• Title/Summary/Keyword: Process and Resource models

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The Design and development of online learning modules for the broadcasting content-based e-PBL (방송콘텐츠 기반 e-PBL을 위한 온라인 학습모듈 설계 및 개발)

  • Jung, Joon-Hwan
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.1
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    • pp.105-115
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    • 2012
  • This study paid attention to the possibility of broadcasting contents as a learning resource, which promoted the knowledge composition and the process of creation from the software having enriched contents not a delivering tool for the information in one direction. and tried to implement it thru e-PBL, which is one of teaching-learning models in e-learning. In order to implement the possibility of broadcasting contents in the e-PBL enviroment as a learning resource, the study focused on the design and development of e-PBL based on the broadcasting contents and found out the educational possibility for the broadcasting contents as the learning resource in e-PBL enviroment. This study focused on the design of learning module and development process which integrated strategic plans to maximize the utilization of broadcasting contents including development of online learning community. Also, This is verified by applying the learning module was to prove a differentiation.

Determination and prediction of amino acid digestibility in brown rice for growing-finishing pigs

  • Qing Ouyang;Rui Li;Ganyi Feng;Gaifeng Hou;Xianji Jiang;Xiaojie Liu;Hui Tang;Ciming Long;Jie Yin;Yulong Yin
    • Animal Bioscience
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    • v.37 no.8
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    • pp.1474-1482
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    • 2024
  • Objective: The experiment aimed to determine the standardized ileal digestibility (SID) of crude protein (CP) and amino acids (AA) in 10 brown rice samples fed to pigs, and to construct predictive models for SID of CP and AA based on the physical characteristics and chemical composition of brown rice. Methods: Twenty-two cannulated pigs (initial body weight: 42.0±1.2 kg) were assigned to a replicated 11×3 incomplete Latin square design, including an N-free diet and 10 brown rice diets. Each period included 5 d adaptation and 2 d ileal digesta collection. Chromic oxide was added at 0.3% to all the diets as an indigestible marker for calculating the ileal CP and AA digestibility. Results: The coefficients of variation of all detected indices for physical characteristics and chemical composition, except for bulk weight, dry matter (DM) and gross energy, in 10 brown rice samples were greater than 10%. The SID of CP, lysine (Lys), methionine, threonine (Thr), and tryptophan (Trp) in brown rice was 77.2% (62.6% to 85.5%), 87.5% (80.3% to 94.3%), 89.2% (78.9% to 98.9%), 55.4% (46.1% to 67.6%) and 92.5% (86.3% to 96.3%), respectively. The best prediction equations for the SID of CP, Lys, Thr, and Trp were as following, SIDCP = -664.181+8.484×DM (R2 = 0.40), SIDLys = 53.126+6.031×ether extract (EE)+0.893×thousand-kernel volume (R2 = 0.66), SIDThr = 39.916+7.843×EE (R2 = 0.41), and SIDTrp = -361.588+4.891×DM+0.387×total starch (R2 = 0.85). Conclusion: Overall, a great variation exists among 10 sources of brown rice, and the thousand-grain volume, DM, EE, and total starch can be used as the key predictors for SID of CP and AA.

Enhanced Coulomb Counting Method for State-of-Charge Estimation of Lithium-ion Batteries based on Peukert's Law and Coulombic Efficiency

  • Xie, Jiale;Ma, Jiachen;Bai, Kun
    • Journal of Power Electronics
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    • v.18 no.3
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    • pp.910-922
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    • 2018
  • Conventional battery state-of-charge (SoC) estimation methods either involve sophisticated models or consume considerable computational resource. This study constructs an enhanced coulomb counting method (Ah method) for the SoC estimation of lithium-ion batteries (LiBs) by expanding the Peukert equation for the discharging process and incorporating the Coulombic efficiency for the charging process. Both the rate- and temperature-dependence of battery capacity are encompassed. An SoC mapping approach is also devised for initial SoC determination and Ah method correction. The charge counting performance at different sampling frequencies is analyzed experimentally and theoretically. To achieve a favorable compromise between sampling frequency and accumulation accuracy, a frequency-adjustable current sampling solution is developed. Experiments under the augmented urban dynamometer driving schedule cycles at different temperatures are conducted on two LiBs of different chemistries. Results verify the effectiveness and generalization ability of the proposed SoC estimation method.

Extended Linear Vulnerability Discovery Process

  • Joh, HyunChul
    • Journal of Multimedia Information System
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    • v.4 no.2
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    • pp.57-64
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    • 2017
  • Numerous software vulnerabilities have been found in the popular operating systems. And recently, robust linear behaviors in software vulnerability discovery process have been noticeably observed among the many popular systems having multi-versions released. Software users need to estimate how much their software systems are risk enough so that they need to take an action before it is too late. Security vulnerabilities are discovered throughout the life of a software system by both the developers, and normal end-users. So far there have been several vulnerability discovery models are proposed to describe the vulnerability discovery pattern for determining readiness for patch release, optimal resource allocations or evaluating the risk of vulnerability exploitation. Here, we apply a linear vulnerability discovery model into Windows operating systems to see the linear discovery trends currently observed often. The applicability of the observation form the paper show that linear discovery model fits very well with aggregate version rather than each version.

