• Physical Therapy Korea
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• v.12 no.3
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• pp.67-73
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• 2005

Prospective memory (PM) is related to remember to carry out a previously intented behaviour. The purpose of this study was to develop a paradigm for measuring PM function to diagnosis in mild cognitive impairment 1 or brain injury in patients 2. among brain injured patients Thirty-eight normal healthy subjects participated in current study. The paradigm was composed of four conditions: a baseline and three intention conditions (expectation, execution 1 and 2). In the expectation condition, subjects were asked to make a new response to intented stimuli during ongoing task, but the intented stimuli never occurred. In the execution 1 (one type of expected stimulus) and 2 (two types of expected stimuli), the intended stimuli did occur in 20% of trials. The reaction time and error rate were calculated in each condition. Repeated measures using ANOVA of subject's mean reaction times (RTs) and mean error rates (ERs) showed main effects of conditions during ongoing task. The comparison of PM tasks in executive condition 1 and 2 also showed significance in RTs and ERs. This paradigm reflects sufficiently the performance of prospective memory function during ongoing task in normal individuals. Thus, we suggest that the paradigm will be helpful to study neural network of PM function using brain imaging techniques and diagnosis of PM dysfunction.

• Journal of Korea Multimedia Society
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• v.14 no.7
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• pp.940-948
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• 2011

In this paper, we design and implement a task scheduler that considers real-time and fault tolerance in embedded system with a single processor. We propose a method how it can meet the deadlines of periodic tasks using RMS and complete the execution of aperiodic tasks by calculating surplus times from a periodic task set. And we describe a method how to recover of a transient fault task by managing backup time. We propose an important level of periodic tasks that can control the response time of periodic and aperiodic tasks. Finally, we analyse and evaluate the proposed methods by simulation.

• The Transactions of the Korea Information Processing Society
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• v.7 no.4
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• pp.1201-1210
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• 2000

In order to tolerate faults which may occur during the execution of distributed tasks in high-performance parallel computer systems, tasks are duplicated on different processors. In this paper, by utilizing the task duplication based scheduling algorithm, a new task scheduling algorithm which duplicates each task on more than two different processors with the minimum schedule length is presented, and the number of processors required for the duplication is analyzed with the ratio of communication cost to computation time and the workload of the system. A simulation with various task graphs reveals that the number of processors required for the full-duplex fault-tolerant task scheduling with the obtainable minimum schedule length increases about 30% to 75% when compared with that of the task duplication based scheduling algorithm.

• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.17-27
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• 2022

In this paper, ED-H algorithm, an optimal real-time scheduling algorithm dealing with the characteristics of the integrated energy harvester system with a capacitor, is extended to satisfy the time constraint under the blackout state which is a deliberate power-off state by an intelligent power management unit adopted in the system. If the power supply system does not have enough energy, it temporarily shuts off the power supply to protect the circuit and capacitor and resumes the supply again when the capacitor is fully charged, which may delay the task execution during these blackout states by calculating the time according to the occurrence of the events. To mitigate the problem, even if task execution is delayed by the original ED-H algorithm, the remaining time of the subsequent time units no longer can afford to delay the execution of the task is predicted in the extended algorithm and the task is forced to be scheduled to meet the time deadline. According to the simulation results, it is confirmed that the algorithm proposed in this paper has a high scheduling performance increase of 0.4% to 7.7% depending on the characteristics of the set of tasks compared to the ED-H.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3523-3543
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• 2022

Autonomous vehicles are gradually being regarded as the mainstream trend of future development of the automobile industry. Autonomous driving networks generate many intensive and delay-sensitive computing tasks. The storage space, computing power, and battery capacity of autonomous vehicle terminals cannot meet the resource requirements of the tasks. In this paper, we focus on the task scheduling problem of autonomous driving in software-defined edge networks. By analyzing the intensive and delay-sensitive computing tasks of autonomous vehicles, we propose an emotion model that is related to task urgency and changes with execution time and propose an optimal base station (BS) task scheduling (OBSTS) algorithm. Task sentiment is an important factor that changes with the length of time that computing tasks with different urgency levels remain in the queue. The algorithm uses task sentiment as a performance indicator to measure task scheduling. Experimental results show that the OBSTS algorithm can more effectively meet the intensive and delay-sensitive requirements of vehicle terminals for network resources and improve user service experience.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.2
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• pp.160-168
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• 2000

In this paper, we present a performance monitor to trace and evaluate the performance of programs running on networked computers. The performance monitor of the JaNeC is online/batch as well as event/time driven. Since it is implemented with the Java programming language, it provides us with high portability among heterogeneous computer systems, and friendly graphical user interface. This performance monitor consists of various views such as 'Task/Event Filter' and 'TimeLine', 'Task View', 'Task Hoistory', 'Message Passing View', 'Host Cpu View', which allow the user to easily analyze event and time during the program execution.

