• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.23 no.1
• /
• pp.56-64
• /
• 2013

Turbulent boundary layer noise is already a significant contributor to sonar self noise. For developing acoustic window of sonar system to reduce self noise, a parametric study of design factors of acoustic window is presented. Distance of sensor array from acoustic window, materials of acoustic window and characteristics of damping layer are studied as design factors to influence in the characteristics of the transfer function of self noise. As the result, these design factors make change the characteristics of transfer function slightly. Among design factors the location of sensor array is most important parameter in the self noise reduction

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.7 no.8
• /
• pp.327-342
• /
• 2017

In this paper, we introduce an integrated processing system of smart sensor data for IoT service which collects sensor data and efficiently processes it. Based on the technology of collecting sensor data to the development of the IoT field and sending it to the network · Based on the receiving technology, as various projects such as smart homes, autonomous running vehicles progress, the sensor data is processed and effectively An autonomous control system to utilize has been a problem. However, since the data type of the sensor for monitoring the autonomous control system varies according to the domain, a sensor data integration processing system applying the autonomous control system to various different domains is necessary. Therefore, in this paper, we introduce the Smart Sensor Data Integrated Processing System, apply it and use the window as a reference to process internal and external sensor data 1) receiveData, 2) parseData, 3) addToDatabase 3 With the process of the stage, we provide and implement the automatic window opening / closing system "Smart Window" which ventilates to create a comfortable indoor environment by autonomous control system. As a result, standby information is collected and monitored, and machine learning for performing statistical analysis and better autonomous control based on the stored data is made possible.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.8A
• /
• pp.600-609
• /
• 2009

The traditional carrier sense multiple access (CSMA) protocol like IEEE 802.11 Distributed Coordination Function (DCF) does not handle the constraints adequately, leading to degraded delay latency and throughput as the network scales are enlarged. We present more efficient method of a medium access for real-time wireless sensor networks. Proposed MAC protocol is like the randomized CSMA protocol, but unlike previous legacy protocols, it does not use a time-varying contention window from which a node randomly picks a transmission slot. To reduce the latency for the delivery of event reports, we carefully decide to select a fixed-size contention window with non-uniform probability distribution of transmitting in each slot. We show that the proposed method can offer up to severaansimes latency reduction compared to legacy of IEEE 802.11 as the size of the sensor network scales up to 256 nodes using widely using network simulation package,caS-2. We finally show that proposed MAC scheme comes close to meet bounds on the best latency being achieved by a decentralized CSMA-based MAC protocol for real-time wireless sensor networks which is sensitive to delay latency.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.4 no.2
• /
• pp.103-110
• /
• 2011

It is necessary to accurate and efficient management for measured digital data from sensors in u-health system. It is not efficient that sensor network process input stream data of mass storage stored in database the same time. We propose to improve the processing performance of multidimensional stream data continuous incoming from multiple sensor. We propose process query based on sliding window for efficient input stream and found multiple query plan to Mjoin method and we reduce stored data using backpropagation algorithm. As a result, we obtained to efficient result about 18.3% reduction rate of database using 14,324 data sets.

• 제어로봇시스템학회:학술대회논문집
• /
• 2000.10a
• /
• pp.164-164
• /
• 2000

This paper proposes a moving window technique that extracts lanes and vehicles using the images captured by a CCD camera equipped inside an automobile in real time. For the purpose, first of all the optimal size of moving window is determined based upon speed of the vehicle, road curvature, and camera parameters. Within the moving windows that are dynamically changing, lanes and vehicles are extracted, and the vehicles within the driving lanes are classified as obstacles. Assuming highway driving, there are two sorts of image-objects within the driving lanes: one is ground mark to show the limit speed or some information for driving, and the other is the vehicle as an obstacle. Using characteristics of three-dimension objects, a neural network can be trained to distinguish the vehicle from ground mark. When it is recognized as an obstacle, the distance from the camera to the front vehicle can be calculated with the aids of database that keeps the models of automobiles on the highway. The correctness of this measurement is verified through the experiments comparing with the radar and laser sensor data.

• KIEAE Journal
• /
• v.9 no.5
• /
• pp.105-113
• /
• 2009

Daylighting provides the opportunity for both energy savings and improved visual comfort. An accurate estimation of the amount of daylight entering a building is the key step for daylight designing. This research aims to assess comparative daylighting performance of four different configurations of fenestration in case of unilateral windows and their variation under clear and overcast sky conditions. The selected window openings in this study were single punched, double punched, multiple punched and clerestory, and the area was same for each type of window. The experiment was designed for an office space using 1/10 scale model. Daylighting performance was evaluated by measuring the illuminance on work-plane height using Agilent data logger and photometric sensor Li-Cor. Thecomputer program ECOTECT was also used to simulate the pattern of interior illuminance distribution. Clerestory window showed the best performance in term of both illuminance level and distribution in the experiment. Multiple punched window provided more uniform illuminance distribution than single punched window. Lowest daylighting performance in the experiment was shown by double punched window.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.3 no.2
• /
• pp.109-118
• /
• 2008

We present a robust localization algorithm using particle filter for mobile robots in a dynamic environment. It is difficult to describe moving obstacles like people or other robots on the map and the environment is changed after mapping. A mobile robot cannot estimate its pose robustly with this incomplete map because sensor observations are corrupted by un-modeled obstacles. The proposed algorithms provide robustness in such a dynamic environment by suppressing the effect of corrupted sensor observations with a selective update or a sampling from non-corrupted window. A selective update method makes some particles keep track of the robot, not affected by the corrupted observation. In a sampling from non-corrupted window method, particles are always sampled from several particle sets which use only non-corrupted observation. The robustness of proposed algorithm is validated with experiments and simulations.

• Proceedings of the Korea Concrete Institute Conference
• /
• 1999.10a
• /
• pp.635-638
• /
• 1999

The crack of concrete is one of the most important factors to evaluate the safety of the structures. The more important point for the safety-evaluation of the concrete structures is to check the crack development, the conventional window paper (Chang Ho Ji) have been used as a simple method in the past, and nowadays the strain gauge is used for more correct way to check the development of the concrete crack quantitatively. However the window-paper method is too simple and not so scientific, and the strain-gauge method is rather complicated for people in general. This Easy-Check Sensor provides the simple usage for the various concrete structures, but also the more correct results to evaluate the development of the concrete crack.

• Proceedings of the Optical Society of Korea Conference
• /
• 2004.02a
• /
• pp.244-245
• /
• 2004

• Journal of Korea Multimedia Society
• /
• v.20 no.8
• /
• pp.1421-1429
• /
• 2017

Human activity recognition has been studied using various sensors and algorithms. Human activity recognition can be divided into sensor based and vision based on the method. In this paper, we proposed an activity recognition system using acceleration sensor and gyroscope sensor in smartphone among sensor based methods. We used Deep Belief Network (DBN), which is one of the most popular deep learning methods, to improve an accuracy of human activity recognition. DBN uses the entire input set as a common input. However, because of the characteristics of different time window depending on the type of human activity, the RBMs, which is a component of DBN, are configured hierarchically by combining them from different time windows. As a result of applying to real data, The proposed human activity recognition system showed stable precision.