Design of a knowledge and management system for starch bioconversion

AbstractIn this paper a knowledge acquisition and management system (KAMS) which allows the collection, analysis, ordering and storage of informations generated at starch liquefaction was developed. KAMS was structured on three levels: PostgreSQL as a backend, D2RQ as middle tier and Seaside as frontend. The system was used to store knowledge about the liquefaction process with the goal to be used as a decision support system in chosing the condition for this operation. The tests had shown that the implemented KAMS provides support for: Distributed acquisition of the scientific data generated by the researchers; Structured data storage; Support for the generation and storage of knowledge on the starch bioconversion

A Simulation Based Analysis of an Multi Objective Diffusive Load Balancing Algorithm

In this paper, we presented a further development of our research on developing an optimal software-hardware mapping framework. We used the Petri Net model of the complete hardware and software High Performance Computing (HPC) system running a Computational Fluid Dynamics (CFD) application, to simulate the behaviour of the proposed diffusive two level multi-objective load-balancing algorithm. We developed an meta-heuristic algorithm for generating an approximation of the Pareto-optimal set to be used as reference. The simulations showed the advantages of this algorithm over other diffusive algorithms: reduced computational and communication overhead and robustness due to low dependence on uncertain data. The algorithm also had the capacity to handle unpredictable events as a load increase due to domain refinement or loss of a computation resource due to malfunction

An ADOxx Based Environment for Problem Based Learning in Manufacturing Systems Design

The Problem Based Learning (PBL) as student centred approach and learning-by-doing method is suited for the modern higher education. However, the first contact with the method can be overwhelming for the students, in the absence of prior domain knowledge. The preparation of the learning material can be time and resource consuming for the teacher. The goal of the research was the implementation of an environment that should enhance the learning experience for the student and reduce the implementation burden for the teacher. The environment is based on the ADOxx platform and allows the collaboration of the learner teams and the teacher-learner interaction on three levels. The Metamodeling level supports the development of the domain-specific language used in the modelling of the manufacturing system; this activity stimulates and directs the gathering and consolidation of domain-specific knowledge. The modelling level allows the development of alternative design solution using models of the factory components. The Simulation level allows the analysis of these variants. The environment supports the teacher in developing instructional scaffolding and uses cases to ease the learners the first time contact with PBL. The functionality of the environment is presented using the case of designing a flexible food production line

Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage

The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing

Insight into the Recent Application of Chemometrics in Quality Analysis and Characterization of Bee Honey during Processing and Storage

The application of chemometrics, a widely used science in food studies (and not only food studies) has begun to increase in importance with chemometrics being a very powerful tool in analyzing large numbers of results. In the case of honey, chemometrics is usually used for assessing honey authenticity and quality control, combined with well-established analytical methods. Research related to investigation of the quality changes in honey due to modifications after processing and storage is rare, with a visibly increasing tendency in the last decade (and concentrated on investigating novel methods to preserve the honey quality, such as ultrasound or high-pressure treatment). This review presents the evolution in the last few years in using chemometrics in analyzing honey quality during processing and storage. The advantages of using chemometrics in assessing honey quality during storage and processing are presented, together with the main characteristics of some well-known chemometric methods. Chemometrics prove to be a successful tool to differentiate honey samples based on changes of characteristics during storage and processing