A thermodynamic analysis on an induced wet cooling tower is presented, using 1st and 2nd laws as well as exergy flow analysis. The variation of the second-law efficiency, exergy destruction and cooling tower effectiveness is determined as a function of various input parameters such as inlet air dry bulb temperature and inlet air relative humidity through a parametric study. Irreversible losses are determined by applying an exergy balance on each of the systems investigated. In this regard, an engineering equation solver program has been developed using thermodynamic functions and pressure and temperature dependent transport properties. For the different input variables that meet Abu Dhabi hot and humid environment, efficiencies were seen to decrease because of increasing the exergy destruction. Cooling down the outlet humid air will condensate a significant amount of pure water, in addition the cooled air can be recycled back to the tower for cooling the hot water.
The manufacture of scaled high-performance complex aerospace structures using RTM/VARTM is one of the most promising manufacturing technologies available in the market. They can be used to manufacture large three dimensional components with desired mechanical properties. Injection phase in Liquid composite molding (LCM) must ensure complete impregnation of resin within the dry preform. Many parameters affect the impregnation phase such as: pressure, temperature, viscosity, fiber compaction and gates/vents location. In the study, resin is going to be characterized as function of temperature and time using differential scanning calorimeter (DSC) and rheological meter. Understanding the injection characteristics and permeability effect is crucial in the whole process as well. These data will be used to simulate filling process using PAM/RTM software in order to estimate filling time and identify optimum gate and vent locations in the scaled structure. Moreover, fiber placement robots are going to be used for complex fiber layups.
Due to the rapid growth of electronic texts in the Internet, the need to identify, verify or profile their authors becomes increasingly attractive for forensics, market analysis, recommender systems, or even anti-forensics (pro-privacy) applications. This paper presents the results of an experiment in electronic text author verification. The novelty of this experiment is two fold. First, the use of a generalized n-grams feature extractor which allowed us to explore additional features beyond what is evaluated in the literature. Second, the generalization of the score aggregation function of the state-of-the-art in author verification. A partial implementation of this classifier ranked first in the international author identification challenge in PAN14: http://www.uni-weimar.de/medien/webis/research/events/pan-14/ --- the leading international competition in stylometry. This paper presents preliminary findings of a further developed author verification classifier with the addition of a feature that represents a special case of syntactic n-grams (sn-grams).
Demand response has become one of the major technologies for smart grids providing the means for efficient management and performance. The higher the demand response incentives set by utility companies, the more customers are participating to demand response schemes. Nonetheless, with increasing customer participation identifying the optimal load curtailment for customers turns out to be computationally complex. This paper proposes efficient algorithms for event-based demand response management for microgrids. In these systems, it is of significant importance to optimally shed loads as fast as possible to conserve microgrid stability, taking into account a combination of active and reactive power. Efficient algorithms for determining the optimal loads to be curtailed during islanded operation are compared and contrasted. A novel algorithm based on a greedy approach that is capable of determining a close-to-optimal load shedding scheme rapidly to maintain microgrid stability is proposed.
The rapid evolution of wireless communication capabilities and vehicular technology would allow traffic data to be disseminated and collected by travelling vehicles in the near future. Vehicular Ad hoc Networks (VANETs) are self-organizing networks that can support different types of traffic applications without requiring fixed infrastructure or centralized administration. Since traffic data is of public interest, it is more appropriate to rely on broadcasting for data dissemination in VANETs. However, broadcasting under high densities may easily lead to the broadcast storm problem due to data redundancy and packet collisions. Instead of blind data flooding, only some of the vehicles can be selected as packet relays. Existing solutions are not yet enabled to estimate traffic density effectively and accurately, and therefore, they do not scale well according to traffic regime. We propose to design a scalable data dissemination method for multi-hop VANETs that can estimate traffic regime for low broadcasting overhead.
Nowadays, agents technology plays an important role in the development of service applications. However, balancing between the flexible features agents provide and their vulnerability to many attacks is considered a great challenge. In this paper we discuss trust models developed by researcher for the sake of providing trustworthiness and security to Multi-Agent Systems (MAS). A framework for comparison of different trust models is provided. Trust models are first compared and classified according to types of evaluations used, weight assignment, consideration of inaccurate evaluations and architecture. They are also compared according to suitability to MAS
In-door wireless access becomes a standard and ensuring a thorough and economically sound wireless signal coverage throughout the building is increasingly important problem. In-building Distributed Antenna System (DAS) extends the wireless access from the base station to distributed antennas through the complex network of coaxial cables and power splitters. For high rise buildings the initial cost of DAS and the running costs of powering the network are quite significant, calling for the optimal design of DAS network. This Report offers a novel, complete building DAS optimization model that utilizes Particle Swarm Optimization (PSO) to provide a near optimal network topology that minimizes the cost of the cabling, equipment and power requirements. As opposed to other approaches which solve this problem only partially our model is a compete proposition for DAS optimization that is scalable and can deliver quality DAS designs even for the tallest buildings with hundreds of floors.
Warfarin dose vary up to 10-fold among patients. The gene encoding for the target enzyme of Warfarin, vitamin K epoxide reductase complex 1 (VKORC1), is a highly polymorphic gene and contributes about 30% of this variability .In this Study, we used PCR amplification and direct DNA Sanger sequencing to genotype the two most important variants in VKORC1 gene. The sample consisted of 117 Emirati healthy nationals as controls and 96 patients on Warfarin therapy. The alleles and genotypes frequencies were determined for both groups. In addition, the daily Warfarin maintenance dose for patients was examined for association with both SNPs. Crucially, both VKORC1 polymorphisms were found to be strongly associated with the Warfarin dose required to achieve the target international normalized ratio INR (p < 0.0001). The results of this study confirm the suitability of VKORC1 genotyping to guide the use of the appropriate Warfarin dose among Emiratis
Diabetes mellitus is a serious and increasing global health burden, with cardiac dysfunction reported as a frequent complication of clinical and experimental diabetes mellitus. In vivo biotelemetry studies in rat have demonstrated that heart rate is progressively reduced after administration of streptozocin1. The effect of streptozotocin-induced diabetes on action potentials in isolated perfused rat heart has been investigated. Heart rate was significantly reduced in Langendorff perfused spontaneously beating diabetic rat heart compared to controls. Prolongation of action potential repolarization may partly underlie reduced spontaneous heart rate in streptozotocin-induced diabetic rat.
Diabetic neuropathy affects more than 50% of diabetics but the underlying pathophysiological mechanism remains poorly understood. The aim of this project is to identify the early changes in gene expression in diabetic neuropathy. Samples of dorsal root ganglia were dissected from STZ rats and age matched controls. RNA was extracted, converted to cDNA for low density arrays. Genes selected for the low density arrays were those involved in sympathetic and afferent nerve function in the dorsal root ganglia. Gene expression was studied based on the results of the low density arrays. Several interesting and promising changes in expression of different genes was seen suggesting their involvement in diabetic neuropathy. Insight into changes in gene expression furthers our knowledge of the pathogenesis of diabetic neuropathy and may pave the way for future therapeutic interventions.
