The worldwide expansion of an education field highly demands for skill based learning with professional approach. In response to this greedy need, the paper emphasises practice based learning in engineering education. The iterative method has been followed for extensive role play simulation in order to develop the product for realistic client. The described learning model is implemented over a student class of an undergraduate level course, Software Engineering and Design’. The evolutionary process is adopted to optimise the students’ performance assessment in terms of critical thinking, technical competency and project management skills. The judgmental abilities are tried to quantify with the help of attainment calculations which define the Difficulty Index of the course. This process helped to form the basis and maintain the quality benchmark for course assessment and provided the opportunity to improve the same through the closure loop.
Abstract: Handwriting recognition of medical prescriptions has been a challenging problem over the recent years with constant research in providing possible accurate solutions. Indecipherable handwritten prescription and inefficiency of Pharmacist to understand the medical prescription can lead to serious and harmful effect to the patients. Even in the recognition of handwriting, mainly doctors notes, they are very difficult for everyone to understand and it takes time for a person to analyse it. So, this idea mainly focused on interpreting doctor’s notes using handwritten recognition and deep learning techniques. The handwritten or printed document pictures are transformed into their electronic counterparts using an optical character recognition (OCR) system. Due to individuals' inconsistent writing styles, dealing with handwritten texts is significantly more difficult than dealing with printed ones. Handwritten text recognition could be done by Image processing, Machine Learning or Deep Learning Techniques. Out of these Deep Learning remains to be the most popular and prominent. Some of the Deep Learning techniques includes Recurrent Neural Networks (RNNs) and Convolutional Neural Networks (CNNs). This gives a review of the various recognition methodologies used for interpreting handwritten texts. It includes the most important algorithms that could be used for detecting the handwritten word/text/character by using various approaches for the recognition process. In the end we are thus comparing the accuracies provided by these systems.
Software testing is very essential to improve the overall quality of software by reducing bugs, errors and software maintenance cost. Software testing is necessary part of Software Development Life Cycle (SDLC) and as testing is critical in post and pre development process, so it needs to be driven with some enhanced and efficient techniques and methodologies. The aim of this paper is to improve the quality of software by discussing about some existing testing technique and some improved testing technique.
Big Data and the Internet of Things (IoT) have been implemented as solution technologies in Information Technology (IT) industries for some time now, but the integration of these technologies to attain higher precision, pattern predictions and reduced hazards with regard to manufacturing industries, is still in its early stages. Along with these setups a remote/mobile access to conclusions has always been a tempting feature for industries.
The technological advancements with the proliferation of data over the internet and varying devices with continuous surging recordings play a vital role in the growth of industries in today's scenario. Academic research in this rapidly spurting field and teleology of this evolving phenomenon of ‘Big Data Analytics in Traditional Manufacturing Industry’ may exhibit insights with significant implications for practicing industrialists as well as academicians.
The manufacturing and industrial entities observe bewilderments and limitations when it comes to real time access to analyzed conclusions regarding discretely placed actuators and sensors collecting data continuously throughout the industrial premises. A heuristic for this obscurity is proposed in the paper highlighting the implementation of popular and niche technologies that are Internet of Things (IoT) and Big Data Analytics in an integrated manner.
This paper is an effort to explore the current state of, ‘Big Data Analytics with IoT in traditional manufacturing industry’, and propound a methodology to accentuate its utilization in the industry for good. Through a review of relevant academic literature, the paper attempts to posit a valid solution and discuss its contributions.
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