3D imaging systems using 2D phased arrays have a large number of active channels, compelling to use a very expensive and bulky beamforming hardware, and suffer from low volume rate because, in principle, at least one ultrasound transmit-receive event is necessary to construct each scanline. A high speed 3D imaging method using a cross array proposed previously to solve the above limitations can implement fast scanning and dynamic focusing in the lateral direction but suffer from low resolution except at the fixed transmit focusing along the elevational direction. To overcome these limitations, we propose a new real-time volumetric imaging method using a cross array based on the synthetic aperture technique. In the proposed method, ultrasound wave is transmitted successively using each elements of an 1D transmit array transducer, one at a time, which is placed along the elevational direction and for each firing, the returning pulse echoes are received using all elements of an 1D receive array transducer placed along the lateral direction. On receive, by employing the conventional dynamic focusing and synthetic aperture method along lateral and elevational directions, respectively, ultrasound waves can be focused effectively at all imaging points. In addition, in the proposed method, a volume of interest consisting of any required number of slice images, can be constructed with the same number of transmit-receive steps as the total number of transmit array elements. Computer simulation results show that the proposed method can provide the same and greatly improved resolutions in the lateral and elevational directions, respectively, compared with the 3D imaging method using a cross array based on the conventional fixed focusing. In the accompanying paper, we will also propose a new real-time 3D imaging method using a cross array for improving transmit power and elevational spatial resolution, which uses linear wave fronts on transmit.
Purpose: To evaluate the efficacy of a belly-board device (BBD) in reducing the volume of small bowel during four-field pelvic irradiation. Materials and Methods: Twenty-two cancer patients (14 uterine cervical cancer, 6 rectal cancer, and 2 endometrial cancer) scheduled to receive pelvic irradiation were selected for this study. Two sets of CT images were taken with and without the belly-board device using the Siemens 16 channel CT scanner. All patients were set in the prone position. The CT images were transferred to a treatment planning system for dose calculation and volume measurements. The external surfaces of small bowel and the bladder were contoured on all CT scans and the 4-pelvic fields were added. The dose-volume-histogram of the bladder and small bowel, with and without the BBD, were plotted and analyzed. Results: In all patients, the total small bowel volume included in the irradiated fields was reduced when the BBD was used. The mean volume reduction was 35% (range, 1∼791∼79) and was statistically significant (p<0.001). The reduction in small bowel volume receiving 10∼10010∼100 of the prescribed dose was statistically significant when the BBD was used in all cases. Almost no change in the total bladder volume involved was observed in the field (<8 cc, p=0.762). However, the bladder volume receiving 90% of the prescribed dose was 100% in 15/22 patients (68%) and 90∼9990∼99 in 7/22 patients (32%) with the BBD. In comparison, the bladder volume receiving 90% of the prescribed dose was 100% in 10/22 patients (45%), 90∼9990∼99 in 7/22 patients (32%), and 80∼8980∼89 in 5/22 patients (23%) without the BBD. When the BBD was used, an increase in the bladder volume receiving a high dose range was observed Conclusion: This study shows that the use of a BBD for the treatment of cancer in the pelvic area significantly improves small bowel sparing. However, since the BBD pushed the bladder into the treatment field, the bladder volume receiving the high dose could increase. Therefore it is recommended to be considerate in using the BBD when bladder damage is of concern.
This study was done to evaluate whether there were any differences in microleakage of class V composite restorations according to restoration site and cavity size. Total sixty-four restorations were made in molar teeth using Esthet-X. Small (2×2×1.5mm2×2×1.5mm) and large (4×2×1.5mm4×2×1.5mm) restorations were made at the buccal/lingual surface and the proximal surface each. After 1,000 times of thermocycling (5∘−55∘C5∘−55∘C), resin replica was made and the percentage of marginal gap to the whole periphery of the restoration was estimated from SEM evaluation. Thermocycled tooth was dye penetrated with 50%50% silver nitrate solution. After imbedding in an auto-curing resin, it was serially ground with a thickness of 0.25 mm. Volumetric microleakage was estimated after reconstructing three dimensionally. Two-way ANOVA and independent T-test for dye volume, Mann-Whitney U test for the percentage of marginal gap, Spearman's rho test for the relationship between two techniques were used, The results were as follows : 1. The site and size of the restoration affected on the microleakage of restoration. Namely, much more leakage was seen in the proximal and the large restorations rather than the buccal/lingual and the small restorations. 2. Close relationship was found between two techniques (Correlation coefficient = 0.614/ P = 0.000). Within the limits of this study, it was noted that proximal and the large restorations leaked more than buccal/lingual and the small restorations. Therefore, it should be strictly recommended large exposure of margins should be avoided by reducing unnecessary tooth reduction.
