• Journal of Korea Multimedia Society
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• v.10 no.12
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• pp.1741-1751
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• 2007

The imprecise computation technique ensures that all time-critical tasks produce their results before their deadlines by trading off the quality of the results for the computation time requirements of the tasks. In the imprecise computation, most scheduling problems of satisfying both 0/1 constraints and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. In the previous studies, the reasonable strategies of scheduling tasks with the 0/1 constraints on uniprocessors and multiprocessors for minimizing the total error are proposed. But, these algorithms are all off-line algorithms. Then, in the on-line scheduling, NORA(No Off-line tasks and on-line tasks Ready upon Arrival) algorithm can find a schedule with the minimum total error. In NORA algorithm, EDF(Earliest Deadline First) strategy is adopted in the scheduling of optional tasks. On the other hand, for the task system with 0/1 constraints, NORA algorithm may not suitable any more for minimizing total error of the imprecise tasks. Therefore, in this paper, an on-line algorithm is proposed to minimize total error for the imprecise real-time task system with 0/1 constraints. This algorithm is suitable for the imprecise on-line system with 0/1 constraints. Next, to evaluate performance of this algorithm, a series of experiments are done. As a consequence of the performance comparison, it has been concluded that IOSMTE(Imprecise On-line Scheduling to Minimize Total Error) algorithm proposed in this paper outperforms LOF(Longest Optional First) strategy and SOF(Shortest Optional First) strategy for the most cases.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.10
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• pp.493-501
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• 2007

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et at suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, the NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In NORA algorithm, EDF strategy is adopted in the optional scheduling. On the other hand, for the task system with 0/1 constraint, EDF_Scheduling may not be optimal in the sense that the total error is minimized. Furthermore, when the optional tasks are scheduled in the ascending order of their required processing times, NORA algorithm which EDF strategy is adopted may not produce minimum total error. Therefore, in this paper, an online algorithm is proposed to minimize total error for the imprecise task system with 0/1 constraint. Then, to compare the performance between the proposed algorithm and NORA algorithm, a series of experiments are performed. As a conseqence of the performance comparison between two algorithms, it has been concluded that the proposed algorithm can produce similar total error to NORA algorithm when the optional tasks are scheduled in the random order of their required processing times but, the proposed algorithm can produce less total error than NORA algorithm especially when the optional tasks are scheduled in the ascending order of their required processing times.

• Communications for Statistical Applications and Methods
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• v.31 no.5
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• pp.487-496
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• 2024

In this paper, we propose a data-driven procedure to segment a binary sequence as an alternative to the popular hidden Markov model (HMM) based procedure. Unlike the HMM, our procedure does not make any distributional or model assumption to the data. To segment the sequence, we suggest to minimize the least square distance from the observations under total variation regularization to the solution, and develop a polynomial time algorithm for it. Finally, we illustrate the algorithm using a toy example and apply it to the Gemini boat race data between Oxford and Cambridge University. Further, we numerically compare the performance of our procedure to the HMM based segmentation through these examples.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.15-20
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• 2021

The imprecise real-time scheduling can be used for minimizing the bad effects of timing faults by leaving less important tasks unfinished if necessary when a transient overload occured. In the imprecise scheduling, every time-critical task can be logically decomposed into two tasks : a mandatory task and an optional task. Recently, some studies in this field showed good schedulability performance and minimum total error by deferring the optional tasks. But the schedulability performance of the studies can be shown only when the execution time of each optional task was less than or equal to the execution time of its corresponding mandatory task. Therefore, in this paper, a new deferring strategy is proposed under the reverse execution time restriction to the previous studies. Nevertheless, the strategy produces comparable or superior schedulability performance to the previous studies and can minimize the total error also.

• Journal of the Korea Computer Industry Society
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• v.7 no.4
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• pp.309-320
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• 2006

The imprecise real-time system provides flexibility in scheduling time-critical tasks. Most scheduling problems of satisfying both 0/1 constraint and timing constraints, while the total error is minimized, are NP-complete when the optional tasks have arbitrary processing times. Liu suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on uniprocessors for minimizing the total error. Song et al suggested a reasonable strategy of scheduling tasks with the 0/1 constraint on multiprocessors for minimizing the total error. But, these algorithms are all off-line algorithms. In the online scheduling, NORA algorithm can find a schedule with the minimum total error for the imprecise online task system. In the NORA algorithm, the EDF strategy is adopted in the optional scheduling.<중략> The algorithm, proposed in this paper, can be applied to some applications efficiently such as radar tracking, image processing, missile control and so on.

