• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권11호
• /
• pp.5436-5458
• /
• 2017

Automatic Video Surveillance System (AVSS) has become important to computer vision researchers as crime has increased in the twenty-first century. As a new branch of AVSS, baggage detection has a wide area of security applications. Some of them are, detecting baggage in baggage restricted super shop, detecting unclaimed baggage in public space etc. However, in this paper, a detection & classification framework of baggage is proposed. Initially, background subtraction is performed instead of sliding window approach to speed up the system and HSI model is used to deal with different illumination conditions. Then, a model is introduced to overcome shadow effect. Then, occlusion of objects is detected using proposed mirroring algorithm to track individual objects. Extraction of rotational signal descriptor (SP-RSD-HOG) with support plane from Region of Interest (ROI) add rotation invariance nature in HOG. Finally, dynamic human body parameter setting approach enables the system to detect & classify single or multiple pieces of carried baggage even if some portions of human are absent. In baggage detection, a strong classifier is generated by boosting similarity measure based multi layer Support Vector Machine (SVM)s into HOG based SVM. This boosting technique has been used to deal with various texture patterns of baggage. Experimental results have discovered the system satisfactorily accurate and faster comparative to other alternatives.

• 한국식생활문화학회지
• /
• 제35권2호
• /
• pp.181-192
• /
• 2020

This study aimed to identify whether or not four service situations varying according to positive and negative combinations of physical evidence and functional service influence store image and purchase behavioral intentions of customers at bulgogi restaurants. The video-scenario technique was used for the study. Data were analyzed with the SPSS (Window 19.0) package using frequency analysis, one-way ANOVA, 2 by 2 factorial ANOVA, exploratory factor analysis, and multiple regression analysis to confirm the hypotheses. The combined effect of functional service and physical evidence influenced store image and purchase intention. In terms of seperate effect of physical evidence and functional service, the effect of employee service on store image was more powerful than that of physical evidence, even though the effect differed depending on the situation. Purchase intention was only influenced by functional service quality from employees under the four different scenarios. Thus, when opening a Korean restaurant, proper management of tangible evidence suitable to service, and the prices expected from local customers should be determined. Additionally, extremely high or low levels of physical evidence management should be avoided.

• Current Optics and Photonics
• /
• 제4권3호
• /
• pp.210-220
• /
• 2020

Aiming at the problem that the Local Sparse Difference Index algorithm has low accuracy and low efficiency when detecting target anomalies in a hyperspectral image, this paper proposes a Weighted Collaborative Representation and Sparse Difference-Based Hyperspectral Anomaly Detection algorithm, to improve detection accuracy for a hyperspectral image. First, the band subspace is divided according to the band correlation coefficient, which avoids the situation in which there are multiple solutions of the sparse coefficient vector caused by too many bands. Then, the appropriate double-window model is selected, and the background dictionary constructed and weighted according to Euclidean distance, which reduces the influence of mixing anomalous components of the background on the solution of the sparse coefficient vector. Finally, the sparse coefficient vector is solved by the collaborative representation method, and the sparse difference index is calculated to complete the anomaly detection. To prove the effectiveness, the proposed algorithm is compared with the RX, LRX, and LSD algorithms in simulating and analyzing two AVIRIS hyperspectral images. The results show that the proposed algorithm has higher accuracy and a lower false-alarm rate, and yields better results.

• Journal of Communications and Networks
• /
• 제13권2호
• /
• pp.132-141
• /
• 2011

IEEE 802.15.4 networks are a feasible platform candidate for connecting all health-care-related equipment dispersed across a hospital room to collect critical time-sensitive data about patient health state, such as the heart rate and blood pressure. To meet the quality of service requirements of health-care systems, this paper proposes a multi-priority queue system that differentiates between various types of frames. The effect of the proposed system on the average delay and throughput is explored herein. By employing different contention window parameters, as in IEEE 802.11e, this multi-queue system prioritizes frames on the basis of priority classes. Performance under both saturated and unsaturated traffic conditions was evaluated using a novel analytical model that comprehensively integrates two legacy models for 802.15.4 and 802.11e. To improve the accuracy, our model also accommodates the transmission retries and deferment algorithms that significantly affect the performance of IEEE 802.15.4. The multi-queue scheme is predicted to separate the average delay and throughput of two different classes by up to 48.4% and 46%, respectively, without wasting bandwidth. These outcomes imply that the multi-queue system should be employed in health-care systems for prompt allocation of synchronous channels and faster delivery of urgent information. The simulation results validate these model's predictions with a maximum deviation of 7.6%.

• 대한기계학회논문집A
• /
• 제33권7호
• /
• pp.681-686
• /
• 2009

Direct laser metal forming technology was applied to restore the damaged mold surface. In order to estimate melting characteristics of the $20{\mu}m$ Fe-Cr-Ni powder, single layer experiments were performed at various levels of heat input. The process window of the $20{\mu}m$ Fe-Cr-Ni powder provided feasible process parameters for the smooth regular surface. The cross hatching scanning strategy on the multiple layer experiment was performed to reduce the thickness non-uniformity of edge portions compared with the one direction scanning. To estimate the coherence between the melted powder and the basematal, the tendency of hardness distribution has been observed. The hardness of the melted and the remelted zone was distributed from 400HV to 600HV. It is over 2 times compared of the hardness of the basemetal. Experimental results show that the mold restoring process using direct laser metal forming can be successfully applied in the mold repair industry.

