• Journal of Korean Neurosurgical Society
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• v.44 no.2
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• pp.63-66
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• 2008

Objective : The purpose of this study is to investigate the correlation between various transcranial Doppler (TCD) ultrasonography parameters and clinical vasospasm after aneurysmal subarachnoid hemorrhage (SAH). Methods : This study enrolled 40 patients presented with aneurysmal SAH between September 2006 and August 2007. We measured differences of mean blood flow velocity (BFVm), highest systolic blood flow velocity (BFVh), and Lindegaard ratio (LR) in the middle cerebral artery on TCD examination. These parameters were evaluated for correlation with clinical vasospasm by univariate analysis and the receiver operating characteristic analysis. Results : Twelve patients (30%) developed clinical vasospasm. The best TCD parameters for the detection of clinical vasospasm were revealed to be differences of BFVm, BFVh, and LR values between $1^{st}$ TCD test and $3^{rd}$ TCD (7 cm/s. 11.5 cm/s, 0.45 respectively). The positive predictive value of anyone of three parameters was 60% and the negative predictive value was 100%. Conclusion : TCD is still considered a useful tool for screening clinical vasospasm. To confirm the predictive value of the above parameters. further prospective study will be needed.

• Smart Structures and Systems
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• v.18 no.3
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• pp.449-470
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• 2016

Energy harvesting is an emerging technique that extracts energy from surrounding environments to power low-power devices. For example, it can potentially provide sustainable energy for wireless sensing networks (WSNs) or structural control systems in civil engineering applications. This paper presents a comprehensive study on harvesting energy from earthquake-induced structural vibrations, which is typically of low frequency, to power WSNs. A macroscale pendulum-type electromagnetic harvester (MPEH) is proposed, analyzed and experimentally validated. The presented predictive model describes output power dependence with mass, efficiency and the power spectral density of base acceleration, providing a simple tool to estimate harvested energy. A series of shaking table tests in which a single-storey steel frame model equipped with a MPEH has been carried out under earthquake excitations. Three types of energy harvesting circuits, namely, a resistor circuit, a standard energy harvesting circuit (SEHC) and a voltage-mode controlled buck-boost converter were used for comparative study. In ideal cases, i.e., resistor circuit cases, the maximum electric energy of 8.72 J was harvested with the efficiency of 35.3%. In practical cases, the maximum electric energy of 4.67 J was extracted via the buck-boost converter under the same conditions. The predictive model on output power and harvested energy has been validated by the test data.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.3
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• pp.41-47
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• 2012

Surface roughness is widely used as an index for processing degree of accuracy. Recently, regression analysis to predict the machining results are actively used to characterize a cutting operations. In the past, diamond machining had been used for ultra precision cutting operation, but now industrial diamond tools like PCD(Polycrystaline Diamond) has been widely used in ultraprecision machining of nonferrous metals. In this study, the authors focus on the effect of PCD tool property on the surface roughness of different types of aluminum alloy after cutting process by CNC operated lathe. Based on the regression analysis approach on a surface roughness data obtained by experiment, predictive analysis of surface roughness is effective to achieve better surface quality.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.6
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• pp.69-74
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• 2012

Surface roughness is widely used as an index for processing degree of accuracy. Recently, regression analysis to predict the machining results are actively used to characterize a cutting operations. In the past, diamond machining had been used for ultra precision cutting operation, but now industrial diamond tools like PCD(Polycrystalline Diamond) have been widely used in ultraprecision machining of nonferrous metals. In this study, the authors focus on the effect of PCD tool property on the surface roughness of Al5083 aluminum alloy after cutting process by CNC operated lathe. Based on the regression analysis approach on a surface roughness data obtained by experiment, predictive analysis of surface roughness is effective to achieve better surface quality.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.11-18
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• 2015

