• Convergence Security Journal
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• v.15 no.7
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• pp.125-134
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• 2015

This study aims to investigate what to be prepared and implemented for the military integration when South and North Korea are making progress toward unification. Although we can not exactly predict when the unification will be completed at this time, preparations for the military integration should be ready ahead of time. Since the failure of the military integration can threat the unification, elaborated and practical solutions are required. Therefore, the study tries to answer the following questions : 1) What types of the military integration are desirable and what are the prerequisites for the unification of Korean Peninsular? ; 2) What potential military tasks could be caused by military integration? ; 3) What are the core and major tasks among them and how could they be solved in practical aspects?

• School Mathematics
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• v.18 no.3
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• pp.711-731
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• 2016

The purpose of this study is to investigate how pre-service secondary mathematics teachers modify mathematical tasks from a textbook and learning opportunities they have during the task modification. In the pursuit of this purpose, tasks was selected from derivative units in a textbook and five pre-service teachers was asked to modify the tasks. The findings from analysis are as follows. First, the cognitive demands of modified tasks were maintained or higher than those of the originals. Pre-service teachers' tendency toward conceptual understanding of derivative seems to make the result. Second, task modification provided a lot of learning opportunities for pre-service teachers. They tried to know intention of curriculum and textbook, realized the importance of predicting students' responses, and had opportunities for cooperation and reflective thinking.

• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2891-2902
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• 1997

This paper presents an analysis on the optimal partitioning configuration of cache (memory) for meeting deadlines of periodic and aperiodic real-time task set. Our goal is not only to decrease the deadline missing ratio of each task by minimizing the task utilization, but also to allocate another tasks to idle spaces of cache. For this reason, we suggest an algorithm so that tasks could be allocated to cache segments. Here, the set of cache segments allocated tasks is called a cache partitioning configuration. Based on how tasks allocate to cache segments, we can get various cache partitioning configurations. From these configurations, we obtain the boundary of task utilization that tasks are possible to schedule, and analyze the cache optimal partitioning configuration that can be executed to minimize the task utilization.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.2
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• pp.175-185
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• 2005

The scheduling methods of the distributed real-time systems have been proposed. However, they have some weak points. They did not schedule both sporadic and periodic tasks and messages at the same time or did not consider the end-to-end constraints such as precedence relations between sporadic tasks. This means that system scheduling must guarantee the constraints of practical systems and be applicable to them. This paper proposes a new scheduling method that can be applied to more practical model of distributed real-time systems. System model consists of sporadic and periodic tasks with precedence relations and sporadic and periodic messages and has end-to-end constraints. The proposed method is based on a binary search-based period assignment algorithm, an end-to-end laxity-based priority assignment algorithm, and three kinds of schedulability analysis, node, network, and end-to-end schedulability analysis. In addition, this paper describes the application model of sporadic tasks with precedence constraints in a distributed real-time system, shows that existing scheduling methods such as Rate Monotonic scheduling are not proper to be applied to the system having sporadic tasks with precedence constraints, and proposes an end-to-end laxity-based priority assignment algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.2
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• pp.55-61
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• 2011

We propose power-saving real-time scheduling method for mixed task sets which consist of both time-based periodic and event-based aperiodic tasks in the automotive operating system. In this system, we have to pursue maximization of power-saving using the slack time estimation and minimization of response time of aperiodic tasks simultaneously. However, since these two goals conflict each other, one has to make a compromise between them according to the given application domain. In this paper, we find the adjustment factor which gives better response time of aperiodic tasks with slight power consumption increase. The adjustment factor denotes the gravity of response time for aperiodic tasks. We apply the ccEDF scheduling for time-based periodic tasks and then calculate new utilization to be applied to the adjustment factor. In this paper, we suggest the lccEDF algorithm to make a tradeoff between the two goals by systematically adjusting the factor. Simulation results show that our approach is excellent for variety of task sets.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5269-5286
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• 2018

Task scheduling is one of the key issues in improving system performance and optimizing resource management in cloud computing environment. In order to provide appropriate services for heterogeneous users, we propose a novel task scheduling strategy with service differentiation, in which the delay sensitive tasks are assigned to the rapid cloud with high-speed processing, whereas the fault sensitive tasks are assigned to the reliable cloud with service restoration. Considering that a user can receive service from either local SaaS (Software as a Service) servers or public IaaS (Infrastructure as a Service) cloud, we establish a hybrid queueing network based system model. With the assumption of Poisson arriving process, we analyze the system model in steady state. Moreover, we derive the performance measures in terms of average response time of the delay sensitive tasks and utilization of VMs (Virtual Machines) in reliable cloud. We provide experimental results to validate the proposed strategy and the system model. Furthermore, we investigate the Nash equilibrium behavior and the social optimization behavior of the delay sensitive tasks. Finally, we carry out an improved intelligent searching algorithm to obtain the optimal arrival rate of total tasks and present a pricing policy for the delay sensitive tasks.

