• Journal of the Korean Society for Railway
• /
• v.12 no.6
• /
• pp.989-995
• /
• 2009

Short-time Fourier transforms (STFT) are useful for analyzing signals with harmonics that vary with time. If the variation of the harmonics with time is smooth, such as in kinematic vibrations in vehicles, then it is possible to improve the STFT using order spectra and correlation analysis. In this paper, it is shown how correlation analysis can be performed when the speed signal is noisy or unknown and then it is shown how order spectra become simple to compute after this analysis. The results are illustrated by an analysis of axle and car body vibrations in the prototype high-speed train, HSR-350x.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.13 no.8
• /
• pp.1679-1686
• /
• 2009

Odor sensing system that is electronic nose device and its signal processing technique has potential to become a critical service for the people who require tangibility of sense of smell in the multimedia communication. PCA(Principal Component Analysis) have been used for dimensionality reduction and visualization of multivariate measurement data. PCA is good for estimating importance value by variance of data but, have some limitation for getting meaningful representation from odor sensing system. This paper explain about how to analyze the data of odor sensing system by ICA(Independent Component Analysis). We show that ICA can give better result like sensor drift analysis, dimensionality reduction and data representation by improved discrimination.

• Proceedings of the Korean Information Science Society Conference
• /
• 2005.11b
• /
• pp.154-156
• /
• 2005

인터넷의 발전은 다양한 데이터의 폭발적인 증가를 가져왔다. 유연하고 효과적인 데이터 표현 능력을 지닌 XML이 인터넷 환경에서 데이터 표현 및 교환 수단으로 여러 분야에서 표준으로 활용되고 있다. 그래서 대용량 XML 문서의 저장 및 관리에 대한 연구의 필요성이 증가하였다. 현재 다양한 XML 저장 기법과 XQuery를 이용한 XML 질의 처리에 대한 연구가 활발히 진행되고 있다. 본 논문에서는 객체 관계 데이터베이스 시스템을 이용하여 대용량 XML 문서 처리에 적합하도록 XML 저장 시스템을 설계 및 구현하였다. 또한 하이브리드 오더 인코딩 기법을 이용하여 저장된 XML 문서의 갱신 성능과 XML 질의 처리 성능을 개선하였다. 그리고 XBench를 이용하여 생성한 대용량 XML 문서로 XML 저장 시스템의 성능을 평가하고 분석하였다.

• The Journal of Bigdata
• /
• v.2 no.2
• /
• pp.33-46
• /
• 2017

Service part has the attribute causing a difficulty of the systematic management like a kind of diversity, uncertainty of demand, high request for quick response against general complete product. Especially, order picking is recognized as the most important work in the warehouse of the parts since inbound cycle of the service part long but outbound cycle is relatively short. But, increasing work efficiency in the warehouse has a limitation that cycle, frequency and quantity for the outbound request depend on the inherent features of the part. Through this research, not only are the types of the parts classified with the various and specified data but also the method is presented that it minimizes (that) the whole distances of the order picking and store location about both inbound and outbound by developing the model of the demand prediction. Based on this study, I expect that all of the work efficiency and the space utilization will be improved without a change of the inbound and outbound quantity in the warehouse.

• Information Systems Review
• /
• v.24 no.2
• /
• pp.41-66
• /
• 2022

With the development of IT, mobile apps and the expansion of contactless services due to COVID-19, "smart orders" have recently been activated in the food and beverage service. Even in recent years, when sales have declined, the number of orders made by smart orders has been steadily increasing, and this ordering method can accumulate customer data, enabling effective customized services in the future. In the present study, satisfaction with smart orders and continuous use intention were studied based on the technology acceptance model (TAM). And it focused on whether there is a difference in personality when using smart orders. For this purpose, a survey was conducted on 317 smart order users, and the hypothesis was verified by structural equation model analysis. Perceived benefits had a significant effect on satisfaction; also, satisfaction had a significant effect on continuous use intention. There is a significant disparity between introvert and extrovert type. As a consequence, the introverted type has a greater intention to perceive usefulness of smart orders and continuously use them. These results suggest that the customer's personality type should be considered in future customer customization strategies.

