Fragiskos A. Batzias

Simulation and optimization of batch autohydrolysis of wheat straw to monosaccharides and oligosaccharides.

Twenty-four non-isothermal wheat straw autohydrolysis experiments were performed in a batch reactor in order to support the development of a new kinetic model. An optimum of 76% w/w total xylose was obtained due to 5% w/w xylose degradation at 180 °C for 70 min. An optimum of 31% w/w total glucose was obtained due to 22% w/w glucose degradation at 240 °C for 82 min. The autohydrolysis of cellulose and hemicelluloses was simulated using a new kinetic model, in which a new phenomenological first-order reaction was introduced to take into account the increasing concentration of acids that are produced during the complex cascade of reactions. The new model simulated experimental results more accurately than the severity factor (R0) model.

Designing a reliable leak bio-detection system for natural gas pipelines.

Monitoring of natural gas (NG) pipelines is an important task for economical/safety operation, loss prevention and environmental protection. Timely and reliable leak detection of gas pipeline, therefore, plays a key role in the overall integrity management for the pipeline system. Owing to the various limitations of the currently available techniques and the surveillance area that needs to be covered, the research on new detector systems is still thriving. Biosensors are worldwide considered as a niche technology in the environmental market, since they afford the desired detector capabilities at low cost, provided they have been properly designed/developed and rationally placed/networked/maintained by the aid of operational research techniques. This paper addresses NG leakage surveillance through a robust cooperative/synergistic scheme between biosensors and conventional detector systems; the network is validated in situ and optimized in order to provide reliable information at the required granularity level. The proposed scheme is substantiated through a knowledge based approach and relies on Fuzzy Multicriteria Analysis (FMCA), for selecting the best biosensor design that suits both, the target analyte and the operational micro-environment. This approach is illustrated in the design of leak surveying over a pipeline network in Greece.

Innovation in biotechnology: moving from academic research to product development: the case of biosensors

The fast pace of technological change in the biotechnology industry and the market demands require continuous innovation, which, owing to the science base of the sector, derives from academic research through a transformation process that converts science-oriented knowledge to marketable products. There appear to be some inherent difficulties in transforming directly the knowledge output of academic research to industrial use. The purpose of this article is to examine certain transition mechanisms from monodisciplinary academic isolation (curiosity-driven and internal-worth innovation) to university-industry alliances (market-driven and public-worth innovation) through inter-organizational multidisciplinary collaboration and contextualize the analysis with the case of biosensors. While the majority of literature on the subject studies the channels of knowledge transfer as determinants of alliance success (transferor/transferee interactions), either from the university side (science base) or the industry side (market base), this article focuses on the transferable (technology base) and how it can be strategically modeled and managed by the industry to promote innovation. Based on the valuable lessons learnt from the biosensor paradigm, the authors argue that strategic industry choices deal primarily with the best stage/point to intersect and seize the university output, implanting the required element of marketability that will transform an idea to a viable application. The authors present a methodological approach for accelerating the knowledge transfer from the university to industry aiming at the effective transition of science to products through a business model reconfiguration.

A Knowledge-Based Approach to Online Fault Diagnosis of FET Biosensors

Real-time diagnosis of insulator-semiconductor field-effect transistor (ISFET)-based biosensor systems aims at promptly correcting errors caused by insufficient function; insufficiency is judged by the operational behavior of the sensor, i.e., the data that it produces. Ultimately, a complete failure of the system (i.e., a “dead” sensor) should easily be recognized. Much more difficult is the recognition of a gradual malfunction of this complex system, which may be attributed to faults or failures in one or more of its subsystems. Evidently, the identification of the possible fault modes and their symptoms requires in-depth knowledge of sensors design and operation, both from the biochemical and electrical/electronic points of view, along with tackling uncertain, incomplete, or imprecise information. In this paper, a novel real-time diagnostic expert scheme for field-effect transistor (FET)-based biosensing is proposed. This paper 1) investigates the causes of sensor misfunction by means of fault tree analysis (FTA) relying on fuzzy reasoning to account for uncertainty and 2) proposes a computer-aided method for diagnosing biosensor failure during operation through an algorithmic procedure that is based on a nested loop mechanism. The tree (dendritic) structure (built using the information provided by the biosensor components and their intrarelations/interrelations on a surface- and a deep-knowledge level) serves as the knowledge base (KB), and the fuzzy-rules-based decision mechanism is the inference engine for fault detection and isolation.

