• The Journal of the Convergence on Culture Technology
• /
• v.4 no.3
• /
• pp.299-303
• /
• 2018

Generally, when predicting the accuracy of the anti-air artillery system, the error is classified as fixed bias, variable bias, and random error. Then the standard deviation on the target is expressed as the square root of the squared sum of each error value which comes from the random error and variable bias and in the case of fixed bias, the mean value is shifted as the sum of errors from the fixed bias. At this time, the variables indicating the displacement of the direction of azimuth and elevation direction with regard to the change of the unit value of each error are weighted. These errors are then used to predict the system's delivery accuracy through a normally distributed integral. This paper presents a method of predicting system accuracy by considering the correlation of errors. This approach shows that it helps to predict the delivery accuracy of the system, precisely.

• The KIPS Transactions:PartB
• /
• v.10B no.4
• /
• pp.419-428
• /
• 2003

Recently, digital watermarking has been proposed as a viable solution to the need of copyright protection and authentication of multimedia data. A robust wavelet-based watermark casting scheme and a watermark retrieval technique are suggested in this paper. We present a method which can add the watermark to the significant coefficients in the DWT domain, and does not require the original image in the detection process. In adaptive watermark casting method is developed to select perceptually significant coefficients for each subband using multiple threshold. In the proposed method, an adaptive multiple threshold scheme is used to reflect characteristics of each subband and complexity of image. The watermark is adaptively weighted in different subbands to achieve robustness as well as high perceptual quality. The watermark, Gaussian random sequence is added to the large coefficients but not in the lowest subband in the DWT domain. Experimental results show that the proposed algorithm produced visually very good watermarked image which has good invisibility to human eyes and very robust against various image processing and compression attacks.

• Journal of the Korean Society for Advanced Composite Structures
• /
• v.1 no.2
• /
• pp.29-35
• /
• 2010

In addition to the Young's modulus, the Poisson's ratio is also at the center of attention in the field stochastic finite element analysis since the parameters play an important role in determining structural behavior. Accordingly, the sole effect of this parameter on the response variability is of importance from the perspective of estimation of uncertain response. To this end, a formulation to determine the response variability in laminate composite plates due to the spatial randomness of Poisson's ratio is suggested. The independent contributions of random Poisson's ratiocan be captured in terms of sub-matrices which include the effect of the random parameter in the same order, which can be attained by using the Taylor's series expansion about the mean of the parameter. In order to validate the adequacy of the proposed formulation, several example analyses are performed, and then the results are compared with Monte Carlo simulation (MCS). A good agreement between the suggested scheme and MCS is observed showing the adequacy of the scheme.

• Asian Pacific Journal of Cancer Prevention
• /
• v.15 no.16
• /
• pp.6643-6647
• /
• 2014

The breast and the thyroid are hormone responsive organs that are closely related with changes of endocrine function and glandular disease. An association between thyroid disorders and breast cancer (BC) risk has been suggested, although the results are inconclusive. The purpose of the present study was to summarize evidence supporting a relationship between BC and the level of thyroid hormones and antibodies. The MEDLINE and EMBASE electronic databases were searched for studies published between 2000 and 2014. The pooled effects were presented as weighted mean differences (WMD) with 95% confidence intervals (CI) using fixed or random effect models. We summarized the results of 8 cross-sectional studies with 4, 189 participants. The overall pooled results showed that the levels of $FT_3$ and $FT_4$ were significantly increased in patients with BC (WMD=1.592 pmol/l; 95% CI: 0.15-3.033 and WMD=0.461 ng/dl; 95% CI: 0.015-0.906; p=0.043). The TPOAb level in patients with BC was higher than that in the control group (WMD=81.4 IU/ml; 95% CI: 78.7-84.0; p=0.000). The overall pooled results of the TgAb with random effects analyses showed that the TgAb level was significantly increased in patients with BC (WMD=101.3 IU/ml; 95% CI: 48.7-153.9; p=0.000). The present results indicated that the serum levels of $FT_3$, TPOAb and TgAb are significantly higher in patients with breast cancer than in healthy controls.

