• Journal of the Ergonomics Society of Korea
• /
• v.32 no.1
• /
• pp.59-68
• /
• 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.

• 한국HCI학회:학술대회논문집
• /
• 2008.02b
• /
• pp.158-164
• /
• 2008

This study was conducted for raising the considering the dynamical context of mobile phone use environment in the mobile-phone research. For this I identified the characteristic of the mobile phone use. The first characteristic is that the mobile phone is the context sensitive device. Also, it reflects the user's life pattern because it is the very personal device. I defined the context of mobile phone use with the basis on this identification of those characteristics. I referenced the definition, 'situational context', defining the mobile phone use context. Also, I set up the research scope within the user task that is influential from the situational context, I named this kind of task as the 'contextual task'. I developed the Contextual Task Model in this study. I named the model as the 'ESR Model'. The reason that I developed this contextual task model is that this model can help novice designers and designers unfamiliar with an application domain understand the user behavior and user centered design. And also this model can be effective to communicate each other, I identified the user's contextual tasks three kinds of model. First, the Extend Model includes user tasks that related to extending from user physical working space to the virtual level. Second model is Synchronize Model, which includes issues that lesson the blocking when use several functions at a time or sequentially. Third model is Replace Model, which is come from the characteristic of user life pattern to use the mobile phone. Finally, I proposed an application of this model, CIQ. Through the process to make CIQ I proved the effectiveness of this ESR Model.

• Journal of Information Processing Systems
• /
• v.17 no.3
• /
• pp.441-452
• /
• 2021

Federated learning provides an efficient integrated model for distributed data, allowing the local training of different data. Meanwhile, the goal of multi-task learning is to simultaneously establish models for multiple related tasks, and to obtain the underlying main structure. However, traditional federated multi-task learning models not only have strict requirements for the data distribution, but also demand large amounts of calculation and have slow convergence, which hindered their promotion in many fields. In our work, we apply the rank constraint on weight vectors of the multi-task learning model to adaptively adjust the task's similarity learning, according to the distribution of federal node data. The proposed model has a general framework for solving optimal solutions, which can be used to deal with various data types. Experiments show that our model has achieved the best results in different dataset. Notably, our model can still obtain stable results in datasets with large distribution differences. In addition, compared with traditional federated multi-task learning models, our algorithm is able to converge on a local optimal solution within limited training iterations.

• Journal of Science Education
• /
• v.37 no.1
• /
• pp.170-185
• /
• 2013

The purpose of this study is to investigate a cognitive model of task commitment on biology classification inquiry. To achieve this goal, first, this study analyzed several literatures on task commitment in biology inquiry, and invented the tentative model of the task commitment. To investigate a tentative model invented, 2 main tasks were developed. These tasks were administered to 8 high-school students, first grade. Raw protocols were collected by thinking aloud method and a retrospective interview method. Collected protocols were converted to segmented protocols and coded by analyzing frame based invented model. The codes were analyzed. As a result, some problems were discovered, tentative model were revised. New analyzing frame based on Improved model were composed, and raw protocols were re-analyzed. Finally, a cognitive model of task commitment on biology classification inquiry was investigated. The investigated cognitive model of task commitment on biology classification inquiry was constructed 3 steps, 'Task commitment Induction', 'Task commitment Reinforcement', 'Task commitment Maintenance'. And each steps were consisted of several sub-factor. And commitment component were changed in each steps. Through this results, base information for strategy that improvement task commitment on biology classification inquiry is provided. Furthermore, the cognitive model of task commitment on biology classification inquiry will assist on evaluation and feedback by stage on task commitment.

• International Journal of Contents
• /
• v.6 no.3
• /
• pp.19-24
• /
• 2010

Task scheduling is an integrated component of computing with the emergence of grid computing. In this paper, we address two different task scheduling models, which are static Round-Robin (RR) and dynamic Fastest Site First (FSF) task scheduling method, using extended timed marked graphs, which is a special case of Stochastic Petri Nets (SPN). Stochastic reward nets (SRN) is an extension of SPN and provides compact modeling facilities for system analysis. We build hierarchical SRN models to compare two task scheduling methods. The upper level model simulates task scheduling and the lower level model implements task serving process for different sites with multiple servers. We compare these two models and analyze their performances by giving reward measures in SRN.