Machine learning is a field of artificial intelligence. It refers to an area of computer science related to providing machines the ability to perform their own data analysis, decision making and forecasting. For example, one of the representative machine learning models is artificial neural network, which is a statistical learning algorithm inspired by the neural network structure of biology. In addition, there are other machine learning models such as decision tree model, naive bayes model and SVM(support vector machine) model. Among the machine learning models, we use SVM model in this study because it is mainly used for classification and regression analysis that fits well to our study. The core principle of SVM is to find a reasonable hyperplane that distinguishes different group in the data space. Given information about the data in any two groups, the SVM model judges to which group the new data belongs based on the hyperplane obtained from the given data set. Thus, the more the amount of meaningful data, the better the machine learning ability. In recent years, many financial experts have focused on machine learning, seeing the possibility of combining with machine learning and the financial field where vast amounts of financial data exist. Machine learning techniques have been proved to be powerful in describing the non-stationary and chaotic stock price dynamics. A lot of researches have been successfully conducted on forecasting of stock prices using machine learning algorithms. Recently, financial companies have begun to provide Robo-Advisor service, a compound word of Robot and Advisor, which can perform various financial tasks through advanced algorithms using rapidly changing huge amount of data. Robo-Adviser's main task is to advise the investors about the investor's personal investment propensity and to provide the service to manage the portfolio automatically. In this study, we propose a method of forecasting the Korean volatility index, VKOSPI, using the SVM model, which is one of the machine learning methods, and applying it to real option trading to increase the trading performance. VKOSPI is a measure of the future volatility of the KOSPI 200 index based on KOSPI 200 index option prices. VKOSPI is similar to the VIX index, which is based on S&P 500 option price in the United States. The Korea Exchange(KRX) calculates and announce the real-time VKOSPI index. VKOSPI is the same as the usual volatility and affects the option prices. The direction of VKOSPI and option prices show positive relation regardless of the option type (call and put options with various striking prices). If the volatility increases, all of the call and put option premium increases because the probability of the option's exercise possibility increases. The investor can know the rising value of the option price with respect to the volatility rising value in real time through Vega, a Black-Scholes's measurement index of an option's sensitivity to changes in the volatility. Therefore, accurate forecasting of VKOSPI movements is one of the important factors that can generate profit in option trading. In this study, we verified through real option data that the accurate forecast of VKOSPI is able to make a big profit in real option trading. To the best of our knowledge, there have been no studies on the idea of predicting the direction of VKOSPI based on machine learning and introducing the idea of applying it to actual option trading. In this study predicted daily VKOSPI changes through SVM model and then made intraday option strangle position, which gives profit as option prices reduce, only when VKOSPI is expected to decline during daytime. We analyzed the results and tested whether it is applicable to real option trading based on SVM's prediction. The results showed the prediction accuracy of VKOSPI was 57.83% on average, and the number of position entry times was 43.2 times, which is less than half of the benchmark (100 times). A small number of trading is an indicator of trading efficiency. In addition, the experiment proved that the trading performance was significantly higher than the benchmark.
Purpose: In this study, we developed a new software tool for the analysis of renal scintigraphy which can be modified more easily by a user who needs to study new clinical applications, and the appropriateness of the results from our program was studied. Materials and Methods: The analysis tool was programmed with IDL5.2 and designed for use on a personal computer running Windows. For testing the developed tool and studying the appropriateness of the calculated glomerular filtration rate (GFR), 99mTc99mTc-DTPA was administered to 10 adults in normal condition. In order to study the appropriateness of the calculated mean transit time (MTT), 99mTc−DTPAand99mTc−MAG399mTc−DTPAand99mTc−MAG3 were administered to 11 adults in normal condition and 22 kidneys were analyzed. All the images were acquired with ORBITOR. the Siemens gamma camera. Results: With the developed tool, we could show dynamic renal images and time activity curve (TAC) in each ROI and calculate clinical parameters of renal function. The results calculated by the developed tool were not different statistically from the results obtained by the Siemens application program (Tmax: p=0.68, Relative Renal Function: p:1.0, GFR: p=0.25) and the developed program proved reasonable. The MTT calculation tool proved to be reasonable by the evaluation of the influence of hydration status on MTT. Conclusion: We have obtained reasonable clinical parameters for the evaluation of renal function with the software tool developed in this study. The developed tool could prove more practical than conventional, commercial programs.
