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"abstract": "Growing B-spline model of curve approximation exploits local control of B-spline which leads to efficient approximation of complex curves, even with higher order B-splines. Approximation is carried out progressively (growing) in this model which is another factor for efficient approximation. Control points are adjusted / re-positioned in each iteration of approximation based on error between two curves. Proposed method can avoid any need of parameterization and complex computations. Proposed growing model can be applied with any degree of B-spline curve.",
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"abstract": "Efficient and informative visualization of surfaces with uncertainties is an important topic with many applications in science and engineering. Examples include environmental pollution borderline identification, identification of the limits of an oil basin, or discrimination between contaminated and healthy tissue in medicine. This paper presents an approach for such visualization using points as display primitives. Our approach is to render each polygon as a collection of points and to displace each point from the surface in the direction of the surface normal by an amount proportional to some random number multiplied by the uncertainty level at that point. This approach can be used in combination with other techniques such as pseudo-coloring and shading to give rise to efficient and revealing visualizations. The method is used to visualize real and simulated tumor formations with uncertainty of tumor boundaries.",
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"abstract": "In the framework of the axiomatic information theory proposed by J. Kampe de Feriet and B. Forte, the authors present some results concerning composable uncertainties. In particular the authors apply the recursive method due to P. Benvenuti in order to obtain the explicit form of the set of generalizations of the uncertainty measures studied by C. Bertoluzza and M. Schneider (1974). Some examples are also presented.<>",
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"content": "In the framework of the axiomatic information theory proposed by J. Kampe de Feriet and B. Forte, the authors present some results concerning composable uncertainties. In particular the authors apply the recursive method due to P. Benvenuti in order to obtain the explicit form of the set of generalizations of the uncertainty measures studied by C. Bertoluzza and M. Schneider (1974). Some examples are also presented.<>",
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"abstract": "This paper presents the manipulation planning of a dual-arm robot for an assembly task. To assemble the parts, two types of paths for the robot are required: assembly and re-grasping. The assembly path assembles and holds the objects with a fixed grasp, while the re-grasping path changes the robots grasp on objects depending on how the object was picked up and how it will be used. We implement a Rapidly-exploring Random Trees (RRT) algorithm to generate the assembly path and the re-grasping path in different ways to obtain the manipulation path of the dual-arm robot for the assembly task. Finally, both simple problems like linear puzzles and very complicated problems like alpha puzzles can be solved using the proposed manipulation planning algorithm. These examples are tested through simulation.",
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"content": "In this paper, a 4 degree-of-freedom (DOF) chess playing robotic manipulator and computer vision based chess recognition system are presented. The robotic system is capable of playing chess game autonomously against human or another robotic system. The logical system consists of anti-glare camera mounted on the chessboard, which acts as an eye of robot, personal computer for run-time implementation of computer vision algorithm, an open-source chess engine used as chess brain of robotic manipulator, which plays chess algorithmic ally on behalf of robot, and of course robot itself. On development side, a simple image segmentation based computer vision algorithm was developed to find the legitimate chess move and human hand motion detection, a software system was developed that enables the robot to pick and drop chess pieces from prescribed chess boxes, lastly communication channel was exploited for interfacing computer vision algorithm with chess engine. The whole robotic system is formulated from recycled machine parts and open source tools. The convincing performance of computer vision algorithm and robotic manipulator testifies by its 1st position in IEEE Final Year Project Competition Lahore 2012.",
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"abstract": "We present the game tree search techniques based on Chinese chess game, and use mobile robots to present the scenario. We design a mobile robot to be applied in many fields, such as entertainment, education and security. The mobile robot has the shape of cylinder and its diameter, height and weight is 8cm, 15cm and 1.5kg. The power of the mobile robot is three Li batteries, and connects with parallel arrangement. It has three IR sensors to detect obstacle. The controller of the mobile robot is MCS-51 chip, and can acquire the detection signal from sensors through I/O pins, and receives the command from the supervised computer and the remote controller via wireless RF interface. The controller of the mobile robot can transmits the detection result to the supervised computer via wireless RF interface. The mobile robot can speak Chinese language using voice driver module. We develop the user interface of mobile robots according to the basic rules of Chinese chess game, and program the motion trajectories for the mobile robot to play the Chinese chess game. In the experimental results, mobile robots can receive the command from the supervised computer, and move the next position according to the attribute of the chess piece.",
