• 대한인간공학회지
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• 제30권2호
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• pp.303-310
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• 2011

In this study, we employ CPM-GOMS analysis for explaining physical and cognitive processes and for quantitatively predicting when users are typing Korean text messages on mobile phones using both hands. First, we observe the behaviors of 10 subjects, when the subjects enter keypads with both hands. Then, basing upon MHP, we categorize the behaviors into perceptual, cognitive, motor operators, and then we analyze those operators. After that, we use the critical paths to model two task sentences. Also, we used Fitts' law method which was applied many times to predict text entering time on mobile phone to compare with the results of our CPM-GOMS model. We followed Lee's (2008) method that is well suited for text entry task using both hands and calculate total task time for each task sentences. For the sake of comparison between the actual data and the results predicted from our CPM-GOMS model, we empirically tested 10 subjects and concluded that there were no significant differences between the predicted values and the actual data. With the CPM-GOMS model, we can observe the human information processes composed on the physical and cognitive processes. Also we verified that the CPM-GOMS model can be well applied to predict the users' performance when they input text messages on mobile phones using both hands by comparing the predicted total task time with the real execution time.

• Journal of Information Processing Systems
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• 제14권3호
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• pp.621-630
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• 2018

Selection of a suitable task from the extensively available large set of tasks is an intricate job for the developers in crowdsourcing software development (CSD). Besides, it is also a tiring and a time-consuming job for the platform to evaluate thousands of tasks submitted by developers. Previous studies stated that managerial and technical aspects have prime importance in bringing success for software development projects, however, these two aspects can be more effective and conducive if combined with human aspects. The main purpose of this paper is to present a conceptual framework for task assignment model for future research on the basis of personality types, that will provide a basic structure for CSD workers to find suitable tasks and also a platform to assign the task directly. This will also match their personality and task. Because personality is an internal force which whittles the behavior of developers. Consequently, this research presented a Task Assignment Model (TAM) from a developers point of view, moreover, it will also provide an opportunity to the platform to assign a task to CSD workers according to their personality types directly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권9호
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• pp.1544-1572
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• 2011

Task placement and scheduling are traditionally studied in following aspects: resource utilization, application throughput, application execution latency and starvation, and recently, the studies are more on application scalability and application performance. A methodology for task placement and scheduling centered on tasks based on virtual machines is studied in this paper to improve the performances of systems and dynamic adaptability in applications development and deployment oriented parallel computing. For parallel applications with no real-time constraints, we describe a thought of feature model and make a formal description for four layers of task placement and scheduling. To place the tasks to different layers of virtual computing systems, we take the performances of four layers as the goal function in the model of task placement and scheduling. Furthermore, we take the personal preference, the application scalability for a designer in his (her) development and deployment, as the constraint of this model. The workflow of task placement and scheduling based on virtual machines has been discussed. Then, an algorithm TPVM is designed to work out the optimal scheme of the model, and an algorithm TEVM completes the execution of tasks in four layers. The experiments have been performed to validate the effectiveness of time estimated method and the feasibility and rationality of algorithms. It is seen from the experiments that our algorithms are better than other four algorithms in performance. The results show that the methodology presented in this paper has guiding significance to improve the efficiency of virtual computing systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권4호
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• pp.1426-1447
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• 2021

The payoff game between task publishers and users in the mobile crowdsensing environment is a hot topic of research. A optimal payoff selection model based on stochastic evolutionary game is proposed. Firstly, the process of payoff optimization selection is modeled as a task publisher-user stochastic evolutionary game model. Secondly, the low-quality data is identified by the data quality evaluation algorithm, which improves the fitness of perceptual task matching target users, so that task publishers and users can obtain the optimal payoff at the current moment. Finally, by solving the stability strategy and analyzing the stability of the model, the optimal payoff strategy is obtained under different intensity of random interference and different initial state. The simulation results show that, in the aspect of data quality evaluation, compared with BP detection method and SVM detection method, the accuracy of anomaly data detection of the proposed model is improved by 8.1% and 0.5% respectively, and the accuracy of data classification is improved by 59.2% and 32.2% respectively. In the aspect of the optimal payoff strategy selection, it is verified that the proposed model can reasonably select the payoff strategy.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• 영어어문교육
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• 제12권3호
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• pp.123-145
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• 2006

The purpose of this study is to propose an efficient vocabulary assessment model in task-based language learning and to verify the viability of this assessment model. Bachman and Palmer (1996) pointed out the fact that many language tests focus on just one of the areas of language knowledge. However, researchers suggested that it is necessary to acknowledge the needs of several analytic scales, which can provide separate ratings for different components of the language ability to be tested. Although there were many studies which tried to evaluate the various aspects of vocabulary ability, most of them measured only one or two factors. Based on previous research, this study proposed an assessment model of general construct of vocabulary ability and tried to measure vocabulary ability in four separate areas. The subjects were two classes of university level Korean EFL students. They participated in small group discussion via synchronous CMC. One class used a lexically focused task, which was proposed by Kim and Jeong (2006) and the other class used a non-lexically focused task. The results showed that the students with a lexically focused task significantly outperformed those with a non-lexically focused task in overall vocabulary ability as well as four subdivisions of vocabulary ability. In conclusion, the assessment model of separate ratings is a viable measure of vocabulary ability and this can provide elaborate interpretation of vocabulary ability.

