40 resultados para drinking context


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Service discovery is vital in ubiquitous applications, where a large number of devices and software components collaborate unobtrusively and provide numerous services without user intervention. Existing service discovery schemes use a service matching process in order to offer services of interest to the users. Potentially, the context information of the users and surrounding environment can be used to improve the quality of service matching. To make use of context information in service matching, a service discovery technique needs to address certain challenges. Firstly, it is required that the context information shall have unambiguous representation. Secondly, the devices in the environment shall be able to disseminate high level and low level context information seamlessly in the different networks. And thirdly, dynamic nature of the context information be taken into account. We propose a C-IOB(Context-Information, Observation and Belief) based service discovery model which deals with the above challenges by processing the context information and by formulating the beliefs based on the observations. With these formulated beliefs the required services will be provided to the users. The method has been tested with a typical ubiquitous museum guide application over different cases. The simulation results are time efficient and quite encouraging.

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Context-sensitive points-to analysis is critical for several program optimizations. However, as the number of contexts grows exponentially, storage requirements for the analysis increase tremendously for large programs, making the analysis non-scalable. We propose a scalable flow-insensitive context-sensitive inclusion-based points-to analysis that uses a specially designed multi-dimensional bloom filter to store the points-to information. Two key observations motivate our proposal: (i) points-to information (between pointer-object and between pointer-pointer) is sparse, and (ii) moving from an exact to an approximate representation of points-to information only leads to reduced precision without affecting correctness of the (may-points-to) analysis. By using an approximate representation a multi-dimensional bloom filter can significantly reduce the memory requirements with a probabilistic bound on loss in precision. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that with an average storage requirement of 4MB, our approach achieves almost the same precision (98.6%) as the exact implementation. By increasing the average memory to 27MB, it achieves precision upto 99.7% for these benchmarks. Using Mod/Ref analysis as the client, we find that the client analysis is not affected that often even when there is some loss of precision in the points-to representation. We find that the NoModRef percentage is within 2% of the exact analysis while requiring 4MB (maximum 15MB) memory and less than 4 minutes on average for the points-to analysis. Another major advantage of our technique is that it allows to trade off precision for memory usage of the analysis.

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The quality of tap water from water supplies from 14 districts of Kerala state, India was studied. Parameters like pH, water temperature, total dissolved solids, salinity, nitrates, chloride, hardness, magnesium, calcium, sodium, potassium, fluoride, sulphate, phosphates, and coliform bacteria were enumerated. The results showed that all water samples were contaminated by coliform bacteria. About 20% of the tap water samples from Alappuzha and 15% samples from Palakkad district are above desirable limits prescribed by Bureau of Indian Standards. The contamination of the source water (due to lack of community hygiene) and insufficient treatment are the major cause for the coliform contamination in the state. Water samples from Alappuzha and Palakkad have high ionic and fluoride content which could be attributed to the geology of the region. Water supplied for drinking in rural areas are relatively free of any contamination than the water supplied in urban area by municipalities, which may be attributed higher chances of contamination in urban area due to mismanagement of solid and liquid wastes. The study highlights the need for regular bacteriological enumeration along with water quality in addition to setting up decentralised region specific improved treatment system.

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When people drink water having a fluoride (F-) concentration >1-1.5 mg/L for a long period of time, various ailments that are collectively referred to as fluorosis occur. Based on the design of Thomas (http://www.planetkerala.org), an inclined basin-type solar still containing sand and water has been used at Bangalore for defluoridation. For water samples having a fluoride concentration in the range 5-20 mg/L, the fluoride concentration in the distillate was usually <1.5 mg/L. During the periods October 2006 May 2007 and October 2007 May 2008, the volume of distillate showed a significant diurnal variation, ranging from 0.3 to 4.0 L/m(2).day. Based on the figures for 2006, the cost of the still was about Rs. 850 (US$16) for collector areas in the range 0.50-0.57 m(2). The occurrence of F- in the distillate merits further investigation. Overall, the still effectively removes F-, but a large area of the collector, in the range 2.5-25 m(2), is needed to produce about 10 L of distilled water for cooking and drinking. Rainwater falling on the upper surface of the still was collected, and its fluoride concentration was found to be below the desirable limit of 1 mg/L. Hence it can also be used for cooking and drinking.

