Logistic enterprises want to be competitive enterprises in fierce logistic market and worry about the securement of discriminative competitiveness for it. The standards for the judgement of logistic industry’s maintenance of competitiveness are not only economic feasibility of logistic costs but also the satisfaction of users because well-established service system for variety and enhancement of logistic needs. Some of the quality attributes sufficiently satisfy expectation of customers, but not guarantee high-quality satisfaction. Therefore, it’s difficult to grasp quality attributes with the existing approach of perceived service quality. Quality attribute model suggested by Kano is widely used as the concept is accurate, there is high possibility to be used at the stage of product/service planning, and it can be easily applied. Kano model has a limitation that quality attributes are classified with mode and the differences between strong property of the quality attribute and week property in quality attributes were ignored. Therefore, Timko calculated customer satisfaction coefficient with the result of Kano’s survey and effects of customer satisfaction and unsatisfaction through relations between satisfaction coefficient and unsatisfaction coefficient. The purposes of this study are to use ASC, the average of satisfaction coefficient and unsatisfaction, as the satisfaction of quality characteristics, decide the importance of quality characteristics with TOPSIS, a representative multi-standard decision-making method, and calculate strategy improvement propriety of logistic service quality.
Cryptography is a science to maintain the security of the message by changing data or information into a different form, so the message cannot be recognized. Today, many algorithms have been proposed for image encryption, but the chaotic encryption methods have a good combination of speed and high security. In recent years, the chaos based cryptographic algorithms have suggested some new and efficient ways to develop secure image encryption techniques. The chaos-based encryption schemes are composed of two steps: chaotic confusion and pixel diffusion. In the chaotic confusion stage, a combination of the chaotic maps is used to realize the confusion of all pixels. In this paper, we first give a brief introduction into chaotic image encryption and then we investigate some important properties and behaviour of the logistic map. The logistic map, aperiodic trajectory, or random-like fluctuation, could not be obtained with some choice of initial condition. Therefore, a noisy logistic map with an additive system noise is introduced. The proposed scheme is based on the extended map of the Clifford strange attractor, where each dimension has a specific role in the encryption process. Two dimensions are used for pixel permutation and the third dimension is used for pixel diffusion. In order to optimize the Clifford encryption system we increase the space key by using the noisy logistic map and a novel encryption scheme based on the Clifford attractor and the noisy logistic map for secure transfer images is proposed. This algorithm consists of two parts: the noisy logistic map shuffle of the pixel position and the pixel value. We use times for shuffling the pixel position and value then we generate the new pixel position and value by the Clifford system. To illustrate the efficiency of the proposed scheme, various types of security analysis are tested. It can be concluded that the proposed image encryption system is a suitable choice for practical applications.
향후 통일이후 북한지역의 급격한 국토개발로 인한 자연 환경 훼손을 미연에 방지하고 한반도의 균형 있는 국토의 보전과 관리를 위해서는 환경계획 기반의 국토계획이 필수적이다. 이러한 환경계획을 위해서는 다양한 환경공간정보를 이용한 국토의 자연환경 우수지역 평가지도 작성은 반드시 필요하다. 이에 본 연구에서는 로지스틱 회귀분석을 통해 북한지역의 자연환경 우수지역 평가지도 구축방안을 제시하였다. 자연환경 우수성 평가 선행연구를 기반으로 평가에 필요한 평가항목들을 선정하고, 해당 평가항목들을 수집 및 구축하였으며 로지스틱 회귀분석을 이용하여 남북한 접경지역을 중심으로 자연환경성 우수지역 평가를 수행하였다. 평가결과 로지스틱회귀분석 적합성 모형은 89.4%의 분류정확도가 나타났으며, ROC 분석결과 정확도가 96.1%로 높게 나타났다. 본 연구의 결과를 국토환경성평가지도 환경생태적평가와 비교한 결과 본 연구에서 제시한 자연환경 우수지역 평가지도 결과가 북한지역의 환경계획에 활용이 가능할 수 있는 정확도를 나타내고 있다고 판단되었다. 따라서, 본 연구에서 도출한 자연환경 우수지역 평가지도의 40% 이상의 우수지역을 자연환경 핵심 우수지역으로 지정하고, 60%까지의 완충 자연환경성 우수지역으로 지정하여, 추후 단계적으로 핵심 자연환경 우수지역으로 확장할 수 있도록 정책적으로 설정하는 것이 바람직할 것으로 판단된다.