• International Journal of Contents
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• v.13 no.4
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• pp.23-28
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• 2017

Of the total economic loss caused by disasters, 40% are due to floods and floods have a severe impact on human health and life. So, it is important to monitor the water level of a river and to issue a flood warning during unfavorable circumstances. In this paper, we propose a modified error function to improve a hydrological modeling using a multi-layer perceptron (MLP) neural network. When MLP's are trained to minimize the conventional mean-squared error function, the prediction performance is poor because MLP's are highly tunned to training data. Our goal is achieved by preventing overspecialization to training data, which is the main reason for performance degradation for rare or test data. Based on the modified error function, an MLP is trained to predict the water level with rainfall data at upper reaches. Through simulations to predict the water level of Nakdong River near a UNESCO World Heritage Site "Hahoe Village," we verified that the prediction performance of MLP with the modified error function is superior to that with the conventional mean-squared error function, especially maximum error of 40.85cm vs. 55.51cm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1032-1041
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• 1999

This paper proposes on-line scheduling algorithms that reduce the largest weighted error incurred by preemptive imprecise tasks running on a single processor system. The first one is a two-level algorithm. The top-level scheduling, which is executed whenever a new task arrives, determines the processing times to be allotted to tasks in such a way to minimize maximum weighted error as well as to minimize total error. The lower-level algorithm actually allocates the processor to the tasks. The second algorithm extends the on-line algorithm studied by Shih and Liu[4] by formalizing the top-level algorithm mathematically. The numerical simulation shows that the proposed algorithm outperforms the previous works in the sense that it greatly reduces the largest weighted error.

• Journal of KSNVE
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• v.7 no.6
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• pp.919-929
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• 1997

Induction motors are used in many areas to transform electrical energy to mechanical energy. In the design of an induction motor, not only energy efficiency but also noise becomes an important factor. To effectively address the noise problem, it will be convenient if one can see where and how noise is generated and propagated. In this study sound radiation by an induction motor is visualized using cylindrical acoustic holography. To minimize the bias error by window effect Minimum Error Window(MEW) is used. Its performance is verified by numerical simulations. Based on these theoretical understanding, sound pressure measurement with an induction motor are performed. Not only sound radiation are visualized but sound pressure level and sound power level are also estimated. Results show that the main source is located at nearly bottom part of the motor and the total sound pressure level is 49dB, which satisfies the guideline value suggested by the KS C 4202.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.929-936
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• 2009

In this paper, we consider designing a multi-input multi-output (MIMO) overlay system for fixed MIMO wireless link, where a frequency flat narrowband channel is shared by multiple transmitter and receiver pairs. Assuming the perfect knowledge of the second-order statistics of the received legacy signals and the composite channels from the overlay transmitter to the legacy receivers, the jointly optimal linear precoder and decoder matrices of the MIMO overlay system is derived to minimize the total mean squared error (MSE) of the data symbol vector, subject to total average transmission power and zero interference induced to legacy MIMO systems already existing in the frequency band of interest. Furthermore, the necessary and sufficient condition for the existence of the optimal solution is also derived.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1438-1441
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• 2005

To establish of standard technique of nano-length measurement in 2D plane, new AFM system has been designed. In this system, measurement uncertainty is dominantly affected by the Abbe error of XY scanning stage. No linear stage is perfectly straight; in other words, every scanning stage is subject to tilting, pitch and yaw motion. In this paper, an AFM system with minimum offset of XY sensing is designed. And XY scanning stage is designed to minimize rotation angle because Abbe errors occur through the multiply of offset and rotation angle. To minimize the rotation angle optimal design has performed by maximizing the stiffness ratio of motion direction to the parasitic motion direction of each stage. This paper describes the design scheme of full AFM system, especially about XY stage. Full range of fabricated XY scanner is $100um\times{100um}$. And tilting, pitch and yaw motion are measured by autocollimator to evaluate the performance of XY stage. Using this AFM system, 3um pitch specimen was measured. As a result, the uncertainty of total system has been evaluated.