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"content": "We present the game tree search techniques based on Chinese chess game, and use mobile robots to present the scenario. We design a mobile robot to be applied in many fields, such as entertainment, education and security. The mobile robot has the shape of cylinder and its diameter, height and weight is 8cm, 15cm and 1.5kg. The power of the mobile robot is three Li batteries, and connects with parallel arrangement. It has three IR sensors to detect obstacle. The controller of the mobile robot is MCS-51 chip, and can acquire the detection signal from sensors through I/O pins, and receives the command from the supervised computer and the remote controller via wireless RF interface. The controller of the mobile robot can transmits the detection result to the supervised computer via wireless RF interface. The mobile robot can speak Chinese language using voice driver module. We develop the user interface of mobile robots according to the basic rules of Chinese chess game, and program the motion trajectories for the mobile robot to play the Chinese chess game. In the experimental results, mobile robots can receive the command from the supervised computer, and move the next position according to the attribute of the chess piece.",
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"abstract": "As the Tibetan traditional game with unique connotation and characteristics of national culture, Tibetan chess plays an important role in Tibetan culture heritage and protection. Tibetan chess includes different types of chess board and regulations. Chess board is with huge branching factor, the complexity of the search space is very high. Besides, chess play record collection is important issue facing the Tibetan chess. In the rare play record case of chess, how to search branch and evaluate the situation effectively is of theoretical significance. The development of high level Tibetan chess computer game system has a very important significance. Compared with the game of chess and Go, Tibetan chess game research is still in its infancy. Minzu University for China has developed the first \"JIU\" system and \"MIMANG\" system, other ethnic research groups have worked in \"JIA\", \"KING and MINISTER\" and so on.",
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"title": "A Method for Estimating Online Chess Game Player Ratings with Decision Tree",
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"abstract": "Chess is a popular game among many people worldwide and is frequently played online. Although players are ranked based on existing rating systems, automation is essential for coordinating matches in tournaments with thousands of participants. In this study, we analyzed the game records of highly skilled chess players and determined appropriate ratings for players without ratings by using a decision tree model. It was determined that high-rated and low-rated players could be identified with accuracy levels above 80%, even for players who were not included at the time of model training.",
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"affiliation": "Tsuda University,Graduate Program of Mathematics and Computer Science,Tokyo,Japan",
"fullName": "Habuki Yamada",
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"affiliation": "Tsuda University,College of Liberal Arts,Tokyo,Japan",
"fullName": "Nobuko Kishi",
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"affiliation": "Ochanomizu University,Department of Science,Tokyo,Japan",
"fullName": "Masato Oguchi",
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"affiliation": "Tsuda University,College of Liberal Arts,Tokyo,Japan",
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"abstract": "Fast Search and Find of Density Peaks (FSFDP) is a newly proposed clustering algorithm that has already been successfully applied in many applications. However, this algorithm shows a dissatisfactory performance on large dataset due to the time-consuming calculation of the distance matrix and potentials. In this paper, we proposed a GPU-accelerated FSFDP with CUDA to improve its performance. Thread/block models and the shared memory usage are dedicatedly designed to maximize the utilization of GPUs' hardware resources, and a merge accumulation algorithm based on the odd and even positions of an array is introduced as well. Experimental results show that our parallel implementation of FSFDP can reach a 4.39X and a 15.75X speedup for the calculation of the distance matrix and potentials respectively compared to the serial program on a single CPU core. Higher speedup can be expected for data of larger scales until the device limits are reached. Besides, CUDA stream mechanism is also employed and extra time savings can be obtained by hiding the corresponding memory latency of multiple kernels in a two-way streams' scheduling. Moreover, we evaluate our GPU-based implementation on GPU clusters of 9 nodes and compared to one GPU node, the program can achieve a further 7.55X speedup.",
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"content": "Fast Search and Find of Density Peaks (FSFDP) is a newly proposed clustering algorithm that has already been successfully applied in many applications. However, this algorithm shows a dissatisfactory performance on large dataset due to the time-consuming calculation of the distance matrix and potentials. In this paper, we proposed a GPU-accelerated FSFDP with CUDA to improve its performance. Thread/block models and the shared memory usage are dedicatedly designed to maximize the utilization of GPUs' hardware resources, and a merge accumulation algorithm based on the odd and even positions of an array is introduced as well. Experimental results show that our parallel implementation of FSFDP can reach a 4.39X and a 15.75X speedup for the calculation of the distance matrix and potentials respectively compared to the serial program on a single CPU core. Higher speedup can be expected for data of larger scales until the device limits are reached. Besides, CUDA stream mechanism is also employed and extra time savings can be obtained by hiding the corresponding memory latency of multiple kernels in a two-way streams' scheduling. Moreover, we evaluate our GPU-based implementation on GPU clusters of 9 nodes and compared to one GPU node, the program can achieve a further 7.55X speedup.",