The main purpose of this study is to help develop the productional system of the three dimensional digital animation domestically. Many 30 digital animation projects are being developed and finished with foreign computer graphics technology. However, the 3D animation market in Korea is not as good as the ones in other countries. One of the most significant problems is the lack of a program of study in Korea concerning productional systems used to create 3D animation. We previously imported an advanced productional system from the U.S., which was adaptable to big projects, and consequently, expanded the international digital animation market. Now, we need to develop a new production system which is fully adaptable to the Korean market. A non-sequential system of 3D digital animation tailored for small projects is more adaptable to domestic industry than the sequential system known as the 'Pipeline system.' A non-sequential system is good for small productions that are trying to create animation on a limited budget. The workers in this system can learn to make animation fast and effectively. They can also learn how to discuss with the others in order to avoid duplication of action. In contrast, in the Pipeline System, many workers repeat confirmation steps during the process for the same animations. The benefit of the non-sequential system is that the worker's interest and education can speed up production, because he/she can quickly learn every step of the animation process instead of just doing a particular job which does not allow him/her to observe the other steps involved. The 'animatic' step is the most important in the non-sequential system. The final animation is produced from the animatic. It is developed from scratch through to the final product but only after the agreement of all the workers, including a director.
Sequential pattern mining aims to discover interesting sequential patterns in a sequence database, and it is one of the essential data mining tasks widely used in various application fields such as Web access pattern analysis, customer purchase pattern analysis, and DNA sequence analysis. In general sequential pattern mining, only the generation order of data element in a sequence is considered, so that it can easily find simple sequential patterns, but has a limit to find more interesting sequential patterns being widely used in real world applications. One of the essential research topics to compensate the limit is a topic of weighted sequential pattern mining. In weighted sequential pattern mining, not only the generation order of data element but also its weight is considered to get more interesting sequential patterns. In recent, data has been increasingly taking the form of continuous data streams rather than finite stored data sets in various application fields, the database research community has begun focusing its attention on processing over data streams. The data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. In data stream processing, each data element should be examined at most once to analyze the data stream, and the memory usage for data stream analysis should be restricted finitely although new data elements are continuously generated in a data stream. Moreover, newly generated data elements should be processed as fast as possible to produce the up-to-date analysis result of a data stream, so that it can be instantly utilized upon request. To satisfy these requirements, data stream processing sacrifices the correctness of its analysis result by allowing some error. Considering the changes in the form of data generated in real world application fields, many researches have been actively performed to find various kinds of knowledge embedded in data streams. They mainly focus on efficient mining of frequent itemsets and sequential patterns over data streams, which have been proven to be useful in conventional data mining for a finite data set. In addition, mining algorithms have also been proposed to efficiently reflect the changes of data streams over time into their mining results. However, they have been targeting on finding naively interesting patterns such as frequent patterns and simple sequential patterns, which are found intuitively, taking no interest in mining novel interesting patterns that express the characteristics of target data streams better. Therefore, it can be a valuable research topic in the field of mining data streams to define novel interesting patterns and develop a mining method finding the novel patterns, which will be effectively used to analyze recent data streams. This paper proposes a gap-based weighting approach for a sequential pattern and amining method of weighted sequential patterns over sequence data streams via the weighting approach. A gap-based weight of a sequential pattern can be computed from the gaps of data elements in the sequential pattern without any pre-defined weight information. That is, in the approach, the gaps of data elements in each sequential pattern as well as their generation orders are used to get the weight of the sequential pattern, therefore it can help to get more interesting and useful sequential patterns. Recently most of computer application fields generate data as a form of data streams rather than a finite data set. Considering the change of data, the proposed method is mainly focus on sequence data streams.
