• Women's Health Nursing
• /
• v.15 no.4
• /
• pp.312-319
• /
• 2009

Purpose: The purpose of this study was to determine the discriminant factors of attitude pattern toward sexual violence of college women. Methods: A cross-sectional research design with non-probability samples was conducted. A total of 292 college women participated. The instruments were Attitude Pattern toward Sexual Violence, Self-Esteem Scale, Gender Role Scale, and Attitude toward Sexuality. Dependent variable is Attitude Pattern toward Sexual Violence, which is composed of two groups; cases either harmer blame or sufferer blame. Independent variables were self-esteem, attitude toward gender role, and attitude toward sexuality. Data were analyzed by SPSS WIN program and descriptive analysis, $x^2$-test, and discriminant analysis. Results: To assess the adequacy of classification, the overall hit ratio was 68.5%, and the significant predictor variable was attitude toward sexuality. Conclusion: Replication of the study needs to be considered to further enrich the specific knowledge base regarding attitude toward sexual violence among college women.

• Structural Engineering and Mechanics
• /
• v.80 no.6
• /
• pp.711-726
• /
• 2021

This paper presents a multiple parameters-based recursive methodology for the reliability quantification of civil structures subjected to meteorological disasters. Recognizing the challenge associated with characterizing at a single stroke all the meteorological disasters that may hit a structure during its service life, the proposed methodology by contrast features a multiparameter recursive mechanism to describe the meteorological demand of the structure. The benefit of the arrangements is that the essentially inevitable deviation of the practically observed meteorological data from those in the existing model can be mitigated in an adaptive manner. In particular, the implications of potential climate change to the relevant reliability of civil structures are allowed for. The application of the formulated methodology of recursive reliability quantification is illustrated by first considering the reliability quantification of a linear shear frame against simulated strong wind loads. A parametric study is engaged in this application to examine the effect of some hyperparameters in the configured hierarchical model. Further, the application is extended to a nonlinear hysteretic shear frame involving some field-observed cyclone data, and the incompleteness of the relevant structural diagnosis data that may arise in reality is taken into account. Also investigated is another application scenario where the reliability of a building envelope is assessed under hailstone impacts, and the emphasis is to demonstrate the recursive incorporation of newly obtained meteorological data.

• Journal of the Society of Naval Architects of Korea
• /
• v.55 no.2
• /
• pp.93-102
• /
• 2018

Quantitative Risk Assessment (QRA) has been used in shipping and offshore industries for many years, supporting the decision-making process to guarantee safe running at different stages of design, fabrication and throughout service life. The assessments of a risk perspective are informed by the frequency of events (probability) and the associated consequences. As the number of offshore platforms increases, so does the length of subsea pipelines, thus there is a need to extend this approach and enable the subsea industry to place more emphasis on uncertainties. On-board operations can lead to objects being dropped on subsea pipelines, which can cause leaks and other pipeline damage. This study explains how to conduct hit frequency analyses of subsea pipelines, using historical data, and how to obtain a finite number of scenarios for the consequences analysis. An example study using probabilistic methods is used.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.7
• /
• pp.730-738
• /
• 1992

This paper alms to analyse the performance of frequency hopping /spread spectrum multiple access system by employing the channel with mixture of AWGN, partial band Jamming, fading and user interference. The performance analysis of FH /SSMA system, taking account of frequency 'hit'(user Interference ) which occurs in the presence of multiple user, produces the following numerical results by computing error probability and throughput of each code in two cases whether the side Information about channel is used or not. The numerical results are as follows : When composite interferences coexist In channel, RS code Is significantly superior to convolutional code in terms of performance. Concatenated code provides the same performance as RS code. The above results show that RS code is pertinent as error-correction code.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.3
• /
• pp.941-955
• /
• 2015

In dual-channel networks (DCNs), all frequency hopping (FH) sequences used for data channels are chosen from the original FH sequence used for the control channel by shifting different initial phases. As the number of data channels increases, the hitting frequency point problem becomes considerably serious because DCNs is non-orthogonal synchronization network and FH sequences are non-orthogonal. The increasing severity of the hitting frequency point problem consequently reduces the resource utilization efficiency. To solve this problem, we propose a novel hitting frequency point collision avoidance method, which consists of a sequence-selection strategy called sliding correlation (SC) and a collision avoidance strategy called keeping silent on hitting frequency point (KSHF). SC is used to find the optimal phase-shifted FH sequence with the minimum number of hitting frequency points for a new data channel. The hitting frequency points and their locations in this optimal sequence are also derived for KSHF according to SC strategy. In KSHF, the transceivers transmit or receive symbol information not on the hitting frequency point, but on the next frequency point during the next FH period. Analytical and simulation results demonstrate that unlike the traditional method, the proposed method can effectively reduce the number of hitting frequency points and improve the efficiency of the code resource utilization.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.13 no.2
• /
• pp.120-126
• /
• 1988