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"abstract": "Graphics Processing Units (GPUs) provide an attractive option for extracting data-level parallelism from diverse applications. However, some applications, although possess abundant data-level parallelism, exhibit irregular memory access patterns to the shared data structures. Porting such applications to GPUs requires synchronization mechanisms such as locks, which significantly increase the programming complexity. Coarse-grained locking, where a single lock controls all the shared resources, although reduces programming efforts, can substantially serialize GPU threads. On the other hand, fine-grained locking, where each data element is protected by an independent lock, although facilitates maximum parallelism, requires significant programming efforts. To overcome these challenges, we propose to support software transactional memory (STM) on GPU that is able to achieve performance comparable to fine-grained locking, while requiring minimal programming efforts. Software-based transactional execution can incur significant runtime overheads due to activities such as detecting conflicts across thousands of GPU threads and managing a consistent memory state. Thus, in this paper we illustrate three lightweight STM designs that are capable of scaling to a large number of GPU threads. In our system, programmers simply mark the critical sections in the applications, and the underlying STM support is able to achieve performance comparable to fine-grained locking.",
"abstracts": [
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"content": "Graphics Processing Units (GPUs) provide an attractive option for extracting data-level parallelism from diverse applications. However, some applications, although possess abundant data-level parallelism, exhibit irregular memory access patterns to the shared data structures. Porting such applications to GPUs requires synchronization mechanisms such as locks, which significantly increase the programming complexity. Coarse-grained locking, where a single lock controls all the shared resources, although reduces programming efforts, can substantially serialize GPU threads. On the other hand, fine-grained locking, where each data element is protected by an independent lock, although facilitates maximum parallelism, requires significant programming efforts. To overcome these challenges, we propose to support software transactional memory (STM) on GPU that is able to achieve performance comparable to fine-grained locking, while requiring minimal programming efforts. Software-based transactional execution can incur significant runtime overheads due to activities such as detecting conflicts across thousands of GPU threads and managing a consistent memory state. Thus, in this paper we illustrate three lightweight STM designs that are capable of scaling to a large number of GPU threads. In our system, programmers simply mark the critical sections in the applications, and the underlying STM support is able to achieve performance comparable to fine-grained locking.",
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"abstract": "Reversible data hiding is a kind of information hiding technique that can exactly recover the original image through data hiding and extraction. It can be potentially used in the medical and military applications. In the literature, by using the maximum inter-class square error to separate the background and foreground, the principal gray-scale values in the segmented background can be identified. By excluding the corresponding histogram bins from being expanded, the contrast of region of interest (ROI) in medical images can be selectively enhanced. In this paper, a new method is proposed to get the foreground contour to enhance the contrast of ROI in medical images, while the original image can be exactly recovered when needed. The experimental results on a set of medical images show that the visibility of ROI can be improved. Compared with the previous method, the proposed method can achieve better contrast enhancement effects and visual quality.",
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"abstract": "Protection of medical images using watermarking is an imperative area of research. In telemedicine, medical images are exchanged between distant places through unsecure networks like internet for diagnosis purpose. During this transfer, medical images may be tampered intentionally or accidentally. The medical practitioner has to check the integrity of Region of Interest (ROI) in the received medical image before making any diagnostic decisions. In this paper, we are developing a novel fragile and block based medical image watermarking technique for producing high quality watermarked medical images, verifying the integrity of ROI, detecting accurately the tampered blocks inside ROI using both average and variance of blocks and recovering the original ROI with zero loss. In the proposed method, the medical image is segmented into three sets of pixels: ROI pixels, Region of Non Interest (RONI) pixels and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on number of medical images reveal that proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI of watermarked medical images with 100% accuracy and recovers the original ROI without any loss.",
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"content": "Protection of medical images using watermarking is an imperative area of research. In telemedicine, medical images are exchanged between distant places through unsecure networks like internet for diagnosis purpose. During this transfer, medical images may be tampered intentionally or accidentally. The medical practitioner has to check the integrity of Region of Interest (ROI) in the received medical image before making any diagnostic decisions. In this paper, we are developing a novel fragile and block based medical image watermarking technique for producing high quality watermarked medical images, verifying the integrity of ROI, detecting accurately the tampered blocks inside ROI using both average and variance of blocks and recovering the original ROI with zero loss. In the proposed method, the medical image is segmented into three sets of pixels: ROI pixels, Region of Non Interest (RONI) pixels and border pixels. Then, authentication data and information of ROI are embedded in border pixels. Recovery data of ROI is embedded into RONI. Results of experiments conducted on number of medical images reveal that proposed method produces high quality watermarked medical images, identifies the presence of tampers inside ROI of watermarked medical images with 100% accuracy and recovers the original ROI without any loss.",
