IMPLEMENTASI ALGORITMA LEVENSTEIN UNTUK KOMPRESI FILE VIDEO PADA APLIKASI CHATTING BERBASIS ANDROID

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Dani Iqbal
Keyword(s):  
Video Compression ◽  
Communication Tool ◽  
Time Restrictions ◽  
Speed Up ◽  
Predetermined Number

Technology is developing very rapidly along with the needs of the community in obtaining information quickly. Chat application as a communication tool that can help communicate without any time restrictions and is free from obstacles. But in communicating through chat applications can not be free or free in communicating in general. Where the chat application has a predetermined number of bits, so that in sending video on the chat application can not be at once but in several times the transmission. The solution to this problem is how the video can be compressed in order to speed up the process of sending and storing video files. compression on video files is done by reducing the size of the video by the process of reducing the bits in the video, but does not eliminate the data information in it. In this study, the algorithm used is Levenstein, using this method, the compression results from the Levenstein value have different results from each value, and the compression results will be advantageous in sending and transferring video files.Keywords: Video Compression, Levenstein Algorithm, Chatting Application

scholarly journals Better Communication Tool for Specially Disabled

2019 ◽  
Vol 8 (4) ◽  
pp. 3008-3011
Keyword(s):  
Neural Networks ◽  
Sign Language ◽  
Convolutional Neural Networks ◽  
Time Lapse ◽  
Normal Person ◽  
Communication Tool ◽  
Deep Convolutional Neural Networks ◽  
Detection Model ◽  
Pruning Strategy ◽  
Speed Up

Sign language is widely used when a dumb communicates. However, non-sign-language people find it difficult in interpreting them. So, we had come up with a system that enables speech impaired to speak with an artificial voice in public communities using Artificial intelligence techniques. we propose a hybrid-weighted metric known as weighted pruning in deep convolutional neural networks. In this work, we report experiments of weighted pruning. we show that using a weighted pruning strategy we can achieve significant speed up in Faster RCNN object detection model by discarding 50% of filters. In this paper we show evidences to our claim by reporting mean Average Precision of weighted pruned CNN is slightly higher than existing pruning techniques. The former part of the paper focus on moulding convolutional neural networks in terms of their speed and scalability for deploying them on mobiles, embedded and further small gadgets. The latter part of the paper describes novel approaches in letting dumb speak as fast as normal person in public, without time lapse using natural language algorithms and recommendations.

Scanning x-ray fluorescence microscopy and principal component analysis

1992 ◽  
Vol 50 (2) ◽  
pp. 1752-1753
Author(s):  
Brian Cross
Keyword(s):  
Principal Component Analysis ◽  
Fluorescence Microscopy ◽  
Spatial Resolution ◽  
High Speed ◽  
Image Acquisition ◽  
Principal Component ◽  
Fluorescence Microscope ◽  
Acquisition Rate ◽  
X Ray ◽  
Speed Up

A relatively new entry, in the field of microscopy, is the Scanning X-Ray Fluorescence Microscope (SXRFM). Using this type of instrument (e.g. Kevex Omicron X-ray Microprobe), one can obtain multiple elemental x-ray images, from the analysis of materials which show heterogeneity. The SXRFM obtains images by collimating an x-ray beam (e.g. 100 μm diameter), and then scanning the sample with a high-speed x-y stage. To speed up the image acquisition, data is acquired "on-the-fly" by slew-scanning the stage along the x-axis, like a TV or SEM scan. To reduce the overhead from "fly-back," the images can be acquired by bi-directional scanning of the x-axis. This results in very little overhead with the re-positioning of the sample stage. The image acquisition rate is dominated by the x-ray acquisition rate. Therefore, the total x-ray image acquisition rate, using the SXRFM, is very comparable to an SEM. Although the x-ray spatial resolution of the SXRFM is worse than an SEM (say 100 vs. 2 μm), there are several other advantages.

