41 resultados para FEED-UTILIZATION


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Traffic Engineering has been the prime concern for Internet Service Providers (ISPs), with the main focus being minimization of over-utilization of network capacity even though additional capacity is available which is under-utilized, Furthermore, requirements of timely delivery of digitized audiovisual information raises a new challenge of finding a path meeting these requirements. This paper addresses the issue of (a) distributing load to achieve global efficiency in resource utilization. (b) Finding a path satisfying the real time requirements of, delay and bandwidth requested by the applications. In this paper we do a critical study of the link utilization that varies over time and determine the time interval during which the link occupancy remains constant across days. This information helps in pre-determining link utilization that is useful in balancing load in the network Finally, we run simulations that use a dynamic time interval for profiling traffic and show improvement in terms number of calls admitted/blocked.

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This paper presents an artificial feed forward neural network (FFNN) approach for the assessment of power system voltage stability. A novel approach based on the input-output relation between real and reactive power, as well as voltage vectors for generators and load buses is used to train the neural net (NN). The input properties of the feed forward network are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The neural network is trained for the L-index output as the target vector for each of the system loads. Two separate trained NN, corresponding to normal loading and contingency, are investigated on the 367 node practical power system network. The performance of the trained artificial neural network (ANN) is also investigated on the system under various voltage stability assessment conditions. As compared to the computationally intensive benchmark conventional software, near accurate results in the value of L-index and thus the voltage profile were obtained. Proposed algorithm is fast, robust and accurate and can be used online for predicting the L-indices of all the power system buses. The proposed ANN approach is also shown to be effective and computationally feasible in voltage stability assessment as well as potential enhancements within an overall energy management system in order to determining local and global stability indices

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This article compares the land use in solar energy technologies with conventional energy sources. This has been done by introducing two parameters called land transformation and land occupation. It has been shown that the land area transformed by solar energy power generation is small compared to hydroelectric power generation, and is comparable with coal and nuclear energy power generation when life-cycle transformations are considered. We estimate that 0.97% of total land area or 3.1% of the total uncultivable land area of India would be required to generate 3400 TWh/yr from solar energy power systems in conjunction with other renewable energy sources.

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In this study, the influence of tool rotation speed and feed rate on the forming limit of friction stir welded Al 6061-T651 sheets has been investigated. The forming limit curve was evaluated by limit dome height test performed on all the friction stir welded sheets. The welding trials were conducted at a tool rotation speed of 1300 and 1400 r/min and feed rate of 90 and 100 mm/min. A third trial of welding was performed at a rotational speed of 1500 r/min and feed rate 120 mm/min. It is found that with increase in the tool rotation speed, from 1300 to 1400 r/min, for a constant feed rate, the forming limit of friction stir welded blank has improved and with increase in feed rate, from 90 to 100 mm/min, for a constant tool rotation speed, it has decreased. The forming limit of friction stir welded sheets is better than unwelded sheets. The thickness gradient after forming is severe in the cases of friction stir welded blanks made at higher feed rate and lower rotation speed. The strain hardening exponent of weld (n) increases with increase in tool rotation speed and it decreases with increase in feed rate. It has been demonstrated that the change in the forming limit of friction stir welded sheets with respect to welding parameters is due to the thickness distribution severity and strain hardening exponent of the weld region during forming. There is not much variation in the dome height among the friction stir welded sheets tested. When compared with unwelded sheets, dome height of friction stir welded sheets is higher in near-plane-strain condition, but it is lesser in stretching strain paths.

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The zinc finger transcription factors Mxr1p and Rop are key regulators of methanol metabolism in the methylotrophic yeast, Pichia pastoris, while Trm1p and Trm2p regulate methanol metabolism in Candida boidinii. Here, we demonstrate that Trm1p is essential for the expression of genes of methanol utilization (mut) pathway in P. pastoris as well. Expression of AOXI and other genes of mut pathway is severely compromised in P. pastoris Delta Trm1 strain resulting in impaired growth on media containing methanol as the sole source of carbon. Trm1p localizes to the nucleus of cells cultured on glucose or methanol. The zinc finger domain of Mxr1p but not Trm1p binds to AOXI promoter sequences in vitro, indicating that these two positive regulators act by different mechanisms. We conclude that both Trm1p and Mxr1p are essential for the expression of genes of mut pathway in P. pastoris and the mechanism of transcriptional regulation of mut pathway may be similar in P. pastoris and C. boidinii. (C) 2014 Elsevier Inc. All rights reserved.

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Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

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The bglA gene of Escherichia coli encodes phospho-beta-glucosidase A capable of hydrolyzing the plant-derived aromatic beta-glucoside arbutin. We report that the sequential accumulation of mutations in bglA can confer the ability to hydrolyze the related aromatic beta-glucosides esculin and salicin in two steps. In the first step, esculin hydrolysis is achieved through the acquisition of a four-nucleotide insertion within the promoter of the bglA gene, resulting in enhanced steady-state levels of the bglA transcript. In the second step, hydrolysis of salicin is achieved through the acquisition of a point mutation within the bglA structural gene close to the active site without the loss of the original catabolic activity against arbutin. These studies underscore the ability of microorganisms to evolve additional metabolic capabilities by mutational modification of preexisting genetic systems under selection pressure, thereby expanding their repertoire of utilizable substrates.

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Fungus-growing termites are involved in many ecological processes and play a central role in influencing soil dynamics in the tropics. The physical and chemical properties of their nest structures have been largely described; however less information is available concerning the relatively temporary structures made above-ground to access food items and protect the foraging space (the soil `sheetings'). This study investigated whether the soil physical and chemical properties of these constructions are constant or if they vary depending on the type of food they cover. Soil samples and soil sheetings were collected in a forest in India, from leaves on the ground (LEAF), fallen branches (WOOD), and vertical soil sheetings covering the bark of trees (TREE). In this environment, termite diversity was dominated by Odontotermes species, and especially Odontotermes feae and Odontotermes obesus. However, there was no clear niche differentiation and, for example, O. feae termites were found on all the materials. Compared with the putative parent soil (control), TREE sheetings showed the greatest (and most significant) differences (higher clay content and smaller clay particle sizes, lower C and N content and smaller delta C-13 and delta N-15), while LEAF sheetings were the least modified, though still significantly different than the control soil. We suggest that the termite diversity is a less important driver of potential soil modification than sheeting diversity. Further, there is evidence that construction properties are adapted to their prospective life-span, with relatively long-lasting structures being most different from the parent soil. (C) 2015 Elsevier Masson SAS. All rights reserved.