• Ocean and Polar Research
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• 제39권1호
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• pp.13-21
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• 2017

Temporal changes in the number of zooplankton species are important information for understanding basic characteristics and species diversity in marine ecosystems. The aim of the present study was to estimate the optimal monitoring frequency (OMF) to guarantee and predict the minimum number of species occurrences for studies concerning marine ecosystems. The OMF is estimated using the temporal number of zooplankton species through bi-weekly monitoring of zooplankton species data according to operational taxonomic units in the Tongyoung coastal sea. The optimal model comprises two terms, a constant (optimal mean) and a cosine function with a one-year period. The confidence interval (CI) range of the model with monitoring frequency was estimated using a bootstrap method. The CI range was used as a reference to estimate the optimal monitoring frequency. In general, the minimum monitoring frequency (numbers per year) directly depends on the target (acceptable) estimation error. When the acceptable error (range of the CI) increases, the monitoring frequency decreases because the large acceptable error signals a rough estimation. If the acceptable error (unit: number value) of the number of the zooplankton species is set to 3, the minimum monitoring frequency (times per year) is 24. The residual distribution of the model followed a normal distribution. This model can be applied for the estimation of the minimal monitoring frequency that satisfies the target error bounds, as this model provides an estimation of the error of the zooplankton species numbers with monitoring frequencies.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 추계학술발표회
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• pp.199-201
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• 2003

The monitoring effectiveness not only depends on the effectiveness of the network, but also the costs of the network. Generally the costs of the monitoring network are mainly on the equipment and personnel; the implementation and maintenance; the observation and sample connection; the sample analysis; and the data storage and processing. The cost of the monitoring network can be expressed as a function of monitoring frequency because the monitoring method can be an automatic or a manual measurement. To determine the sampling frequency of subsidiary groundwater monitoring stations, time series data of national groundwater monitoring stations were used. The proposed optimal sampling frequency for subsidiary groundwater monitoring station is about 7 to 20 days and the average frequency is about 2 weeks.

• 한국물환경학회지
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• 제28권3호
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• pp.473-478
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• 2012

To protect human health and manage increasing hazardous chemicals in stream area, it is necessary to expand water quality hazardous items based on risk assessment with proper monitoring data. Also, it is essential to set up the suitable monitoring frequency to produce reliable exposure data to derive water quality guidelines. However, there has been no harmonized monitoring frequency for risk assessment in both domestic and international monitoring systems. In addition, the monitoring frequency for risk assessment has been selected as 'Research needs' in the International Conference on Deriving Environmental Quality Standards for the Protection of Aquatic Ecosystems (EQSPAE) of 2011. In this study, Cases of UNEP/WHO, EU, European countries, USEPA, ANZECC/ARMCANZ, CCME, Japan, and Korea were analyzed to propose the monitoring frequency for risk assessment. Monitoring frequencies depending on environmental conditions, monitoring object, measurement parameters, and monitoring duration were extensively collected. We observed that a monthly monitoring has been applied at most of organizations including EU, USEPA, and UNEP/WHO. In this study, monitoring frequency of minimum 6 times during 3 years were proposed to conduct the risk assessment based on the current domestic status. However, it is necessary to make agreements among interested parties, and perform additional studies about optimal monitoring frequency to protect the aquatic ecosystem and human health in Korean rivers and streams.

• 한국지하수토양환경학회:학술대회논문집
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• 한국지하수토양환경학회 2003년도 추계학술발표회
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• pp.289-292
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• 2003

Laboratory tests were performed to investigate the dielectric property of saturated sands contaminated by heavy metals solution at low frequency. Differences of contamination and the real part of dielectric constant depend on heavy metal concentration was measured at low frequency, 100KHz below. The optimal frequency to develop the detection potentials of monitoring was 1KHz, 10KHz, 100KHz. At this frequency, Heavy metal contamination of saturated sands contamination can be recommended by analysis of complex dielectric constant.

• Journal of Electrical Engineering and Technology
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• 제13권5호
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• pp.1769-1777
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• 2018

This paper proposes a method for optimal placement of Phasor Measurement Units (PMUs) considering system configuration and its attributes during the planning phase of PMU deployment. Each bus of the system is assessed on four diverse attributes; namely, redundancy of measurements, rotor angle and frequency monitoring of generator buses, reactive power deficiency, and maximum loading limit under transmission line outage contingency, and a consolidated 'degree of criticality' is determined using Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The major contribution of the proposed work is the development of modified objective function which incorporates values of the degree of criticality of buses. The problem is formulated as maximization of the aggregate degree of criticality of the system. The resultant PMU configuration extends complete observability of the system and majority of the PMUs are located on critical buses. As budgetary restrictions on utilities may not allow installation PMUs even at optimal locations in a single phase, multi-horizon deployment of PMUs is also addressed. The proposed approach is tested on IEEE 14-bus, IEEE 30-bus, New England (NE) 39-bus, IEEE 57-bus and IEEE 118-bus systems and compared with some existing methods.

• 전기학회논문지P
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• 제61권2호
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• pp.87-92
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• 2012

Voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in a power system. The PMU technique can not easily get the field data and it is impossible to share information, so that there has been used a FNET(Frequency Monitoring Network) method for the wide-area intelligent protection in USA. It consists of FDR(Fault Disturbance Recorder) and IMS(Information Management System). Therefore, FDR must provide an optimal frequency estimation method that is robust to noise and failure. In this paper, we present comparative studies for the frequency estimation method using IRDWT(Improved Recursive Discrete Wavelet Transform), FRDWT(Fast Recursive Discrete Wavelet Transform), and DFT(Discrete Fourier Transform). The Republic of Korea345[kV] power system modeling data by EMTP-RV are used to evaluate the performance of the proposed two kinds of RDWT(Recursive Discrete Wavelet Transform) and DFT. The simulation results show that the proposed frequency estimation technique using FRDWT could be the optimal frequency measurement method, and thus be applied to FDR.

