Performance Analysis of TFRC and UDP over Mobile-IP Network with Competing Flows

This study aimed to conduct a performance analysis of TFRC and UDP over mobile-IP network with competing flows that enables to investigate three major performance metrics such as jitter, throughput, packet loss and packet delay. Two different transport layer protocols have been used in this analysis. As mobility has been the core issue of computing of 21st century, this research aims to contribute to this phenomenon by implementing performance analysis in mobile IP network, where mobile devices (nodes) are moved from access points to access points (AP) in order to exemplify the suitability of TFRC and UDP in wireless networking. Moreover to collect data about crucial performance metrics features. The experiment has been conducted by Network Simulation (NS-2)

Neural network fault diagnosis of a trolling motor based on feature reduction techniques for an unmanned surface vehicle

This article presents a novel approach to the diagnosis of unbalanced faults in a trolling motor under stationary operating conditions. The trolling motor being typically of that used as the propulsion system for an unmanned surface vehicle, the diagnosis approach is based on the use of discrete wavelet transforms as a feature extraction tool and a time-delayed neural network for fault classification. The time-delayed neural network classifies between healthy and faulty conditions of the trolling motor by analysing the stator current and vibration. To overcome feature redundancy, which affects diagnosis accuracy, several feature reduction methods have been tested, and the orthogonal fuzzy neighbourhood discriminant analysis approach is found to be the most effective method. Four faulty conditions were analysed under laboratory conditions, where one of the blades causing damage to the trolling motor is cut into 10%, 25%, half and then into full to simulate the effects of propeller blades being damaged partly or fully. The results obtained from the real-time simulation demonstrate the effectiveness and reliability of the proposed methodology in classifying the different faults faster and accurately

Using genetic algorithm for optimal sizing of stand-alone hybrid energy system

When planning a hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources—those that rely on fossil fuels—the primary considerations are the total cost of the system and the CO? emissions. In this paper, we will investigate the typical hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources involving a detailed simulation process that may require specific inputs, models, and data. Then, we employed dual optimization methods: genetic algorithm (GA) and particle swarm optimization (PSO). The consequences of GA and PSO execution in the bus timetabling problem depict that the GA algorithm is better at finding the optimal solution in terms of accuracy and iteration. Additionally, the GA algorithm is also superior to the straightforwardness of the techniques used. So, in this work, we employed a Genetic Algorithm Optimization (GA)–-based optimal sizing technique for HES configurations that include sustainability wind turbines (WTs), battery storage (BS), and diesel generators (DGs). HES improved power delivery to a rural community in the Wasit Province, Iraq, situated at 46° - 36° and 32° - 31° in the country's southeastern central region. Throughout the project's 25-year lifespan, the optimization primarily aims to minimize the total cost (CT) and total CO? emissions (ECO2T). The outcomes demonstrate that the GA algorithm may, with continuous electricity supply, minimize the objectives while meeting the load demand

La rhodophycée Gelidium spinosum (S.G. Gmelin) P.C. Silva, des côtes de Monastir (Tunisie) : quelques éléments hydrobiologiques et potentialités en agar-agar

La rhodophycée Gelidium spinosum (S.G. Gmelin) P.C. Silva (Rhodophycées ; Gélidiales) a été étudiée pendant une année, depuis septembre 2000 jusqu’à août 2001, sur la côte de Monastir (Est de la Tunisie). Les résultats globaux obtenus montrent que le poids humide maximum (environ 37 g/individu) a été atteint en mai. La longueur maximale (environ 11 cm) a été enregistrée en juin. La biomasse maximale en poids humide (environ 7000 g/m2) a été obtenue en mai. Quant à la fertilité, elle a varié entre 0%(Mai) et 100% (Septembre, Juin, Juillet et Août). Concernant le rendement en agar, le maximum a été obtenu en avril (33.4 % du poids sec), La force de gel maximale a atteint environ 705 g.cm-² (juin). Le point de gélification et le point de fusion les plus élevés ont été obtenus respectivement en août (34.33°C) et septembre (94.33°C).Mots-clés : Gelidium spinosum, poids, longueur, biomasse, fertilité, agar-agar

A Robust Bearing Fault Detection and Diagnosis Technique for Brushless DC Motors Under Non-stationary Operating Conditions

