912 resultados para Symbolic Execution


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Altered expression of the INT6 gene, encoding the e subunit of the translational initiation factor eIF3, occurs in human breast cancers, but how INT6 relates to carcinogenesis remains unestablished. Here, we show that INT6 is involved in the DNA damage response. INT6 was required for cell survival following γ-irradiation and G(2)-M checkpoint control. RNA interference-mediated silencing of INT6 reduced phosphorylation of the checkpoint kinases CHK1 and CHK2 after DNA damage. In addition, INT6 silencing prevented sustained accumulation of ataxia telangiectasia mutated (ATM) at DNA damage sites in cells treated with γ-radiation or the radiomimetic drug neocarzinostatin. Mechanistically, this result could be explained by interaction of INT6 with ATM, which together with INT6 was recruited to the sites of DNA damage. Finally, INT6 silencing also reduced ubiquitylation events that promote retention of repair proteins at DNA lesions. Accordingly, accumulation of the repair factor BRCA1 was defective in the absence of INT6. Our findings reveal unexpected and striking connections of INT6 with ATM and BRCA1 and suggest that the protective action of INT6 in the onset of breast cancers relies on its involvement in the DNA damage response.

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This paper proposes a technique that supports process participants in making risk-informed decisions, with the aim to reduce the process risks. Risk reduction involves decreasing the likelihood and severity of a process fault from occurring. Given a process exposed to risks, e.g. a financial process exposed to a risk of reputation loss, we enact this process and whenever a process participant needs to provide input to the process, e.g. by selecting the next task to execute or by filling out a form, we prompt the participant with the expected risk that a given fault will occur given the particular input. These risks are predicted by traversing decision trees generated from the logs of past process executions and considering process data, involved resources, task durations and contextual information like task frequencies. The approach has been implemented in the YAWL system and its effectiveness evaluated. The results show that the process instances executed in the tests complete with substantially fewer faults and with lower fault severities, when taking into account the recommendations provided by our technique.

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In Virgtel Ltd v Zabusky [2009] QCA 92 the Queensland Court of Appeal considered the scope of an order “as to costs only” within the meaning of s 253 of the Supreme Court Act 1995 (Qld) (‘the Act”). The Court also declined to accept submissions from one of the parties after oral hearing, and made some useful comments which serve as a reminder to practitioners of their obligations in that regard.

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Business Process Management describes a holistic management approach for the systematic design, modeling, execution, validation, monitoring and improvement of organizational business processes. Traditionally, most attention within this community has been given to control-flow aspects, i.e., the ordering and sequencing of business activities, oftentimes in isolation with regards to the context in which these activities occur. In this paper, we propose an approach that allows executable process models to be integrated with Geographic Information Systems. This approach enables process models to take geospatial and other geographic aspects into account in an explicit manner both during the modeling phase and the execution phase. We contribute a structured modeling methodology, based on the well-known Business Process Model and Notation standard, which is formalized by means of a mapping to executable Colored Petri nets. We illustrate the feasibility of our approach by means of a sustainability-focused case example of a process with important ecological concerns.

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Animals are often used as symbols in policy debates and media accounts of marine pollution. Images of miserable oil-soaked marine birds and mammals are prominent following high profile oil spills such as the Exxon Valdez, Prestige and Pacific Adventurer incidents. Portrayed as hapless victims, these animal actors are not only cast as powerful symbols of the effects of anthropogenic pollution but also represent an environment in crisis. Animals, like the broader environment, are seen as something which is acted upon. Less attention has been given to the ways in which animals have been cast as either the cause of marine pollution or as having the potential to actively mitigate the potential impacts of anthropogenic marine pollution. This article explores how animals are constructed with respect to vessel-sourced sewage pollution. Through a process of interpretive policy analysis, drawing on media reports and responses to an Australian regulatory review process this study found that, when defending the perceived right to pollute recreational boaters implicated animals such as dogs, fish, turtles, dolphins and seabirds in their pollution discourses. Scapegoating was an important rhetorical feature of claims-making strategies designed to avoid responsibility for changing sewage disposal practices.

