As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.
To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.
The Transactions of the Korea Information Processing Society
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v.5
no.10
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pp.2575-2583
/
1998
The productionof the highly relible softwae systems and theirs performance evaluation hae become important interests in the software industry. The software evaluation has been mainly carried out in ternns of both reliability and performance of software system. Software reliability is the probability that no software error occurs for a fixed time interval during software testing phase. These theoretical software reliability models are sometimes unsuitable for the practical testing phase in which a software error at a certain testing stage occurs by causes of the imperfect debugging, abnornal software correction, and so on. Such a certatin software testing stage needs to be considered as an outlying stage. And we can assume that the software reliability does not improve by means of muisance factor in this outlying testing stage. In this paper, we discuss Bavesian software reliability growth modeling and estimation procedure in the presence of an imidentitied outlying software testing stage by the modification of Jehnski Moranda. Also we derive the Bayes estimaters of the software reliability panmeters by the assumption of prior information under the squared error los function. In addition, we evaluate the proposed software reliability growth model with an unidentified outlying stage in an exchangeable model according to the values of nuisance paramether using the accuracy, bias, trend, noise metries as the quantilative evaluation criteria through the compater simulation.
Variable Message Sign (VMS), which provides drivers with direct information about state of traffic congestion and for prevent an accident, is the most effective method among the methods of providing information in Advanced Transportation Management System. Currently establishment and the VMS which is operated foundation lets in Guidelines on the use of Variable message sign (a book of the VMS) of 1999 November the Ministry Construction & Transportation, these contents mean main viewpoint on physical part such as message special quality variable (font, character size and line space, word interval) and position mainly among standard about establishment in general. But, it is true that using without effect verification on the character of VMS display and that using mode of stationary-centered. In this paper, it executed significance test to effort verification on the character of VMS display for more practical and effective information transmission based on the driver viewpoint For the researches; develop 3D-Simulation, select characteristics of driver's visual cognition behavior (the conspicuity, the legibility and the comprehensibility), evaluation each issue (day or night, 80km/h or 100km/h). Especially, that used the Eye Marker Recorder to measure of reading-time (legibility) thus, confirmed objectivity and reduce an observational error. The results showed that the conspicuity is Flashing> Stationary>Scroll. The legibility is not deference that Flashing between stationary form. Also the comprehensibility result showed that Flashing> Stationary>Stroll form.
Today, the modern art is extremely diverse. It is denying its own boundary through chaos, extreme, abjection. In fact the diversity of the modern art can be best described as questioning and challenging to the essence of the reality, rather than the artistic pursuit of the beauties. The pursuit of the reality has been a long lasting discourse since the ancient. Through the history, the reality (referent) and representation (image) has been complementing and disposing each other in a relationship of a meaningful construction until the modern times. The limit of modernistic self-reference and the emergence of the figure leads to the emergence of Post-modernism in a trend of experimenting new visual arts. The return to the figure is clearly distinguished from existing representation's system and it brought new meanings to approaches and interpretations of the reality. In the case of Pop arts of 1960's and the following the modern sculptures, which is covered by this thesis, I put an emphasis on the diversification of those via changed strategies on the reality. In a situation where the reality is dictated by signified, the modern arts can no longer stay on a classic concept of representation, rather it pursuits new system and diverse strategies. I provide three types of strategic characters of the reality and the diversification of reality: the transition of the reality. These three types can be used as a frame work, which is supporting new aspects of the modern arts in reflecting on existing system. Therefore, the reason of categorizing is to distinguish modernistic arts and post modernistic arts, and to propose new post-modernistic discourses. Adapting J.F, Lyotard's view, absence is used to trace down the diversification of the reality thorough the sublime on the deconstruction of the mega discourses and the relationship of representation. Based on H. Faster's theory of the appropriation, the appropriation is used to exemplify the strategies of visual arts are in variations and being delayed. Lastly, in the transition, J. Baudrilliard's simulacre is used in terms of the concept of post modernistic representation. Based on the core of his theories, the deconstruction of existing concepts and simulation as the post modernistic representation, and the world of hyperreality based on simulacre are explained. These allows us to deny that representation is the expression of reality through mimesis. My aim is to work on the definition of the arts and representation in the modern era, and go further from there in order to clarify meaning and extension of the modern sculptures. Now two artists are reviewed based on their own art works: George Seagal; Jeff Koons. They are selected among numerous artists from the Post Modern era. Epic contents and emphasis on daily life of Seagal's works show good examples to artists from Pop Arts and following time period and may have served as a start point for Postmodernism. Indeed, he tried to show a newly defined relationship between art works and daily life experience. On the other hand, J.Koons used the strategies of fabrication and appropriation, which shows characteristics of the postmodernism. Through his four individual exhibitions, he shows the diversification of the reality based on art works as fetishistic merchandises, and newly defined concept of Ready-made since M Duchamp. Lastly, the diversification of the reality is analyzed again in context of my art works. I focused on the return to the figure among a variety of trends of late 20 th century modern sculpture. It showed the post modernistic point of view on the reality. Post modernistic diversified strategies are adopted as a method of distinguishing each art works via the diversification of the reality. This is the result of contemporary social and cultural situations.