In the preoperative evaluation before coronary artery bypass surgery, review of the coronary arteriogram is the most important step. Expected "normal" lumen diameter at a given coronary anatomic location is a basis for quantative estimation of coronary disease severity that could be more useful than the traditional "percent stenosis". The distribution and number of major coronary artery branches are determinants of number of bypass grafts needed. We reviewed the coronary artery anatomy in 174 adult patients who revealed no coronary pathology in angiographic studies done from September 1994 to June 1996. Quantative analysis was done in all cases by a single person using a Computerized System (Arripro 35ⓡ). The results were follows; 1) The mean diametre of left main coronary artery was 4.45 mm(range 2.74~6.72). The pattern of branching was bifurcation in 67.24%, trifurcation in 28.74% and quadrifurcation in 4.02% of the patients. 2) The mean diametre of left anterior descending artery was 3.17 mm(range 2.10~5.85), 2.79 (range 1.55~5.59) and 2.17 mm(range 1.37~3.81) in the proximal, mid, and the distal portions, respectively. The number of diagonal branches of left anterior artery was from one to four(mode=2). 3) The mean diametre of proximal and distal left circumflex artery were 3.17mm(range 1.74~4.89) and 2.19 mm(range 1.21~4.46). The number of obtuse marginal branches of left circumflex artery is from one to six(mode 2). 4) The mean diametre of proximal and distal right coronary artery, the posterior descending artery and the largest posterolateral branch were mean 3.51 mm(range 2.07~5.67), 2.09 mm (range 1.42~3.60), 2.09 mm(range 1.02~3.60) and 2.30 mm(range 1.39~4.39). 5) The right coronary artery dominant was 163 cases(93.68%) of the total 174 cases. 6) The large significant acute marginal artery was visualized in more than half of the people. half of the people.
Criticism of the postmodern philosophy of the system of representation, which has continued since the Renaissance, is based on a critique of the dichotomy that separates the subjects and objects and the environment from the human being. Interactivity, highlighted in a series of works emerging as postmodern trends in the 1960s, was transmitted to an interactive aspect of digital art in the late 1990s. The key feature of digital art is the possibility of infinite variations reflecting unpredictable changes based on public participation on the spot. In this process, the importance of computer programs is highlighted. Instead of using the existing program as it is, more and more artists are creating and programming their own algorithms or creating unique algorithms through collaborations with programmers. We live in an era of paradigm shift in which programming itself must be considered as a creative act. Simulation technology and VR technology draw attention as a technique to represent the meaning of reality. Simulation technology helps artists create experimental works. In fact, Baudrillard's concept of Simulation defines the other reality that has nothing to do with our reality, rather than a reality that is extremely representative of our reality. His book Simulacra and Simulation refers to the existence of a reality entirely different from the traditional concept of reality. His argument does not concern the problems of right and wrong. There is no metaphysical meaning. Applying the concept of simulation to algorithmic art, the artist models the complex attributes of reality in the digital system. And it aims to build and integrate internal laws that structure and activate the world (specific or individual), that is to say, simulate the world. If the images of the traditional order correspond to the reproduction of the real world, the synthesized images of algorithmic art and simulated space-time are the forms of art that facilitate the experience. The moment of seeing and listening to the work of Ian Cheng presented in this article is a moment of personal experience and the perception is made at that time. It is not a complete and closed process, but a continuous and changing process. It is this active and situational awareness that is required to the audience for the comprehension of post-representation's forms.
The U-Healthcare era has evolved with the development of the Internet of things (IoT) in the early stages of being connected as a society. Already, many changes such as increased well-being and the extension of human life are becoming evident across cultures. Korea entered the growing group of aging societies in 2017, and its silver industry is expected to grow rapidly by adopting the IoT of a super-connected society. In particular, the senior shift phenomenon has resulted in increased interest in the promotion of the health and well-being of the emergent silver generation which, unlike the existing silver generation, is highly active and wields great economic power. This study conducted in-depth interviews to investigate the characteristics of the new silver generation, and to develop the design for a wearable serious game that intends to boost the interest of the elderly in exercise and fitness activities according to their personalized physical training regimes as prescribed by the U-Hospital service. The usage scenario of this wearable serious game for the 'U-silver generation' is derived from social necessity. Medical professionals can utilize this technology to conduct health examinations and to monitor the rehabilitation of senior patients. The elderly can also use this tool to request checkups or to interface with their healthcare providers. The wearable serious game is further aimed at mitigating concerns about the deterioration of the physical functions of the silver generation by applying personalized exercise prescriptions. The present investigation revealed that it is necessary to merge the on / off line community activities to meet the silver generation's daily needs for connection and friendship. Further, the sustainability of the serious game must be enhanced through the inculcation of a sense of accomplishment as a player rises through the levels of the game. The proposed wearable serious game is designed specifically for the silver generation that is inexperienced in using digital devices: simple game rules are applied to a familiar interface grounded on the gourmet travels preferred by the target players to increase usability.
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