• Journal of Family Resource Management and Policy Review
• /
• v.5 no.2
• /
• pp.29-44
• /
• 2001

The purpose of this study was to analyze the relationship between urban housewive's the pattern leisure activities and leisure satisfaction by the level of informationization, leisure resoureces. A total of 287 questionnaires were used as for the final data analysis. The results could be summarized as follows: First, there were significant difference in the pattern of leisure activities according to socio- demographic and economic variables(age, eduactional attaintment, the age of lastbone child). Second, The leisure resource variables influence them. The higher leisure needs, leisure time, leisure cost is the higher degree participated in the pattern of leisure activities. Third, the higher the level of informationalization, the higher time-oriented pattern. And leisure time, leisure needs, natural-oriented pattern had an effect on leisure satisfaction.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.4 no.6
• /
• pp.616-623
• /
• 1999

Elevator velocity pattern is basL'C! on combining the time-based velocity pattern according to which the car m trip from starting position to vicinity of target position, and distance-based velocity pattern for precise landing ( of car. To obtain the lide comfortability, the impact caused by velocity pattern switching should be minimizLD b by removing the discontinuity of velocity and acceleration. In this paper, new velocity pattern generation m method which ensure the continuity of velocity and acceleration during pattern switching is proposed. P ProPOSLD velocity pattern also shorten the landing time to the target position.

• Proceedings of the Korean Institute of Interior Design Conference
• /
• 2005.10a
• /
• pp.143-146
• /
• 2005

Human activity pattern has been changed as the contemporary urban society changes. Diverse activities repeat regular patterns as time passes. Diagram is a simple drawing which aims to organize and unify various information. The elements of the social behaviour could be spatialized by means of diagram applications. By using diagrams, architects understand contemporary urban society and form new space conditions. Time-based activity patterns consists of activity pattern in a restricted space and in urban structure for space use. Activity patterns for different time zones are explained by two types of diagrams, space occupation and flexibility of space, By the characteristic of space system structred by these diagrams, activities and programs are rearranged and variety of space is allowed through flexibility. Also, programs are mixed to apply to simultaneous occurrence of ever-changing human activities.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2253-2261
• /
• 1999

ACK generates optimized code using the string pattern matching technique in pattern table generator and peephole optimizer. But string pattern matching method is not effective due to the many comparative actions in pattern selection. We designed and implemented the EM intermediate code optimizer using tree pattern matching algorithm composed of EM tree generator, optimization pattern table generator and tree pattern matcher. Tree pattern matching algorithm practices the pattern matching that centering around root node with refer to the pattern table, with traversing the EM tree by top-down method. As a result, compare to ACK string pattern matching methods, we found that the optimized code effected to pattern selection time, and contributed to improved the pattern selection time by about 10.8%.

• Molecules and Cells
• /
• v.26 no.4
• /
• pp.338-343
• /
• 2008

An embryonic stem cell is a powerful tool for investigation of early development in vitro. The study of embryonic stem cell mediated neuronal differentiation allows for improved understanding of the mechanisms involved in embryonic neuronal development. We investigated expression profile changes using time course cDNA microarray to identify clues for the signaling network of neuronal differentiation. For the short time course microarray data, pattern analysis based on the quadratic regression method is an effective approach for identification and classification of a variety of expressed genes that have biological relevance. We studied the expression patterns, at each of 5 stages, after neuronal induction at the mRNA level of embryonic stem cells using the quadratic regression method for pattern analysis. As a result, a total of 316 genes (3.1%) including 166 (1.7%) informative genes in 8 possible expression patterns were identified by pattern analysis. Among the selected genes associated with neurological system, all three genes showing linearly increasing pattern over time, and one gene showing decreasing pattern over time, were verified by RT-PCR. Therefore, an increase in gene expression over time, in a linear pattern, may be associated with embryonic development. The genes: Tcfap2c, Ttr, Wnt3a, Btg2 and Foxk1 detected by pattern analysis, and verified by RT-PCR simultaneously, may be candidate markers associated with the development of the nervous system. Our study shows that pattern analysis, using the quadratic regression method, is very useful for investigation of time course cDNA microarray data. The pattern analysis used in this study has biological significance for the study of embryonic stem cells.

