• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.606-611
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• 2007

Pulsation is an inherent phenomenon in reciprocating compressors. It interacts with piping to cause vibrations and performance problems. Indiscriminately connecting to a compressor can be dangerous and cost money in the form of broken equipment and piping, poor performance, inaccurate metering, unwanted vibration, and sometimes noise. Piping connected to a compressor can materially affect the performance and response. To minimize these detrimental effects, reciprocating compressor system should be equipped by pulsation suppression system. This study discusses pressure pulsation phenomena occurred in a reciprocating compressor system. An experiment applied air compressor unit, as pulsating pressure generator, has been done. The compressor was connected sequentially to a snubber model and pressure tank. Sensor probes were placed on the inlet and outlet pipes of snubber. Compressor was driven by a motor controlled by a frequency regulator. The experiment was conducted by adjusting the regulator at 40Hz. General information about an internal gas flow can be achieved by numerical analysis approach. Information of the velocity, pressure and turbulence kinetic energy distribution are presented in this paper. Based on this result, the design improvement might be done.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• Proceedings of the Korean Vacuum Society Conference
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• 2010.02a
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• pp.464-464
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• 2010

A few years ago, for maintaining high stability and production yield of production equipment in a semiconductor fab, on-line monitoring of wafers is required, so that semiconductor manufacturers are investigating a software based process controlling scheme known as virtual metrology (VM). As semiconductor technology develops, the cost of fabrication tool/facility has reached its budget limit, and reducing metrology cost can obviously help to keep semiconductor manufacturing cost. By virtue of prediction, VM enables wafer-level control (or even down to site level), reduces within-lot variability, and increases process capability, $C_{pk}$. In this research, we have practiced VM on $SiO_2$ etch rate with optical emission spectroscopy(OES) data acquired in-situ while the process parameters are simultaneously correlated. To build process model of $SiO_2$ via, we first performed a series of etch runs according to the statistically designed experiment, called design of experiments (DOE). OES data are automatically logged with etch rate, and some OES spectra that correlated with $SiO_2$ etch rate is selected. Once the feature of OES data is selected, the preprocessed OES spectra is then used for in-situ sensor based VM modeling. ICP-RIE using 葰.56MHz, manufactured by Plasmart, Ltd. is employed in this experiment, and single fiber-optic attached for in-situ OES data acquisition. Before applying statistical feature selection, empirical feature selection of OES data is initially performed in order not to fall in a statistical misleading, which causes from random noise or large variation of insignificantly correlated responses with process itself. The accuracy of the proposed VM is still need to be developed in order to successfully replace the existing metrology, but it is no doubt that VM can support engineering decision of "go or not go" in the consecutive processing step.

• Smart Structures and Systems
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• v.13 no.2
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• pp.257-280
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• 2014

In this paper, a novel PARAllel FACtor (PARAFAC) decomposition based Blind Source Separation (BSS) algorithm is proposed for modal identification of structures equipped with tuned mass dampers. Tuned mass dampers (TMDs) are extremely effective vibration absorbers in tall flexible structures, but prone to get de-tuned due to accidental changes in structural properties, alteration in operating conditions, and incorrect design forecasts. Presence of closely spaced modes in structures coupled with TMDs renders output-only modal identification difficult. Over the last decade, second-order BSS algorithms have shown significant promise in the area of ambient modal identification. These methods employ joint diagonalization of covariance matrices of measurements to estimate the mixing matrix (mode shape coefficients) and sources (modal responses). Recently, PARAFAC BSS model has evolved as a powerful multi-linear algebra tool for decomposing an $n^{th}$ order tensor into a number of rank-1 tensors. This method is utilized in the context of modal identification in the present study. Covariance matrices of measurements at several lags are used to form a $3^{rd}$ order tensor and then PARAFAC decomposition is employed to obtain the desired number of components, comprising of modal responses and the mixing matrix. The strong uniqueness properties of PARAFAC models enable direct source separation with fine spectral resolution even in cases where the number of sensor observations is less compared to the number of target modes, i.e., the underdetermined case. This capability is exploited to separate closely spaced modes of the TMDs using partial measurements, and subsequently to estimate modal parameters. The proposed method is validated using extensive numerical studies comprising of multi-degree-of-freedom simulation models equipped with TMDs, as well as with an experimental set-up.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.6
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• pp.9-13
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• 2019

In this study, a miniature thin film-patterned heater was fabricated on a silicon substrate using semiconductor process technology and the thermal characteristics of the applied voltage, power, and temperature of the thin film heater were measured and analyzed. The temperature of the thin film pattern heater increased with increasing power, but the temperature increase rate was gradual at high power intervals. The characteristics of the high temperature section of the platinum thin film-patterned heater were analyzed using the heat resistance model under atmospheric and vacuum conditions. The thermal resistance measured in a vacuum atmosphere was 0.79 [K/mW] higher than the heat resistance value 0.69 [K/mW] in air. The temperature of the thin film pattern heater can be maintained at a low power in a vacuum rather than in air, and these results are expected to be utilized in the structural design of a thin film-patterned heater element.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.993-995
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• 2014

