Facing tremendous and potentially infinite stream data, it is impossible to record them entirely. Thus synopses are required to be generated timely to capture the underlying model for stream management systems. Traditionally, curve fitting through Multiple Linear Regression (MLR) is a powerful and efficient modeling tool. In order to further accelerate its processing efficiency, we propose Step...

Massive amount of new information being created and the world’s data doubles every 18 months, 80-90% of all data is held in various unstructured formats. Useful information can be derived from this unstructured data. The aim of this research is to present a framework for handling handwritten documents in all its trends. Since the handwritten documents are unstructured data, so the objectives of...

In today’s garment industry, garment defects have to be minimized so as to fulfill the expectations of demanding customers who seek products of high quality but low cost. However, without any data mining tools to manage massive data related to quality, it is difficult to investigate the hidden patterns among defects which are important information for improving the quality of garments. This pap...

In the paper, we discuss the relation between ethnomethodologically inspired video analysis and curricular design. Often the relation between analysis and design is taken as a relation between descriptive and prescriptive accounts. Conceptualised in this way, ethnomethodology and curricular design is a world apart. With a focus on ethnomethodology’s take on analytical and normative questions, h...

http://www.cogsys.wiai.uni-bamberg.de/effalip/ Cognitive Systems Group Faculty Information Systems and Applied Computer Science University of Bamberg Inductive Programming (IP) • Inductive Synthesis of Functional Programs – not only concepts, as in ILP, but recursive programs – from incomplete specifications (IO examples) – 100% accuracy on training data – challenging subfield of machine learni...

Blended Learning (BL) essentially fuses high-tech digital learning with traditional ones to involve students in “network learning”, which helps transcending physical boundaries. Especially during the ongoing COVID-19 pandemic, BL has been embraced as a realistic possibility ensure seamless knowledge distribution regardless of time and space. Knowledge Management (KM)-based approaches are typica...

This paper is about the construction of various specific machine learning paradigms using a primitive-based generic machine learning model. The generic model identifies five functional components involved in a machine learning process, including an input, a transformation, a control, an output, and a knowledge base. It also identifies a set of basic machine learning mechanisms for each componen...