• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.160-160
• /
• 2019

Water is a limited source that needs to be properly managed and distributed to the ever-growing population of the world. Rapid urbanization and development have increased the overall water demand of the world drastically. However, there is loss of billions of liters of water every year due to leakages in water distribution systems. Such water loss means significant financial loss for the utilities as well. World bank estimates a loss of $14 billion annually from wasted water. To address these issues and for the development of efficient and reliable leakage management techniques, high efforts have been made by the researchers and engineers. Over the past decade, various techniques and technologies have been developed for leakage management and leak detection. These include ideas such as pressure management in water distribution networks, use of Advanced Metering Infrastructure, use of machine learning algorithms, etc. For leakage detection, techniques such as acoustic technique, and in recent yeats transient test-based techniques have become popular. Smart Water Grid uses two-way real time network monitoring by utilizing sensors and devices in the water distribution system. Hence, valuable real time data of the water distribution network can be collected. Best results and outcomes may be produced by proper utilization of the collected data in unison with advanced detection and management techniques. Long term reduction in Non Revenue Water can be achieved by detecting, localizing and repairing leakages as quickly and as efficiently as possible. However, there are still numerous challenges to be met and future research works to be conducted in this field.

• International Journal of Internet, Broadcasting and Communication
• /
• v.11 no.4
• /
• pp.71-75
• /
• 2019

Sleep apnea is a disease that causes various complications, and the polysomnography is expensive and difficult to measure. The purpose of this study is to develop an unrestricted wearable monitoring system so that patients can be examined in a familiar environment. We used a method to detect sleep apnea events and to determine sleep satisfaction by non-constrained method using SpO2 measurement sensor and 3-axis acceleration sensor. Heart rate and SpO2 were measured at the finger using max30100. After acquiring the SpO2 data of the user in real time, the apnea measurement algorithm was used to transmit the number of apnea events of the user to the mobile phone using Bluetooth (HC-06) on the wrist. Using the three-axis acceleration sensor (mpu6050) attached to the upper body, the number of times of tossing and turning during sleep was measured. Based on this data, this algorithm evaluates the patient's tossing and turning during sleep and transmits the data to the mobile phone via Bluetooth. The power source used 9 volts battery to operate Arduino UNO and sensors for portability and stability, and the data received from each sensor can be used to check the various degree between sleep apnea and sleep tossing and turning on the mobile phone. Through thisstudy, we have developed a wearable sleep apnea measurement system that can be easily used at home for the problem of low sleep efficiency of sleep apnea patients.

• Smart Structures and Systems
• /
• v.6 no.5_6
• /
• pp.749-765
• /
• 2010

There are on-going efforts to utilize guided waves for structural damage detection. Active sensing devices such as lead zirconate titanate (PZT) have been widely used for guided wave generation and sensing. In addition, there has been increasing interest in adopting wireless sensing to structural health monitoring (SHM) applications. One of major challenges in wireless SHM is to secure power necessary to operate the wireless sensors. However, because active sensing devices demand relatively high electric power compared to conventional passive sensors such as accelerometers and strain gauges, existing battery technologies may not be suitable for long-term operation of the active sensing devices. To tackle this problem, a new wireless power transmission paradigm has been developed in this study. The proposed technique wirelessly transmits power necessary for PZT-based guided wave generation using laser and optoelectronic devices. First, a desired waveform is generated and the intensity of the laser source is modulated accordingly using an electro-optic modulator (EOM). Next, the modulated laser is wirelessly transmitted to a photodiode connected to a PZT. Then, the photodiode converts the transmitted light into an electric signal and excites the PZT to generate guided waves on the structure where the PZT is attached to. Finally, the corresponding response from the sensing PZT is measured. The feasibility of the proposed method for wireless guided wave generation has been experimentally demonstrated.

