955 resultados para Quantified Autoepistemic Logic


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Molecular logic-based computation continues to throw up new applications in sensing and switching, the newest of which is the edge detection of objects. The scope of this phenomenon is mapped out by the use of structure-activity relationships, where several structures of the molecules and of the objects are examined. The different angles and curvatures of the objects are followed with good-fidelity in the visualized edges, even when the objects are in reverse video.

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This article examines how civilian defense militias shape violence during civil war. We define civilian defense forces as a sedentary and defensive form of pro-government militia that incumbents often use to harness the participation of civilians during a counterinsurgency campaign. We argue that civilian defense forces reduce the problem of insurgent identification. This leads to a reduction in state violence against civilians. However, we also claim that these actors undermine civilian support for insurgents, which leads to an increase in rebel violence against civilians and overall intensification of conflict. A statistical analysis of government and rebel violence against civilians from 1981 to 2005, and a qualitative assessment of a civilian defense force operating in Iraq from 2005 to 2009, offer strong support for our theoretical claims. These findings provide further insight into pro-government militias and their effects on violence. They also have wider ethical implications for the use of civilian collaborators during civil war.

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The non-covalent incorporation of responsive luminescent lanthanide, Ln(iii), complexes with orthogonal outputs from Eu(iii) and Tb(iii) in a gel matrix allows for in situ logic operation with colorimetric outputs. Herein, we report an exemplar system with two inputs ([H(+)] and [F(-)]) within a p(HEMA-co-MMA) polymer organogel acting as a dual-responsive device and identify future potential for such systems.

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Structural and functional information encoded in DNA combined with unique properties of nanomaterials could be of use for the construction of novel biocomputational circuits and intelligent biomedical nanodevices. However, at present their practical applications are still limited by either low reproducibility of fabrication, modest sensitivity, or complicated handling procedures. Here, we demonstrate the construction of label-free and switchable molecular logic gates (AND, INHIBIT, and OR) that use specific conformation modulation of a guanine- and thymine-rich DNA, while the optical readout is enabled by the tunable metamaterials which serve as a substrate for surface enhanced Raman spectroscopy (MetaSERS). Our MetaSERS-based DNA logic is simple to operate, highly reproducible, and can be stimulated by ultra-low concentration of the external inputs, enabling an extremely sensitive detection of mercury ions down to 2×10-4 ppb, which is four orders of magnitude lower than the exposure limit allowed by United States Environmental Protection Agency

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Current variation aware design methodologies, tuned for worst-case scenarios, are becoming increasingly pessimistic from the perspective of power and performance. A good example of such pessimism is setting the refresh rate of DRAMs according to the worst-case access statistics, thereby resulting in very frequent refresh cycles, which are responsible for the majority of the standby power consumption of these memories. However, such a high refresh rate may not be required, either due to extremely low probability of the actual occurrence of such a worst-case, or due to the inherent error resilient nature of many applications that can tolerate a certain number of potential failures. In this paper, we exploit and quantify the possibilities that exist in dynamic memory design by shifting to the so-called approximate computing paradigm in order to save power and enhance yield at no cost. The statistical characteristics of the retention time in dynamic memories were revealed by studying a fabricated 2kb CMOS compatible embedded DRAM (eDRAM) memory array based on gain-cells. Measurements show that up to 73% of the retention power can be saved by altering the refresh time and setting it such that a small number of failures is allowed. We show that these savings can be further increased by utilizing known circuit techniques, such as body biasing, which can help, not only in extending, but also in preferably shaping the retention time distribution. Our approach is one of the first attempts to access the data integrity and energy tradeoffs achieved in eDRAMs for utilizing them in error resilient applications and can prove helpful in the anticipated shift to approximate computing.

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A key assumption of dual process theory is that reasoning is an explicit, effortful, deliberative process. The present study offers evidence for an implicit, possibly intuitive component of reasoning. Participants were shown sentences embedded in logically valid or invalid arguments. Participants were not asked to reason but instead rated the sentences for liking (Experiment 1) and physical brightness (Experiments 2-3). Sentences that followed logically from preceding sentences were judged to be more likable and brighter. Two other factors thought to be linked to implicit processing-sentence believability and facial expression-had similar effects on liking and brightness ratings. The authors conclude that sensitivity to logical structure was implicit, occurring potentially automatically and outside of awareness. They discuss the results within a fluency misattribution framework and make reference to the literature on discourse comprehension. 

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Some plants of genus Schinus have been used in the folk medicine as topical antiseptic, digestive, purgative, diuretic, analgesic or antidepressant, and also for respiratory and urinary infections. Chemical composition of essential oils of S. molle and S. terebinthifolius had been evaluated and presented high variability according with the part of the plant studied and with the geographic and climatic regions. The pharmacological properties, namely antimicrobial, anti-tumoural and anti-inflammatory activities are conditioned by chemical composition of essential oils. Taking into account the difficulty to infer the pharmacological properties of Schinus essential oils without hard experimental approach, this work will focus on the development of a decision support system, in terms of its knowledge representation and reasoning procedures, under a formal framework based on Logic Programming, complemented with an approach to computing centered on Artificial Neural Networks and the respective Degree-of-Confidence that one has on such an occurrence.

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Research on how customers engage in the co-creation processes envisaged by the Servicedominant logic paradigm is currently limited and even less work has been published on frameworks for organizations to manage the co-creation process. This conceptual paper examines a particular aspect of co-creation: co-production as a result of the application of self-service technology (SST). We propose a conceptual framework for co-production, which emphasizes the need to understand productivity from the point of view of the customer, and demonstrate how this can be applied in both consumer (b2c) and interorganizational(b2b) contexts. We conclude that service organizations might benefit from clearly identifying co-production with task-performance, and co-creation with the valueattributing aspects of the customer service experience. Both aspects generate a range of design and management challenges for suppliers particularly the need to understand the cocreation process 'outputs' desired by customers and the full costs of moving away from person to person interaction.

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Thesis (Master's)--University of Washington, 2015

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Thesis (Master's)--University of Washington, 2015

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This paper present a methodology to choose the distribution networks reconfiguration that presents the lower power losses. The proposed methodology is based on statistical failure and repair data of the distribution power system components and uses fuzzy-probabilistic modeling for system component outage parameters. The proposed hybrid method using fuzzy sets and Monte Carlo simulation based on the fuzzyprobabilistic models allows catching both randomness and fuzziness of component outage parameters. A logic programming algorithm is applied, once obtained the system states by Monte Carlo Simulation, to get all possible reconfigurations for each system state. To evaluate the line flows and bus voltages and to identify if there is any overloading, and/or voltage violation an AC load flow has been applied to select the feasible reconfiguration with lower power losses. To illustrate the application of the proposed methodology, the paper includes a case study that considers a 115 buses distribution network.