The computer has become an indispensable tool for animation works. However if you don't understand the characteristics of the computer and its software, you might not have the result satisfying your efforts. The incorrect understanding of image format sometimes causes it. Habitually image formats are selected usually for most of works but there is a distinct difference among those image formats while the efficient usages of them are different from each other. For your more efficient work therefore, you need to identify the characteristics of various kinds of image format used mostly for animation works. First I took a look at the theories of the lossy compression and lossless compression, which are two types of data compression widely used in the whole parts of computer world and the difference between bitmap method and vector method, which are respectably different in terms of the way of expressing images and finally the 24 bit true color and 8 bits alpha channel. Based on those characteristics, I have analyzed the functional difference among image formats used between various types of animation works such as 2D, 3D, composing and editing and also the benefits and weakness of them. Additionally I've proved it is wrong that the JPEG files consume a small space in computer work. In conclusion, I suggest the TIF format as the most efficient format for whatever it is editing, composing, 3D and 2D in considering capacity, function and image quality and also I'd like to recommend PSD format which has compatibility and excellent function, since the Adobe educational programs are used a lot for the school education. I hope this treatise to contribute to your right choice of image format in school education and practical works.
Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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v.4
no.1
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pp.65-75
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2006
Transparency on the Total System Performance Assessment (TSPA) is the key issue to enhance the public acceptance for a radioactive repository. To approve it, all performances on TSPA through Quality Assurance is necessary. The integrated Cyber R&D Platform is developed by KAERI using the T2R3 principles applicable for five major steps : planning, research work, documentation, and internal & external audits in R&D's. The proposed system is implemented in the web-based system so that all participants in TSPA are able to access the system. It is composed of three sub-systems; FEAS (FEp to Assessment through Scenario development) showing systematic approach from the FEPs to Assessment methods flow chart, PAID (Performance Assessment Input Databases) being designed to easily search and review field data for TSPA and QA system containing the administrative system for QA on five key steps in R&D's in addition to approval and disapproval processes, corrective actions, and permanent record keeping. All information being recorded in QA system through T2R3 principles is integrated into Cyber R&D Platform so that every data in the system can be checked whenever necessary. Throughout the next phase R&D, Cyber R&D Platform will be connected with the assessment tool for TSPA so that it will be expected to search the whole information in one unified system.
Nowadays, product recommendation is one of the important issues regarding both CRM and Internet shopping mall. Generally, a recommendation system tracks past actions of a group of users to make a recommendation to individual members of the group. The computer-mediated marketing and commerce have grown rapidly and thereby automatic recommendation methodologies have got great attentions. But the researches and commercial tools for product recommendation so far, still have many aspects that merit further considerations. To supplement those aspects, we devise a recommendation methodology by which we can get further recommendation effectiveness when applied to Internet shopping mall. The suggested methodology is based on web log information, product taxonomy, association rule mining, and decision tree learning. To implement this we also design and intelligent Internet shopping mall support system based on agent technology and develop it as a prototype system. We applied this methodology and the prototype system to a leading Korean Internet shopping mall and provide some experimental results. Through the experiment, we found that the suggested methodology can perform recommendation tasks both effectively and efficiently in real world problems. Its systematic validity issues are also discussed.
Biomolecular computing is a new computing paradigm that uses biomolecules such as DNA for information representation and processing. The huge number of molecules in a small volume and the innate massive parallelism inspired a novel computation method, and various computation models and molecular algorithms were developed for problem solving. In the meantime, the use of biomolecules for information processing supports the possibility of DNA computing as an application for biological problems. It has the potential as an analysis tool for biochemical information such as gene expression patterns. In this context, a DNA computing-based model of a biomolecular perceptron has been proposed and the result of its experimental implementation was presented previously. The weight encoding and weighted sum operation, which are the main components of a biomolecular perceptron, are based on the competitive hybridization reactions between the input molecules and weight-encoding probe molecules. However, thermodynamic symmetry in the competitive hybridizations is assumed, so there can be some error in the weight representation depending on the probe species in use. Here we suggest a generalized model of hybridization reactions considering the asymmetric thermodynamics in competitive hybridizations and present a weight encoding method for the reliable implementation of a biomolecular perceptron based on this model. We compare the accuracy of our weight encoding method with that of the previous one via computer simulations and present the condition of probe composition to satisfy the error limit.