Direct measurement of electron-diffraction-pattern intensities using an energy loss spectrometer

1989 ◽  
Vol 47 ◽  
pp. 668-669
Author(s):  
A. G. Jackson ◽  
M. Rowe
Keyword(s):  
Thermal Effects ◽  
Dynamic Range ◽  
Scattering Amplitude ◽  
Dynamical Theory ◽  
Site Symmetry ◽  
Proof Of Concept ◽  
Parallel Acquisition ◽  
Kinematic Approximation ◽  
Speed Up ◽  
Structure Calculations

Diffraction intensities from intermetallic compounds are, in the kinematic approximation, proportional to the scattering amplitude from the element doing the scattering. More detailed calculations have shown that site symmetry and occupation by various atom species also affects the intensity in a diffracted beam. [1] Hence, by measuring the intensities of beams, or their ratios, the occupancy can be estimated. Measurement of the intensity values also allows structure calculations to be made to determine the spatial distribution of the potentials doing the scattering. Thermal effects are also present as a background contribution. Inelastic effects such as loss or absorption/excitation complicate the intensity behavior, and dynamical theory is required to estimate the intensity value.The dynamic range of currents in diffracted beams can be 104or 105:1. Hence, detection of such information requires a means for collecting the intensity over a signal-to-noise range beyond that obtainable with a single film plate, which has a S/N of about 103:1. Although such a collection system is not available currently, a simple system consisting of instrumentation on an existing STEM can be used as a proof of concept which has a S/N of about 255:1, limited by the 8 bit pixel attributes used in the electronics. Use of 24 bit pixel attributes would easily allowthe desired noise range to be attained in the processing instrumentation. The S/N of the scintillator used by the photoelectron sensor is about 106 to 1, well beyond the S/N goal. The trade-off that must be made is the time for acquiring the signal, since the pattern can be obtained in seconds using film plates, compared to 10 to 20 minutes for a pattern to be acquired using the digital scan. Parallel acquisition would, of course, speed up this process immensely.

The internet—A useful communication tool but no replacement for the doctor-patient relationship

2001 ◽  
Vol 120 (5) ◽  
pp. A735-A735
Author(s):  
C STREETS ◽  
J PETERS ◽  
D BRUCE ◽  
P TSAI ◽  
N BALAJI ◽  
...  
Keyword(s):  
The Internet ◽  
Patient Relationship ◽  
Communication Tool ◽  
Doctor Patient Relationship

How to speed up to be in time: Action-judgment dissociations in children and adults

2004 ◽  
Vol 63 (1) ◽  
pp. 17-29 ◽  
Author(s):  
Friedrich Wilkening ◽  
Claudia Martin
Keyword(s):  
Rating Scale ◽  
Constant Speed ◽  
Linear Condition ◽  
Speed Up ◽  
Nonlinear Condition ◽  
Speed Change ◽  
Catch Up ◽  
Normative Rule ◽  
Judgment Condition ◽  
Time Linear

Children 6 and 10 years of age and adults were asked how fast a toy car had to be to catch up with another car, the latter moving with a constant speed throughout. The speed change was required either after half of the time (linear condition) or half of the distance (nonlinear condition), and responses were given either on a rating scale (judgment condition) or by actually producing the motion (action condition). In the linear condition, the data patterns for both judgments and actions were in accordance with the normative rule at all ages. This was not true for the nonlinear condition, where children’s and adults’ judgment and also children’s action patterns were linear, and only adults’ action patterns were in line with the nonlinearity principle. Discussing the reasons for the misconceptions and for the action-judgment dissociations, a claim is made for a new view on the development of children’s concepts of time and speed.

Coronavirus: indexed data speed up solutions

Nature ◽  
2020 ◽  
Vol 584 (7820) ◽  
pp. 192-192 ◽  
Author(s):  
Lucila Ohno-Machado ◽  
Hua Xu
Keyword(s):  
Speed Up
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