• Journal of Ginseng Research
• /
• v.37 no.4
• /
• pp.483-490
• /
• 2013

Gamma-irradiation (0-7 kGy) of ginseng is permitted in Korea for the purpose of microbial decontamination; with strict labeling, traceability and monitoring requirements. An identification study was conducted to determine the photostimulated-luminescence (PSL) and thermoluminescence (TL) properties of gamma-irradiated fresh and white ginsengs cultivated in different areas. Dose- dependent PSL-based screening was possible for white ginseng samples; however, inappropriate results from non-irradiated fresh ginseng samples were obtained, showing intermediate (700 to 5,000) or positive ($T_2$ >5,000, irradiated) PSL counts due to the abundance of minerals on the surfaces of the samples. TL analysis of separated minerals from all non-irradiated samples gave TL glow curves of low intensity with a maximum peak after $300^{\circ}C$. However, well-defined irradiation-specific (high intensity with a maximum peak at about $200^{\circ}C$) glow curves were observed for all the irradiated samples, regardless of their type and origins. TL ratios (first glow curve /second glow curve) were also determined to confirm the irradiated (>0.1) and non-irradiated (<0.1) results. SEM-EDX (scanning electron microscope-energy dispersive X-ray) and XRD (X-ray diffraction) spectroscopic analyses showed that feldspar and quartz minerals were the main source for the typical radiation-specific luminescence properties.

• Smart Structures and Systems
• /
• v.19 no.1
• /
• pp.1-10
• /
• 2017

The operation of subway trains induces secondary structure-borne vibrations in the nearby underground spaces. The vibration, along with the associated noise, can cause annoyance and adverse physical, physiological, and psychological effects on humans in dense urban environments. Traditional tethered instruments restrict the rapid measurement and assessment on such vibration effect. This paper presents a novel approach for Wireless Smart Sensor (WSS)-based autonomous evaluation system for the subway train-induced vibrations. The system was implemented on a MEMSIC's Imote2 platform, using a SHM-H high-sensitivity accelerometer board stacked on top. A new embedded application VibrationLevelCalculation, which determines the International Organization for Standardization defined weighted acceleration level, was added into the Illinois Structural Health Monitoring Project Service Toolsuite. The system was verified in a large underground space, where a nearby subway station is a good source of ground excitation caused by the running subway trains. Using an on-board processor, each sensor calculated the distribution of vibration levels within the testing zone, and sent the distribution of vibration level by radio to display it on the central server. Also, the raw time-histories and frequency spectrum were retrieved from the WSS leaf nodes. Subsequently, spectral vibration levels in the one-third octave band, characterizing the vibrating influence of different frequency components on human bodies, was also calculated from each sensor node. Experimental validation demonstrates that the proposed system is efficient for autonomously evaluating the subway train-induced ambient vibration of underground spaces, and the system holds the potential of greatly reducing the laboring of dynamic field testing.

• Journal of the Korean Institute of Gas
• /
• v.25 no.5
• /
• pp.57-62
• /
• 2021

Gas is an energy source widely used in general households and industrial sites, and is also a process material widely used in petrochemical and semiconductor processes. However, while it is easy to use, it can cause large-scale human damage due to leakage, explosion, and human inhalation. Therefore, a gas facility safety management solution that can be safely used at home and industrial sites is essential. In particular, the need to develop advanced gas safety solutions is emerging as gas facilities are aging. In this paper, a technology was developed to measure the presence and concentration of gas leaks from a distance by irradiating photons, the minimum energy unit that can no longer be divided into gas facilities, and analyzing the number of reflected photons. This overcomes technical limitations such as short detection distance and inability to detect fine leaks, which are the limitations of conventional electric/chemical gas sensors or infrared-based gas leak detectors.

• Journal of Korean Society for Quality Management
• /
• v.49 no.3
• /
• pp.299-312
• /
• 2021

Purpose: We provide a condition-based maintenance policy where a surrogate variable is used for monitoring system performance. We constructed a risk function by taking into account the risk and losses accompanied with erroneous decisions. Methods: Assuming a unique degradation process for the performance variable and its specific relationship with the surrogate variable, the maintenance policy is determined. A risk function is developed on the basis of producer's and consumer's risks accompanied with each decision. With a strategic safety factor considered, the optimal threshold value for the surrogate variable is determined based on the risk function. Results: The condition-based maintenance is analyzed from the point of risk. With an assumed safety consideration, the optimal threshold value of the surrogate variable is provided for taking a maintenance action. The optimal solution cannot be obtained in a closed form. An illustrative numerical example and solution is provided with a source code of R program. Conclusion: The study can be applied to situation where a sensor signal is issued if the system performance begins to degrade gradually and reaches eventually its functional failure. The study can be extended to the case where two or more performance variables are connected to a same surrogate variable. Also estimation of the distribution parameters and risk coefficients should be further studied.

