![]() Assembly times were significantly reduced, in most cases by over 50%. The results of the study strongly support the use of this type of system. The interface simplifies the expertise required of an assembly worker by replacing complex blueprints with simple directions and illustrations, thus supporting the rapid introduction of new products and the assembly of a wide variety of parts with minimal off-line training. real-time computer support system that provided interactive assembly instructions through a graphical user interface combining text and illustration for workers on a flexible assembly line. The objective of this study was to test a. Advances in flexible automation have far outpaced the research supporting flexibility in the manual operations that are required alongside automation. This trend has increased the need for flexibility in manufacturing processes. There is a growing trend in many industries to expand the diversity of product offerings to meet widespread customer needs. Although descriptions of rate and state friction fitting routines have been published in the past, RSFit3000 marks the first time a software package for analyzing friction experiments has been described in the literature. Here we describe how to use the software, and illustrate its flexibility and utility by analyzing two sets of synthetic friction data, as well as some previously published experimental data. The GUI makes the program simple to use, as all fitting tasks are completed via interaction with the interface. Completed fits are conveniently saved in MATLAB structure arrays that contain fitted parameter values with their error intervals, and all information required to reproduce a given fit. trends from the data, and provides options for using two state variables, applying a weighting function, and treating stiffness as a fitting parameter. RSFit3000 includes features for removing strain hardening or weakening. Called RSFit3000, the software allows users to easily determine frictional parameters by fitting velocity-step and slide-hold-slide events using the aging- and slip-law forms for state variable evolution. We present a MATLAB graphical user interface (GUI) software package for analyzing rate and state friction experiments. This model can recognize and convert a maximum of 20 Tamil characters. The framework is on implementing the image capturing technique in the embedded system based on Raspberry Pi board and converting it into voice using Win32 SAPI. The text will then be processed by Microsoft Speech Application Program Interface (SAPI) speech synthesizer and translated to voice as output in both English and Tamil languages. The proposed approach is capable of recognizing text in a variety of challenging conditions where traditional character recognition systems fail, notably in the presence of substantial blur, low resolution, low contrast, high image noise, and other distortions. The recognized text is then converted into machine-readable text using optical character recognition (OCR) technique and then compared with the stored character set. This work aims at hardcopy text extracted and recognized from images in bilingual languages (Tamil and English). The new research idea focuses on automatic assistance to be developed for the visually impaired and illiterates. This work shows that for languages such as Tamil or Sinhala text-to-speech engines can be successfully developed with the available resources. The sound editing software “Sound Forge” was used when preparing the phonemes with correct pitch. The Tamil font “TSC_Avarangal” was selected as the font to develop the user interface. The text can be stored to be used at a later time. The front-end of the engine is a GUI interface that allows users to input Tamil text in letters or even numbers. The text-to-speech engine splits the given text into the basic units of Tamil, extracts the correct phonemes from the database and concatenates the basic unit waveforms in the correct sequence to produce the required sound waveform. The back-end of the engine was a sound database created with 343 phonemes which were chosen as the basic units of Tamil language. A text-to-speech conversion engine was developed for Tamil language that could successfully convert any arbitrary Tamil text into spoken utterance.
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