• International Journal of Advanced Culture Technology
• /
• 제10권1호
• /
• pp.274-283
• /
• 2022

Korea is facing a number difficulties arising from rising housing prices. As 'housing' takes the lion's share in personal assets, many difficulties are expected to arise from fluctuating housing prices. The purpose of this study is creating housing price prediction model to prevent such risks and induce reasonable real estate purchases. This study made many attempts for understanding real estate instability and creating appropriate housing price prediction model. This study predicted and validated housing prices by using the LSTM technique - a type of Artificial Intelligence deep learning technology. LSTM is a network in which cell state and hidden state are recursively calculated in a structure which added cell state, which is conveyor belt role, to the existing RNN's hidden state. The real sale prices of apartments in autonomous districts ranging from January 2006 to December 2019 were collected through the Ministry of Land, Infrastructure, and Transport's real sale price open system and basic apartment and commercial district information were collected through the Public Data Portal and the Seoul Metropolitan City Data. The collected real sale price data were scaled based on monthly average sale price and a total of 168 data were organized by preprocessing respective data based on address. In order to predict prices, the LSTM implementation process was conducted by setting training period as 29 months (April 2015 to August 2017), validation period as 13 months (September 2017 to September 2018), and test period as 13 months (December 2018 to December 2019) according to time series data set. As a result of this study for predicting 'prices', there have been the following results. Firstly, this study obtained 76 percent of prediction similarity. We tried to design a prediction model of real estate transaction price with the LSTM Model based on AI and Bigdata. The final prediction model was created by collecting time series data, which identified the fact that 76 percent model can be made. This validated that predicting rate of return through the LSTM method can gain reliability.

• 디지털콘텐츠학회 논문지
• /
• 제3권1호
• /
• pp.47-57
• /
• 2002

최근, 정보 통신 기술의 발전에 따라 무선 통신망에서 음성, 데이터, 정지화면, 동영상 및 다양한 멀티미디어 데이터를 추구하고 있다. 효율적인 실시간 멀티미디어 데이터 전송을 위해서는 실시간 데이터의 지연 한계를 보장하고 비실시간 멀티미디어 데이터의 데이터 손실을 최소화해야 한다. 무선 ATM은 유선 ATM을 기본으로 하고 있지만 무선 환경에서의 다양한 서비스에 대한 힘든 전송률과 품질에 따른 문제점들이 수반된다. 그 결과, 무선 통신 환경에서 각각의 트래픽 종류에 따른 품질 서비스(QoS)를 보장하는 방법을 찾는 것이 중요하다. 이 논문에서는 무선 ATM망에서 실시간 멀티미디어 데이터 서비스 전송을 위한 스케줄링 방법으로 개선된 TCRM 스케줄링 알고리즘을 제시한다. 무선 환경에 따라 Uplink와 Downlink시 각각 다른 방법으로 실시간 멀티미디어 데이터 전송 스케줄링 정책을 적용하며 실시간 데이터와 비실시간 데이터의 QoS의 요구사항을 보장하고 불충분한 무선 자원을 공유분배를 위한 공평성 문제를 다룬다. 또한 VC(Virtual Control)를 BS(Base Station)에 두어 예약버퍼와 임의의 전송속도 pk를 사용하여 TCRM의 단점인 비실시간 데이터에 대한 비효율성 문제를 해결한다.

• 정보과학회 논문지
• /
• 제44권1호
• /
• pp.84-94
• /
• 2017

최근 다양하고 방대한 양의 데이터를 처리하기 위해 빅데이터의 특성인 5V(Volume, Variety, Velocity, Veracity, Value) 중에서도 속도(Velocity)의 중요성이 강조되면서 대량의 데이터를 빠르고 정확하게 처리하는 기술인 실시간 스트림 처리(Real-time Stream processing)를 위해 많은 연구가 진행되고 있다. 본 논문에서는 실시간 빅데이터 처리를 위해 대표적인 실시간 객체 모델인 TMO(Time-triggered Message-triggered Object) 개념을 도입한 Squall 프레임워크를 제시하고, 단일 노드에서 동작하는 Squall 프레임워크와 그 동작들에 대해 기술한다. TMO는 작업을 수행할 때, 특정 조건에 대해 실시간으로 처리하는 비주기적인 처리방법과 일정 시간 간격동안 주기적인 처리를 지원하는 객체 모델이다. 따라서 Squall 프레임워크는 실시간 빅데이터의 실시간 이벤트 스트림 및 마이크로-배치 처리를 동시에 지원하고, 기존 아파치 스톰과 스파크 스트리밍 대비 상대적으로 우수한 성능을 제공한다. 하지만 Squall은 대부분의 프레임워크에서 제공되는 다중 노드에서의 실시간 분산처리를 위한 추가적인 개발이 필요하다. 결론적으로, TMO 모델의 장점은 실시간 빅데이터 처리시 기존 아파치의 스톰이나 스파크 스트리밍의 단점들을 극복할 수 있다. 이러한 TMO 모델은 실시간 빅데이터 처리에 있어 유용한 모델로서의 가능성을 가지고 있다.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제52권11호
• /
• pp.644-649
• /
• 2003