Rolling element bearing defects are among the main reasons for the breakdown of electrical machines, and therefore, early diagnosis of these is necessary to avoid more catastrophic failure consequences. This paper presents a novel approach for identifying rolling element bearing defects in brushless DC motors under non-stationary operating conditions. Stator current and lateral vibration measurements are selected as fault indicators to extract meaningful features, using a discrete wavelet transform. These features are further reduced via the application of orthogonal fuzzy neighbourhood discriminative analysis. A recurrent neural network is then used to detect and classify the presence of bearing faults. The proposed system is implemented and tested in simulation on data collected from an experimental setup, to verify its effectiveness and reliability in accurately detecting and classifying the various faults

Modeling and Experimental Investigation of Laminar Ceiling Air Distribution System for Operating Room in Merjan Teaching Hospital

Room air distribution in operating rooms is critical to successful surgical treatment. The present study investigated the effects of the location of the air supply and exhaust grills on the air movement and air parameters inside an operating room. This paper presents an experimental and numerical analysis of air distribution in the operating room. The experimental work was conducted in an operating room in Merjan Teaching Hospital in the city of Babylon. Air was supplied from one square plenum box located in the middle of the ceiling, while air was exhausted through eight grills: large exhaust grills in the four upper corners and small exhaust grills in the four lower corners. In the theoretical work, a model of the operating room was developed and two cases were analyzed using the FLUEN 6.3.26 software program. The first case included all eight exhaust grills, while the second case included only the four lower exhaust grills. The ceiling system gave good ventilation for air distribution inside the operating room. There was no clear effect of the small exhaust grills located in the upper corners of the operating room. The height of the ceiling room is an effective factor in air distribution

Common evolutionary origin of planktonic and benthic nitrogen-fixing oscillatoriacean cyanobacteria from tropical oceans

The filamentous cyanobacteria belonging to the genus Hydrocoleum (Blennothrix) are among the most common mat-forming cyanobacteria in tropical oceans. We present here the evidence that these benthic cyanobacteria are morphologically and phylogenetically very close to the planktonic species of Trichodesmium. Genetic relationship was established independently with regard to sequences of the 16S rRNA gene, nifH gene, and phycocyanin and phycoerythrin intergenic spacers. The species of both genera formed a common distinct branch in phylogenetically reconstructed cyanobacterial trees, suggesting that the main constituents of cyanobacterial benthos and plankton have an early common origin and both represent major contributors to nitrogen budget of tropical oceans today as in the distant geological past

Interactions of lipid monolayers with the natural biopolymer hyaluronic acid

AbstractThe interaction of the natural mucopolysaccharide hyaluronic acid with different lipids, present in the natural membranes, was studied at the lipid/water interface using thermodynamic methods and X-ray diffraction. The results show that this biopolymer modifies the properties and the structure of the lipid monolayer. The two-dimensional crystalline lattice and domain structure of the charged octadecylamine monolayer are strongly disturbed by the hyaluronic acid, the monolayer compressibility increases and the monolayer collapse pressure drops down. In addition, the presence of charged lipid interfaces influences the structural organisation of the hyaluronic acid at the membrane/water interfaces. The impacts of these results on the structural organisation at the membrane interface are discussed

Rodent models of neuroinflammation for Alzheimer\u27s disease

Alzheimer\u27s disease remains incurable, and the failures of current disease-modifying strategies for Alzheimer\u27s disease could be attributed to a lack of in vivo models that recapitulate the underlying etiology of late-onset Alzheimer\u27s disease. The etiology of late-onset Alzheimer\u27s disease is not based on mutations related to amyloid-beta (A beta) or tau production which are currently the basis of in vivo models of Alzheimer\u27s disease. It has recently been suggested that mechanisms like chronic neuroinflammation may occur prior to amyloid-beta and tau pathologies in late-onset Alzheimer\u27s disease. The aim of this study is to analyze the characteristics of rodent models of neuroinflammation in late-onset Alzheimer\u27s disease. Our search criteria were based on characteristics of an idealistic disease model that should recapitulate causes, symptoms, and lesions in a chronological order similar to the actual disease. Therefore, a model based on the inflammation hypothesis of late-onset Alzheimer\u27s disease should include the following features: (i) primary chronic neuroinflammation, (ii) manifestations of memory and cognitive impairment, and (iii) late development of tau and A beta pathologies. The following models fit the pre-defined criteria: lipopolysaccharide-and PolyI:C-induced models of immune challenge; streptozotocin-, okadaic acid-, and colchicine neurotoxin-induced neuroinflammation models, as well as interleukin-1 beta, anti-nerve growth factor and p25 transgenic models. Among these models, streptozotocin, PolyI:C-induced, and p25 neuroinflammation models are compatible with the inflammation hypothesis of Alzheimer\u27s disease