Numerical Analysis of a Vortex Tube: A Review

Ranque–Hilsch vortex tube is a simple devise with no moving parts which could generate cold and hot air/gas streams simultaneously with compressed air/gas as a working fluid. The energy and flow separation in a vortex tube is highly depends on factors like nozzle shape, nozzle number, diameter and length of the vortex tube, inlet pressure, control valve, diaphragm hole size and cold mass fraction. As the energy separation and flow patterns in a vortex tube are highly complex and were not explained successfully by any researcher, a computational study of vortex tube flow and energy separation will give a better understanding about the physics and mechanism involved. Many researchers conducted computational fluid dynamic analysis of the vortex to have a deep insight about the process of flow separation. In this paper computational analysis of vortex by many researchers were presented along with the results obtained and suggestions to improve the performance of the vortex tube. Researchers considered Turbulence models which predict the performance precisely were discussed in the present paper. Researchers considered turbulence models like LES, k–ε, k–ω and RMS to predict the energy separation in vortex tube. Some researchers considered artificial neural networks (ANN) and Taguchi methods for their analysis. Comparison of the predictions with simulation results were also presented to give a clear idea for the reader about the CFD models prediction capabilities.     

A secure and provable multi-server authenticated key agreement for TMIS based on Amin et al. scheme

The security for Telecare Medicine Information Systems (TMIS) has been crucial for reliable dispensing of the medical services to patients at distant locations. Security and privacy element needs to be there for any physician or caregiver to make certain an appropriate diagnosis, medical treatment or any other exchange of critical information. In this connection, many relevant TMIS-based authentication schemes have been presented, however various forms of attacks and inefficiencies render these schemes inapplicable for a practical scenario. Lately, Amin et al. proposed a scheme based on a multi-server authentication for TMIS. However, the Amin et al., scheme has been found vulnerable to user and server impersonation attacks. We have proposed an improved model with higher performance and efficiency, as evident from the forthcoming sections. Besides, the scheme has been backed up by formal security analysis using BAN logic to ensure the resilience of the proposed scheme.     

Development of a Reconfigurable and Miniaturized CPW Antenna for Selective and Wideband Communication

The Planar microwave antennas with simultaneously selectively narrowband and wideband resonance characteristics are essential for the diversity applications. The paper presents modeling, fabrication and experimental verification of a coplanar waveguide excited antenna with a complementary patch which exhibits a narrow-band resonance at 2.47 GHz, and a wideband resonance between 5.52 and 11 GHz. A reconfigurability in the antenna design was achieved by placing a PIN diode across the slot position, and the wideband resonance was switched to the narrowband resonance with a center frequency of 9.56 GHz. The device was fabricated on a foam-based substrate of relative permittivity ε _r  = 2.2 and loss factor tanδ = 0.007. The tested antenna shows a comparable matching with the simulated results and a superior performance over the other reported reconfigurable CPW antennas was achieved.

     

Tailoring Terahertz Propagation by Phase and Amplitude Control in Metasurfaces

Metasurfaces have been very successful at demonstrating the ability to control the wave propagation over the broad electromagnetic spectrum in recent years. The output wavefronts can be controlled at will, by encoding specially designed abrupt changes of electromagnetic parameters into the metasurfaces, such as phase and amplitude. Constituted by a single- or few-layer of planar structures, metasurfaces are straightforward in design and fabrication, thus promising many credible applications. Moreover, such control concept can be further extended to the surface wave regime. In this review, we present our recent progress on metasurfaces capable of tailoring the propagation of both free-space and surface terahertz waves. Following an introduction of the basic concept and theory, a number of unique terahertz metasurfaces are presented, showing the ability to device ultra-thin and compact functional terahertz components.     

Causal relationships among electricity consumption,foreign direct investment and economic growth in India

An empirical analysis of the causal relationship among gross domestic product, foreign direct investment and electricity consumption in India suggests that consumption plays a vital role in GDP and high GDP attracts more FDI into India.     