Latent topic models are statistical models which automatically captures salient patterns or correlation among features underlying a data collection in a probabilistic way. They are gaining an increased popularity as an effective tool in the application of automatic semantic feature extraction from text corpus, multimedia data analysis including image data, and bioinformatics. Among the important issues for the effectiveness in the application of latent topic models to the massive data set is the efficient learning of the model. The paper proposes an accelerated learning technique for PLSA model, one of the popular latent topic models, by an incremental EM algorithm instead of conventional EM algorithm. The incremental EM algorithm can be characterized by the employment of a series of partial E-steps that are performed on the corresponding subsets of the entire data collection, unlike in the conventional EM algorithm where one batch E-step is done for the whole data set. By the replacement of a single batch E-M step with a series of partial E-steps and M-steps, the inference result for the previous data subset can be directly reflected to the next inference process, which can enhance the learning speed for the entire data set. The algorithm is advantageous also in that it is guaranteed to converge to a local maximum solution and can be easily implemented just with slight modification of the existing algorithm based on the conventional EM. We present the basic application of the incremental EM algorithm to the learning of PLSA and empirically evaluate the acceleration performance with several possible data partitioning methods for the practical application. The experimental results on a real-world news data set show that the proposed approach can accomplish a meaningful enhancement of the convergence rate in the learning of latent topic model. Additionally, we present an interesting result which supports a possible synergistic effect of the combination of incremental EM algorithm with parallel computing.
The Self-organizing Feature Map(SOFM) that is one of unsupervised neural networks is a very powerful tool for data clustering and visualization in high-dimensional data sets. Although the SOFM has been applied in many engineering problems, it needs to cluster similar weights into one class on the trained SOFM as a post-processing, which is manually performed in many cases. The traditional clustering algorithms, such as t-means, on the trained SOFM however do not yield satisfactory results, especially when clusters have arbitrary shapes. This paper proposes automatic clustering on trained SOFM, which can deal with arbitrary cluster shapes and be globally optimized by graph cuts. When using the graph cuts, the graph must have two additional vertices, called terminals, and weights between the terminals and vertices of the graph are generally set based on data manually obtained by users. The Proposed method automatically sets the weights based on mode-seeking on a distance matrix. Experimental results demonstrated the effectiveness of the proposed method in texture segmentation. In the experimental results, the proposed method improved precision rates compared with previous traditional clustering algorithm, as the method can deal with arbitrary cluster shapes based on the graph-theoretic clustering.
The purpose of this study is to define the effects of the roles played by the Doulas : one group educated on the conventional Lamaze method known to have effects on birth pang during delivery process and the other group educated both on Lamaze and therapeutic touch. On the various factors of delivery, and thereby, provide for some basic data to develop an effective nursing intervention to relieve women of their birth pang. 136 mothers who were hospitalized in a general hospital from June 13, 1998 to May 13, 1998 to May 13, 1999 to deliver their first babies were sampled to be divided into control group, test group I and test group II and thus be subject to interviews and observations. As for the tool of study, melzack's(1975) 'pain scale', McCaffery's(1972) and Mcrachlan's(1974) 'pain expression scales' and Spielberger's (1975) 'anxiety scale' were used. The preparatory educational programs consisted of 5week Lamaze method and therapeutic touch. The research, design was quasi-experimental, non equivalent, posttest only control group design. The collected data were processed using the SPSS/PC statistics software for frequencies, means and one-way Anova as well as Tukey HSD and Scheffe test as post hoc for individual comparison. Moreover, chi-square test was used to test the differences between groups, while Pearson's correlation coefficients were analyzed to determine the correlations between anxiety and variables. The findings are as follows ; 1. The birth pain of the mothers delivering first babies scored in a subjective and objective pain scale; 1) There was a significant difference of subjective birth pain at 8~10cm opening of cervix between control group and two test groups. 2) There was no significant difference of objective birth pain as per opening of cervex among three groups in terms of sweating, facial movement, bodily posture and vocal changes. 2. There was no significant difference of trait anxiety among three groups. however, there was a significant difference of state anxiety during labor process between control group and two test groups. On the other hand, all the three groups showed a significantly lower level of anxiety during labor process than when they were carried to the hospital. 3. There was a significant difference of the time of total and first-stage labor among three groups, while there was a significant but small difference of the time elapsed from 8~10cm cervix open to the full among three groups. 4. Two test groups showed a higher frequency of natural deliveries than the control group. 5. Two test groups were subject to these drugs than the control group. In conclusion, it was found that the test group I and II showed a shorter delivery time than the control group, a higher frequency of natural delivery and a lesser use of anodyne or epidural. In particular, this study is significant to develop a nursing intervention service or a therapeutic touch which the nursing administrators can apply to their hospitals in marketing programs.