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"title": "2021 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)",
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"abstract": "Medical scene graph contributes to cognitive tasks such as question answering. An automatic medical scene graph generator can annotate medical images with scene graphs conveniently. An end-to-end model is proposed, which contains an automatic medical scene graph generator based on medical images and surgery records. The novel model can extract symptom information of the images from surgery records via name entity recognition then convert it into scene graphs. The content and format of the scene graph are pre-defined according to the features of the images. A medical scene graph (MSG) dataset is also produced. The dataset contains 116 scene graphs where each graph includes 6 to 30 entities. Experiments show that our model performs well on making scene graphs of CT coronary angiography. Significantly, the scene graphs have the type, state, location, and index of arteries. To verify the practicability of the MSG dataset, We construct an intelligent model that can generate key diagnostic results. In addition, our medical scene graph generator can be applied to other medical areas to annotate different kinds of medical images intelligently. And the MSG dataset can directly be used in other cognitive visual tasks.",
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"content": "Medical scene graph contributes to cognitive tasks such as question answering. An automatic medical scene graph generator can annotate medical images with scene graphs conveniently. An end-to-end model is proposed, which contains an automatic medical scene graph generator based on medical images and surgery records. The novel model can extract symptom information of the images from surgery records via name entity recognition then convert it into scene graphs. The content and format of the scene graph are pre-defined according to the features of the images. A medical scene graph (MSG) dataset is also produced. The dataset contains 116 scene graphs where each graph includes 6 to 30 entities. Experiments show that our model performs well on making scene graphs of CT coronary angiography. Significantly, the scene graphs have the type, state, location, and index of arteries. To verify the practicability of the MSG dataset, We construct an intelligent model that can generate key diagnostic results. In addition, our medical scene graph generator can be applied to other medical areas to annotate different kinds of medical images intelligently. And the MSG dataset can directly be used in other cognitive visual tasks.",
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"title": "Medical image fusion: a proposed methodology for treatment evaluation",
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"abstract": "Medical image fusion allows to combine multiple images from single or multiple imaging modalities to improve the imaging quality. It supports physicians in performing more accurate clinical decisions and analysis based on medical images. Hybrid imaging with FDG PET/CT is became a standard in the day-to-day clinical practice for management of cancer because it combines the subtle biologic changes detected by FDG PET with the anatomic information offered by CT scans.In this context, we consider hybrid imaging with FDG PET/CT to propose a methodology aiming to use the fusion CT and PET images to evaluate drug administration in patients undergoing treatment.",
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"abstract": "We introduce the light localization problem. A scene is illuminated by a set of unobserved isotropic point lights. Given the geometry, materials, and illuminated, appearance of the scene, the light localization problem is to completely recover the number, positions, and intensities of the lights. We first present a scene transform that identifies likely light positions. Based on this transform, we develop an iterative algorithm to locate remaining lights and determine all light intensities. We demonstrate the success of this method in a large set of 2D synthetic scenes, and show that it extends to 3D, in both synthetic scenes and real-world scenes.",
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"affiliation": "Waseda University",
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"abstract": "The high peak-to-average power ratio (PAR) in Orthogonal Frequency Division Multiplexing (OFDM) modulation systems can significantly reduce power efficiency and performance. This paper examines the problem of reducing the peak-to-average power ratio (PAPR) occurring in OFDM systems based on IEEE 802.11a. A low complexity PAPR reduction algorithm is proposed. A revised ACE-POCS method is put forward and the simulation results for its performance are given. Proposed algorithm used revised ACE-POCS as the preferred method to reduce PAPR while clipping is used as last resort. System simulation based on OFDM shows that proposed algorithm can reduce system PAPR efficiently with low calculation complexity at the cost of Bit-Error-Ratio (BER) performance degradation slightly.",
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"content": "The high peak-to-average power ratio (PAR) in Orthogonal Frequency Division Multiplexing (OFDM) modulation systems can significantly reduce power efficiency and performance. This paper examines the problem of reducing the peak-to-average power ratio (PAPR) occurring in OFDM systems based on IEEE 802.11a. A low complexity PAPR reduction algorithm is proposed. A revised ACE-POCS method is put forward and the simulation results for its performance are given. Proposed algorithm used revised ACE-POCS as the preferred method to reduce PAPR while clipping is used as last resort. System simulation based on OFDM shows that proposed algorithm can reduce system PAPR efficiently with low calculation complexity at the cost of Bit-Error-Ratio (BER) performance degradation slightly.",
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