The purpose of this study was to investigate the environmental factors that affect the computer literacy of childcare teachers. A survey was conducted to get information about teachers' ICT utilization ability and their physical and educational condition. Binary logistic regression analysis was performed using SPSS 17.0 program on the data of 293 teachers who work in childcare centers in capital area, and the following results were obtained. First, computer-related physical environment and computer training did not affect the teachers' computer literacy. Second, taking computer course had effects on the basic skills, word-processing ability, internet communication ability and computer program utilization. Third, the number of hours of using computers affected the ability to install and maintain computers. Fourth, the purchase of computer-related books and magazines and the number of computer programs they use had an effect on their computer program utilization. These results have significance in that they imply what is needed for improving childcare teachers' computer literacy in terms of institutional support.
Recognize the QR code and develops the position and orientation of the robot can recognize the robot. It is expected to become the innovative technology of robotic navigation systems and logistics systems. The existing vision of the position recognition method(Vision) or artificial surface(Artificial Landmark)based positioning of pushing the location recognition promoted to use a commercially available wireless signal. When commercially available through these technology are expected to be able to make the logistics robot capable of precise position recognition excellent in cost and performance. In the case of the Amazon by Kiva Systems of automation and robotics technology and logistics system in the same way that suggests supplied to the consumer in the short term it innovates in the current logistics. This same technology is location-aware robot control system of the Amazon and is expected to be an innovative logistics system to transfer after development is complete.
East Nusa Tenggara (ENT) is one of seven provinces in the eastern region of Indonesia that contribute to the large number of out of school children (OOSC). A research study has been carried out to investigate the characteristics of OOSC and to determine the statistical model explaining factors that influence the OOSC occurrence in the age group 13 – 15 years in ENT. Data of OOSC were obtained from the Education Department and Regional Planning Board in 6 selected districts in ENT that were produced from the community based education information system (CBEIS) survey in coordination with UNICEF Kupang in 2013. The districts were Sikka, Timor Tengah Selatan (TTS), West Sumba, East Sumba, Central Sumba and the City of Kupang. A response variable of the study was the state of the children’s education with the category ‘yes’ for school and ‘no’ for out of school. Data was then analysed using descriptive analysis and multiple logistic regression method. The analysis shows that there were 795 OOSC in 10350 children in the junior high school age group. The majority of them are males, living in the country side, have farmer parents, are from families with wealth quintile on the bottom class and have mothers with no education. Logistic analysis on the best model shows that literacy, working status, disability, occupation of household heads, wealth quintile, possession of birth certificate, living status are the factors that significantly affect the number of OOSC in the 13-15 age group. Odds ratio values of the first three factors are 26.5; 12.8 and 7.5 respectively.
In this paper, we have considered the modeling and analyses of categorical data. We modeled binary data with categorical predictors, using logistic regression to develop a statistical method. We found that ANOVA-type analyses often performed unsatisfactory, even when using arcsine-square-root transformations. We concluded that such methods are not appropriate, especially in cases where the fractions were close to 0 or 1. The logistic transformation of fraction data could be a promising alternative, but it is not desirable in the statistical sense. The major purpose of this paper is to demonstrate that logistic regression with an ANOVA-model like parameterization aids our understanding and provides a somewhat different, but sound, statistical background. We examined a simple real-world example to show that we can efficiently test the significance of regression parameters, look for interactions, estimate confidence intervals, and calculate the difference between the mean values of the referent and experimental subgroups. This paper demonstrates that precise confidence interval estimates can be obtained using the proposed ANOVA-model like approach. The method discussed here can be extended to any type of fraction data analysis, particularly for experimental design.