• Journal of Information Technology Applications and Management
• /
• v.13 no.2
• /
• pp.145-162
• /
• 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.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.2713-2718
• /
• 2003

Some of manufacturing tasks such as sawing task often requires continuous impulsive motion. In case of sawing task, such impulsive motions can be observed between the teeth of the saw and the object. The amount of the external impulse exerted on the object has been treated as an important control parameter. The purpose of this work is to introduce a new concept of an effective mass in sawing task and to suggest an external impulse model in sawing task. A normalized impulse ellipsoid reflecting the velocity direction is employed to visualize the impact geometry. Experiments are performed for soft and hard workpieces to justify the external impulse model in the sawing task. It is demonstrated through simulation and experiment that the proposed external impulse model is effective to characterize the impact property.

• ETRI Journal
• /
• v.36 no.5
• /
• pp.704-713
• /
• 2014

Most natural language processing tasks depend on the outputs of some other tasks. Thus, they involve other tasks as subtasks. The main problem of this type of pipelined model is that the optimality of the subtasks that are trained with their own data is not guaranteed in the final target task, since the subtasks are not optimized with respect to the target task. As a solution to this problem, this paper proposes a consolidation of subtasks for a target task ($CST^2$). In $CST^2$, all parameters of a target task and its subtasks are optimized to fulfill the objective of the target task. $CST^2$ finds such optimized parameters through a backpropagation algorithm. In experiments in which text chunking is a target task and part-of-speech tagging is its subtask, $CST^2$ outperforms a traditional pipelined text chunker. The experimental results prove the effectiveness of optimizing subtasks with respect to the target task.

• English Language & Literature Teaching
• /
• v.11 no.4
• /
• pp.365-389
• /
• 2005

The purpose of this study is to present the task model that is the most effective in English language methodology based on the investigation of task-based performance in Korean EFL classroom practice. The subjects were 538 high school students and 126 high school teachers, each of whom had common experiences using the materials of task-based activities for more than one year. To analyze the data, the program SPSS WIN 11.0 including frequency distribution and chi-square analysis was used. The results of the questionnaire analysis showed that both teachers and students had a comparatively high level of satisfaction in task rationale, but that they had some mixed responses in the fields of input data, settings, and activity types. To conclude, a few suggestions are made to provide some meaningful considerations for the EFL teachers and material developers: a) task goals and rationale that encourage the learner's positive motivation; b) authenticity of input data based on the real-world context; c) collaborative learning environment that enhances communicative interaction; d) proportional representation of the creative problem-solving activities related to discussions and decision-making processes; e) systematic introduction of integrated language skills. It also suggests that the multi-lateral task model, which has some positive assets compared to previous task models, be newly introduced and applied to the second language learning classrooms.

• Asia pacific journal of information systems
• /
• v.15 no.4
• /
• pp.61-87
• /
• 2005

This paper has two primary objectives: (1) to propose a comprehensive theoretical model that incorporates valuable insights from two complementary streams of research, and (2) to empirically test the model that explain the task-media fit and satisfaction of customer contact center users. The comprehensive model was tested using LISREL analysis on the sample of 232 users who have experience with the customer contact center. The model was supported in customer contact center context, accounting for 29% of the variance in the task-media fit, 53% of the variance in the perceived ease of use, 61% of the variance in the perceived usefulness, and 52% of the variance in the user satisfaction. The results showed that the task-media fit, the perceived ease of use, and the perceived usefulness play a significant role in influencing the user satisfaction of the customer contact center. In addition, task analyzability, media richness, media interactivity, and self-efficacy were found to influence the task-media fit. The paper concludes with discussions and implications for researchers and practitioners.