scholarly journals Android App: Appno ki Madad (AKM)

Author(s):  
Gaurav Tiwari

In covid-19 we have seen in our localities/societies/village people faces lot of difficulties and problem and they really want to help each other but they don't know which person need help and how to help them. by taking all these into accounts we have made an application on a small scale in which people can help each other. In this research paper we have done complete analysis of an android application developed by us for to help in need. this paper refers the aim behind developing the android application in this paper we have mentioned how we can help each other in needy and keep record . In addition this paper also gives an introduction of some basic concepts of android application development.

Author(s):  
Charles E. Andraka ◽  
Scott Sadlon ◽  
Brian Myer ◽  
Kirill Trapeznikov ◽  
Christina Liebner

Mirror facets for Concentrating Solar Power (CSP) systems have stringent requirements on slope accuracy in order to provide adequate system performance. This paper presents a newly developed tool that can characterize facets quickly enough for 100% inspection on a production line. A facet for a CSP system, specifically a dish concentrator, has a parabolic design shape. This shape will concentrate near-parallel rays from the sun to a point (or a line for trough systems). Deviations of surface slope from the design shape impact the performance of the system, either losing power that misses the target, or increasing peak fluxes to undesirable levels. Three types of facet slope errors can impact performance. The first is a focal length error, typically caused by springback in the facet forming process. In this case, the wavelength of the error exceeds the size of the facet, resulting in a parabola, but with the wrong focal length. The results in a slope error that is largely systematic across the facet when the measured slope is compared to the design slope. A second shape error, in which the period of the error is on the order of the length of the facet, manifests also as a systematic slope error. In this case, the facet deviates from a parabolic shape, but can be modeled with a higher order curve. Finally, the residual errors after a model is proposed are usually lumped through a Root Mean Square (RMS) process and characterized as the 1-sigma variation of a normal distribution. This usually characterizes the small-scale imperfections in the facet, and is usually called “slope error”. However, all of these deviations from design are in facet errors in the slope of the manufactured facet. The reported characterization system, named SOFAST (Sandia Optical Fringe Analysis Slope Tool) has a computer-connected camera that images the reflective surface, which is positioned so that it views the reflection of an active target, such as an LCD screen. A series of fringe patterns are displayed on the screen while images are captured. Using the captured information, the reflected target location of each pixel of mirror viewed can be determined, and thus through a mathematical transformation, the surface normal map can be developed. This is then fitted to the selected model equation, and the errors from design are characterized. The reported system currently characterizes point focus mirrors (for dish systems), but extensions to line focus facets are planned. While similar approaches have been explored, several key developments are presented here. The combination of the display, capture, and data reduction in one system allows rapid capture and data reduction. An “electronic boresight” approach is developed accommodating physical equipment positioning errors, making the system insensitive to setup errors. A very large number of points are determined on each facet, providing significant detail as to the location and character of the errors. The system is developed in MatLab, providing intimate interactions with the data as techniques and applications are developed. Finally, while commercial systems typically resolve the data to shape determination, this system concentrates on slope characterization and reporting, which is tailored to the solar applications. This system can be used for facet analysis during development. However, the real payoff is in production, where complete analysis is performed in about 10 seconds. With optimized coding, this could be further reduced.


2021 ◽  
Vol 47 (05) ◽  
Author(s):  
NGUYỄN THỊ PHƯƠNG GIANG ◽  
TRẦN THỊ MINH KHOA

Continuous Integration (CI) is the most common practice among software developers where they integrate their work into a frequent baseline. The industry 4.0 is facing huge challenges while developing Software at multiple sites and tested on multiple platforms. Today, so many CI tools widely used for software development as CircleCI, Jenkins, Travis. CircleCI is one of the CI tools that can helps in automating the complete process, reducing the works of a developer and check the development at each and every step of Software evolution. In this paper, we discuss the implementation of CircleCI for android application development. Firebase Test Lab will be used for some additional automation testing.


Author(s):  
D. Wilfred Shiju

Android smart car is designed with safety in mind. A simple and sensitiveline, included steering wheels and new voice events, this is designed to reduceinterruption so you can stay focused on the highway.This car which can be controlling using an Android APP for smart phones.A car is regularly an electronic mechanic machine that is guide by computer and electronic controlling programming. The innovation of the Smart Car technology to developing based on remote connection using android application can control the car movements. This system use Bluetooth device controller to control the mobile App. This Bluetooth device interface with UART communication. The UART receive the command via the Bluetooth device.   This design is may helps to our rural citifies. This system is developing to help to self driving vehicles.


Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 399 ◽  
Author(s):  
David González-Ortega ◽  
Francisco Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.


2019 ◽  
Vol 16 (8) ◽  
pp. 3316-3318 ◽  
Author(s):  
S. Dhamodaran ◽  
Md. Afridi ◽  
M. Rahul ◽  
J. Refonaa ◽  
K. Ashok Kumar

Predominantly all the customers are smartphone users and they want shopping to be easier and seamless. However, the retail store experiences in India does not tap into the mobile channel of interaction when the customer is in the shop. The implementation is that make the shopping easier. Developing the application in the Android platform. In this application, we can make easy checkout and pay the shopping bills in any wallets (Dhamodarn, S., et al., 2016. Identification of User Poi in Spatial Data Using Android Application. International Conference on Computation of Power, Energy Information and Communication (ICCPEIC). IEEE. ISBN: 978-1-5090-0901-5). And capturing the customer behavior in the store. The user will add the Product and corresponding ID and its Cost is added in the Android App and finally, total Payment is made by the user via an android based Payment system. Details are transferred to the shop server. If the customer makes any mistake during the billing of products. The alarm will be raised in the trolley and in the bill counter.


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