The growing logistics strategy of a company is to optimize their vehicle route scheduling in their supply chain system. It is very important to analyze for continuous pickups and delivery vehicle scheduling. This paper is a computational study to investigate the effectiveness of continuous pickups and delivery vehicle routing problems. These scheduling problems have 3 subproblems; Inbound Vehicle Routing Problem with Makespan and Pickup, Line-haul Network Problem, and Outbound Vehicle Routing Problem with Delivery. In this paper, we propose 5 heuristic Algorithms; Selecting Routing Node, Routing Scheduling, Determining Vehicle Type with Number and Quantity, and Modification Selecting Routing Node. We apply these Algorithms to S vehicle company. The results of computational experiments demonstrate that proposed methods perform well and have better solutions than other methods considering the basic time and due-date.
OSHA(Occupational Safety and Health Act) generally regulates employer's business principles in the workplace to maintain safety environment. This act has the fundamental purpose to protect employee's safety and health in the workplace by reducing industrial accidents. Authors tried to investigate the correlation between 'occupational injuries and illnesses' and level of regulation compliance using Survey on Current Status of Occupational Safety & Health data by the various statistical methods, such as generalized regression analysis, logistic regression analysis and poison regression analysis in order to compare the results of those methods. The results have shown that the significant affecting compliance factors were different among those statistical methods. This means that specific interpretation should be considered based on each statistical method. In the future, relevant statistical technique will be developed considering the distribution type of occupational injuries.
An attempt is given to the problem of analyzing the two-way binary attribute data using the logistic regression model in order to find a sound statistical methodology. It is demonstrated that the analysis of variance (ANOVA) may not be good enough, especi
In this paper, an analysis of two-way binary attribute data is performed using the logistic regression model in order to find a sound statistical methodology. It is demonstrated that the ANOVA may not be enough, especially for the case that the proportion is very low or high. The logistic transformation of proportion data could be a help, but not sound in the statistical sense. The adoption of generalized least squares(GLS) method entails much to estimate the variance-covariance matrix. On the other hand, the logistic regression methodology provides sound statistical background in estimating model parameters and related confidence intervals. The efficiencies of estimates are ensured with a simulated data with a view to demonstrate the usefulness of the methodology.
The medium and small logistic companies that have an outsourcing contract from the large corporation are encountered with a problem to introduce the ERP system to their current business environment due to following risk of change in current business environment, high cost involved in investment, and lack of understanding of business requirement of ERP. Instead of build their own ERP system, the small and medium logistic companies are using the large corporation's ERP system and get the benefit of efficiency in management and control process. Therefore, it is more like the organization hierarchy, not collaboration between the medium and small companies with the large corporation. In this study, the survey method to find out how the medium and small logistic companies understand the importance of ERP system on continuous growth of business by AHP. as result, they are recognized. The benefit of the ERP system as having much effect on business competitiveness.
교통사고발생시 사고 심각도에 영향을 미치는 요인과 그 관계를 이해하는 것은 기하구조나 환경 측면에서 교통사고 발생을 예방하고 운전자와 사고 차량의 특성을 이해하는데 도움을 준다. 본 연구에서는 계층 이항 로지스틱모형에 의해 고속도로 교통사고 심각도에 영향을 미치는 요인을 파악하고 영향변수 간 차이를 나타내는 비교위험도(odds ratio)를 도출하였다. 사고 심각도는 인명피해와 차량피해로 구분하여 사망사고모형과 차량완파사고모형을 구축하였다, 종속변수는 사망자 발생과 완파차량 발생 여부이며, 각각 사고-탑승자, 사고-차량의 2수준 계층구조를 적용하였다. 추정 결과 설명변수의 고정효과는 두 모형이 유사한 결과를 보이나 종속변수의 속성에 따라 차별화된 결과를 나타내기도 하였다. 본선과 진출입부에서의 사고가 가장 위험하며, 중앙선 침범과 통행위반, 과속 사고의 상해나 차량 파손 위험도가 높고, 충돌사고와 추돌사고, 화재 사고의 피해가 크다. 사고 심각도는 노면 상태나 시야 조건 등 외부환경에 영향을 받으나 기하구조 조건은 관련이 없다.
