In this paper, 2-steps software using image processing and enhancement technologies is developed to obtain a scoliosis patient's spine pattern from 2D coronal X-Ray images without manual land marking. Then, a Rule...
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We introduce a new region-based SELective Flow-Sensitive (Selfs) approach to inter-procedural pointer analysis for C that operates on the regions partitioned from a program. Flow-sensitivity is maintained between the ...
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Cloud Computing is a new technology that has rapidly established itself in computer science since it allows the usage of huge computing resources that are dynamically allocated in order to satisfy user's needs and...
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Cloud Computing is a new technology that has rapidly established itself in computer science since it allows the usage of huge computing resources that are dynamically allocated in order to satisfy user's needs and that are accessible as a service through a remote interface, such as a web browser. Cloud resources can be distributed in different places and such distribution is made transparent to the user;this one does not need to worry about data replication and/or maintenance of the infrastructure but he/she benefits only of the required services, by exploiting the Pay-Per-Use business model. In this context, the interoperability among different providers becomes critical due to the vendor lock-in problem. Here we present a multi agent system that accesses, on behalf of the user, the utility market of Cloud computing to maintain the best resources configuration that satisfies the application requirements. It also offers management and monitoring facilities for the Cloud infrastructure in order to guide the user in all the phases of the application's lifecycle. Together with the platform, we present client-side tools that can be used to orchestrate agents' based services.
Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to iden- tifying fetuses which...
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Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate (FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to iden- tifying fetuses which suffer from lack of oxygen, i.e. hypoxia. This situation is defined as fetal dis- tress and requires fetal intervention in order to prevent fetus death or other neurological disease caused by hypoxia. In this study a computer-based approach for analyzing cardiotocogram in- cluding diagnostic features for discriminating a pathologic fetus. In order to achieve this aim adaptive boosting ensemble of decision trees and various other machine learning algorithms are employed.
In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a...
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In this work, classification of cellular structures in the high resolutional histopathological images and the discrimination of cellular and non-cellular structures have been investigated. The cell classification is a very exhaustive and time-consuming process for pathologists in medicine. The development of digital imaging in histopathology has enabled the generation of reasonable and effective solutions to this problem. Morever, the classification of digital data provides easier analysis of cell structures in histopathological data. Convolutional neural network (CNN), constituting the main theme of this study, has been proposed with different spatial window sizes in RGB color spaces. Hence, to improve the accuracies of classification results obtained by supervised learning methods, spatial information must also be considered. So, spatial dependencies of cell and non-cell pixels can be evaluated within different pixel neighborhoods in this study. In the experiments, the CNN performs superior than other pixel classification methods including SVM and k-Nearest Neighbour (k-NN). At the end of this paper, several possible directions for future research are also proposed.
Sum of squares (SOS) optimization has been a powerful and influential addition to the theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite programming, however, has seriously ...
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Sum of squares (SOS) optimization has been a powerful and influential addition to the theory of optimization in the past decade. Its reliance on relatively large-scale semidefinite programming, however, has seriously challenged its ability to scale in many practical applications. In this paper, we introduce DSOS and SDSOS optimization as more tractable alternatives to sum of squares optimization that rely instead on linear programming and second order cone programming. These are optimization problems over certain subsets of sum of squares polynomials and positive semidefinite matrices and can be of potential interest in general applications of semidefinite programming where scalability is a limitation.
Optical character recognition(OCR) can be used in some management mechanisms of state and business world to organize documents scanned or captured by camera. Therefore, OCR is one of the subjects rapidly evolving in t...
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Optical character recognition(OCR) can be used in some management mechanisms of state and business world to organize documents scanned or captured by camera. Therefore, OCR is one of the subjects rapidly evolving in the recent times. This study investigates the procedure steps until character recognition. That's because, the more correctly preprocessings are applied;the better results can be obtained in character recognition. In this study, the algorithms providing the best results are determined by following the procedure stages of gray scale transformation, noise removal and image thresholding. Binarization plays an important role in character recognition. For this reason, algorithms dynamically determine thresholds are preferred for character recognition in this study. Accordingly, Otsu thresholding method was determined to give the best results in terms of both picture quality and speed. Therefore, this method was used for character recognition. Primarily, lines were determined for character separation and then letters were individually obtained.
Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate(FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to identifying fetuses which su...
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Cardiotocography is one of the most widely used technique for recording changes in fetal heart rate(FHR) and uterine contractions. Assessing cardiotocography is crucial in that it leads to identifying fetuses which suffer from lack of oxygen, i.e. hypoxia. This situation is defined as fetal distress and requires fetal intervention in order to prevent fetus death or other neurological disease caused by hypoxia. In this study a computer-based approach for analyzing cardiotocogram including diagnostic features for discriminating a pathologic fetus. In order to achieve this aim adaptive boosting ensemble of decision trees and various other machine learning algorithms are employed.
Uninitialized variables can cause system crashes when used and security vulnerabilities when exploited. With source rather than binary instrumentation, dynamic analysis tools such as MSan can detect uninitialized memo...
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ISBN:
(纸本)9781450326704
Uninitialized variables can cause system crashes when used and security vulnerabilities when exploited. With source rather than binary instrumentation, dynamic analysis tools such as MSan can detect uninitialized memory uses at significantly reduced overhead but are still *** this paper, we introduce a static value-flow analysis, called Usher, to guide and accelerate the dynamic analysis performed by such tools. Usher reasons about the definedness of values using a value-flow graph (VFG) that captures def-use chains for both top-level and address-taken variables interprocedurally and removes unnecessary instrumentation by solving a graph reachability problem. Usher works well with any pointer analysis (done a priori) and facilitates advanced instrumentation-reducing optimizations (with two demonstrated here). Implemented in LLVM and evaluated using all the 15 SPEC2000 C programs, Usher can reduce the slowdown of MSan from 212% -- 302% to 123% -- 140% for a number of configurations tested.
Member of the Russian Academy of Sciences Vladimir Melnikov was a disciple of the great Russian scientist, academician Sergei Lebedev, who was the founder of the national computer science, the creator of the first Sov...
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Member of the Russian Academy of Sciences Vladimir Melnikov was a disciple of the great Russian scientist, academician Sergei Lebedev, who was the founder of the national computer science, the creator of the first Soviet computers, the chief designer of computers that made up the famous BESM line (high-speed electronic computers). Since 1950, being the fifth-year student, he worked in the Academic Institute of Precise Mechanics and computerengineering (IPMCE), where participated in the development of the first soviet electronic computer. The serial BESM version was called BESM-2, and Melnikov became the executive in charge. Later this computer was replicated in China. A significant role in the life of Melnikov was played by the creation of the transistor BESM-6 computer, on which he worked as a deputy chief designer. In 1967, this computer was put into production and was produced for 17 years. In 1969 Melnikov started the design and development of a computing system "BESM-6 pairing hardware interface" (HI-6). In 1975, during the Soviet-American space flight 'Soyuz-Apollo' the operation was carried out on the system, built on the basis of HI-6 and BESM-6, that also provided a highly automated processing of ballistic and telemetry data in the Soviet Mission Control Center. Since 1978 Melnikov began to develop a new supercomputer, which had the name 'Electronics SS BIS' and was close to the American supercomputer Cray 1 in its instruction set.
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