• Journal of the Ergonomics Society of Korea
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• 제32권1호
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• pp.59-68
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• 2013

Objective: The purpose of this paper is to introduce a task complexity model combining task design aspects and complexity dimensions and to explain an approach to identifying and organizing task complexity factors based on the model. Background: Task complexity is a critical concept in describing and predicting human performance in complex systems such as nuclear power plants(NPPs). In order to understand the nature of task complexity, task complexity factors need to be identified and organized in a systematic manner. Although several methods have been suggested for identifying and organizing task complexity factors, it is rare to find an analytical approach based on a theoretically sound model. Method: This study regarded a task as a system to be designed. Three levels of design ion, which are functional, behavioral, and structural level of a task, characterize the design aspects of a task. The behavioral aspect is further classified into five cognitive processing activity types(information collection, information analysis, decision and action selection, action implementation, and action feedback). The complexity dimensions describe a task complexity from different perspectives that are size, variety, and order/organization. Combining the design aspects and complexity dimensions of a task, we developed a model from which meaningful task complexity factors can be identified and organized in an analytic way. Results: A model consisting of two facets, each of which is respectively concerned with design aspects and complexity dimensions, were proposed. Additionally, twenty-one task complexity factors were identified and organized based on the model. Conclusion: The model and approach introduced in this paper can be effectively used for examining human performance and human-system interface design issues in NPPs. Application: The model and approach introduced in this paper could be used for several human factors problems, including task allocation and design of information aiding, in NPPs and extended to other types of complex systems such as air traffic control systems as well.

• The Journal of Korean Institute of Communications and Information Sciences
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• 제27권10C호
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• pp.887-901
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• 2002

Software management model divided into the software project model and design estimation model, software matrices model, reliability growth model, process improvement model(or process maturity model) etc. Among these software management models, software complexity model make an estimated of the product software. For a practice of software managed, need to guideline of the static analysis of software. Especially, Software complexity model introduced for the estimation of software quantity and program complexity. In case of measurement the software matrices, its need for us to analysis of software quality and products. On the other hand, we known that complexity program include many defects and consuming of source cost. So, we apply to complexity model using of the program complexity, control structure and volume matrices, interface metrics, process complexity metrics method. In this paper, we represent that the analysis of fault data detected during the system test. Also, we analysis of program control structure and interface, volume matrices in various aspect of switching software. Others, their results utilized similar of project and system development.

• Health Policy and Management
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• 제14권1호
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• pp.89-120
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• 2004

The purpose of this empirical study is to test hypotheses in order to identify the cost drivers that drive indirect costs in general hospitals in Korea. In various cases' studies, it has been suggested that overhead costs are driven by volume and complexity variables, how they are structurally related and how the cost impacts of these variables can be A unique feature of the research is the treatment of complexity as an endogenous variable. It is hypothesized that level of hospital complexity in terms of the number of services provided(i.e., “breath" complexity) and the intensity of individual estimated in practice. overhead services(ie., “depth" complexity) are simultaneous determined with the level of costs needed to support the complexity. Data used in this study were obtained from the Database of Korean Health Industry Development Institute, Health Insurance Review Agency and analyzed using simultaneous equation model, path model. The results found those volume and complexity variables are all statistically signi-ficance drivers of general hospital overhead costs. This study has documented that the level of service complexity is a significant determinant of hospital overhead costs, caution should be exercised in interpreting this as supportive of the cost accounting procedures associated with ABC. with ABC.

• Asia Marketing Journal
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• 제23권1호
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• pp.5-27
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• 2021

This paper seeks to suggest user satisfaction model of digital signage to see how new in-store technology can effectively lead to customers' shopping satisfaction in fashion retails. Authors in particular focus on technological complexity, which is expected to serve a subtle role in using digital signage. This study employed a scenario-based online survey. Interactive digital signage with virtual try-on and video-captures functions was used as stimuli. Data were collected from 320 respondents and 307 useable responses were analyzed to examine a proposed model. Research model compares dual paths of motivators: the extrinsic motivation route that leads from usefulness to shopping outcome satisfaction and intrinsic motivation route that leads from enjoyment to shopping process satisfaction. Technological complexity of digital signage indirectly and negatively influences shopping outcome and process satisfaction, mediated by usefulness and enjoyment, but directly and positively affects shopping process satisfaction. In omni-channel environments, the findings have implications for fashion retail managers in using digital signage to maximize customer satisfaction and to counterbalance the advantages and disadvantages of technological complexity.

