This paper discusses how to effectively guarantee the coverage and connectivity quality of wireless sensor networks when joint perception model is used for the nodes whose communication ranges are multi-level adjustable in the absence of position information. A Connect Coverage Algorithm Based on Joint Sensing model (CCAJS) is proposed, with which least working nodes are chosen based on probability model ensuring the coverage quality of the network. The algorithm can balance the position distribution of selected working nodes as far as possible, as well as reduce the overall energy consumption of the whole network. The simulation results show that, less working nodes are needed to ensure the coverage quality of networks using joint perception model than using the binary perception model. CCAJS can not only satisfy expected coverage quality and connectivity, but also decrease the energy consumption, thereby prolonging the network lifetime.

Conceptual Data Modeling: Entity-Relationship Models as Thinging Machines

  • Al-Fedaghi, Sabah
    • International Journal of Computer Science & Network Security
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    • v.21 no.9
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    • pp.247-260
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    • 2021
  • Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).

Beyond SDLC: Process Modeling and Documentation Using Thinging Machines

  • Al-Fedaghi, Sabah
    • International Journal of Computer Science & Network Security
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    • v.21 no.7
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    • pp.191-204
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    • 2021
  • The software development life cycle (SDLC) is a procedure used to develop a software system that meets both the customer's needs and real-world requirements. The first phase of the SDLC involves creating a conceptual model that represents the involved domain in reality. In requirements engineering, building such a model is considered a bridge to the design and construction phases. However, this type of model can also serve as a basic model for identifying business processes and how these processes are interconnected to achieve the final result. This paper focuses on process modeling in organizations, per se, beyond its application in the SDLC when an organization needs further documentation to meet its growth needs and address regular changes over time. The resultant process documentation is created alongside the daily operations of the business process. The model provides visualization and documentation of processes to assist in defining work patterns, avoiding redundancy, or even designing new processes. In this paper, a proposed diagrammatic representation models each process using one diagram comprising five actions and two types of relations to build three levels of depiction. These levels consist of a static description, events, and the behavior of the modeled process. The viability of a thinging machine is demonstrated by re-modeling some examples from the literature.

A Self-regulated Learning Model Development in Computer Programming Education (컴퓨터 프로그램 교육에서 자기조절 학습 모델 개발)

  • Kim, Kapsu
    • Journal of The Korean Association of Information Education
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    • v.19 no.1
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    • pp.21-30
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    • 2015
  • Information and knowledge society in the 21st century computer education is very important. Computer programming education in computer education is very important. There are very few teaching and learning model of computer programming education. In this paper, we develop a self-regulated learning model for students to be self-regulated learning. In this study, we propose self-regulated learning elements, a self-regulated learning steps and self-regulated learning modele. Self-regulated learning elements are task level, generalized level, and efficiency level. Self-regulated learning phases are problem understanding, design, and coding, testing, and maintenance. Self-regulated learning models are to copy, to modify, create, and to challenge. The results of this study are as follows. At Correlations between learning elements and achievement, generalized level, and efficiency level are higher than the task level. At Correlations between learning and achievement, Understanding and design stages are higher than the other stages. At Correlations between learning model and achievement, to transform, to create, and to challenge are higher than to copy.