In this study, we aim to design the architecture of the kV imaging system for tumor tracking in the dual-head gantry system and analyze its accuracy by simulations. We established mathematical formulas and algorithms to track the tumor position with the two-pair kV imaging systems when they are in the non-orthogonal positions. The algorithms have been designed in the homogeneous coordinate framework and the position of the source and the detector coordinates are used to estimate the tumor position. 4D XCAT (4D extended cardiac-torso) software was used in the simulation to identify the influence of the angle between the two-pair kV imaging systems and the resolution of the detectors to the accuracy in the position estimation. A metal marker fiducial has been inserted in a numerical human phantom of XCAT and the kV projections were acquired at various angles and resolutions using CT projection software of the XCAT. As a result, a positional accuracy of less than about 1mm was achieved when the resolution of the detector is higher than 1.5 mm/pixel and the angle between the kV imaging systems is approximately between $90^{\circ}$ and $50^{\circ}$. When the resolution is lower than 1.5 mm/pixel, the positional errors were higher than 1mm and the error fluctuation by the angles was greater. The resolution of the detector was critical in the positional accuracy for the tumor tracking and determines the range for the acceptable angle range between the kV imaging systems. Also, we found that the positional accuracy analysis method using XCAT developed in this study is highly useful and will be a invaluable tool for further refined design of the kV imaging systems for tumor tracking systems.
Radiation exposure to humans can be caused by the gamma rays emitted from natural radioactive elements(such as uranium, thorium and potassium and any of their decay products) of Naturally Occurring Radioactive Materials(NORM) or Technologically Enhanced Naturally Occurring Radioactive Materials(TENORM) added consumer products. In this study, assume that activity of radioactive elements is $^{238}U$, $^{235}U$, $^{232}Th$$1Bq{\cdot}g^{-1}$, $^{40}K$$10Bq{\cdot}g^{-1}$ and the gamma rays emitted from these natural radioactive elements radioactive equilibrium state. In this study, reflected End-User circumstances and evaluated annual exposure dose for products based on ICRP reference voxel phantoms and ICRP Recommendation 103 using the Monte Carlo Method. The consumer products classified according to the adhere to the skin(bracelet, necklace, belt-wrist, belt-ankle, belt-knee, moxa stone) or not(gypsum board, anion wallpaper, anion paint), and Geometric Modeling was reflected in Republic of Korea "Residential Living Trend-distributions and Design Guidelines For Common Types of Household.", was designed the Room model($3m{\times}4m{\times}2.8m$, a closed room, conservatively) and the ICRP reference phantom's 3D segmentation and modeling. The end-user's usage time assume that "Development and Application of Korean Exposure Factors." or conservatively 24 hours; in case of unknown. In this study, the results of the effective dose were 0.00003 ~ 0.47636 mSv per year and were confirmed the meaning of necessary for geometric modeling to ICRP reference phantoms through the equivalent dose rate of belt products.
Kim, Bo-Kyung;Chie, Eui-Kyu;Huh, Soon-Nyung;Lee, Hyoung-Koo;Ha, Sung-Whan
Journal of Radiation Protection and Research
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v.27
no.1
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pp.37-49
/
2002
The accuracy of radiation dose delivery to target volume is one of the most important factors for good local control and less treatment complication. In vivo dosimetry is an essential QA procedure to confirm the radiation dose delivered to the patients. Transmission dose measurement is a useful method of in vivo dosimetry and it's advantages are non-invasiveness, simplicity and no additional efforts needed for dosimetry. In our department, in vivo dosimetry system using measurement of transmission dose was manufactured and algorithms for estimation of transmission dose were developed and tested with phantom in various conditions successfully. This system was applied in clinic to test stability, reproducibility and applicability to daily treatment and the accuracy of the algorithm. Transmission dose measurement was performed over three weeks. To test the reproducibility of this system, X-tay output was measured before daily treatment and then every hour during treatment time in reference condition(field size; $10 cm{\times} 10 cm$, 100 MU). Data of 11 patients whose pelvis were treated more than three times were analyzed. The reproducibility of the dosimetry system was acceptable with variations of measurement during each day and over 3 week period within ${\pm}2.0%$. On anterior- posterior and posterior fields, mean errors were between -5.20% and +2.20% without bone correction and between -0.62% and +3.32% with bone correction. On right and left lateral fields, mean errors were between -10.80% and +3.46% without bone correction and between -0.55% and +3.50% with bone correction. As the results, we could confirm the reproducibility and stability of our dosimetry system and its applicability in daily radiation treatment. We could also find that inhomogeneity correction for bone is essential and the estimated transmission doses are relatively accurate.
Proper packaging design can meet both the environmental and economic aspects of packaging materials by reducing the use of packaging materials, waste generation, material costs, and logistics costs. Finite element analysis(FEM) is used as a useful tool in various fields such as structural analysis, heat transfer, fluid motion, and electromagnetic field, but its application in the field of packaging is still insufficient. Therefore, the application of FEM to the field of packaging can save the cost and time in the future research because it is possible to design the package by computer simulation, and it is possible to reduce the packaging waste and logistics cost through proper packaging design. Therefore, this study investigated the FEM papers published in Korea for the purpose of helping research design using FEM program in the field of packaging in the future. In this paper, we analyzed the 29 papers that were directly related to the analysis of FEM papers published in domestic journals from 1991 to 2017. As a result, we analyzed the research topic, FEM program, and analysis method using each paper, and presented the direction that can be applied in future packaging field. When the FEM is applied to the packaging field, it is possible to change the structure and reduce the thickness through the stress and vibration analysis applied to the packaging material, thereby reducing the cost by improving the mechanical strength and reducing the amount of the packaging material. Therefore, in the field of packaging research in the future, if the FEM is performed together, economical and reasonable packaging design will be possible.
Journal of the Institute of Electronics and Information Engineers
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v.54
no.3
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pp.3-9
/
2017
Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).
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