Incheon port is located near the Seoul metropolitan area and it is gateway port to Korea. It has the efficient location conditions in geography and economics. Many logistics industry had been developed taking the advantage of above conditions. Since Incheon International Airport opened in 2001, the function in logistics had been grown gradually. But most of logistics companies in Incheon are lack of basic usage of logistic information. To identify the status for logistic industry in Incheon we analysed various statistical data and literature in this study. From the survey results, we found that logistic industry has higher weight than other industries. It is sure that logistics industry is the specific industry in Incheon.
A probability prediction model for tropical cyclone (TC) genesis in the Northwestern Pacific area was developed using the logistic regression method. Total five predictors were used in this model: the lower-level relative vorticity, vertical wind shear, mid-level relative humidity, upper-level equivalent potential temperature, and sea surface temperature (SST). The values for four predictors except for SST were obtained from difference of spatial-averaged value between May and January, and the time average of Niño-3.4 index from February to April was used to see the SST effect. As a result of prediction for the TC genesis frequency from June to December during 1951 to 2007, the model was capable of predicting that 21 (22) years had higher (lower) frequency than the normal year. The analysis of real data indicated that the number of year with the higher (lower) frequency of TC genesis was 28 (29). The overall predictability was about 75%, and the model reliability was also verified statistically through the cross validation analysis method.
The recent market trend of demand and supply of domestic paper industry expected confusion in near future due to massive imports of low cost product because of suddenly emerging of China's mass productive equipment and capacity. Related domestic industry is deploying joint co-coperative partnership and logistic service, joint operations of transportation and distribution center and innovation activity for customer satisfaction. This paper tries to present a solution through analysis of related paper industry a case study.
본 연구의 목적은 사고위치별(유입부, 유출부, 교차로내 및 횡단보도) 로지스틱 회귀 교통사고 모형을 개발하는 것이다. 충북지방경찰청의 2004~2005년도 사고 자료와 현장조사 자료를 근거로, 교통사고와 관련된 기하구조 요소, 환경 요소 등이 분석되었다. 개발된 모형은 카이제곱 p 값은 0.000 그리고 Nagelkerke R2값 0.363~0.819로 모두 통계적으로 유의한 것으로 분석된다. 개발된 모형의 공통 사고요인은 교통량, 횡단거리 및 좌회전전용차로이며, 특정변수는 교차로내 사고모형의 부도로 교통량, 그리고 횡단보도 사고모형의 주도로 U턴인 것으로 나타나고 있다. Hosmer & Lomeshow 검정은 유입부를 제외한 모형들은 p값이 0.05보다 크기 때문에 통계적으로 적합한 것으로 평가된다. 또한 정분류율 결과는 모든 모형식이 73.9% 이상으로 높은 예측력을 보이는 것으로 분석된다.
This is to prevent accidents that can be caused during the process of hospital logistics and accidents in relation to the traceability of medical wastes. And this is also to set up the logistic management system of medical wastes is hospital where the safety of patients shall to regard as the first priority. through these case studies effective operating plans shall be provided.
We adapted association rules of data mining in order to investigate the relation among the factors of musculoskeletal disorders and proposed the method of preventing the musculoskeletal disorders associated with multiple logistic regression in previous study. This multiple logistic regression was difficult to establish the method of preventing musculoskeletal disorders in case factors can't be managed by worker himself, i.e., age, gender, marital status. In order to solve this problem, we devised association rules of factors of musculoskeletal disorders and proposed the interactive method of preventing the musculoskeletal disorders, by applying association rules with the result of multiple logistic regression in previous study. The result of correlation analysis showed that prevention method of one part also prevents musculoskeletal disorders of other parts of body.