Typical dwelling pattern of apartment houses in Korea. Because of this the noise of life problem arise, complaints are surging. In real-life, if suffering is unavoidable due to ambient noise, to handle a civil complaint the using a noise meter. At home, it is difficult to measure the noise using professional equipment. So, many uses smartphone application in general. But released existing noise measurement application has different value from the sensor sensitivity for each smartphone model to same situation. The value is lacks precision and this is not considered as having been made by measuring the actual noise purpose. Therefore in this paper, we propose a mobile data processing system for the living environment of noise measurement using a smartphone. Benefits of this study is to improve the accuracy of noise measurements and to find direction of noise to handle complaints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2148-2167
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• 2021

The proliferation of the Internet of Things (IoT) technologies and applications, especially the rapid rise in the use of mobile devices, from individuals to organizations, has led to the fundamental role of secure wireless networks in all aspects of services that presented with many opportunities and challenges. To ensure the CIA (confidentiality, integrity and accessibility) security model of the networks security and high efficiency of performance results in various resource-constrained applications and environments of the IoT platform, DDO-(data-driven operation) based constructions have been introduced as a primitive design that meet the demand of high speed encryption systems. Among of them, the TMN-family ciphers which were proposed by Tuan P.M., Do Thi B., etc., in 2016, are entirely suitable approaches for various communication applications of wireless mobile networks (WMNs) and advanced wireless sensor networks (WSNs) with high flexibility, applicability and mobility shown in two different algorithm selections, TMN64 and TMN128. The two ciphers provide strong security against known cryptanalysis, such as linear attacks and differential attacks. In this study, we demonstrate new probability results on the security of the two TMN construction versions - TMN64 and TMN128, by proposing efficient related-key recovery attacks. The high probability characteristics (DCs) are constructed under the related-key differential properties on a full number of function rounds of TMN64 and TMN128, as 10-rounds and 12-rounds, respectively. Hence, the amplified boomerang attacks can be applied to break these two ciphers with appropriate complexity of data and time consumptions. The work is expected to be extended and improved with the latest BCT technique for better cryptanalytic results in further research.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.113-120
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• 2023

Smart farms are steadily increasing in research to minimize labor, energy, and quantity put into crops as IoT technology and artificial intelligence technology are combined. However, research on efficiently managing crop growth information in smart farms has been insufficient to date. In this paper, we propose a management technique that can efficiently monitor crop growth information by applying autonomous sensors to smart farms. The proposed technique focuses on collecting crop growth information through autonomous sensors and then recycling the growth information to crop cultivation. In particular, the proposed technique allocates crop growth information to one slot and then weights each crop to perform load balancing, minimizing interference between crop growth information. In addition, when processing crop growth information in four stages (sensing detection stage, sensing transmission stage, application processing stage, data management stage, etc.), the proposed technique computerizes important crop management points in real time, so an immediate warning system works outside of the management criteria. As a result of the performance evaluation, the accuracy of the autonomous sensor was improved by 22.9% on average compared to the existing technique, and the efficiency was improved by 16.4% on average compared to the existing technique.

• Design Convergence Study
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• v.16 no.6
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• pp.123-135
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• 2017

In recent mobile health care service, health management using number of steps is becoming popular. In addition, a variety of activity trackers have made it possible to measure the number of steps more accurately and easily. Nevertheless, the activity tracker is not popularized, and it is a trend to use the pedometer sensor of the smartphone as an alternative. In this study, we tried to find out how much the number of steps collected by the smartphone versus the actual number of steps in actual situations, and what factors make the difference. We conducted an experiment to collect number of steps data of 21 people using the smartphone and wearable device simultaneously for 7 days. As a result, we found that the average number of steps of the smartphone is 62% compared to the actual number of steps, and that there is a large variation among users. We derived a regression model in which the accuracy of smartphone increases with the degree of awareness of smartphone. We expect that this can be used as a factor to correct the difference from the actual number of steps in the smartphone alone healthcare service.

• International Journal of Highway Engineering
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• v.9 no.1 s.31
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• pp.1-15
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• 2007

The objective of this paper is the establishment of finite element analysis frame work for pavement research. Finite element analysis results simulating various loading experiments are verified with sensor measurements obtained from the KHC Test Road. The accuracy of the finite element analysis can be supported by these efforts so that it helps spread out the finite element analysis to pavement research and design processes. The finite element model used in this research is the full 3D nonlinear model including concrete slab, lean concrete base, subbase, shoulder, dowel, and tie-bar. In order to accomplish the accurate verification, the loading condition and the pavement temperature distribution are exactly simulated with field measured data. The curling behavior and the strain distribution are compared with measured responses from the loading tests with a truck and the FWD. Strain and curling predictions from the concrete slab are matched well with measured responses but the strain prediction from the lean concrete base is not matched with measured response. In addition, the magnitude of permanent curling is evaluated with the finite element analysis.