• Computers and Concrete
• /
• v.21 no.4
• /
• pp.407-417
• /
• 2018

Concrete which is a composite material is one of the most important construction materials. Compressive strength is a commonly used parameter for the assessment of concrete quality. Accurate prediction of concrete compressive strength is an important issue. In this study, we utilized an experimental procedure for the assessment of concrete quality. Firstly, the concrete mix was prepared according to C 20 type concrete, and slump of fresh concrete was about 20 cm. After the placement of fresh concrete to formworks, compaction was achieved using a vibrating screed. After 28 day period, a total of 100 core samples having 75 mm diameter were extracted. On the core samples pulse velocity determination tests and compressive strength tests were performed. Besides, Windsor probe penetration tests and Schmidt hammer tests were also performed. After setting up the data set, twelve artificial intelligence (AI) models compared for predicting the concrete compressive strength. These models can be divided into three categories (i) Functions (i.e., Linear Regression, Simple Linear Regression, Multilayer Perceptron, Support Vector Regression), (ii) Lazy-Learning Algorithms (i.e., IBk Linear NN Search, KStar, Locally Weighted Learning) (iii) Tree-Based Learning Algorithms (i.e., Decision Stump, Model Trees Regression, Random Forest, Random Tree, Reduced Error Pruning Tree). Four evaluation processes, four validation implements (i.e., 10-fold cross validation, 5-fold cross validation, 10% split sample validation & 20% split sample validation) are used to examine the performance of predictive models. This study shows that machine learning regression techniques are promising tools for predicting compressive strength of concrete.

• International Journal of Industrial Entomology and Biomaterials
• /
• v.29 no.2
• /
• pp.169-178
• /
• 2014

In this study, we investigated genetic diversity of 22 microsporidian isolates infecting tropical tasar silkworm, Antheraea mylitta collected from various geographical forest locations in the state of Jharkhand, India, using polymerase chain reaction (PCR)-based marker assay: random amplified polymorphic DNA (RAPD). A type species, NIK-1s_mys was used as control for comparison. The shape of mature microsporidians was found to be oval to elongate, measuring 3.80 to $5.10{\mu}m$ in length and 2.56 to $3.30{\mu}m$ in width. Of the 20 RAPD primers screened, 16 primers generated reproducible profiles with 298 polymorphic fragments displaying high degree of polymorphism (97%). A total of 14 RAPD primers produced 45 unique putative genetic markers, which were used to differentiate the microsporidians. Calculation of genetic distance coefficients based on dice coefficient method and clustering with un-weighted pair group method using arithmetic average (UPGMA) analysis was conducted to unravel the genetic diversity of microsporidians infecting tasar silkworm. The similarity coefficients varied from 0.059 to 0.980. UPGMA analysis generated a dendrogram with four microsporidian groups, which appear to be different from each other as well as from NIK-1s_mys. Two-dimensional distribution based on Euclidean distance matrix also revealed considerable variability among different microsporidians identified from the tasar silkworms. Clustering of few microsporidian isolates was in accordance with the geographic origin. The results indicate that the RAPD profiles and specific/unique genetic markers can be used for differentiating as well as to identify different microsporidians with considerable accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.2 no.6
• /
• pp.312-332
• /
• 2008

Password-based authentication key exchange (PAKE) protocols in the literature typically assume a password that is shared between a client and a server. PAKE has been applied in various environments, especially in the “client-server” applications of remotely accessed systems, such as e-banking. With the rapid developments in modern communication environments, such as ad-hoc networks and ubiquitous computing, it is customary to construct a secure peer-to-peer channel, which is quite a different paradigm from existing paradigms. In such a peer-to-peer channel, it would be much more common for users to not share a password with others. In this paper, we consider password-based authentication key exchange in the three-party setting, where two users do not share a password between themselves but only with one server. The users make a session-key by using their different passwords with the help of the server. We propose an efficient password-based authentication key exchange protocol with different passwords that achieves forward secrecy in the standard model. The protocol requires parties to only memorize human-memorable passwords; all other information that is necessary to run the protocol is made public. The protocol is also light-weighted, i.e., it requires only three rounds and four modular exponentiations per user. In fact, this amount of computation and the number of rounds are comparable to the most efficient password-based authentication key exchange protocol in the random-oracle model. The dispensation of random oracles in the protocol does not require the security of any expensive signature schemes or zero-knowlegde proofs.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.101-101
• /
• 2019