• Smart Structures and Systems
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• v.31 no.4
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• pp.383-392
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• 2023

Post-earthquake building condition assessment is crucial for subsequent rescue and remediation and can be automated by emerging computer vision and deep learning technologies. This study is based on an endeavour for the 2nd International Competition of Structural Health Monitoring (IC-SHM 2021). The task package includes five image segmentation objectives - defects (crack/spall/rebar exposure), structural component, and damage state. The structural component and damage state tasks are identified as the priority that can form actionable decisions. A multi-task Convolutional Neural Network (CNN) is proposed to conduct the two major tasks simultaneously. The rest 3 sub-tasks (spall/crack/rebar exposure) were incorporated as auxiliary tasks. By synchronously learning defect information (spall/crack/rebar exposure), the multi-task CNN model outperforms the counterpart single-task models in recognizing structural components and estimating damage states. Particularly, the pixel-level damage state estimation witnesses a mIoU (mean intersection over union) improvement from 0.5855 to 0.6374. For the defect detection tasks, rebar exposure is omitted due to the extremely biased sample distribution. The segmentations of crack and spall are automated by single-task U-Net but with extra efforts to resample the provided data. The segmentation of small objects (spall and crack) benefits from the resampling method, with a substantial IoU increment of nearly 10%.

• The Journal of Korean Physical Therapy
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• v.35 no.3
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• pp.64-70
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• 2023

Purpose: This study investigated the influence of attention-demanding tasks on gait and measured differences in the temporal, spatial and kinematic characteristics between young healthy adults and elderly healthy adults. Methods: We recruited 16 healthy young adults and 15 healthy elderly adults in this study. All participants performed two cognitive tasks: a subtraction dual-task (SDT) and working memory dual-task (WMDT) during gait plus one normal gait. Using the LEGSys+ system, knee and hip-joint kinematic data during stance and swing phase and spatiotemporal parameter data were assessed in this study. Results: In the elderly adult group, attention-demanding tasks with gait showed a significant decrease in hip-joint motion during the stance phase, compared to the normal gait. Step length, stride length and stride velocity of the elderly adult group were significantly decreased in WMDT gait compared to normal gait (p<0.05). In the young adult group, kinematic data did not show any significant difference. However, stride velocity and cadence during SDT and WMDT gaits were significantly decreased compared to those of normal gait (p<0.05). Conclusion: We determined that attention-demanding tasks during gait in elderly adults can induce decreased hip-joint motion during stance phase and decreased gait speed and stride length to maintain balance and prevent risk of falling. We believe that understanding the changes during gait in older ages, particularly during attention-demanding tasks, would be helpful for intervention strategies and improved risk assessment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.47-52
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• 2023

With the growing data size and the increased computing load in machine learning, energy-efficient resource planning in IoT systems is becoming increasingly important. In this paper, we suggest a new resource planning policy for real-time workloads that can be fluctuated over time in IoT systems. To handle such situations, we categorize real-time tasks into fixed tasks and variable tasks, and optimize the resource planning for various workload conditions. Based on this, we initiate the IoT system with the configuration for the fixed tasks, and when variable tasks are activated, we update the resource planning promptly for the situation. Simulation experiments show that the proposed policy saves the processor and memory energy significantly.

• Research in Mathematical Education
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• v.26 no.3
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• pp.167-202
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• 2023

A central problem of mathematics teaching worldwide is probably the insufficient adaptive handling of tasks-especially in computational practice phases and modeling tasks. All students in a classroom must often work on the same tasks. In the process, the high-achieving students are often underchallenged, and the low-achieving ones are overchallenged. This publication uses different modeling of the tennis serve as an example to show a possible solution to the problem and develops and discusses one adaptive task each for middle school, high school, and college using three mathematical models of the tennis serve each time. From model to model within the task, the complexity of the modeling increases, the mathematical or physical demands on the students increase, and the new modeling leads to more realistic results. The proposed models offer the possibility to address heterogeneous learning groups by their arrangement in the surface structure of the so-called parallel adaptive task and to stimulate adaptive mathematics teaching on the instructional topic of mathematical modeling. Models A through C are suitable for middle school instruction, models C through E for high school, and models E through G for college. The models are classified in the specific modeling cycle and its extension by a digital tool model, and individual modeling steps are explained. The advantages of the presented models regarding teaching and learning mathematical modeling are elaborated. In addition, we report our first teaching experiences with the developed parallel adaptive tasks.