• ETRI Journal
• /
• v.43 no.3
• /
• pp.483-510
• /
• 2021

In computational biology, desired patterns are searched in large text databases, and an exact match is preferable. Classical benchmark algorithms obtain competent solutions for pattern matching in O (N) time, whereas quantum algorithm design is based on Grover's method, which completes the search in $O(\sqrt{N})$ time. This paper briefly explains existing quantum algorithms and defines their processing limitations. Our initial work overcomes existing algorithmic constraints by proposing the quantum-based combined exact (QBCE) algorithm for the pattern-matching problem to process exact patterns. Next, quantum random access memory (QRAM) processing is discussed, and based on it, we propose the QRAM processing-based exact (QPBE) pattern-matching algorithm. We show that to find all t occurrences of a pattern, the best case time complexities of the QBCE and QPBE algorithms are $O(\sqrt{t})$ and $O(\sqrt{N})$, and the exceptional worst case is bounded by O (t) and O (N). Thus, the proposed quantum algorithms achieve computational speedup. Our work is proved mathematically and validated with simulation, and complexity analysis demonstrates that our quantum algorithms are better than existing pattern-matching methods.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.3
• /
• pp.86-97
• /
• 2021

As mechatronic systems have various, complex functions and require high performance, automatic fault detection is necessary for secure operation in manufacturing processes. For conducting automatic and real-time fault detection in modern mechatronic systems, multiple sensor signals are collected by internet of things technologies. Since traditional statistical control charts or machine learning approaches show significant results with unified and solid density models under normal operating states but they have limitations with scattered signal models under normal states, many pattern extraction and matching approaches have been paid attention. Signal discretization-based pattern extraction methods are one of popular signal analyses, which reduce the size of the given datasets as much as possible as well as highlight significant and inherent signal behaviors. Since general pattern extraction methods are usually conducted with a fixed size of time segmentation, they can easily cut off significant behaviors, and consequently the performance of the extracted fault patterns will be reduced. In this regard, adjustable time segmentation is proposed to extract much meaningful fault patterns in multiple sensor signals. By considering inflection points of signals, we determine the optimal cut-points of time segments in each sensor signal. In addition, to clarify the inflection points, we apply Savitzky-golay filter to the original datasets. To validate and verify the performance of the proposed segmentation, the dataset collected from an aircraft engine (provided by NASA prognostics center) is used to fault pattern extraction. As a result, the proposed adjustable time segmentation shows better performance in fault pattern extraction.

• Archives of Orthopedic and Sports Physical Therapy
• /
• v.14 no.2
• /
• pp.55-64
• /
• 2018

Purpose : The purpose of this study was to investigate the effect of the sprinter and skater combined patterns on muscle contraction onset time and muscle activation of body stabilizing muscles. Method : Our study included young and healthy men in their 20s. The participants used the sprinter and skater combined patterns of the proprioceptive neuromuscular facilitation (PNF) methods to measure muscle activation and muscle contraction onset time of the trunk muscles. To measure muscle contraction onset time and muscle activation, electrodes were attached to the rectus abdominis (RA), external oblique (EO), internal oblique (IO), and erector spinalis (ES) regions. Significant differences were identified using a paired t-test and a one-way analysis of variance (ANOVA) analysis. Result : In the sprinter combined pattern, the muscle with the fastest onset time of contraction was the RES, and that with the slowest was the RRA (p<.001). In the skater combined pattern, the muscle with the fastest onset time of contraction was the LES, and that with the slowest was the LRA (p<.001). In the sprinter combined pattern, the REO and LIO presented medium muscle contraction onset times (p<.001). In the skater combined pattern, the LEO and RIO presented medium muscle contraction onset times (p<.001). Conclusions: Based on these results, these patterns could be used as exercise methods for the elderly with delayed proactive response speeds of the body stabilization methods due to imbalances in body stabilizing muscles or limbs movement.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.58 no.7
• /
• pp.1424-1434
• /
• 2009

DNA computing-inspired pattern classification based on the hypernetwork model is a novel approach to pattern classification problems. The hypernetwork model has been shown to be a powerful tool for multi-class data analysis. However, the ordinary hypernetwork model has limitations, such as operating sequentially only. In this paper, we propose a efficient implementing method of DNA computing-inspired pattern classifier using GPU. We show simulation results of multi-class pattern classification from hand-written digit data, DNA microarray data and 8 category scene data for performance evaluation. and we also compare of operation time of the proposed DNA computing-inspired pattern classifier on each operating environments such as CPU and GPU. Experiment results show competitive diagnosis results over other conventional machine learning algorithms. We could confirm the proposed DNA computing-inspired pattern classifier, designed on GPU using CUDA platform, which is suitable for multi-class data classification. And its operating speed is fast enough to comply point-of-care diagnostic purpose and real-time scene categorization and hand-written digit data classification.

• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.557-561
• /
• 2011

The study proposes three types of production lead time according to the production or demand pattern. First of all, it discusses the difference of three lead times. While pitch time and cycle time are used in push system with process stock and mass conveyor production, the tact time is used in pull system like as JIT based lean production system.