• 제어로봇시스템학회논문지
• /
• 제21권11호
• /
• pp.1008-1016
• /
• 2015

This paper proposes a method for detecting the front side of vehicles. The method can find the car side with a license plate even with complicated and cluttered backgrounds. A convolutional neural network (CNN) is used to solve the detection problem as a unified framework combining feature detection, classification, searching, and localization estimation and improve the reliability of the system with simplicity of usage. The proposed CNN structure avoids sliding window search to find the locations of vehicles and reduces the computing time to achieve real-time processing. Multiple responses of the network for vehicle position are further processed by a weighted clustering and probabilistic threshold decision method. Experiments using real images in parking lots show the reliability of the method.

• 간호행정학회지
• /
• 제20권4호
• /
• pp.383-393
• /
• 2014

Purpose: The purpose of this descriptive study was to identify the impact of workplace bullying and LMX (Leader-Member Exchange) on turnover intention among nurses. Methods: The participants were 364 nurses from the Seoul metropolitan area who were attending a continuing education program. A structured questionnaire was used for data collection and data were analyzed using the SPSS/Window program. Hierarchical multiple regression analysis was performed to verify the effect of variables on turnover intention. Results: Higher workplace bullying was associated with higher turnover intention. Workplace bullying was negatively correlated with leader-member exchange. The most influential factors for turnover intention were LMX (${\beta}=-7.22$, p<.001), work load (${\beta}=2.96$, p=.003), and workplace bullying (${\beta}=2.64$, p=.009). These factors accounted for 28% of the variance in turnover intention. Conclusion: The study results indicate that there is need to develop strategies to prevent workplace bullying and cultivate a good relationship between nursing managers and nurses to lower nurses' turnover intention.

• 간호행정학회지
• /
• 제19권3호
• /
• pp.329-339
• /
• 2013

Purpose: This study was conducted to provide basic data on the nursing Happiness Index and identify factors influencing nurses by describing their perception of lifestyle, health behavior, nursing professionalism, Happiness Index, and turnover intention. Methods: On July 2012, 700 nurses from 10 general hospitals were surveyed, but 23 were omitted due to missing or incomplete data. The focus of this study was the Organization for Economic Co-operation and Development (OECD) Happiness Index, consisting of 11 OECD identified topics concerning living conditions and quality of life. Data were analyzed using $x^2$-tests, t-test, ANOVA, Pearson correlation coefficients and multiple regression with SPSS/WINdow 14.0. Results: Mean score for nurses' Happiness Index was 3.03 on a scale of 5. There were significant differences on the Happiness Index for the following: age, marriage, children, education, position, work experience, wages, number of beds, medical institution, health behavior, weight, and meal patterns. There was a positive correlation between the happiness index and nursing professionalism but a negative correlation between the happiness index and turnover intention. Conclusion: Results indicate that factors influencing happiness are autonomy, sense of calling and turnover intention suggesting the need to improve nursing professionalism for a life of happiness among hospital nurses.

• 대한간호학회지
• /
• 제35권7호
• /
• pp.1353-1361
• /
• 2005

Purpose: This study was done to provide fundamental data for developing a depression prediction model by discovering main factors that affect depression in patients who do maintenance hemodialysis. Method: The subjects were 191 patients doing maintenance hemodialysis selected from outpatient dialysis clinics at 9 major general hospitals, The Instrument tools utilized in this study were adapted from depression, fatigue, sleep disturbance, stress, adaptation, symptoms, daily activities, and role limitation and thoroughly modified to verify reliability and validity. The collected data was analyzed with a SPSS-PC 11.0 Window Statistics Program for real numbers, percentage, average, standard deviation, and multiple regression. Results: The correlation factor for depression was (M=2.54) fatigue(M=3.12), sleep disturbance (M=2.82), stress(M=3.04), adaptation(M=2.53), daily activities(M=2.24), symptoms(M=2.37), and role limitation(M=2.24). The strongest factor that affected depression was explained by symptoms of the patients who performed hemodialysis. The analysis of the factors that affected depression revealed a $58.4\%$ prediction in symptoms, stress, role limitation, and adaptation. Conclusion: It has been confirmed that the regression equation model(Depression=7.351 + .266$^{\ast}$symptoms + .260$^{\ast}$stress -.l89$^{\ast}$adaptation + .057$^{\ast}$fatigue) of this research may serve as a prediction factor for depression in Hemodialysis Patients.

• 복식문화연구
• /
• 제22권6호
• /
• pp.899-910
• /
• 2014

The purpose of this study was to analyze high school students' school uniform wearing attitude by group according to clothing attitude targeting Gyeongnam area. This study aims to provide preliminary data in the field of school uniform and marketing that clothing propensity by groups is considered. This study conducted a survey targeting 762 high school students in Gyeongnam. For statistical analysis, SPSS for Window 14.0 was used for frequency analysis, factor analysis, reliability analysis, multiple sponse analysis, cluster analysis, ANOVA analysis and Duncan's ex-post analysis method. As a result of cluster analysis on the clothing attitude, students were divided into 4 segmentation of fashion seeking group, fashion indifference group, conformity group and modesty group. As a result of verification on the difference in perception toward wearing school uniform by groups which were classified according to the propensity of clothing attitude, activity, stability, and practicality were all varied according to the propensity of clothing attitude. 4 groups were significant differences in the degree of consent to wearing school uniform, price of school uniforms, tendency to prefer famous brand when purchasing school uniform, experience of transforming school uniform, opinion about school uniform modification and reason for school uniform modification. While low graders were many in 'modesty group', upper graders were many in 'fashion seeking group', which means that more segmentalized satisfaction of clothing by group may be raised if such a fact is considered when planning clothing for high school students segmentalized by age.