Can-GLWS: Canadian Great Lakes Weather Service for the Soil and Water Assessment Tool (SWAT) modelling

The rapid rise in availability of large geospatial datasets for the development of hydrological models such as Soil and Water Assessment Tool (SWAT) has led to a dramatic increase in both the demand and availability of web services and tools that assist watershed modellers in incorporating data and knowledge into their modelling frameworks. Within the Canadian Great Lakes region, there is a huge potential for the application of SWAT in integrated water resources management. However, a potential barrier is the preparation of SWAT weather inputs that require time-intensive preprocessing of large data sets. Because such preprocessing is reproducible, the redundancy associated with it can be removed by introducing a web service that enables easy and open dissemination of climate data (including climate change and historical data) in SWAT-ready format. This short communication introduces such a web service called the Canadian Great Lakes Weather Data Service for SWAT (Can-GLWS). It hosts observed (historical) and projected (future) daily precipitation, daily maximum/minimum temperature, as well as weather generator database at regular grids (300 arc seconds or ~10 km) for use in SWAT simulations of the region. The novel Can-GLWS web service offers flexibility in selecting the region of interest by allowing them to be uploaded as a shapefile or to draw a rectangle or a polygon. We believe that such data as a service platform will help many practitioners to explore several issues pertaining to the sustainability of the freshwater resources of Canadian Great Lakes using the SWAT model.     

Deep learning for vision‐based fall detection system: Enhanced optical dynamic flow

Accurate fall detection for the assistance of older people is crucial to reduce incidents of deaths or injuries due to falls. Meanwhile, vision‐based fall detection system has shown some significant results to detect falls. Still, numerous challenges need to be resolved. The impact of deep learning has changed the landscape of the vision‐based system, such as action recognition. The deep learning technique has not been successfully implemented in vision‐based fall detection system due to the requirement of a large amount of computation power and requirement of a large amount of sample training data. This research aims to propose a vision‐based fall detection system that improves the accuracy of fall detection in some complex environments such as the change of light condition in the room. Also, this research aims to increase the performance of the pre‐processing of video images. The proposed system consists of Enhanced Dynamic Optical Flow technique that encodes the temporal data of optical flow videos by the method of rank pooling, which thereby improves the processing time of fall detection and improves the classification accuracy in dynamic lighting condition. The experimental results showed that the classification accuracy of the fall detection improved by around 3% and the processing time by 40–50 ms. The proposed system concentrates on decreasing the processing time of fall detection and improving the classification accuracy. Meanwhile, it provides a mechanism for summarizing a video into a single image by using dynamic optical flow technique, which helps to increase the performance of image preprocessing steps.     

Status,ecological services and management of aquatic weeds of floodplain wetlands in India: An overview

Floodplain wetlands of India are biologically rich and productive ecosystems that support unique aquatic flora and fauna. Covering an area of about 0.354 million ha, the floodplain wetlands are a major source of self‐recruiting small indigenous fish (SIF). They offer vast potential for both capture and culture‐based fisheries, securing livelihood and nutrition for a large section of the population. In addition to tremendous anthropogenic pressures and climatic variability, these resources have experienced a significant reduction in their geographical and areal extent. Aquatic macrophytes infestation in Indian floodplain wetlands is posing serious challenges to their ecological and economic functioning. Degradation and shrinkage of these important resources have been observed over the past few decades, attributable to the spread of aquatic weed infestation, warranting urgent attention in regard to their conservation and restoration to address their impending challenges. The present study compiled a total of 530 species under 103 families of aquatic macrophyte, representing four Indian states of the Ganga and Brahmaputra river basin. Among these 530 species, 85 species exhibit medicinal values and 30 species are edible, whereas some other species are used for basketry, cordage, fodder and as dye. Accordingly, the present study reviews the present status of the floodplain wetlands, their common aquatic weeds and their ecological services. It also synthesizes the latest knowledge and discusses the challenging issues of aquatic weed management and their control measures directed to the sustainable management of the aquatic resources.     

A novel enhanced region proposal network and modified loss function: threat object detection in secure screening using deep learning

The Journal of Supercomputing - Detection of threat objects concealed in passenger clothing and baggage poses a challenge to aviation security. At present, the detection technology is capable of...