This study develops an analytical model for the delay analysis of real-time data in the token-passing service of Foundation Fieldbus(FF). Using the analytical model, this study proposes a network design scheme of FF Two design criteria are introduced in this study; one is the average delay of real-time data, and the other is the maximum allowable delay of real-time data. The network design scheme determines the network parameters that satisfies the performance requirements given by these design criteria.

• 대한안전경영과학회지
• /
• 제8권4호
• /
• pp.109-117
• /
• 2006

This paper deals with the middleware development for real time data processing using ubiquitous RFID(Radio Frequency Identification). This middleware system supports the real time data gathering, filtering, and collaborative operations within SCM. We expect to decrease the data processing cost and to upgrade the status of RTE(Real Time Enterprise) and competitive power of company.

• International Journal of Control, Automation, and Systems
• /
• 제6권1호
• /
• pp.119-125
• /
• 2008

This paper examines the use of a wireless Fieldbus based on IEEE 802.15.4 MAC protocol. The superframe of IEEE 802.15.4 is applied to a transmission scheme of real-time mixed data. The transmission and bandwidth allocation scheme are proposed for real-time communication using a superframe. The proposed wireless Fieldbus protocol is able to transmit three types of data (periodic data, sporadic data, and non real-time messages), and guarantee realtime transmission simultaneously within a limited timeframe.

• Journal of Astronomy and Space Sciences
• /
• 제19권4호
• /
• pp.403-408
• /
• 2002

3D display of spacecraft motion by using telemetry data received from satellite in real-time is described. Telemetry data are converted to the appropriate form for 3-D display by the real-time preprocessor. Stored playback telemetry data also can be processed for the display. 3D display of spacecraft motion by using real telemetry data provides intuitive comprehension of spacecraft dynamics.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
• /
• pp.1432-1435
• /
• 1996

This paper obtains maximum allowable delay bounds for stability of network-based control systems and presents a network scheduling method which makes the network-induced delay be less than the maximum allowable delay bound. The maximum allowable delay bounds are obtained using the Lyapunov theorem. Using the network scheduling method, the bandwidth of a network can be allocated to each node and the sampling period of each sensor and controller can be determined. The presented method can handle three kinds of data (periodic, real-time asynchronous, and non real-time asynchronous data) and guarantee real-time transmissions of real-time synchronous data and periodic data, and possible transmissions of non real-time asynchronous data. The proposed method is shown to be useful by examples in two types of network protocols such as the token control and the central control.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권6호
• /
• pp.3055-3073
• /
• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• 제어로봇시스템학회논문지
• /
• 제3권1호
• /
• pp.77-88
• /
• 1997

Fieldbus is the lowest level communication network in factory automation and process control systems. Performance of factory automation and process control systems is directly affected by the data delay induced by network traffic. Data generated from several distributed field devices can be largely divided into three categories: sporadic real-time, periodic real-time and non real-time data. Since these data share one fieldbus network medium, the limited bandwidth of a fieldbus network must be appropriately allocated to the sporadic real-time, periodic real-time and non real-time traffic. This paper introduces a new fieldbus design scheme which allocates the limited bandwidth of fieldbus network to several different kinds of traffic. The design scheme introduced in this study not only satisfies the performance requirements of application systems interconnected into the fieldbus but also fully utilizes the network resources. The design scheme introduced in this study can be applicable to cyclic service protocols operated under single-service discipline. The bandwidth allocation scheme introduced in this study is verified using a discrete-event/continuous-time simulation experiment.