전 지구적 기온상승으로 인한 기후변화는 사회적, 수문학적, 다양한 분야에 영향을 미친다. 또한 IPCC(Intergovernmental Panel on Climate Change)의 보고서에 따르면 미래에도 지속적으로 기온상승이 예상되며, 이러한 현상은 인류의 삶에 큰 영향을 미칠것으로 예상된다. 또한 수자원 및 관련 분야에서도 기온 상승에 따른 강수량, 강수의 주기 변동, 극한 기후사상의 심도(severity)와 빈도 변화에 따른 다양한 연구가 진행되고 있으며, 미래의 강우량과 온도를 예측하는 기후변화연구에서는 다양한 기후모형을 고려하여 분석한다. 하지만 모든 기후모형이 우리나라에 적합한 것은 아니므로 과거 기후를 모의한 결과를 토대로 성능이 뛰어난 모형의 결과에 더 높은 가중치를 주고 미래를 예측하는 연구가 활발히 진행되고 있다. 일반적으로 기후모형으로 GCM (General Circulation Model) 모의 결과가 이용되는데 우리나라에 대한 GCM 결과의 정확성을 분석하는 연구는 부족한 실정이다. 따라서 본 연구에서는 21개의 GCM을 대상으로 과거 모의 자료(1970년~2005년)를 실제 관측소에서 관측된 강수량과 비교하여 각 GCM들의 성능을 평가하고 이를 토대로, GCM들의 우선순위를 선정하였다. 또한 격자 기반 GCM 결과를 IDW (Inverse Distance Weighted) 방법을 사용하여 기상관측소로 지역적 상세화를 수행하였으며, GCM과 관측자료 사이의 편이를 보정하기 위해 6가지의 Quantile Mapping 방법과 Random Forest 기법을 사용하였다. 또한 편이 보정 기법 중 성능이 좋은 기법을 선택하여 관측소에 적용하였다. 편이 보정된 GCM 모의결과에 대한 성능을 토대로 우수한 GCM 순위를 도출하기 위해 다기준의사결정기법 중 하나인 TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)를 이용하였다. 그리고 GCM의 전망기간인 2010년부터 2018년까지의 Machine learning 방법과 Quantile mapping의 기법을 비교 및 성능이 우수한 편이 보정 방법을 선택한 후 전망기간 동안의 GCM 성능의 우선순위를 선정하였다.

• Nuclear Engineering and Technology
• /
• v.54 no.1
• /
• pp.49-60
• /
• 2022

Motivated by the high-resolution properties of high-order Weighted Essentially Non-Oscillatory (WENO) and flux limiter (FL) for steep-gradient problems and the robust convergence of Jacobian-free Newton-Krylov (JFNK) methods for nonlinear systems, the preconditioned JFNK fully implicit high-order WENO and FL schemes are proposed to solve the transient two-phase two-fluid models. Specially, the second-order fully-implicit BDF2 is used for the temporal operator and then the third-order WENO schemes and various flux limiters can be adopted to discrete the spatial operator. For the sake of the generalization of the finite-difference-based preconditioning acceleration methods and the excellent convergence to solve the complicated and various operational conditions, the random vector instead of the initial condition is skillfully chosen as the solving variables to obtain better sparsity pattern or more positions of non-zero elements in this paper. Finally, the WENO_JFNK and FL_JFNK codes are developed and then the two-phase steep-gradient problem, phase appearance/disappearance problem, U-tube problem and linear advection problem are tested to analyze the convergence, computational cost and efficiency in detailed. Numerical results show that WENO_JFNK and FL_JFNK can significantly reduce numerical diffusion and obtain better solutions than traditional methods. WENO_JFNK gives more stable and accurate solutions than FL_JFNK for the test problems and the proposed finite-difference-based preconditioning acceleration methods based on the random vector can significantly improve the convergence speed and efficiency.

• The Journal of Korean Academy of Sensory Integration
• /
• v.15 no.2
• /
• pp.46-65
• /
• 2017

Objective : The purpose of this research is to find clinical effects of application of weighted vest during task-oriented training focused on gross motor performance and balance abilities of children with spastic diplegia. Methods : 34 subjects were divided by simple random sampling into two groups; experimental group (male : 9, female : 8, average age : 8.12) and placebo group (male : 9, female : 9, average age : 7.53). Both two groups underwent to 40 minute intervention, twice a week for 12 weeks. The intervention was task-oriented training focused on facilitating closed kinematic chain and multi-joint functional movement pattern. During the training, the experimental group received loaded-resistance weighted vest and placebo group also received weighted vest but without loaded-resistance. Participants in both groups underwent 8 to 10 reps of the task-oriented training and there were 3 minutes break time between tasks. There were pre-test of gross motor performance and balance abilities, and two times of post-tests were performed upon 6 weeks and 12 weeks after the intervention completed. And in final, an additional follow-up test was performed 12 weeks after the evaluation was finished in order to find any difference between the two groups over time. Results : There was significant difference in Gross Motor Performance Measure (GMPM) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). There was significant difference in Pediatric Berg's Balance Scale (PBS) between two groups. It is found that average score of the experimental group increased more than the placebo group after 6 weeks and 12 weeks intervention (p<.05). Conclusion : Based on the results in this study, it is proposed that application of weighted vest into task-oriented training to facilitating closed kinematic chain and multi-joint movement can improve gross motor performance and balance abilities of children with cerebral palsy.