• Proceedings of the Korean Geotechical Society Conference
• /
• 2002.03a
• /
• pp.49-54
• /
• 2002

This paper describes a systematic way of simultaneously identifying the ambient pore pressure and the rigidity index (=G/s$\_$u/) of soil by applying an optimization technique to the piezocone dissipation test result. An ambient pore pressure and optimal rigidity index were determined by minimizing the differences between theoretical excess pore pressures developed by Randolph ＆ Wroth(1979) and measured excess pore pressures from piezocone using optimization technique. The effectiveness of the proposed back-analysis method was examined against the well-documented performance of piezocone dissipation tests (Tanaka ＆ Sakagami, 1989), from the viewpoints of proper determination of selected target parameters and saving of test duration. It is shown that the proposed back-analysis method can evaluate properly the ambient pore pressure and the rigidity index by using only the early phase of the dissipation test data. Also, it is shown that with the optimized rigidity index and ambient pore pressure the proposed back-analysis method permits the horizontal coefficient of consolidation to be identified rationally.

• World Technopolis Review
• /
• v.6 no.2
• /
• pp.130-147
• /
• 2017

This paper aims to identify the spatial concentrations and linkage properties of industrial clusters in the Chungbuk Province region in Korea using a three-step approach, which is composed of the cluster index, Getis-Ord's $Gi^*$, and qualitative input-output analysis. The results of the study reveal: a) what industrial sectors are concentrated and where they are; b) where the spatially interdependent industries are; and c) how the industrial sectors of the identified clusters in different locations are vertically interconnected. In addition, the degree of strength of the interindustry linkages between industrial clusters are assessed. Based on the findings, some plausible industrial policies are suggested.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.6
• /
• pp.106-118
• /
• 1998

The study concerns a design procedure of rule-based systems. The proposed rule-based fuzzy modeling implements system structure and parameter identification in the efficient from of "IF..., THEN..." statements, and exploits the theory of system optimization and fuzzy implication rules. The method for rule-based fuzzy modeling concerns the from of the conclusion part of the the rules that can be constant. Both triangular and Gaussian-like membership function are studied. The optimization hinges on an autotuning algorithm that covers as a modified constrained optimization method known as a complex method. The study introduces a weighted performance index (objective function) that helps achieve a sound balance between the quality of results produced for the training and testing set. This methodology sheds light on the role and impact of different parameters of the model on its performance. The study is illustrated with the aid of two representative numerical examples.

• The Journal of Korean Medicine
• /
• v.45 no.1
• /
• pp.225-232
• /
• 2024

Objectives: The purpose of this case study was to report the effect of Chuna therapy include Space Spinal Conduction Exercise and Manipulation Treatment for Functional dyspepsia patients. Methods: A 32-years-old male patients with functional dyspepsia visited the clinic ten times from March 17th 2023 to April 22th 2023. To assess the treatment outcomes, we used the Standard tool for pattern identification of Functional dyspepsia and Nepean Dyspepsia Index-Korean version (NDI-K) symptom score. Result: After treatment, Standard tool for pattern identification of Functional dyspepsia and Nepean Dyspepsia Index-Korean version (NDI-K) score decreased. Conclusion: Chuna therapy include Space Spinal Conduction Exercise and Manipulation Treatment was effective in the treatment of patient with Functional dyspepsia.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.20 no.2
• /
• pp.85-89
• /
• 2012

This paper presents a study on the system identification of the in-situ output shaft torque measurement system using a non-contacting magneto-elastic torque transducer installed in a vehicle drivline. The frequency response (transfer) function (FRF) analysis is conducted to interpret the dynamic interaction between the output shaft torque and road side excitation due to the road roughness. In order to identify the frequency response function of vehicle driveline system, two power spectral density (PSD) functions of two random signals: the road roughness profile synthesized from the road roughness index equation and the stationary noise torque extracted from the original torque signal, are first estimated. System identification results show that the output torque signal can be affected by the dynamic characteristics of vehicle driveline systems, as well as the road roughness.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1310-1312
• /
• 1996