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In this paper we present for the first time a complete symbolic navigation system that performs goal-directed exploration to unfamiliar environments on a physical robot. We introduce a novel construct called the abstract map to link provided symbolic spatial information with observed symbolic information and actual places in the real world. Symbolic information is observed using a text recognition system that has been developed specifically for the application of reading door labels. In the study described in this paper, the robot was provided with a floor plan and a destination. The destination was specified by a room number, used both in the floor plan and on the door to the room. The robot autonomously navigated to the destination using its text recognition, abstract map, mapping, and path planning systems. The robot used the symbolic navigation system to determine an efficient path to the destination, and reached the goal in two different real-world environments. Simulation results show that the system reduces the time required to navigate to a goal when compared to random exploration.

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This paper presents a technique for the automated removal of noise from process execution logs. Noise is the result of data quality issues such as logging errors and manifests itself in the form of infrequent process behavior. The proposed technique generates an abstract representation of an event log as an automaton capturing the direct follows relations between event labels. This automaton is then pruned from arcs with low relative frequency and used to remove from the log those events not fitting the automaton, which are identified as outliers. The technique has been extensively evaluated on top of various auto- mated process discovery algorithms using both artificial logs with different levels of noise, as well as a variety of real-life logs. The results show that the technique significantly improves the quality of the discovered process model along fitness, appropriateness and simplicity, without negative effects on generalization. Further, the technique scales well to large and complex logs.

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Despite a wealth of studies focusing on innovation, types of innovations and their outcomes, the process of innovation has largely been under studied. In 2010, Swanson calls for researchers to address the ‘innovation process black box’, to better understand how IT innovation potential can be exploited upon. This study derives and instantiates three unique and mutually exclusive innovation execution mechanisms: Continual, Progressive and Plug and Play. The innovation execution mechanisms of this study are developed with reference to Swanson (1994) Information Systems innovation types.

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This paper addresses the problem of predicting the outcome of an ongoing case of a business process based on event logs. In this setting, the outcome of a case may refer for example to the achievement of a performance objective or the fulfillment of a compliance rule upon completion of the case. Given a log consisting of traces of completed cases, given a trace of an ongoing case, and given two or more possible out- comes (e.g., a positive and a negative outcome), the paper addresses the problem of determining the most likely outcome for the case in question. Previous approaches to this problem are largely based on simple symbolic sequence classification, meaning that they extract features from traces seen as sequences of event labels, and use these features to construct a classifier for runtime prediction. In doing so, these approaches ignore the data payload associated to each event. This paper approaches the problem from a different angle by treating traces as complex symbolic sequences, that is, sequences of events each carrying a data payload. In this context, the paper outlines different feature encodings of complex symbolic sequences and compares their predictive accuracy on real-life business process event logs.

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This practice-led project is implemented in the context of rites of passage based on significant events in formative transitions of Self. It employs an intuitive methodology to examine and explore the 'Child archetype', mythos, symbolic imagination and self-narrative, through the manifestation of a visual symbolic language. The contexts, methods and processes enable empowerment, heightened awareness of personal and collective relationships, meaningful discovery and development of innovative ideas and forms. The implications for this project highlight the importance of intuition in creativity and innovation. Creative practice is a vehicle for personal and collective interconnectedness. I have discovered self-empowerment, meaningful learning and innovative forms of personal and collective communication as a way of enabling transition of a significant life event.

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The StreamIt programming model has been proposed to exploit parallelism in streaming applications oil general purpose multicore architectures. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on accelerators such as Graphics Processing Units (GPUs) or CellBE which support abundant parallelism in hardware. In this paper, we describe a novel method to orchestrate the execution of if StreamIt program oil a multicore platform equipped with an accelerator. The proposed approach identifies, using profiling, the relative benefits of executing a task oil the superscalar CPU cores and the accelerator. We formulate the problem of partitioning the work between the CPU cores and the GPU, taking into account the latencies for data transfers and the required buffer layout transformations associated with the partitioning, as all integrated Integer Linear Program (ILP) which can then be solved by an ILP solver. We also propose an efficient heuristic algorithm for the work-partitioning between the CPU and the GPU, which provides solutions which are within 9.05% of the optimal solution on an average across the benchmark Suite. The partitioned tasks are then software pipelined to execute oil the multiple CPU cores and the Streaming Multiprocessors (SMs) of the GPU. The software pipelining algorithm orchestrates the execution between CPU cores and the GPU by emitting the code for the CPU and the GPU, and the code for the required data transfers. Our experiments on a platform with 8 CPU cores and a GeForce 8800 GTS 512 GPU show a geometric mean speedup of 6.94X with it maximum of 51.96X over it single threaded CPU execution across the StreamIt benchmarks. This is a 18.9% improvement over it partitioning strategy that maps only the filters that cannot be executed oil the GPU - the filters with state that is persistent across firings - onto the CPU.

