Madjid Fathi

Semi-inverse Monte Carlo reconstruction of two-phase heterogeneous material using two-point functions

A new Monte Carlo (MC) methodology using ant Colony and kinetic growth models is developed to reconstruct the microstructure of two-phase composites using correlation statistics. After the initial patterns are generated, the new patterns evolved by introducing optimisation parameters for rotation, shrinkage, transportation and distribution. The realisations are then optimised using kinetic growth rate applied to each representative cell. For each realisation, the final microstructures are then compared to the experimental results through minimisation of the error function. Finally an optimisation methodology was developed to introduce initial input parameters for MC simulation to minimise the error function.

Knowledge discovery from social media using big data-provided sentiment analysis SoMABiT

In today’s competitive business world, being aware of customer needs and market-oriented production is a key success factor for industries. To this aim, the use of efficient analytical algorithms ensures better understanding of customer feedback and improves the next generation of products. Accordingly, the dramatic increase in the use of social media in daily life provides beneficial sources for market analytics. Yet how traditional analytic algorithms and methods can be scaled up for such disparate and multistructured data sources is a major challenge. This paper presents and discusses the technological and scientific focus of SoMABiT as a social media analysis platform using big data technology. Sentiment analysis has been employed in order to discover knowledge from social media. The use of MapReduce and the development of a distributed algorithm towards an integrated platform that can scale for any data volume and provide social media-driven knowledge is the main novelty of the proposed concept in comparison to the state-of-the-art technologies.

Knowledge-based fuzzy color processing

This paper concerns the application of digital image processing in combination with rulebased reasoning as a nondestructive quality testing method for resistance spot welding. The use of fuzzy logic gives the possibility to characterize colors by linguistic terms rather than by names for wavelength or wavelength intervals. The presented method supplements Lotfi Zadehs idea of soft computing and computing with words. It can be applied to many problems in which color carries important information.

Evaluation of Intelligent Greenhouse Climate Control System, Based Fuzzy Logic in Relation to Conventional Systems

In this paper, at first a model of greenhouse is simulated with thermodynamic equations and then two greenhouse climate controllers (GHCC) are designed using a Fuzzy Logic controller and On/Off controller. The developed Fuzzy Logic Controller (FLC) prototype is based on Mamdani controller and it is built on the MATLAB software, then both of controllers are used with greenhouse model in simulation space of MATLAB software to understand the performance of each controllers and affection on the controlling parameters such as temperature and air humidity of inside the Greenhouse. The results show that the proposed Fuzzy Logic Controller is very user friendly, easy to design, highly adaptable and quick to perform.

Knowledge Management support for Quality Management to achieve higher customer satisfaction

As a Quality Management society transforms into a more knowledge and learned based society, it requires enhancement and improvement of strategies, systems and techniques towards meeting new expectations and demands. The importance of knowledge continues to grow to the spread of global networks, accelerated product cycles and changing market conditions. In this era; a progressive enterprise should strive to adapt itself successfully to new management skills, principles, abilities and higher levels of competency. Also customer demands and their levels of satisfaction are determined by new factors. In this paper, we surveyed related aspects of Knowledge Management in order to be integrated in Quality Management. Finally we have proposed a model of Knowledge Management approaches for supporting Quality Management to achieve higher customer satisfaction. It has been revealed that Knowledge Management brings and sustains advantages to fulfill customer demands by creating and supporting beneficial features through launching of appropriate Knowledge Management processes.

Textual meta-analysis of maintenance management’s knowledge assets

Maintenance management activities include identifying, creating and storing knowledge assets. The knowledge assets are either documented/codified or undocumented/non-codified. In order to utilise the accumulated knowledge assets in the operational, tactical and strategic layers, documented knowledge should be meta-analysed. Meta-analysis is to discover the strength of the relationship between certain variables by means of automatic or semi-automatic algorithms. Meta-analysis has three methods: (1) statistical; (2) mathematical; and (3) textual. In this paper, the textual meta-analysis of maintenance managements knowledge assets is examined. In particular, the objective is to develop a virtual application for finding the relationship between three classes of text entities such as machines, practitioners and maintenance operations by means of technical implementation of the concept for the imitation of the mental ability of word association (CIMAWA). In addition, the virtual application is designed to be integrated as an add-on in the framework of computerised maintenance management information system (CMMIS).

Using Word Association to Detect Multitopic Structures in Text Documents

A new method for detecting multitopic structures in text documents, called Associative Gravity, is based on a text-mining method entitled CIMAWA, which imitates the human ability of word association. Specifically, Associative Gravity utilizes word association to detect different topics in a text. The authors named it Associative Gravity because of its resemblance to the physical law of gravitation, that is, mass and attraction. The mass corresponds to the importance of words in a text and the attraction to the asymmetrical associative word space. The innovative characteristic of the described topic detection method is supplied with asymmetrical associative word space provided by CIMAWA. A comparative case study proves the capability of Associative Gravity to separate different topics at very high accuracy.

Integration of Practice-Oriented Knowledge Technology: Trends and Prospectives

Applied Knowledge Management in Practice -- Semantic Technologies for Industrial Management and Process Controlling -- Knowledge Driven Approaches for Product Engineering.

Knowledge integration of collaborative product design using cloud computing infrastructure

The pivotal key for the success of manufacturing enterprises is sustainable and innovative product design and development. In collaborative design, stakeholders are heterogeneously distributed chain-like. Due to the growing volume of data and knowledge, an effective management of the knowledge acquired in the product design and development is one of the key challenges facing most manufacturing enterprises. Opportunities for improving efficiency and performance of IT-based product design applications through centralization of resources such as knowledge and computation have increased in the last few years with maturation of technologies such as SOA, virtualization, grid computing, and/or cloud computing. The main focus of this paper is the concept of ongoing research in providing the knowledge integration service for collaborative product design and development using cloud computing infrastructure. Potentials of the cloud computing to support the Knowledge integration functionalities as a Service by providing functionalities such as knowledge mapping, merging, searching, and transferring in product design procedure are described in this paper. Proposed knowledge integration services support users by giving real-time access to knowledge resources. The framework has the advantage of availability, efficiency, cost reduction, less time to result, and scalability.

Advanced Condition Monitoring Services in Product Lifecycle Management

This paper describes a specialized PLM approach with operation monitoring and maintenance of the product during its usage based on a condition monitoring method framework. A coupling procedure integrates the PLM meta data model with associated condition monitoring and diagnosis method framework results. Graphical models dealing with a priori information play a key part based on modeling, learning from sensor data and probabilistic inference.