Production Efficiency Evaluation Considering Various Process Parameters (다양한 공정변수를 포함한 생산품의 효율성 평가방법에 관한 연구)

  • Kim, Chu;Cho, YongJu;Seo, Yoonho;Jo, Hyunjae
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.6
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    • pp.921-930
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    • 2013
  • From an economic perspective, an enterprise's business activity depends on the efficient use of corporate resources for generating profits. However, on the enterprise side, it is difficult to measure and evaluate the effective use of each resource. This paper suggests an alternative for eliminating process inefficiencies in the consolidation of competitive power in auto parts manufacturing company A. Multitudinous process variables from company A's raw materials-to-shipment process are configured as input resources, and a Data Envelopment Analysis(DEA) is carried out to determine economical benefit of said resources' operation, as well as how products are manufactured. The DEA model offers a non-parametric approach to measuring relative efficiency using input and output factors. Furthermore, AHP is used for logically deciding the importance of each evaluation factor. In general, DEA models have been used for measuring efficiency of the service and public sectors. However, this study focused on measuring the efficiency of SMEs production lines.

Adaptive Process Decision-Making with Simulation and Regression Models (시뮬레이션과 회귀분석을 연계한 적응형 공정의사결정방법)

  • Lee, Byung-Hoon;Yoon, Sung-Wook;Jeong, Suk-Jae
    • Journal of the Korea Society for Simulation
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    • v.23 no.4
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    • pp.203-210
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    • 2014
  • This study proposes adaptive decision making method having feed-back structure of regression and simulation models to support the quick decision making of production managers by managing and integrating the mutual relationship among historical data. For that, from historical data that have extracted and accumulated from each process, we first selected major constraint resources that are used as independent variables in regression model. The regression model is designed by using the dependent variables (objectives) that defined above by managers and independent variables selected in previous step and simulation model that are composed of constraint resources is designed. In process of simulation run, we obtain the multiple feasible solutions (alternatives) by using meta-heuristic method. Each solution is substituted by regression equation and we found the optimal solution that is minimum of difference between values obtained by regression model and simulation results. The optimal solution is delivered and incorporated to production site and current operation results from production site is used to generate new regression model after that time.

An Essay on Human Resource Management and Personnel Economics - A Behavioral Scientist's Viewpoint - (인적자원관리와 인사경제학의 비교 - 행동과학자의 시각에서 -)

  • Baek, Gwang-Gi
    • Korean Business Review
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    • v.23 no.2
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    • pp.1-29
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    • 2010
  • Traditional human resource management explains human characteristics with motivation, attitude, perception, value, etc., based upon behavioral science approach. And system approach is adopted in analyzing the interaction between people and the environment. However, personnel economics excludes social and psychological variables in the human choice models, and assumes very unrealistic and simple rational decision making process. For environmental variables, personnel economists considers only income and price. Traditional human resource management research model successfully explains the phenomenon for each specific situation, but lacks universality. On the other hand, personnel economics model is strict and analytical, but tends to distort the understanding of the results because of the unrealistic assumptions. These two academic fields may get benefits by introducing the other's research methodologies, theories, and ideas.

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An Activity-Performer Bipartite Matrix Generation Algorithm for Analyzing Workflow-supported Human-Resource Affiliations (워크플로우 기반 인적 자원 소속성 분석을 위한 업무-수행자 이분 행렬 생성 알고리즘)

  • Ahn, Hyun;Kim, Kwanghoon
    • Journal of Internet Computing and Services
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    • v.14 no.2
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    • pp.25-34
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    • 2013
  • In this paper, we propose an activity-performer bipartite matrix generation algorithm for analyzing workflow-supported human-resource affiliations in a workflow model. The workflow-supported human-resource means that all performers of the organization managed by a workflow management system have to be affiliated with a certain set of activities in enacting the corresponding workflow model. We define an activity-performer affiliation network model that is a special type of social networks representing affiliation relationships between a group of performers and a group of activities in workflow models. The algorithm proposed in this paper generates a bipartite matrix from the activity-performer affiliation network model(APANM). Eventually, the generated activity-performer bipartite matrix can be used to analyze social network properties such as, centrality, density, and correlation, and to enable the organization to obtain the workflow-supported human-resource affiliations knowledge.

A Study on VV&A Application for the Korean Wartime Resource Requirement Model (한국형 전시자원소요산정 모델에 대한 VV&A 적용방안 연구)

  • Kim, Min-Suk;Jung, Whan-Sik;Lee, Jae-Yeong
    • Journal of the military operations research society of Korea
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    • v.35 no.2
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    • pp.51-61
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    • 2009
  • Recently, the necessity of VV&A and the importance of M&S are increasing in the national defense area. The purpose of VV&A is to assure a proper development of M&S and to provide users with sufficient information to determine if M&S could meet their demands. Therefore, VV&A process needs to be performed to guarantee the credibility of the M&S. However, the basic guidance and regulation of VV&A are not yet developed in Korea. This paper proposed the VV&A application process in the Korean Wartime Resource Requirement Model, focusing on the close combat situation of the model. The VV&A process provided in this paper can also be applied to other analytical models currently developing in Korea.

Dimensioning of linear and hierarchical wireless sensor networks for infrastructure monitoring with enhanced reliability

  • Ali, Salman;Qaisar, Saad Bin;Felemban, Emad A.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.9
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    • pp.3034-3055
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    • 2014
  • Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.