• Journal of the Ergonomics Society of Korea
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• v.36 no.5
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• pp.437-446
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• 2017

Objective: This study aims to draw an efficient UI design by comparing the usability of App drawer and single-layered home screens, which are smartphone home screens. Background: Because smartphone home screen is frequently used including the installation, deletion, and editing of APPs, it should be designed with easily controllable information structure. There is a need to seek a user-friendly UI by comparing the usability of App drawer and single-layered home screens, of which methods to search Apps are different. There is also a need to examine an efficient UI and the factors to improve from the user perspective. Method: This study targeted 30 Android OS and iOS users to evaluate the App drawer and single-layered home screens, of which UI structures are different. Each participant was instructed to carry out an App searching task and App deleting task, and the execution time and the number of errors were measured. After the tasks were completed, they evaluated satisfaction through a questionnaire survey. Results: In the App searching task with low task level, there was no difference in execution level between the App drawer and single-layered home screens. However, the single-layered home screen showed higher efficiency and accuracy in the App deleting task with high task level. As for the group difference according to use experience, there was no difference in satisfaction among Android OS users, but iOS user satisfaction with single-layered home screen with which they were familiar was higher. Conclusion: As for home screen usability, the single-layered home screen UI structure can be advantageous, as task level is higher. Repulsion was higher, when users, who had used easier UI, used complex UI in comparison with user satisfaction, when users familiar with complex UI used easier UI. A UI indicating the current status with clear label marking through a task flow chart-based analysis, and a UI in which a user can immediately recognize by exposing hidden functions to the first depth were revealed as things to improve. Application: The results of this study are expected to be used as reference data in designing smartphone home screens. Especially, when iOS users use Android OS, the results are presumed to contribute to the reduction of predicted barriers.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.148-154
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• 2012

For a successful checkpointing strategy, we should place checkpoints so as to optimize fault-tolerance capability of real-time systems. This paper presents a novel scheme of checkpoint placement for real-time systems with periodic multi-tasks. Under the influence of transient faults, multi-tasks are scheduled by the Rate Monotonic (RM) algorithm. The optimal checkpoint intervals are derived to maximize the probability of task completion. In particular, this paper is concerned about the general case that the deadline of a task is longer than the period. Compared with the special condition that the deadline is equal to or less than the period, this general case causes a more complicate test procedure for schedulability of the RM algorithm with respect to a given set of checkpoint re-execution vectors. The probability of task completion is also derived in a more complex form. A case study is given to show the applicability of the proposed scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1265-1278
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• 2017

Dynamic task scheduling is one of the most popular research topics in the cloud computing field. The cloud scheduler dynamically provides VM resources to variable cloud tasks with different scheduling strategies in cloud computing. In this study, we utilized a valid model to describe the dynamic changes of both computing facilities (such as hardware updating) and request task queuing. We built a novel approach called Policy Iteration Scheduling (PIS) to globally optimize the independent task scheduling scheme and minimize the total execution time of priority tasks. We performed experiments with randomly generated cloud task sets and varied the performance of VM resources using Poisson distributions. The results show that PIS outperforms other popular schedulers in a typical cloud computing environment.

• Journal of information and communication convergence engineering
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• v.18 no.4
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• pp.222-229
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• 2020

Recent multi-core processors for smart devices use per-core dynamic voltage and frequency scaling (DVFS) that enables independent voltage and frequency control of cores. However, because the conventional task scheduler was originally designed for per-core DVFS disabled processors, it cannot effectively utilize the per-core DVFS and simply allocates tasks evenly across all cores to core utilization with the same CPU frequency. Hence, we propose a novel task scheduler to effectively utilize percore DVFS, which enables each core to have the appropriate frequency, thereby improving performance and decreasing energy consumption. The proposed scheduler classifies applications into two types, based on performance-sensitivity and allows a performance-sensitive application to have a dedicated core, which maximizes core utilization. The experimental evaluations with a real off-the-shelf smart device showed that the proposed task scheduler reduced 13.6% of CPU energy (up to 28.3%) and 3.4% of execution time (up to 24.5%) on average, as compared to the conventional task scheduler.