More efforts have been given to solve the problems related to computer software by process assessment. ISO/IEC 15504(SPICE) has been developed as standardized means for process assessment. The purpose of this paper is to design and implement a process assessment system which is appropriated to the Korean assessment environment based on ISO/IEC 15504. Referring documents are: IS0/1EC 15504 standardized documents, the assessment provisions of the SPICE committee in Korea, and research papers applied the existing process assessment system to real cases. Among a lot of processes, this system is designed for (ENG2). The proposed system in the paper will support the whole process of assessment, presenting the goals and end-products for each assessment step and making it possible to compose and save the product on the same screen. In determining process rating, assessors can retrieve the saved data and documents. By doing so, the system will improve reliability in process rating. The proposed system includes 7 steps of pre-assessment and 9 steps of actual assessment in order to fully prepare assessors for process assessment. And each step has been standardized to improve user-friendliness. This system is designed to provide assessors with specific details of standardized documents, the goals of the process, outcomes of implementing the process, and presentations of base practices and input/output products. Above all, the system automatically generates an assessment rating, by calculating based on input data which assessors make out. It also presents outcomes graphically.
A mobile phone has became as a payment tool in e-commerce and on-line banking areas. This trend of a payment system using various types of mobile devices is rapidly growing, especially in the Internet transaction and small-money payment. Hence, there will be a need to define its standard for secure and safe payment technology. In this thesis, we consider the service types of the current mobile payments and the authentication method, investigate the disadvantages, problems and their solutions for smart and secure payment. Also, we propose a novel authentication method which is easily adopted without modification and addition of the existed mobile hardware platform. Also, we present a simple implementation as a demonstration version. Based on virtual machine (VM) approach, the proposed model is to use a pseudo-random number which is confirmed by the VM in a user's mobile phone and then is sent to the authentication site. This is more secure and safe rather than use of a random number received by the previous SMS. For this payment operation, a user should register the serial number at the first step after downloading the VM software, by which can prevent the illegal payment use by a mobile copy-phone. Compared with the previous SMS approach, the proposed method can reduce the amount of packet size to 30% as well as the time. Therefore, the VM-based method is superior to the previous approaches in the viewpoint of security, packet size and transaction time.
KIPS Transactions on Software and Data Engineering
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v.5
no.4
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pp.195-202
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2016
There have been many studies on subject tests for 3D contents using 3D glasses, but there is a limited research for 3D contents using autostereoscopic display. In this study, we investigated to assess usability of electroencephalogram (EEG) as an objective evaluation for 3D contents with different quality using autosteroscopic display, especially for lenticular lens type. The image with optimal quality and the image with distorted quality were separately generated for autostereosopic display with lenticular lens type and displayed sequentially through lenticular lens for 26 subjects. EEG signals of 8 channels from 26 subjects exposed to those images were detected and correlation between EEG signal and the quality of 3D images were statistically evaluated to check differences between optimal and distorted 3D contents. What we found was that there was no statistical significance for a wave vibration, however b wave vibration shows statistically significant between optimal and distorted 3D contents. b wave vibration observed for the distorted 3D image was stronger than that for the optimal 3D image. This results suggest that subjects viewing the distorted 3D contents through lenticular lens experience more discomfort or fatigue than those for the optimum 3D contents, which resulting in the greater b wave activity for those watching the distorted 3D contents. In conclusion, these results confirm that electroencephalogram (EEG) analysis can be used as a tool for objective evaluation of 3D contents using autosteroscopic display with lenticular lens type.
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