In this study, the algorithm for detection of evoked potentials is proposed. The observed evoked potentials are first preprocessed by blind identification so as to eliminate the ongoing EEG Bile noise. Then, statistic characteristics of the peak components i.e latency and amplitude are detected from prefiltered responses by latency-corrected averaging method. The performance of blind identification is compared with those of adaptive fillers as to deterministic and stochastic EPs, is assessed in terms of NMSE, distortion index, correlation coefficient with original EPs. The estimated deterministic and stochastic EPs restored with peak components are compared and assessed. The results show the superiority of this proposed algorithm using blind identification in detecting deterministic and stochastic EPs.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.2 no.2
• /
• pp.111-117
• /
• 2001

Screening of fifteen bivoltine silkworm breeds of Bombyx mori Linn at a temperature of $31{\pm}1^{\circ}C$ and relative humidity of 85${\pm}$5% resulted in the identification of eight thermo-tolerant breeds. The survival and cocoon shell ratio of the tolerant breeds ranged from 72.7 to 78.7% and 20.0 to 20.1% respectively. The tolerant breeds comprised of four oval breeds and four dumb-bell breeds. Eight foundation crosses prepared by crossing the oval and dumb-bell parents among themselves were screened at a temperature of $31{\pm}1^{\circ}C$ and relative humidity of 85{\pm}5%. The performance of the foundation crosses on 11 economic characters were analysed by employing Multipie Trait Evaluation Index method. Four foundation crosses which scored average index value > 50 were selected as breeding parents and breeding initiated for the evolution of thermo-tolerant bivoltine silkworm breeds. The methodology and the results of the foundation crosses reared both at 31{\pm}1$^{\circ}C$ and at $25{\pm}1^{\circ}C$ temperatures, are discussed.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.16 no.1
• /
• pp.15-20
• /
• 2008

Under the all India programme of evaluation of mulberry and silkworm genotypes, twelve bivoltine silkworm breeds obtained from Central Silkworm Germplasm Resource Centre, Hosur (CSGRC) were evaluated at the bivoltine silkworm breeding laboratory, Central Sericultural Research & Training Institute, Mysore (CSR&TI). These breeds were tested during September-October 2003, August-September 2004 and February-March 2005. The average temperature and humidity during September-October 2003 was $26.5^{\circ}C$ and 72.6% RH, while during August-September 2004, it was $26.5^{\circ}C$ and 75.2% RH and during February-March 2005 it was $24^{\circ}C$ and 48% RH respectively. The performance of the breeds in respect of 21 traits was studied and statistically analyzed using analysis of variance (Singh and Choudhary, 1985). Silkworm breeds were short-listed using multiple trait evaluation index method as suggested by Mano et at., (1993). Evaluation Index values were calculated for all the 11 traits of economic importance and six breeds were short-listed based on average index value 50 and above 50. Two breed viz., BV 183 (SMGS-1) have recorded average E.I. >50 in 10 traits (except in neatness) and ranked first and the breed BV 262 (SMGS9) with E.I. value >50 in nine traits except in cocoon weight and neatness ranked second, in the order of merit. These two breeds may be selected as resource material for evolving region specific silkworm breeds.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.12
• /
• pp.1-8
• /
• 2015

Wear leveling techniques have been studied to prolong the lifetime of NAND flash memory. Most of studies have used Program/Erase(P/E) cycles as wear index for wear leveling. Unfortunately, P/E cycles could not predict the real lifetime of NAND flash blocks. Therefore, these algorithms have the limited performance from prolonging the lifetime when applied to the SSD. In order to apply the real lifetime, wear leveling algorithms, which use raw Bit Error Rate(rBER) as wear index, have been studied in recent years. In this paper, we propose CrEWL(Cold data identification using raw Bit error rate in Wear Leveling), which uses rBER as wear index to apply to the real lifetime. The proposed wear leveling reduces an overhead of garbage collections by using HBSQ(Hot Block Sequence Queue) which identifies hot data. In order to reduce overhead of wear leveling, CrEWL does not perform wear leveling until rBER of the some blocks reaches a threshold value. We evaluate CrEWL in comparison with the previous studies under the traces having the different Hot/Cold rate, and the experimental results show that our wear leveling technique can reduce the overhead up to 41% and prolong the lifetime up to 72% compared with previous wear leveling techniques.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.43 no.6
• /
• pp.877-884
• /
• 1994

In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.