• Journal of KIISE:Software and Applications
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• 제26권11호
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• pp.1282-1287
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• 1999

통신 프로그램은 고도의 신뢰성과 기능성, 확장성, 그리고 유지 보수성이 필요하다. 프로그램 테스트의 결과와 McCabe의 Complexity를 측정한 데이타를 가지고 회귀모델을 만들고 그 신뢰성을 분석함으로서 프로그램의 결함과 복잡도의 관련성을 평가한다.본 연구에서 사용한 통신 프로그램은 500개 블록이 59가지 기능을 수행하는 교환 기능 중에서 복잡도가 너무 많아서 통계 처리의 bias가 될 블록을 제외하고 394 블록을 선정하여 SAS에 의해서 통계 분석을 하고 회귀 분석 모델을 설계하였다. t 분포에 의하여 방정식의 유의성 수준을 검증하고 프로그램의 결함수에 가장 큰 영향을 주고 있는 복잡도가 McCabe의 복잡도와 설계 복잡도 임을 밝혀냈다. 이 연구 결과에 의해서 설계 정보 및 유지 보수 정보를 얻을 수 있다. Abstract Switching software requires high reliability, functionality, extendability and maintainability. For doing, software quality model based on MaCabe's complexity measure is investigated. It is experimentally shown using regression analysis the program fault density depends on the complexity and size of the function unit. The software should be verified and tested if it satisfies its requirements with automated analysis tools. In this paper we propose the regression model with the test data.The sample program for the regression model consists of more than 500 blocks, where each block compose of 10 files, which has 59 functions of switching activity.Among them we choose 394 blocks and analyzed for 59 functions by testing tools and SAS package. We developed Regression Analysis Model and evaluated significant of the equation based on McCabe's cyclomatic complexity, block design complexity, design complexity, and integration complexity.The results of our experimental study are that number of fault are under the influence of McCabe's complexity number and design complexity.

• Magazine of the Korean Society of Agricultural Engineers
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• 제45권4호
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• pp.89-97
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• 2003

Using inference models developed for estimation of the parameters necessary to implement the Runoff Block of the Stormwater Management Model (SWMM), a number of alternative inference scenarios were developed to assess the influence of inference model complexity and structure on the calibration of the catchment modelling system. These inference models varied from the assumption of a spatially invariant value (catchment average) to spatially variable with each subcatchment having its own unique values. Fur-thermore, the influence of different measures of deviation between the recorded information and simulation predictions were considered. The results of these investigations indicate that the model performance is more influenced by model structure than complexity, and control parameter values are very much dependent on objective function selected as this factor was the most influential for both the initial estimates and the final results.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.173-184
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• 2001

We present an algorithm for the complexity reduction of a general Gaussian mixture model by using a penalized likelihood method. One of our important assumptions is that we begin with an overfitted model in terms of the number of components. So our main goal is to eliminate redundant components in the overfitted model. As shown in the section of simulation results, the algorithm works well with the selected densities.

• Journal of Korea Multimedia Society
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• 제9권12호
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• pp.1607-1616
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• 2006

The growing market of multimedia and digital signal processing requires significant data-path portions of SoCs. However, the common models for verification are not suitable for SoCs. A novel model--WGL (Weighted Generalized List) is proposed, which is based on the general-list decomposition of polynomials, with three different weights and manipulation rules introduced to effect node sharing and the canonicity. Timing parameters and operations on them are also considered. Examples show the word-level WGL is the only model to linearly represent the common word-level functions and the bit-level WGL is especially suitable for arithmetic intensive circuits. The model is proved to be a uniform and efficient model for both bit-level and word-level functions. Then Based on the WGL model, a backward-construction logic-verification approach is presented, which reduces time and space complexity for multipliers to polynomial complexity(time complexity is less than $O(n^{3.6})$ and space complexity is less than $O(n^{1.5})$) without hierarchical partitioning. Finally, a construction methodology of word-level polynomials is also presented in order to implement complex high-level verification, which combines order computation and coefficient solving, and adopts an efficient backward approach. The construction complexity is much less than the existing ones, e.g. the construction time for multipliers grows at the power of less than 1.6 in the size of the input word without increasing the maximal space required. The WGL model and the verification methods based on WGL show their theoretical and applicable significance in SoC design.

• Smart Structures and Systems
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• 제29권2호
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• pp.321-336
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• 2022

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

• Journal of Information Technology Applications and Management
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• 제13권2호
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• pp.145-162
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• 2006

Despite the careful attention paid by managers and researchers to the effective administration of the S/W Development Project, there are cases where the project goes over-budget or misses deadlines. Existing research blames these problems on task complexity or mismanagement. In order to verify the results that varied according to the fitness between the Task Characteristics and the Project Management Types, a contingency model was employed. The verification of the contingency model demonstrated that the greater the task complexity, the greater the effectiveness of the project coordination, and the lesser the task complexity, the greater the effectiveness of project control. This research is theoretically important in that it develops a composite model to verify the relation between the three factors of Task Characteristics, Project Management Types, and Project Performance that compose the S/W Development Project.