• The Journal of Bigdata
• /
• v.2 no.1
• /
• pp.49-58
• /
• 2017

The inventory location is the mos important factor which decide the efficiency of picking orders. According to the inventory location, it is possible to optimize the route for picking order, and then it makes us to expect the cost reduction and efficiency improvement. However, it is practical situation to make decisions where to keep the products based on manager's intuition and experience, not based on the systematical or analytical approach. In this research, with the practical order data of cropper product and layout for the storage yard, the association rules have found, and then the new methodology has been devised to make the decision where to keep the inventory. By utilizing the practical order data for a year, it has been proved that the proposed approach can reduce the total distance of the all routes for picking order and solve the problem of delayed delivery.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.17 no.5
• /
• pp.684-690
• /
• 2007

We describe our method to predict the direction of conditional probabilistic dependencies between clusters of random variables. Selected variables called 'gateway variables' are used to predict the conditional probabilistic dependency relations between clusters. The direction of conditional probabilistic dependencies between clusters are predicted by finding directed acyclic graph (DAG)-shaped dependency structure between the gateway variables. We show that our method shows meaningful prediction results in determining directions of conditional probabilistic dependencies between clusters.

• Journal of Convergence for Information Technology
• /
• v.8 no.1
• /
• pp.253-263
• /
• 2018

Textile fashion industry is a core foundation industry, having the majority of companies with 10 or more workers, in Northern Gyeonggi Province. however the industry is mostly comprised of small unit-stream enterprises, orders are greatly reduced due to lately accelerated overseas expansion of medium/large-sized vendors and the growth-inhibiting vicious circle has being set in, as this situation causes the reduction of investment. For resolving the problems, this study proposes required political factors and concrete policy proposals by designing AHP research model(4 layers and 36 elements), based on grasp of the transitional aspect of industrial scale and business environment through analysis of various industrial statistics, preceding research such as related literature search and (industrial/academic/R&D/government) specialist opinion investigation, and then calculating relative importance and priority of each factor(element) within each layer. And for raising usefulness and availability of the research result by concretely suggesting the vision, strategies, core tasks and detailed projects in which the research model and deduced result are reflected.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.29 no.11
• /
• pp.580-591
• /
• 2017

In accordance with 2015 Paris agreement, each individual country around the world should voluntarily propose not only its (individual) reduction target, but also actively develop and present expansion targets of its scope and concrete reduction goals exceeding the previous ones. Accordingly, it is necessary to prepare a macroscopic, long-range strategy for reducing energy consumption and greenhouse gas emissions, which can cover a single building, town, city and eventually even a province. The purpose of this research is to gather and compile government-acquired data from various sources and (in accordance with contents and specificity), combine building data by stages by using multi-variable matrix and then analyze the significance of combined data for each stage. The first order data presents the probability and the cost effectiveness of energy saving on the scale of a city or a province, based only upon general information, size and power consumption of buildings. The second order data can identify a pattern of energy consumption for a building of a specific purpose and which tends to consume a larger amount of energy during one particular season (than others). Finally, the third order data can derive influential factors (base load, humidity) from the energy consumption pattern of a building, and thus propose an informed and practical energy-saving method to be applied in real time.

• KIISE Transactions on Computing Practices
• /
• v.24 no.1
• /
• pp.40-45
• /
• 2018

With the advent of big data and social networks, large-scale graph processing becomes popular research topic. Recently, an optimization technique called Gorder has been proposed to improve the performance of in-memory graph processing. This technique improves performance by optimizing the graph layout on memory to have better cache locality. However, since it is designed for in-memory graph processing systems, the technique is not suitable for disk-based graph engines; also the cost for applying the technique is significantly high. To solve the problem, we propose a new graph ordering called I/O Order. I/O Order considers the characteristics of I/O accesses for SSDs and HDDs to improve the performance of disk-based graph engine. In addition, the algorithmic complexity of I/O Order is simple compared to Gorder, hence it is cheaper to apply I/O Ordering. I/O order reduces the cost of pre-processing up to 9.6 times compared to that of Gorder's, still its performance is 2 times higher compared to the Random in low-locality graph algorithms.