• Communications for Statistical Applications and Methods
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• 제26권1호
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• pp.11-25
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• 2019

The present paper utilizes auxiliary information to neutralize the effect of non-response for estimating the population mean. Improved ratio type estimators for population mean have been proposed and their properties are studied. These estimators are suggested for both single phase sampling and two phase sampling in presence of non-response. Empirical studies are conducted to validate the theoretical results and demonstrate the performance of the proposed estimators. The proposed estimators are shown to perform better than those used by Cochran (Sampling Techniques (3rd ed), John Wiley & Sons, 1977), Khare and Srivastava (In Proceedings-National Academy Science, India, Section A, 65, 195-203, 1995), Rao (Randomization Approach in Incomplete Data in Sample Surveys, Academic Press, 1983; Survey Methodology 12, 217-230, 1986), and Singh and Kumar (Australian & New Zealand Journal of Statistics, 50, 395-408, 2008; Statistical Papers, 51, 559-582, 2010) under the derived optimality condition. Suitable recommendations are put forward for survey practitioners.

• Communications for Statistical Applications and Methods
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• 제28권5호
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• pp.493-510
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• 2021

The present article endeavours to develop partial optional randomized - response technique (PORT) to deal with sensitive issues in presence of non-response in successive sampling. Calibration techniques have been embedded with PORT to estimate sensitive population mean at current move in two move successive sampling in presence of non-response. Optimum calibration weights are computed at each move with the aid of constraints based on auxiliary information. Detailed properties of the proposed estimators have been discussed. Possible cases in which non-response may creep at two moves has been explored. The proposed technique has been compared with the modified existing technique. Simulation results indicate that the proposed technique is more efficient than existing, modified one. Suitable recommendations are forwarded.

• International journal of advanced smart convergence
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• 제12권4호
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• pp.344-352
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• 2023

The purpose of this study is to empirically grasp the relationship between website immersion and website attitude by the attribute factors of the Taekwondo information website and provide it as basic data for effective operation of the Taekwondo information website. The subjects of this study were Taekwondo athletes enrolled in high schools and universities affiliated with the Korean Taekwondo Association, and the sampling method was sampled using the convient sampling method, a non-probability sampling method. Of the 820 questionnaires finally obtained, 789 were processed using PASW Statistics 20.0 and AMOS, except for 31 that were deemed to have poor respondents' contents or were not valuable as data. For data analysis, the statistical analysis techniques used in this study were frequency analysis, factor analysis, Cronbach's α test, correlation analysis, and structural equation model analysis (SEM), and the significance level of the research hypothesis was α=.It was verified at 05. The following conclusions were drawn through such research methods and procedures. First, information, entertainment, structure, cognition, searchability, and connectivity of Taekwondo information website attributes affect website immersion. Second, website immersion is affecting website attitudes.

• 산업경영시스템학회지
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• 제46권3호
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• pp.139-147
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• 2023

The metal bush assembling process is a process of inserting and compressing a metal bush that serves to reduce the occurrence of noise and stable compression in the rotating section. In the metal bush assembly process, the head diameter defect and placement defect of the metal bush occur due to metal bush omission, non-pressing, and poor press-fitting. Among these causes of defects, it is intended to prevent defects due to omission of the metal bush by using signals from sensors attached to the facility. In particular, a metal bush omission is predicted through various data mining techniques using left load cell value, right load cell value, current, and voltage as independent variables. In the case of metal bush omission defect, it is difficult to get defect data, resulting in data imbalance. Data imbalance refers to a case where there is a large difference in the number of data belonging to each class, which can be a problem when performing classification prediction. In order to solve the problem caused by data imbalance, oversampling and composite sampling techniques were applied in this study. In addition, simulated annealing was applied for optimization of parameters related to sampling and hyper-parameters of data mining techniques used for bush omission prediction. In this study, the metal bush omission was predicted using the actual data of M manufacturing company, and the classification performance was examined. All applied techniques showed excellent results, and in particular, the proposed methods, the method of mixing Random Forest and SA, and the method of mixing MLP and SA, showed better results.

• 제어로봇시스템학회논문지
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• 제22권9호
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• pp.710-715
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• 2016

Due to its simplicity and high reliability, the box-counting(BC) method is one of the most frequently used techniques to estimate the fractal dimensions of a binary image with a self-similarity property. The fractal calculation requires data sampling that determines the size of boxes to be sampled from the given image and directly affects the accuracy of the fractal dimension estimation. There are three non-overlapping regular grid methods: geometric-step method, arithmetic-step method and divisor-step method. These methods have some drawbacks when the image size M becomes large. This paper presents a BC algorithm for enhancing the accuracy of the fractal dimension estimation based on a new sampling method. Instead of using the geometric-step method, the new sampling method, called the coverage ratio-step method, selects the number of steps according to the coverage ratio. A set of experiments using well-known fractal images showed that the proposed method outperforms the existing BC method and the triangular BC method.

