• 천문학회지
• /
• 제52권4호
• /
• pp.121-131
• /
• 2019

I investigate the origin of arc degeneracies in satellite microlens parallax ${\pi}_E$ measurements with only late time data, e.g., t > $t_0+t_E$ as seen from the satellite. I show that these are due to partial overlap of a series of osculating, exactly circular, degeneracies in the ${\pi}_E$ plane, each from a single measurement. In events with somewhat earlier data, these long arcs break up into two arclets, or (with even earlier data) two points, because these earlier measurements give rise to intersecting rather than osculating circles. The two arclets (or points) then constitute one pair of degeneracies in the well-known four-fold degeneracy of space-based microlens parallax. Using this framework of intersecting circles, I show that next-generation microlens satellite experiments could yield good ${\pi}_E$ determinations with only about five measurements per event, i.e., about 30 observations per day to monitor 1500 events per year. This could plausibly be done with a small (hence cheap, in the spirit of Gould & Yee 2012) satellite telescope, e.g., 20 cm.

• 천문학회보
• /
• 제43권2호
• /
• pp.36.3-37
• /
• 2018

By utilizing large-scale graph analytic tools in the modern Big Data platform, Apache Spark, we investigate the topological structures of five different multiverses produced by cosmological n-body simulations with various cosmological initial conditions: (1) one standard universe, (2) two different dark energy states, and (3) two different dark matter densities. For the Big Data calculations, we use a custom build of stand-alone Spark cluster at KIAS and Dataproc Compute Engine in Google Cloud Platform with the sample sizes ranging from 7 millions to 200 millions. Among many graph statistics, we find that three simple graph measurements, denoted by (1) $n_\k$, (2) $\tau_\Delta$, and (3) $n_{S\ge5}$, can efficiently discern different topology in discrete point distributions. We denote this set of three graph diagnostics by kT5+. These kT5+ statistics provide a quick look of various orders of n-points correlation functions in a computationally cheap way: (1) $n = 2$ by $n_k$, (2) $n = 3$ by $\tau_\Delta$, and (3) $n \ge 5$ by $n_{S\ge5}$.

• 한국경영과학회지
• /
• 제39권2호
• /
• pp.1-19
• /
• 2014

Recently, one of the core keywords in information technology (IT) as well as areas such as business management is big data. Big data is a term that includes technology, personnel, and organization required to gather/manage/analyze collection of data sets so large and complex that it becomes difficult to manage and analyze using traditional tools. The military has been accumulating data for a long period due to the organization's characteristic in placing emphasis on reporting and records. Considering such characteristic of the military, this study verifies the possibility of improving the performance of the military organization through use of big data and furthermore, create scientific development of operation, strategy, and support environment. For this purpose, the study organizes general status and case studies related to big data, traces back examples of data utilization by Korean's national defense sector through US military data collection and case studies, and proposes the possibility of using and applying big data in the national defense sector.

• Smart Structures and Systems
• /
• 제22권2호
• /
• pp.175-183
• /
• 2018

Time-series data often contain one of the most valuable pieces of information in many fields including manufacturing. Because time-series data are relatively cheap to acquire, they (e.g., vibration signals) have become a crucial part of big data even in manufacturing shop floors. Recently, deep-learning models have shown state-of-art performance for analyzing big data because of their sophisticated structures and considerable computational power. Traditional models for a machinery-monitoring system have highly relied on features selected by human experts. In addition, the representational power of such models fails as the data distribution becomes complicated. On the other hand, deep-learning models automatically select highly abstracted features during the optimization process, and their representational power is better than that of traditional neural network models. However, the applicability of deep-learning models to the field of prognostics and health management (PHM) has not been well investigated yet. This study integrates the "residual fitting" mechanism inherently embedded in the wavelet transform into the convolutional neural network deep-learning structure. As a result, the architecture combines a signal smoother and classification procedures into a single model. Validation results from rotor vibration data demonstrate that our model outperforms all other off-the-shelf feature-based models.

• Maxillofacial Plastic and Reconstructive Surgery
• /
• 제36권6호
• /
• pp.239-246
• /
• 2014

Many kinds of membrane have been used for the guided bone regeneration (GBR) technique. However, most membranes do not fulfill all requirements for the ideal membrane for the GBR technique. Among them, collagen membrane has been most widely used. However, its high price and weak tensile strength in wet condition are limitations for wide clinical application. Synthetic polymers have also been used for the GBR technique. Recently, silk based membrane has been considered as a membrane for the GBR technique. Despite many promising preclinical data for use of a silk membrane, clinical data regarding the silk membrane has been limited. However, silk based material has been used clinically as vessel-tie material and an electrospun silk membrane was applied successfully to patients. No adverse effect related to the silk suture has been reported. Considering that silk membrane can be provided to patients at a cheap price, its clinical application should be encouraged.

