Image-Based Automatic Energy Meter Reading Using Deep Learning

We propose to perform an image-based framework for electrical energy meter reading.Our aim is to extract the image region that depicts the digits and then recognize them to record the consumed units.Combining the readings of serial numbers and energy meter units,an automatic billing system using the Internet of Things and a graphical user interface is deployable in a real-time setup.However,such region extraction and character recognition become challenging due to image variations caused by several factors such as partial occlusion due to dust on the meter display,orientation and scale variations caused by camera positioning,and non-uniform illumination caused by shades.To this end,our work evaluates and compares the stateof-the art deep learning algorithm You Only Look Once(YOLO)along with traditional handcrafted features for text extraction and recognition.Our image dataset contains 10,000 images of electrical energymeters and is further expanded by data augmentation such as in-plane rotation and scaling tomake the deep learning algorithms robust to these image variations.For training and evaluation,the image dataset is annotated to produce the ground truth of all the images.Consequently,YOLO achieves superior performance over the traditional handcrafted features with an average recognition rate of 98%for all the digits.It proves to be robust against the mentioned image variations compared with the traditional handcrafted features.Our proposed method can be highly instrumental in reducing the time and effort involved in the currentmeter reading,where workers visit door to door,take images ofmeters and manually extract readings from these images.

V-Shaped Monopole Antenna with Chichena Itzia Inspired Defected Ground Structure for UWB Applications

Due to rapid growth in wireless communication technology,higher bandwidth requirement for advance telecommunication systems,capable of operating on two or higher bands with higher channel capacities and minimum distortion losses is desired.In this paper,a compact Ultra-Wideband(UWB)V-shaped monopole antenna is presented.UWB response is achieved by modifying the ground plane with Chichen Itzia inspired rectangular staircase shape.The proposed V-shaped is designed by incorporating a rectangle,and an inverted isosceles triangle using FR4 substrate.The size of the antenna is 25 mm×26 mm×1.6 mm.The proposed V-shaped monopole antenna produces bandwidth response of 3 GHz Industrial,Scientific,and Medical(ISM),Worldwide Interoperability for Microwave Access(WiMAX),(IEEE 802.11/HIPERLAN band,5G sub 6 GHz)which with an additional square cut amplified the bandwidth response up to 8 GHz ranging from 3.1 GHz to 10.6 GHz attaining UWB defined by Federal Communications Commission(FCC)with a maximum gain of 3.83 dB.The antenna is designed in Ansys HFSS.Results for key performance parameters of the antenna are presented.The measured results are in good agreement with the simulated results.Due to flat gain,uniform group delay,omni directional radiation pattern characteristics and well-matched impedance,the proposed antenna is suitable for WiMAX,ISM and heterogeneous wireless systems.

Gain-Enhanced Metamaterial Based Antenna for 5G Communication Standards

Metamaterial surfaces play a vital role to achieve the surface waves suppression and in-phase reflection,in order to improve the antenna performance.In this paper,the performance comparison of a fifth generation(5G)antenna design is analyzed and compared with a metamaterial-based antenna for 5G communication system applications.Metamaterial surface is utilized as a reflector due to its in-phase reflection characteristic and high-impedance nature to improve the gain of an antenna.As conventional conducting ground plane does not give enough surface waves suppression which affects the antenna performance in terms of efficiency and gain etc.These factors are well considered in this work and improved by using the metamaterial surface.The radiating element of the proposed metamaterial based antenna is made up of copper material which is backed by the substrate,i.e.,Rogers-4003 with a standard thickness,loss tangent and a relative permittivity of 1.524 mm,0.0027 and 3.55,correspondingly.The proposed antenna with and without metamaterial surface operates at the central frequency of 3.32 GHz and 3.60 GHz,correspondingly.The traditional antenna yields a boresight gain of 2.76 dB which is further improved to 6.26 dB,using the metamaterial surface.The radiation efficiency of the proposed metamaterial-based 5G antenna is above 85%at the desired central frequency.

Molecular and functional characterization of the American cockroach, Periplaneta americana, Rab5： the first exopterygotan low molecular weight ovarian GTPase during oogenesis

The small Rab GTPases are key regulators of membrane vesicle trafficking. Ovaries of Periplaneta americana （Linnaeus） （Blattodea： Blattidae） have small molecular weight GTP/ATP-binding proteins during early and late vitellogenic periods of oogenesis. However, the identification and characterization of the detected proteins have not been yet reported. Herein, we cloned a cDNA encoding Rab5 from the American cockroach, P. americana, ovaries （PamRab5）. It comprises 796 bp, encoding a protein of 213 amino acid residues with a predicted molecular weight of 23.5 kDa. PamRab5 exists as a single-copy gene in the P. americana genome, as revealed by Southern blot analysis. An approximate 2.6 kb ovarian mRNA was transcribed especially at high levels in the previtellogenic ovaries, detected by Northern blot analysis. The muscle and head tissues also showed high levels of PamRab5 transcript. PamRab5 protein was localized, via immunofluorescence labeling, to germline-derived cells of the oocytes, very early during oocyte differentiation. Immunoblotting detected a ~25 kDa signal as a membrane-associated form revealed after application of detergent in the extraction buffer, and 23 kDa as a cytosolic form consistent with the predicted molecular weight from amino acid sequence in different tissues including ovary, muscles and head. The PamRab5 during late vitellogenic periods is required to regulate the endocytotic machinery during oogenesis in this cockroach. This is the first report on Rab5 from a hemimetabolan, and presents an inaugural step in probing the molecular premises of insect oocyte endocytotic trafficking important for oogenesis and embryonic development.

Dynamic trip point categorisation using manufacturing process for polycrystalline diamond compact bits as case study

Disruptions in the manufacturing process cast substantial impacts on the consumer’s centric values,cost,and overall efficiency.The ripple effect of these disruptions is observed in the whole assembly line.The proper analysis and mitigation of disruptions is the key to the proficiency of the plant and resource utilisation.The research focuses on the quantitative analysis of the impact of disruptions of the manufacturing process,which is performed by analysing the disruptive workstation dynamically.The disruptive workstations have a significant impact on succeeding and preceding workstations,which have been analysed dynamically,and accordingly,the preset alarm trip points are elevated.The results show that lowering the number of starts and stops decreases the number of rejections of valuable process batches that finally improve efficiency.Finally,the developed model is implemented on a polycrystalline diamond compact drill bit manufacturing plant.The results are compared with the research work of other researchers,showing a 60%reduction in the number of start/stop events,60%reduction in downtime,while a 75%reduction in the number of rejections is noted.