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The yeast Bud31 protein, a Prp19 complex (NTC) member, aids spliceosome assembly and thus promotes efficient pre-mRNA splicing. The bud31 null cells show mild budding abnormalities at optimal growth temperatures and, at higher temperatures, have growth defects with aberrant budding. Here we have assessed cell cycle transitions which require Bud31. We find Bud31 facilitates passage through G1-S regulatory point (Start) but is not needed for G2-M transition or for exit from mitosis. To co-relate Bud31 functions in cell division with splicing, we studied the splicing status of transcripts that encode proteins involved in budding. We find Bud31 promotes efficient splicing of only some of these pre-mRNAs, for example, ARP2 and SRC1. Wild type cells have a long and a short isoform of SRC1 mRNA and protein, out of which the shorter mRNA splice variant is predominant. bud31 Delta cells show inefficient SRC1 splicing and entirely lack the shorter SRC1 spliced mRNA isoform. Yeast PRP17, another NTC sub-complex member, is also required for G1-S and G2-M cell cycle transitions. We examined genetic interactions between BUD31 and PRP17. While both factors were needed for efficient cell cycle dependent gene expression, our data indicate that distinct pre-mRNAs depend on each of these non-essential splicing factors.

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We interpret the recent discovery of a 125 GeV Higgs-like state in the context of a two-Higgs-doublet model with a heavy fourth sequential generation of fermions, in which one Higgs doublet couples only to the fourth-generation fermions, while the second doublet couples to the lighter fermions of the first three families. This model is designed to accommodate the apparent heaviness of the fourth-generation fermions and to effectively address the low-energy phenomenology of a dynamical electroweak-symmetry-breaking scenario. The physical Higgs states of the model are, therefore, viewed as composites primarily of the fourth-generation fermions. We find that the lightest Higgs, h, is a good candidate for the recently discovered 125 GeV spin-zero particle, when tan beta similar to O(1), for typical fourth-generation fermion masses of M-4G = 400-600 GeV, and with a large t-t' mixing in the right-handed quark sector. This, in turn, leads to BR(t' -> th) similar to O(1), which drastically changes the t' decay pattern. We also find that, based on the current Higgs data, this two-Higgs-doublet model generically predicts an enhanced production rate (compared to the Standard Model) in the pp -> h -> tau tau channel, and reduced rates in the VV -> h -> gamma gamma and p (p) over bar /pp -> V -> hV -> Vbb channels. Finally, the heavier CP-even Higgs is excluded by the current data up to m(H) similar to 500 GeV, while the pseudoscalar state, A, can be as light as 130 GeV. These heavier Higgs states and the expected deviations from the Standard Model din some of the Higgs production channels can be further excluded or discovered with more data.

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Context-aware computing is useful in providing individualized services focusing mainly on acquiring surrounding context of user. By comparison, only very little research has been completed in integrating context from different environments, despite of its usefulness in diverse applications such as healthcare, M-commerce and tourist guide applications. In particular, one of the most important criteria in providing personalized service in a highly dynamic environment and constantly changing user environment, is to develop a context model which aggregates context from different domains to infer context of an entity at the more abstract level. Hence, the purpose of this paper is to propose a context model based on cognitive aspects to relate contextual information that better captures the observation of certain worlds of interest for a more sophisticated context-aware service. We developed a C-IOB (Context-Information, Observation, Belief) conceptual model to analyze the context data from physical, system, application, and social domains to infer context at the more abstract level. The beliefs developed about an entity (person, place, things) are primitive in most theories of decision making so that applications can use these beliefs in addition to history of transaction for providing intelligent service. We enhance our proposed context model by further classifying context information into three categories: a well-defined, a qualitative and credible context information to make the system more realistic towards real world implementation. The proposed model is deployed to assist a M-commerce application. The simulation results show that the service selection and service delivery of the system are high compared to traditional system.

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Ubiquitous Computing is an emerging paradigm which facilitates user to access preferred services, wherever they are, whenever they want, and the way they need, with zero administration. While moving from one place to another the user does not need to specify and configure their surrounding environment, the system initiates necessary adaptation by itself to cope up with the changing environment. In this paper we propose a system to provide context-aware ubiquitous multimedia services, without user’s intervention. We analyze the context of the user based on weights, identify the UMMS (Ubiquitous Multimedia Service) based on the collected context information and user profile, search for the optimal server to provide the required service, then adapts the service according to user’s local environment and preferences, etc. The experiment conducted several times with different context parameters, their weights and various preferences for a user. The results are quite encouraging.

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A porous carbon foam (CF) electrode modified with a reduced graphene oxide-Ag (rGO-Ag) nanocomposite has been fabricated to purify water. It can perform as an antibacterial device by killing pathogenic microbes with the aid of a 1.5 V battery, with very little power consumption. The device is recycled ten times with good performance for long term usage. It is shown that the device may be implemented as a fast water purifier to deactivate the pathogens in drinking water.

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In the process of service provisioning, providing required service to the user without user intervention, with reduction of the cognitive over loading is a real challenge. In this paper we propose a user centred context aware collaborative service provisioning system, which make use of context along with collaboration to provide the required service to the user dynamically. The system uses a novel approach of query expansion along with interactive and rating matrix based collaboration. Performance of the system is evaluated in Mobile-Commerce environment. The results show that the system is time efficient and perform with better precision and recall in comparison with context aware system.