• 대한의용생체공학회:학술대회논문집
• /
• 대한의용생체공학회 1993년도 추계학술대회
• /
• pp.44-47
• /
• 1993

In this paper, the wall follwing method of a motorized wheelchair is discussed. The wall fellowing problem is characterized by maintaining a constant distance to the wall, which should be possible using a distance measuring sensor only. Ultrasonic sensors are cheap are fairly simple to use in this case. The main problem is the calculation of the distance and orientation of the wheelchair with respect the wall from the sensor data. This is solved by the method that sensor data is obtained from 3 ultrasonic sensors arranged at a same perpendicular pivot. The results show that a new method is very effiecient for a motorized wheelchair.

• 한국가시화정보학회지
• /
• 제19권1호
• /
• pp.57-61
• /
• 2021

In order to determine erythrocyte sedimentation rate (ESR) indicating acute phase inflammation, a Westergren method has been widely used because it is cheap and easy to be implemented. However, the Westergren method requires quite a long time for 1 hour. In this study, a gated recurrent unit (GRU) neural network was used to reduce measurement time of ESR evaluation. The sedimentation sequences of the erythrocytes were acquired by the camera and data processed through image processing were used as an input data into the neural network models. The performance of a proposed models was evaluated based on mean absolute error. The results show that GRU model provides best accurate prediction than others within 30 minutes.

• Asian-Australasian Journal of Animal Sciences
• /
• 제26권7호
• /
• pp.1030-1037
• /
• 2013

Early detection of anomalies is an important issue in the management of group-housed livestock. In particular, failure to detect oestrus in a timely and accurate way can become a limiting factor in achieving efficient reproductive performance. Although a rich variety of methods has been introduced for the detection of oestrus, a more accurate and practical method is still required. In this paper, we propose an efficient data mining solution for the detection of oestrus, using the sound data of Korean native cows (Bos taurus coreanea). In this method, we extracted the mel frequency cepstrum coefficients from sound data with a feature dimension reduction, and use the support vector data description as an early anomaly detector. Our experimental results show that this method can be used to detect oestrus both economically (even a cheap microphone) and accurately (over 94% accuracy), either as a standalone solution or to complement known methods.

• 한국식품조리과학회지
• /
• 제19권3호
• /
• pp.308-317
• /
• 2003

The purpose of this study was to identify combinations of factors, with regard to the use of restaurants by tourists, and to establish the relative importance of these factors in terms of their contribution to the total usage. Of 250 questionnaires, 209 were utilized for analysis in this study. Crosstabs, conjoint analysis, paired-samples t-test, k-means cluster analysis, one-way ANOVA analysis, and the Friedman test were used for the statistical analysis. The findings from this study were as follows: First, the Pearson's R and Kendall's tau statistics show that the model fits the data well. Second, it was found that 209 tourists most preferred restaurants that provided excellent quality traditional food, with a high quality of service, at a cheap price for the suburb. The 81 tourists of the first cluster most preferred restaurant that provided excellent quality fusion food, at a cheap price for the suburb. The 65 tourists of tile second cluster most preferred restaurant that provided average quality national food, at an expensive price for the suburb. The 63 tourists of the third cluster most preferred restaurant that provided excellent quality traditional food, at a reasonable price for the suburb. Third, it wis found that all tourists and the three clusters groups regarded both the type of food and its price to be very important factors. Finally, the results used in this study have provided some insight into the types of marketing strategies and tourism policies that may be successfully used by the operators and policymakers managing a location, the quality, price and type of food, and quality of service required by tourists dining at restaurants.

• 한국전자거래학회:학술대회논문집
• /
• 한국전자거래학회 2001년도 International Conference CALS/EC KOREA
• /
• pp.591-596
• /
• 2001

To deliver new products to market in a due time, companies often develop their products with numerous partners distributed around the world. Internet technologies can provide a cheap and efficient basis of collaborative product development among distributed partners. This paper provides a framework and its product database model that can support consistent product data during collaborative product development. This framework consists of four components for representing consistent product structure: the product configuration, assembly structure, multiple representations and engineering changes. A product database model realizing the framework is designed and implemented as a system that supports collaborative works in the areas of product design and technical publication. The system enables participating designers and technical publishers to complete their tasks with shared and consistent product data. It also manages the propagation of engineering changes among different representations for individual participants. The Web technologies introduced in this system enable participants to easily access and operate shared product data in a standardized and distributed computing environment.