• 한국안전학회지
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• 제24권2호
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• pp.76-82
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• 2009

The NIOSH lifting equation has been used as a dominant tool in evaluating the hazard levels of lifting tasks. Although it provides two different ways for each simple and complex lifting task, the NIOSH simple lifting equation is almost used for not only simple tasks but also complex tasks. However, most of lifting tasks in industries are in the form of complex lifting. Therefore some errors occur inevitably in the evaluation of complex lifting tasks. Among complex lifting tasks, a multi-stacking task is the most popular in lifting tasks. To compensate the error in the evaluation of multi-stacking tasks by using the NIOSH simple lifting equation, a set of calculations for finding LIs(Lifting Indices) was performed for the systematically varying multi-stacking tasks. Then a regression model which finds the equivalent height in simple lifting task for multi-stacking task was established. By using this model, multi-stacking tasks can be evaluated with less error. To validate this model, some real multi-stacking tasks were evaluated as examples.

• 한국정보시스템학회지:정보시스템연구
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• 제16권1호
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• pp.179-200
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• 2007

In this research, we study how task and KMS fit influences on KMS performance in large corporations during its practical use. Based on the task-technology fit theory and information system success model, we developed a research model by considering the characteristics of KMS for supporting tasks. We try to verify how individual traits, task traits, and KMS Units affect task-KMS fit and how task KMS fit influences on KMS performance. We surveyed 212 employees who were using KMS and working for the large-sized manufacturing firms. We analyzed the collected data from LISREL 8.54 for Windows, and found the following significant results. First user satisfaction is increased when KMS provides knowledge to help to perform task rather than KMS' functionality. Second, user satisfaction is increased when KMS is suitable for performing task Hence, we verified task-KMS fit is an antecedent of user satisfaction. Third, task-KMS fit and user satisfaction have significant impacts on KMS performance. And user satisfaction affected more heavily on KMS performance than task-KMS fit did. As a result, we realized an individual performance can be improved when task KMS fit is high and, consequently, user satisfaction is increased. Forth while the usefulness of task-KMS fit is demonstrated, causal factors such as individual traits, task traits, and KMS traits significantly affect task-KMS fit. Formalization and knowledge trait we significant in enhancing user satisfaction, but KMS self-efficacy, autonomy, md system trait are not. These results indicate that task-KMS fit variable is useful as a measure of KMS performance as well as that of user satisfaction. Based on these results, we conclude that when KMS supports task activity, performance can be significantly improved by coordinating the task with KMS.

• 한국문헌정보학회지
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• 제48권4호
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• pp.71-90
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• 2014

이 연구는 학교도서관 사서가 자신의 과업을 수행함에 있어 SNS를 어떻게 이용하고, 과업의 특성과 1인 운영체제의 특성으로 인하여 SNS를 활용하는 것이 자신의 성과에 영향을 미치는 지를 파악하고자 하였다. 사서의 과업, SNS이용 및 성과에 대한 상관관계를 객관적으로 설명하기 위해서 기술수용모델(Technology Acceptance Model)과 과업-기술적합도(Task-Technology Fit)의 결합을 통하여 사서과업-SNS기술적합도의 모형을 제시하였다. 229건의 설문조사를 분석한 결과, 학교도서관 사서의 업무적인 SNS활용이 자신의 성과에 영향을 미친다는 것을 증명하였다. 또한 학교도서관 사서가 SNS를 활용하는 것이 단순히 개인적 취향이나 업무를 방해하는 요소만 있는 것이 아니라, 과업의 특성이나 1인 운영체제와 같은 조직의 특성으로 인해 업무성과를 향상시키는 요인이라는 것을 확인하였다.

• 산업공학
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• 제17권3호
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• pp.314-329
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• 2004

The rapid growth of investments in mobile service to reach a large and growing body of customers, coupled with low communication costs, has made user acceptance an increasingly critical management issue. The study draws upon the task-technology fit (TTF) model as its theoretical basis and its empirical findings to pragmatically explain the key factors that affect the performance and user acceptance of mobile service in medical field. A total of 110 usable responses were obtained. The findings indicate that the task, technology, and individual user characteristics positively affect task-technology fit and mobile service usage. The task-technology fit and mobile service usage are the dominant factors that affect mobile service performance. The result points out the importance of the fit between technologies and users' tasks in achieving individual performance impact from mobile service in medical arena.