In this paper the performance of the asynchronous Repeated FH/MFSK system for the CDMA(Code Division Multiple Access) was analyzed. Actually there was no difference in the probabilities of hit of frequency between Random Coding method and frequency hopping pattern vector suggested by Einarsso. Actual situation was adopted as a model in thie simulation, on the assumption thet;a:there was no Noise, Multipath propagation, b:there was only mutual interference. c:the number of users M was given. Also it was found that there is almost no deviation between the value calculated from the formula of word error probability expressed by bound and that obtained from this simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
• /
• v.15 no.11 s.104
• /
• pp.1303-1310
• /
• 2005

Stabilization error of target aiming systems mounted on moving vehicles is an important performance because the error directly affects hit Probability. In a heavy load targetaiming system, the disturbance torque comes from mass unbalance and linear acceleration is a main source of stabilization error. This study suggests an experimental design method of disturbance feedforward compensation control to improve the stabilization performance of heavy load target aiming systems. The filtered_x least square(FxLMS) algorithm is used to estimate the compensator coefficients adaptively. The proposed control is applied to a simple experimental set-up which simulates dynamic characteristics of a real target aiming system. The feasibility of the proposedtechnique is illustrated, along with results of experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.7
• /
• pp.1610-1623
• /
• 2013

In-network caching is a key component of information-centric networking (ICN) for reducing content download time, network traffic, and server workload. Data center network (DCN) is an ideal candidate for applying the ICN design principles. In this paper, we have evaluated the effectiveness of caching placement and replacement in DCN with butterfly-topology. We also suggest a new cache placement policy based on the number of routing nodes (i.e., hop counts) through which travels the content. With a probability inversely proportional to the hop counts, the caching placement policy makes each routing node to cache content chunks. Simulation results lead us to conclude (i) cache placement policy is more effective for cache performance than cache replacement, (ii) the suggested cache placement policy has better caching performance for butterfly-type DCNs than the traditional caching placement policies such as ALWASYS and FIX(P), and (iii) high cache hit ratio does not always imply low average hop counts.

• Journal of Intelligence and Information Systems
• /
• v.23 no.1
• /
• pp.127-141
• /
• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of Distribution Science
• /
• v.12 no.11
• /
• pp.77-83
• /
• 2014

Purpose - The National Agricultural Cooperative Federation of Korea and National Fisheries Cooperative Federation of Korea have prosecuted both financial and retail businesses. As cooperatives are public institutions and receive government support, their sound management is required by the Financial Supervisory Service in Korea. This is mainly managed by CAEL, which is changed by CAMEL. However, NFFC's business section, managing the finance and retail businesses, is unified and evaluated; the CAEL model has an insufficient classification to evaluate the retail industry. First, there is discrimination power as regards CAEL. Although the retail business sector union can receive a higher rating on a CAEL model, defaults have often been reported. Therefore, a default prediction model is needed to support a CAEL model. As we have the default prediction model using a subdivision of indexes and statistical methods, it can be useful to have a prevention function through the estimation of the retail sector's default probability. Second, separating the difference between the finance and retail business sectors is necessary. Their businesses have different characteristics. Based on various management indexes that have been systematically managed by the National Fisheries Cooperative Federation of Korea, our model predicts retail default, and is better than the CAEL model in its failure prediction because it has various discriminative financial ratios reflecting the retail industry situation. Research design, data, and methodology - The model to predict retail default was presented using logistic analysis. To develop the predictive model, we use the retail financial statements of the NFCF. We consider 93 unions each year from 2006 to 2012 to select confident management indexes. We also adapted the statistical power analysis that is a t-test, logit analysis, AR (accuracy ratio), and AUROC (Area Under Receiver Operating Characteristic) analysis. Finally, through the multivariate logistic model, we show that it is excellent in its discrimination power and higher in its hit ratio for default prediction. We also evaluate its usefulness. Results - The statistical power analysis using the AR (AUROC) method on the short term model shows that the logistic model has excellent discrimination power, with 84.6%. Further, it is higher in its hit ratio for failure (prediction) of total model, at 94%, indicating that it is temporally stable and useful for evaluating the management status of retail institutions. Conclusions - This model is useful for evaluating the management status of retail union institutions. First, subdividing CAEL evaluation is required. The existing CAEL evaluation is underdeveloped, and discrimination power falls. Second, efforts to develop a varied and rational management index are continuously required. An index reflecting retail industry characteristics needs to be developed. However, extending this study will need the following. First, it will require a complementary default model reflecting size differences. Second, in the case of small and medium retail, it will need non-financial information. Therefore, it will be a hybrid default model reflecting financial and non-financial information.