• Diabetes and Metabolism Journal
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• 제42권6호
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• pp.480-487
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• 2018

Background: This study aimed to evaluate the relationship between the frequency of self-monitoring of blood glucose (SMBG) and glycosylated hemoglobin (HbA1c) levels among Korean adolescents with type 1 diabetes mellitus (T1DM). Factors affecting the SMBG frequency were analyzed in order to improve their glycemic control. Methods: Sixty-one adolescents aged 13 to 18 years with T1DM were included from one tertiary center. Clinical and biochemical variables were recorded. Factors associated with SMBG frequency were assessed using structured self-reported questionnaires. Results: Average total daily SMBG frequency was $3.8{\pm}2.1$ and frequency during the school day was $1.3{\pm}1.2$. The mean HbA1c level was $8.6%{\pm}1.4%$. As the daily SMBG frequency increased, HbA1c levels declined (P=0.001). The adjusted odds of achieving the target HbA1c in participants who performed daily SMBG ${\geq}5$ significantly increased 9.87 folds (95% confidence interval [CI], 1.58 to 61.70) compared with those performed SMBG four times a day. In the subjects whose SMBG frequency <1/day during the school day, an 80% reduction in the adjusted odds ratio 0.2 (95% CI, 0.05 to 0.86) showed compared to the group with performing two SMBG measurements in the school setting. The number of SMBG testing performed at school was significantly high for individuals assisted by their friends (P=0.031) and for those who did SMBG in the classrooms (P=0.039). Conclusion: Higher SMBG frequency was significantly associated with lower HbA1c in Korean adolescents with T1DM. It would be necessary to establish the school environments that can facilitate adequate glycemic control, including frequent SMBG.

• Earthquakes and Structures
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• 제15권3호
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• pp.263-273
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• 2018

Operational modal analysis is being widely used in aerospace, mechanical and civil engineering. Common research fields include optimal design and rehabilitation under dynamic loads, structural health monitoring, modification and control of dynamic response and analytical model updating. In many practical cases, influence of noise contamination in the recorded data makes it difficult to identify the modal parameters accurately. In this paper, an improved frequency domain method called Enhanced Least Square Complex Frequency (eLSCF) is developed to extract modal parameters from noisy recorded data. The proposed method makes the use of pre-defined approximate mode shape vectors to refine the cross-power spectral density matrix and extract fundamental frequency for the mode of interest. The efficiency of the proposed method is illustrated using an example five story shear frame loaded by random excitation and different noise signals.

• Smart Structures and Systems
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• 제17권1호
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• pp.135-147
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• 2016

This paper describes a smart structural system, which uses smart materials for real-time monitoring and active control of bolted-joints in steel structures. The goal of this research is to reduce the possibility of failure and the cost of maintenance of steel structures such as bridges, electricity pylons, steel lattice towers and so on. The concept of the smart structural system combines impedance based health monitoring techniques with a shape memory alloy (SMA) washer to restore the tension of the loosened bolt. The impedance-based structural health monitoring (SHM) techniques were used to detect loosened bolts in bolted-joints. By comparing electrical impedance signatures measured from a potentially damage structure with baseline data obtained from the pristine structure, the bolt loosening damage could be detected. An outlier analysis, using generalized extreme value (GEV) distribution, providing optimal decision boundaries, has been carried out for more systematic damage detection. Once the loosening damage was detected in the bolted joint, the external heater, which was bonded to the SMA washer, actuated the washer. Then, the heated SMA washer expanded axially and adjusted the bolt tension to restore the lost torque. Additionally, temperature variation due to the heater was compensated by applying the effective frequency shift (EFS) algorithm to improve the performance of the diagnostic results. An experimental study was conducted by integrating the piezoelectric material based structural health monitoring and the SMA-based active control function on a bolted joint, after which the performance of the smart 'self-monitoring and self-healing bolted joint system' was demonstrated.

• 전기학회논문지
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• 제60권8호
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• pp.1492-1501
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• 2011

A wide-area protection intelligent technique has been used to improve a reliability in power systems and to prevent a blackout. Nowadays, voltage and current phasor estimation has been executed by GPS-based synchronized PMU, which has become an important way of wide-area blackout protection for the prevention of expending faults in power systems. As this technique has the difficulties in collecting and sharing of information, there have been used a FNET method for the wide-area intelligent protection. This technique is very useful for the prediction of the inception fault and for the prevention of fault propagation with accurate monitoring frequency and frequency deviation. It consists of FDRs and IMS. It is well known that FNET can detect the dynamic behavior of system and obtain the real-time frequency information. Therefore, FDRs must adopt a optimal frequency estimation method that is robust to noise and fault. In this paper, we present comparative studies for the frequency estimation method using IRDWT(improved recursive discrete wavelet transform), for the frequency estimation method using FRDWT(fast recursive discrete wavelet transform). we used the Republic of Korea 345kV power system modeling data by EMTP-RV. The user-defined arbitrary waveforms were used in order to evaluate the performance of the proposed two kinds of RDWT. Also, the frequency variation data in various range, both large range and small range, were used for simulation. The simulation results showed that the proposed frequency estimation technique using FRDWT can be the optimal frequency measurement method applied to FDRs.