• 대한기계학회논문집B
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• 제23권9호
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• pp.1139-1150
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• 1999

The evolution of silica aggregate particles in coflow diffusion flames has been studied experimentally using light scattering and thermophoretic sampling techniques. The measurements of scattering cross section from $90^{\circ}$ light scattering have been utilized to calculate the aggregate number density and volume fraction using with combination of measuring the particle size and morphology through the localized sampling and a TEM image analysis. Aggregate or particle number densities and volume fractions were calculated using Rayleigh-Debye-Gans and Mie theory for fractal aggregates and spherical particles, respectively. Of particular interests are the effects of flame temperature on the evolution of silica aggregate particles. As the flow rate of $H_2$ increases, the primary particle diameters of silica aggregates have been first decreased, but, further increase of $H_2$ flow rate causes the diameter of primary particles to increase and for sufficiently larger flow rates, the fractal aggregates finally become spherical particles. The variation of primary particle size along the upward jet centerline and the effect of burner configuration have also been studied.

• 전자공학회논문지
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• 제50권10호
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• pp.98-104
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• 2013

본 논문에서는 무선 통신 및 근거리 위치 인식이 가능한 WBAN(wireless body area network) 용 UWB(Ultra-wide band) 수신기 회로를 제안한다. UWB 수신기는 에너지 검출 방식의 OOK(on-off keying) 변조가 가능하도록 설계가 되었다. 고속의 sampling 을 하기 위해서 4bit ADC 는 DLL(delay locked loop) 을 이용하여 sub-sampling 기법을 사용하도록 설계되었다. 제안된 UWB 수신기는 CMOS $0.18{\mu}m$ 공정을 이용하여 설계되었으며, 전원 전압 1.8V에서 61mA의 전류를 소모하면서 -85.7dBm의 수신 감도, 42.1dB의 RF front-end 게인, 3.88 dB의 noise figure, 최대 4m 까지의 거리 감지 성능을 가지고 있다.

• Bulletin of the Korean Chemical Society
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• 제34권8호
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• pp.2353-2357
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• 2013

The objective of this study was to develop a simple, less time-consuming and accurate sampling technique based on solid-phase sorption with activated carbon as the sorbents. The results from solid-phase sorption techniques were compared to that from a conventional solvent impinger-based technique to confirm the efficacy of the proposed method. The laboratory results indicated that the solid-phase sorption method was suitable for the determination of siloxanes as the measured concentrations were similar to that from a solvent impinge method. The data from solid-phase sorption method showed excellent recovery and reproducibility while the sampling was less labor intensive and less time consuming than the solvent impinge method. Following the laboratory tests, the solid-phase sorption technique was successfully applied to sampling biogas from a field site. This study shows that the activated carbon-based solid-phase sorption can be a reliable and less time-consuming option for the sampling and collection of siloxanes under various different landfill conditions.

• International Journal of Internet, Broadcasting and Communication
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• 제11권4호
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• pp.37-42
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• 2019

In this paper, we explore the details of three classic data augmentation methods and two generative model based oversampling methods. The three classic data augmentation methods are random sampling (RANDOM), Synthetic Minority Over-sampling Technique (SMOTE), and Adaptive Synthetic Sampling (ADASYN). The two generative model based oversampling methods are Conditional Generative Adversarial Network (CGAN) and Wasserstein Generative Adversarial Network (WGAN). In imbalanced data, the whole instances are divided into majority class and minority class, where majority class occupies most of the instances in the training set and minority class only includes a few instances. Generative models have their own advantages when they are used to generate more plausible samples referring to the distribution of the minority class. We also adopt CGAN to compare the data augmentation performance with other methods. The experimental results show that WGAN-based oversampling technique is more stable than other approaches (RANDOM, SMOTE, ADASYN and CGAN) even with the very limited training datasets. However, when the imbalanced ratio is too small, generative model based approaches cannot achieve satisfying performance than the conventional data augmentation techniques. These results suggest us one of future research directions.

• 한국항공운항학회지
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• 제27권2호
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• pp.1-8
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• 2019

Optimal path planning refers to find the safe route to the destination at a low cost, is a major problem with regard to autonomous navigation. Sampling Based Planning(SBP) approaches, such as Rapidly-exploring Random Tree Star($RRT^*$), are the most influential algorithm in path planning due to their relatively small calculations and scalability to high-dimensional problems. $RRT^*$-Smart introduced path optimization and biased sampling techniques into $RRT^*$ to increase convergent rate. This paper presents an improvement plan that has changed the biased sampling method to increase the initial convergent rate of the $RRT^*$-Smart, which is specified as m$RRT^*$-Smart. With comparison among $RRT^*$, $RRT^*$-Smart and m$RRT^*$-Smart in 2 & 3-D environments, m$RRT^*$-Smart showed similar or increased initial convergent rate than $RRT^*$ and $RRT^*$-Smart.