PURPOSES : The purpose of this thesis is to evaluate the effectiveness of an active noise cancellation (ANC) system in reducing the traffic noise level against frequencies from the predictive model developed by previous research. The predictive model is based on ISO 9613-2 standards using the Noble close proximity (NCPX) method and the pass-by method. This means that the use of these standards is a powerful tool for analyzing the traffic noise level because of the strengths of these methods. Traffic noise analysis was performed based on digital signal processing (DSP) for detecting traffic noise with the pass-by method at the test site. METHODS : There are several analysis methods, which are generally divided into three different types, available to evaluate traffic noise predictive models. The first method uses the classification standard of 12 vehicle types. The second method is based on a standard of four vehicle types. The third method is founded on 5 types of vehicles, which are different from the types used by the second method. This means that the second method not only consolidates 12 vehicle types into only four types, but also that the results of the noise analysis of the total traffic volume are reflected in a comparison analysis of the three types of methods. The constant percent bandwidth (CPB) analysis was used to identify the properties of different frequencies in the frequency analysis. A-weighting was applied to the DSP and to the transformation process from analog to digital signal. The root mean squared error (RMSE) was applied to compare and evaluate the predictive model results of the three analysis methods. RESULTS : The result derived from the third method, based on the classification standard of 5 vehicle types, shows the smallest values of RMSE and max and min error. However, it does not have the reduction properties of a predictive model. To evaluate the predictive model of an ANC system, a reduction analysis of the total sound pressure level (TSPL), dB(A), was conducted. As a result, the analysis based on the third method has the smallest value of RMSE and max error. The effect of traffic noise reduction was the greatest value of the types of analysis in this research. CONCLUSIONS : From the results of the error analysis, the application method for categorizing vehicle types related to the 12-vehicle classification based on previous research is appropriate to the ANC system. However, the performance of a predictive model on an ANC system is up to a value of traffic noise reduction. By the same token, the most appropriate method that influences the maximum reduction effect is found in the third method of traffic analysis. This method has a value of traffic noise reduction of 31.28 dB(A). In conclusion, research for detecting the friction noise between a tire and the road surface for the 12 vehicle types needs to be conducted to authentically demonstrate an ANC system in the Republic of Korea.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.9
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• pp.5455-5459
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• 2013

Background: The risk of malignancy index (RMI) for the evaluation of adnexal masses is a sensitive tool in certain populations. The best cut off value for RMI 1, 2 and 3 is 200. The cut off value of RMI-4 to differentiate benign from malignant lesions is 450. Our aim was to evaluate the efficiency of four different malignancy indexes (RMI1-4) in a homogeneous population. Materials and Methods: We evaluated a total of 153 non-pregnant women with adnexal masses who did not have a history of malignancy and who were above 18 years of age. Results: A cut-off value of 250 for RMI-1 provided 95.9% inter-observer agreement, yielding 95.9% specificity, 93.5% negative predictive value, 75.0% sensitivity and 82.8% positive predictive value. A cut-off value of 250 for RMI-1 showed high performance in preoperative diagnosis of invasive malignant lesions than cut-off value of 200 in our population. A cut-off value of 350 for RMI-2 provided 94.5% inter-observed agreement, yielding 94.2% specificity, 93.4% negative predictive value, 75.0% sensitivity and 77.4% positive predictive value. RMI-2 showed the higher performance when the cut-off value was set at 350 in our population. A cut-off value of 250 provided 95.2% inter-observer agreement, yielding 95.0% specificity, 93.2% negative predictive value, 75.0% sensitivity, and 88.0% positive predictive value. RMI-3 showed the highest performance to diagnose malignant adnexal masses when the cut-off value was set at 250. In our study, RMI-4 showed similar statistical performance when the cut-off value was set at 400 [(Kappa: 0.684/p=0.000), yielding 93.8% inter-observer agreement, 93.4% specificity, 93.4% negative predictive value, 75.0% sensitivity, and 75.0% negative predictive value]. Conclusions: We showed successful utilization of RMIs in preoperative differentiation of benign from malignant masses. Many studies conducted in Asian and Pacific countries have reported different cut-off values as was the case in our study. We think that it is difficult to determine universally accepted cut-off values for RMIs for common use around the globe.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.7
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• pp.2967-2970
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• 2015

