• Journal of Educational Research in Mathematics
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• v.8 no.1
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• pp.163-182
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• 1998

Performance assessment is one of the authentic assessment method that are consistent with new curriculum goal, concentrated on the process rather than the results of problem solving. But the key to good assessment is matching the assessment task to intended objectives. Based on the review of literatures, the current performance assessment task was critically analysed. As a result, this study developed appropriate model and criteria of performance assessment task to elementary mathematics.

• Journal of the Korean Society of Radiology
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• v.83 no.6
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• pp.1208-1218
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• 2022

In the medical field, artificial intelligence has been used in various ways with many developments. However, most artificial intelligence technologies are developed so that one model can perform only one task, which is a limitation in designing the complex reading process of doctors with artificial intelligence. Multi-task learning is an optimal way to overcome the limitations of single-task learning methods. Multi-task learning can create a model that is efficient and advantageous for generalization by simultaneously integrating various tasks into one model. This study investigated the concepts, types, and similar concepts as multi-task learning, and examined the status and future possibilities of multi-task learning in the medical research.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.38-40
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• 2021

Medical domain has a massive number of data records without the response value. Self-supervised learning is a suitable method for medical data since it learns pretext-task and supervision, which the model can understand the semantic representation of data without response values. However, since self-supervised learning performance depends on the expression learned by the pretext-task, it is necessary to define an appropriate Pretext-task with data feature consideration. In this paper, to actively exploit the unlabeled medical data into artificial intelligence research, experimentally find pretext-tasks that suitable for the medical data and analyze the result. We use the x-ray image dataset which is effectively utilizable for the medical domain.

• Korean Management Science Review
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• v.21 no.2
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• pp.111-122
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• 2004

Measuring performance of corporate information system has become one of the core issues in that development of the information system requires substantial amount of investments and the system works as a crucial leverage to enhance competitive edge. Most of the previous researches for performance of the information system have narrow and limited focus on such as the effect of user satisfaction and productivity. This paper suggests a model to measures the comprehensive performance which is classified as user scope (user involvement and satisfaction), operational scope (task productivity, task innovation, customer satisfaction, management control) and efficiency scope (financial performance), and to represent the relationship among the scopes by the path analysis model. Followings are conclusions from statistical hypothesis test of the model: (i) user involvement through user satisfaction has positive effect on all the performances in the operational scope, (ii) task innovation and customer satisfaction in the operational scope has statistically significant impact on financial performance but task productivity and management control do not. This conclusion indicates that task productivity and management control has the long term effect in nature, and evaluation of the information system has managerial implication when it Is measured in comprehensive performance which includes internal operational performances as well as financial performance.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.219-221
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• 1995

This paper proposes a model for simulation and performance evaluation of distributed computer systems(DCS). The model is composed of operating system(OS), resource, task, environment submodel. Task Flow Graph(TFG) is suggested to describe the relation between tasks. This paper considers task response time, the scheduler's ready queue length, utilization of each resource as performance indices. The distributed system of Continuous Annealing Line(CAL) in iron process is simulated with the proposed model.

• Journal of the Ergonomics Society of Korea
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• v.14 no.1
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• pp.25-35
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• 1995

For information processing tasks, it is an important cognitive skill to manipulate and store information, which is known as information intake. One of the tasks which greatly involve this skill would be a spreadsheet calculation task. In this study, a spreadsheet calculation task is analyzed by the cognitive task analysis based on the cognitive factors having been usef for a model of human information processing. By the results of the cognitive task analysis, the spreadsheet calculation tasks to be used in the experiments are designed and the testbattery of cognitive abilities assessment (CCAB ; complex cognitive asssessment battery) are selected. Then, the features of cognitive demands and a human performance model of the spreadsheet calculation task are suggested by means of correlation analysis, principal component factor analysis, and regression analysis of the results of the experiments on task performances and the assessment of cognitive abilities. Also, the application of the results of the study to job placement and further research issues are described.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.450-464
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• 2023

To address the problems of large system overhead and low timeliness when dealing with task scheduling in mobile edge cloud computing, a task scheduling and resource management strategy for edge cloud computing based on an improved genetic algorithm was proposed. First, a user task scheduling system model based on edge cloud computing was constructed using the Shannon theorem, including calculation, communication, and network models. In addition, a multi-objective optimization model, including delay and energy consumption, was constructed to minimize the sum of two weights. Finally, the selection, crossover, and mutation operations of the genetic algorithm were improved using the best reservation selection algorithm and normal distribution crossover operator. Furthermore, an improved legacy algorithm was selected to deal with the multi-objective problem and acquire the optimal solution, that is, the best computing task scheduling scheme. The experimental analysis of the proposed strategy based on the MATLAB simulation platform shows that its energy loss does not exceed 50 J, and the time delay is 23.2 ms, which are better than those of other comparison strategies.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.10-18
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• 1997

This paper presents the development of real-time estimation and control details for a computer vision-based robot control method. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes know 4-axis Scorbot manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method. The method is tested experimentally in two ways : First the validity of estimation model is tested by using the self-built test model. Second, the practicality of the presented control method is verified in performing 4-axis manipulator's assembly task. These results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as deburring and welding.

• The KIPS Transactions:PartA
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• v.8A no.1
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• pp.16-26
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• 2001

This paper proposes an extended scheduler model that is an extension of the existing model proposed already in [4, 5], which consists of upper layer task scheduler and lower layer scheduling framework. However, in order to support aperiodic task scheduling, the task scheduler has been divided into two parts, such as periodic task control component and aperiodic task control component. Thus, the proposed model can support various bandwidth-preserving servers that can service aperiodic tasks. The model distinctly separates a classic monolithic kernel scheduler into several kernel components according to their functionality. This enables system developers to implement a new scheduling algorithm or aperiodic task server independent of complex low kernel mechanism, and reconfigure the system at need. In Real-Time Linux [6], we implemented the proposed scheduling framework representative scheduling algorithms, and server bandwidth-preserving servers on purpose to test. Throughout these implementations, we confirmed that a new algorithm or server could be developed independently without updates of complex low kernel modules. In order to verify efficiency of the proposed model, we measured the performance of several aperiodic task servers. The results showed this the performance of model, which even consisted of two hierarchical components and several modules, didnt have such high run-time overhead, and could efficiently support reconfiguration and scheduler development.

• Journal of the Ergonomics Society of Korea
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• v.19 no.2
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• pp.87-99
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• 2000

This study aims to examine a fuzzy logic-based human expert EMG prediction model (FLHEPM) for predicting electromyographic responses of trunk muscles due to manual lifting based on two task (control) variables. The FLHEPM utilizes two variables as inputs and ten muscle activities as outputs. As the results, the lifting task variables could be represented with the fuzzy membership functions. This provides flexibility to combine different scales of model variables in order to design the EMG prediction system. In model development, it was possible to generate the initial fuzzy rules using the neural network, but not all the rules were appropriate (87% correct ratio). With regard to the model precision, the EMG signals could be predicted with reasonable accuracy that the model shows mean absolute error of 8.43% ranging from 4.97% to 13.16% and mean absolute difference of 6.4% ranging from 2.88% to 11.59%. However, the model prediction accuracy is limited by use of only two task variables which were available for this study (out of five proposed task variables). Ultimately, the neuro-fuzzy approach utilizing all five variables to predict either the EMG activities or the spinal loading due to dynamic lifting tasks should be developed.