Aerodynamic analysis of Speedo Fastskin-I Swimsuit

Swimming is one of the most energy intensive sporting events, where a winner is decided by a short margin. The winning time margin can be increased by various means, including engineered outfits within the game's regulations. In swimming, apart from optimisation of the swimmer's body, an appropriately devised swimsuit can play a significant role in reducing the drag, thereby enhancing the winning time margin. The main motivation for undertaking this study stems from the increasing levels of technical sophistication in the swimsuits that are claimed by the manufacturers for performance enhancement. Therefore, the goal of this paper is to undertake an experimental study with microscopic illustration of the swimsuit fabric, and its effects on aerodynamic properties. The study utilised a commercial swimsuit under stretched and un-stretched conditions of fabric morphology, and their impact on aerodynamic drag. This study was conducted using a wind tunnel for a range of Reynolds numbers. The simplified body shape was used to determine the aerodynamic drag. The finding of this study illustrates that there is a significant difference between the aerodynamic drag for the stretched and un-stretched surface morphology of the Speedo FS-I swimsuit. Furthermore, the microscopic analysis of the stretched and un-stretched fabric was undertaken to extend our undertstanding

Distribution System Operation with Solid State Controller and Energy Storage Management

A novel distribution system infrastructure is proposed with solid state controller locating at load sites. an energy storage management algorithm is developed to optimize battery charge/discharge operation using forward dynamic programming method. This algorithm is implemented in a system test bed in PSCAD. the simulation results present economic benefits to private customers with reduced energy cost. It also reduces system peak demand which may improve system reliability. © 2012 IEEE

Transfer Learning with Deep Convolutional Neural Network (CNN) for Pneumonia Detection using Chest X-ray

Pneumonia is a life-threatening disease, which occurs in the lungs caused by either bacterial or viral infection. It can be life-endangering if not acted upon in the right time and thus an early diagnosis of pneumonia is vital. The aim of this paper is to automatically detect bacterial and viral pneumonia using digital x-ray images. It provides a detailed report on advances made in making accurate detection of pneumonia and then presents the methodology adopted by the authors. Four different pre-trained deep Convolutional Neural Network (CNN)- AlexNet, ResNet18, DenseNet201, and SqueezeNet were used for transfer learning. 5247 Bacterial, viral and normal chest x-rays images underwent preprocessing techniques and the modified images were trained for the transfer learning based classification task. In this work, the authors have reported three schemes of classifications: normal vs pneumonia, bacterial vs viral pneumonia and normal, bacterial and viral pneumonia. The classification accuracy of normal and pneumonia images, bacterial and viral pneumonia images, and normal, bacterial and viral pneumonia were 98%, 95%, and 93.3% respectively. This is the highest accuracy in any scheme than the accuracies reported in the literature. Therefore, the proposed study can be useful in faster-diagnosing pneumonia by the radiologist and can help in the fast airport screening of pneumonia patients.Comment: 13 Figures, 5 tables. arXiv admin note: text overlap with arXiv:2003.1314

Instability of dilute granular flow on rough slope

We study numerically the stability of granular flow on a rough slope in collisional flow regime in the two-dimension. We examine the density dependence of the flowing behavior in low density region, and demonstrate that the particle collisions stabilize the flow above a certain density in the parameter region where a single particle shows an accelerated behavior. Within this parameter regime, however, the uniform flow is only metastable and is shown to be unstable against clustering when the particle density is not high enough.Comment: 4 pages, 6 figures, submitted to J. Phys. Soc. Jpn.; Fig. 2 replaced; references added; comments added; misprints correcte

Traditional utilization of wild date palm (Phoenix sylvestris Roxb) in rural Bangladesh: An approach to sustainable biodiversity management

The original publication is available at www.springerlink.com.A study was conducted to explore the traditional utilization pattern and indigenous management practices of wild date palm (Phoenix sylvestris Roxb) in the rural agrarian regions of Bangladesh. A multistage sampling method with 10% intensity and a semi-structured questionnaire were used for the study. The farmers manage the palm mainly for sap production with which sugar based secondary goods are manufactured. The sap is either used fresh as drink or after some sort of processing as molasses and/or alcoholic beverage. Seven diversified sites support the palm as its habitat and most palms (20.40%) occur in orchards. Besides growing naturally, the palm is also established in orchards using the wildings as the staple planting material. Although the medium category farmers own most of the palms (33%), a considerable portion (28.68%) of it is managed by the landless farmers, who earn a substantial livelihood from the palms. The farmers practice their own indigenous wisdom in every stage of the palm’s maintenance from planting through tapping for sap collection to the processing of products. If managed more scientifically on a sustainable basis with the collaboration of farmers’ indigenous knowledge, this familiar palm could be able to support the rural economy of the country to a great extent. Side by side, it would also be able to contribute to the richness of biodiversity in the region.ArticleJournal of Forestry Research. 19(3):245-251 (2008)journal articl

A (Running) Bolt for New Reasons

We construct a four-parameter family of smooth, horizonless, stationary solutions of ungauged five-dimensional supergravity by using the four-dimensional Euclidean Schwarzschild metric as a base space and "magnetizing" its bolt. We then generalize this to a five-parameter family based upon the Euclidean Kerr-Taub-Bolt. These "running Bolt" solutions are necessarily non-static. They also have the same charges and mass as a non-extremal black hole with a classically-large horizon area. Moreover, in a certain regime their mass can decrease as their charges increase. The existence of these solutions supports the idea that the singularities of non-extremal black holes are resolved by low-mass modes that correct the singularity of the classical black hole solution on large (horizon-sized) scales.Comment: 25 pages, 3 figures, LaTeX; v2: minor changes, references adde

Intelligent Controlling Simulation of Traffic Flow in a Small City Network

We propose a two dimensional probabilistic cellular automata for the description of traffic flow in a small city network composed of two intersections. The traffic in the network is controlled by a set of traffic lights which can be operated both in fixed-time and a traffic responsive manner. Vehicular dynamics is simulated and the total delay experienced by the traffic is evaluated within specified time intervals. We investigate both decentralized and centralized traffic responsive schemes and in particular discuss the implementation of the {\it green-wave} strategy. Our investigations prove that the network delay strongly depends on the signalisation strategy. We show that in some traffic conditions, the application of the green-wave scheme may destructively lead to the increment of the global delay.Comment: 8 pages, 10 eps figures, Revte