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An important question which has to be answered in evaluting the suitability of a microcomputer for a control application is the time it would take to execute the specified control algorithm. In this paper, we present a method of obtaining closed-form formulas to estimate this time. These formulas are applicable to control algorithms in which arithmetic operations and matrix manipulations dominate. The method does not require writing detailed programs for implementing the control algorithm. Using this method, the execution times of a variety of control algorithms on a range of 16-bit mini- and recently announced microcomputers are calculated. The formulas have been verified independently by an analysis program, which computes the execution time bounds of control algorithms coded in Pascal when they are run on a specified micro- or minicomputer.

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The StreamIt programming model has been proposed to exploit parallelism in streaming applications on general purpose multi-core architectures. This model allows programmers to specify the structure of a program as a set of filters that act upon data, and a set of communication channels between them. The StreamIt graphs describe task, data and pipeline parallelism which can be exploited on modern Graphics Processing Units (GPUs), as they support abundant parallelism in hardware. In this paper, we describe the challenges in mapping StreamIt to GPUs and propose an efficient technique to software pipeline the execution of stream programs on GPUs. We formulate this problem - both scheduling and assignment of filters to processors - as an efficient Integer Linear Program (ILP), which is then solved using ILP solvers. We also describe a novel buffer layout technique for GPUs which facilitates exploiting the high memory bandwidth available in GPUs. The proposed scheduling utilizes both the scalar units in GPU, to exploit data parallelism, and multiprocessors, to exploit task and pipelin parallelism. Further it takes into consideration the synchronization and bandwidth limitations of GPUs, and yields speedups between 1.87X and 36.83X over a single threaded CPU.

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REDEFINE is a reconfigurable SoC architecture that provides a unique platform for high performance and low power computing by exploiting the synergistic interaction between coarse grain dynamic dataflow model of computation (to expose abundant parallelism in applications) and runtime composition of efficient compute structures (on the reconfigurable computation resources). We propose and study the throttling of execution in REDEFINE to maximize the architecture efficiency. A feature specific fast hybrid (mixed level) simulation framework for early in design phase study is developed and implemented to make the huge design space exploration practical. We do performance modeling in terms of selection of important performance criteria, ranking of the explored throttling schemes and investigate effectiveness of the design space exploration using statistical hypothesis testing. We find throttling schemes which give appreciable (24.8%) overall performance gain in the architecture and 37% resource usage gain in the throttling unit simultaneously.

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Ramakrishnan A, Chokhandre S, Murthy A. Voluntary control of multisaccade gaze shifts during movement preparation and execution. J Neurophysiol 103: 2400-2416, 2010. First published February 17, 2010; doi: 10.1152/jn.00843.2009. Although the nature of gaze control regulating single saccades is relatively well documented, how such control is implemented to regulate multisaccade gaze shifts is not known. We used highly eccentric targets to elicit multisaccade gaze shifts and tested the ability of subjects to control the saccade sequence by presenting a second target on random trials. Their response allowed us to test the nature of control at many levels: before, during, and between saccades. Although the saccade sequence could be inhibited before it began, we observed clear signs of truncation of the first saccade, which confirmed that it could be inhibited in midflight as well. Using a race model that explains the control of single saccades, we estimated that it took about 100 ms to inhibit a planned saccade but took about 150 ms to inhibit a saccade during its execution. Although the time taken to inhibit was different, the high subject-wise correlation suggests a unitary inhibitory control acting at different levels in the oculomotor system. We also frequently observed responses that consisted of hypometric initial saccades, followed by secondary saccades to the initial target. Given the estimates of the inhibitory process provided by the model that also took into account the variances of the processes as well, the secondary saccades (average latency similar to 215 ms) should have been inhibited. Failure to inhibit the secondary saccade suggests that the intersaccadic interval in a multisaccade response is a ballistic stage. Collectively, these data indicate that the oculomotor system can control a response until a very late stage in its execution. However, if the response consists of multiple movements then the preparation of the second movement becomes refractory to new visual input, either because it is part of a preprogrammed sequence or as a consequence of being a corrective response to a motor error.