Many patients with few cerebral metastases receive radiosurgery alone. The goal of this study was to create a tool to estimate the survival of such patients. To identify characteristics associated with survival, nine variables including radiosurgery dose, age, gender, Eastern cooperative oncology group performance score (ECOG-PS), primary tumor type, number/size of cerebral metastases, location of cerebral metastases, extra-cerebral metastases and time between cancer diagnosis and radiosurgery were analyzed in 214 patients. On multivariate analysis, age (p=0.03), ECOG-PS (p=0.02) and extra-cerebral metastases (p<0.01) had significant impacts on survival. Scoring points for each patient were obtained from 12-month survival rates (in %) related to the significant variables divided by 10. Addition of the scoring points of the three variables resulted in a patient's total predictive score. Two groups were designed, A (10-14 points) and B (16-17 points). Twelve-month survival rates were 33% and 77%, respectively (p<0.001). Median survival times were 8 and 20 months, respectively. Because most patients of group A died from extra-cerebral disease and/or new cerebral lesions, early systemic treatment and additional WBI should be considered. As cause of death in group B was mostly new cerebral metastases, additional WBI appears even more important for this group.

• Nutrition Research and Practice
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• v.9 no.3
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• pp.268-277
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• 2015

BACKGROUND/OBJECTIVES: Although it is crucial to identify those children likely to be treated in an appropriate nutrition rehabilitation programme and discharge them at the appropriate time, there is no golden standard for such identification. The current study examined the appropriateness of using Mid-Upper Arm Circumference for the identification, follow-up and discharge of malnourished children. We also assessed its discrepancy with the Weight-for-Height based diagnosis, the rate of recovery, and the discharge criteria of the children during nutrition rehabilitation. SUBJECTS/METHODS: The study present findings from 156 children (aged 6-59 months) attending a supplementary feeding programme at Makadara and Jericho Health Centres, Eastern District of Nairobi, Kenya. Records of age, weight, height and mid-upper arm circumference were selected at three stages of nutrition rehabilitation: admission, follow-up and discharge. The values obtained were then used to calculate z-scores as defined by WHO Anthro while estimating different diagnostic indices. RESULTS: Mid-upper arm circumference single cut-off (< 12.5 cm) was found to exhibit high values of sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio at both admission and discharge. Besides, children recorded higher rate of recovery at 86 days, an average increment of 0.98 cm at the rate of 0.14mm/day, and a weight gain of 13.49gm/day, albeit higher in female than their male counterparts. Nevertheless, children admitted on basis of low MUAC had a significantly higher MUAC gain than WH at 0.19mm/day and 0.13mm/day respectively. CONCLUSIONS: Mid-upper arm circumference can be an appropriate tool for identifying malnourished children for admission to nutrition rehabilitation programs. Our results confirm the appropriateness of this tool for monitoring recovery trends and discharging the children thereafter. In principle the tool has potential to minimize nutrition rehabilitation costs, particularly in community therapeutic centres in developing countries.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.11 no.4
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• pp.89-96
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• 2002

This paper aims to develop an intelligent model for predicting top-bead width for the robotic GMA(Gas Metal Arc) welding process using BP(Back-propagation) neural network and multiple regression analysis. Firstly, based on experimental data, the basic factors affecting top-bead width are identified. Then BP neural network model and multiple regression models of top-bead width are established. The modeling methods and procedure are explained. The developed models are then verified by data obtained from the additional experiment and the predictive behaviors of the two kind of models are compared and analysed. Finally the modeling methods, predictive behaviors md the advantages of each models are discussed.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.268-276
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• 2008

In highway construction projects, concrete pavement productivity has been challenged with constructors and decision-makers; at present there are few methods available to accurately evaluate the factors impacting on it. Any inefficient method to analyze it leads to the excessive schedule, higher rehabilitation costs, shorter service life, and reduction of ride quality. To implement these negative outcomes, constructors or decision-makers need a systematic tool that can be used to categorize the factors related to construction productivity. This paper applies multiple regression technique for productivity analysis of the Jointed Plane Concrete Pavement (JPCP), identifies the significant factors, and provides a predictive model assisting in monitoring and managing the productivity of the JPCP construction process. The completed and progressive projects are employed to derive and assess the proposed model. The results are analyzed to illustrate its capabilities.