• Healthcare Informatics Research
• /
• v.24 no.4
• /
• pp.253-262
• /
• 2018

Objectives: We reviewed digital epidemiological studies to characterize how researchers are using digital data by topic domain, study purpose, data source, and analytic method. Methods: We reviewed research articles published within the last decade that used digital data to answer epidemiological research questions. Data were abstracted from these articles using a data collection tool that we developed. Finally, we summarized the characteristics of the digital epidemiological studies. Results: We identified six main topic domains: infectious diseases (58.7%), non-communicable diseases (29.4%), mental health and substance use (8.3%), general population behavior (4.6%), environmental, dietary, and lifestyle (4.6%), and vital status (0.9%). We identified four categories for the study purpose: description (22.9%), exploration (34.9%), explanation (27.5%), and prediction and control (14.7%). We identified eight categories for the data sources: web search query (52.3%), social media posts (31.2%), web portal posts (11.9%), webpage access logs (7.3%), images (7.3%), mobile phone network data (1.8%), global positioning system data (1.8%), and others (2.8%). Of these, 50.5% used correlation analyses, 41.3% regression analyses, 25.6% machine learning, and 19.3% descriptive analyses. Conclusions: Digital data collected for non-epidemiological purposes are being used to study health phenomena in a variety of topic domains. Digital epidemiology requires access to large datasets and advanced analytics. Ensuring open access is clearly at odds with the desire to have as little personal data as possible in these large datasets to protect privacy. Establishment of data cooperatives with restricted access may be a solution to this dilemma.

• Journal of Korean Society on Water Environment
• /
• v.34 no.6
• /
• pp.579-590
• /
• 2018

The lakes' metabolism bears important information for the assessment of the carbon budget due to the accumulation or loss of carbon in the lake as well as the dynamics of the food webs through primary production. A lake-scale metabolism is evaluated by Gross Primary Production (GPP), Ecosystem Respiration (R), and Net Ecosystem Production (NEP), which is the difference between the first two values. Methods for estimating GPP and R are based on the levels carbon and oxygen. Estimation of carbon is expensive because of the use of radioactive materials which requires a high degree of proficiency. The purpose of this study was to estimate Lake Daecheong ecosystem metabolism using high frequency water temperature data and DO measurement sensor, widely utilized in the field of water quality monitoring, and to evaluate the possibility of using the application method. High frequency data was collected at intervals of 10 minutes from September to December 2017 by installing a thermistor chain and a DO sensor in downstream of Daechung Dam. The data was then used to estimate GPP, R and NEP using the R public program LakeMetabolizer, and other metabolism models (mle, ols, kalman, bookkeep). Calculations of gas exchange coefficient methods (cole, crusius, heiskanen, macIntyre, read, soloviev, vachon) were compared. According to the result, Lake Daecheong has some deviation based on the application method, but it was generally estimated that the NEP value is negative and acts as a source of atmospheric carbon in a heterotrophic system. Although the high frequency sensor data used in this study had negative and positive GPP and R values during the physical mixing process, they can be used to monitor real-time metabolic changes in the ecosystem if these problems are solved.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.2
• /
• pp.711-732
• /
• 2019

Many unmanned aerial vehicle (UAV) applications have been employed for performing data collection in facilitating tasks such as surveillance and monitoring objectives in remote and dangerous environments. In light of the fact that most of the existing UAV relaying applications operate in conventional half-duplex (HD) mode, a full-duplex (FD) based UAV relay aided wireless network is investigated, in which the UAV relay helps forwarding information from the source (S) node to the destination (D). Since the activated UAV relays are always floating and flying in the air, its channel state information (CSI) as well as channel capacity is a time-variant parameter. Considering decode-and-forward (DF) relaying protocol in UAV relays, the cooperative relaying channel capacity is constrained by the relatively weaker one (i.e. in terms of signal-to-noise ratio (SNR) or signal-to-interference-plus-noise ratio (SINR)) between S-to-relay and relay-to-D links. The channel capacity can be optimized by adaptively optimizing the transmit power of S and/or UAV relay. Furthermore, a hybrid HD/FD mode is enabled in the proposed UAV relays for adaptively optimizing the channel utilization subject to the instantaneous CSI and/or remaining self-interference (SI) levels. Numerical results show that the channel capacity of the proposed UAV relay aided wireless networks can be maximized by adaptively responding to the influence of various real-time factors.