Creating a specific domain ontology for supporting R&D in the science-based sector - The case of biosensors

In science-based and technology-intensive projects, knowledge management challenges require a tentative and cautious review of the technological domains, as well as, venues to monitor and assess the way those domains evolve, emerge, mature, and decline. Ontologies play a crucial role in conceptualizing/formalizing domain knowledge, yet any ontological platform that is constructed for supporting R&D throughout the knowledge creation process, must explicitly address the interplay between exploitation and exploration of knowledge at deep and surface levels. Focusing on the product per se and its downstream and upstream knowledge evolution complex system, ontology engineering adopts herein a process-driven view for capturing a continuously changing environment. The authors present a methodological framework for creating specific domain ontologies by means of a cybernetic infrastructure built on a modification of the Nonakas SECI process. This rationale is exemplified on biosensors, a class of devices strongly attached to multidisciplinary basic and applied science, bearing along many levels of input and output knowledge. The proposed ontological representation, expresses and defines a target product as a metamodel. Combined with knowledge about the scientific background of the product, an aspect model at physical concept level is generated from the metamodel and is further converted into a design model. This scheme enables knowledge to be used not only for representation but also for reasoning at functional level. The research logic followed herein does not bring yet another ontology building methodology through a project-management context, but rather contributes to an ontological approach for exploring the diverse knowledge inputs that a product requires through a specific domain-derived and domain-oriented context, which relies on a collaborative model building methodology and a systemic modeling formalism by using 2nd order cybernetics in order to include human intervention.

Restructuring the Keywords Interface to Enhance CAPE Knowledge Acquisition via an Intelligent Agent

Abstract This work proposes an improved KeyWord Interface (KWI) to enhance the efficiency of information retrieval when using an advanced search engine, as an intelligent agent. This can be achieved by restructuring the KWI into a new hierarchical structure based on an { n domains} by {3 levels} arrangement of keywords ( n ×3 KWI), forming a loose/adaptive semantic network. The hierarchical levels used in the suggested implementation are set of species, logical category , and holistic entity . As an illustration, the method is applied to an example of literature survey concerning a well-documented process engineering field. The results of the proposed technology are compared with the outcome of general-purpose search-engines built in common academic publication databases. The comparison reveals the advantage of intelligent searching in creating a local base according to the orders/interests of the researcher.

A methodological combined framework for roadmapping biosensor research: a fault tree analysis approach within a strategic technology evaluation frame

Abstract Biosensor technology began in the 1960s to revolutionize instrumentation and measurement. Despite the glucose sensor market success that revolutionized medical diagnostics, and artificial pancreas promise currently the approval stage, the industry is reluctant to capitalize on other relevant university-produced knowledge and innovation. On the other hand, the scientific literature is extensive and persisting, while the number of university-hosted biosensor groups is growing. Considering the limited marketability of biosensors compared to the available research output, the biosensor field has been used by the present authors as a suitable paradigm for developing a methodological combined framework for “roadmapping” university research output in this discipline. This framework adopts the basic principles of the Analytic Hierarchy Process (AHP), replacing the lower level of technology alternatives with internal barriers (drawbacks, limitations, disadvantages), modeled through fault tree analysis (FTA) relying on fuzzy reasoning to count for uncertainty. The proposed methodology is validated retrospectively using ion selective field effect transistor (ISFET) – based biosensors as a case example, and then implemented prospectively membrane biosensors, putting an emphasis on the manufacturability issues. The analysis performed the trajectory of membrane platforms differently than the available market roadmaps that, considering the vast industrial experience in tailoring and handling crystallic forms, suggest the technology path of biomimetic and synthetic materials. The results presented herein indicate that future trajectories lie along with nanotechnology, and especially nanofabrication and nano-bioinformatics, and focused, more on the science-path, that is, on controlling the natural process of self-assembly and the thermodynamics of bioelement-lipid interaction. This retained the nature-derived sensitivity of the biosensor platform, pointing out the differences between the scope of academic research and the market viewpoint.

Fuzzy multicriteria choice of instrumental methods for measuring physical quantities - application in the case of dielectric aluminium anodic oxide films

This work suggests fuzzy multicriteria analysis as a powerful method for optimal choice of instrumental methods for measuring physical quantities within a common laboratory that supports Small/Medium enterprises (SMEs). The criteria used include time requirements, convenience/simplicity operating and capital cost, precision, trueness, range and robustness, degree of acceptance, and comparability with results obtained by other instrumental methods currently in use by SMEs. A 4-stage Delphi method, especially designed for the needs of the present work, has been applied for the assignment of fuzzy values to the elements of both, the preference matrix and the criteria vector. A case study is also presented, concerning small/medium aluminium anodizers; the physical quantity examined is the thickness of the dielectric anodic oxide film and the alternative instrumental methods considered are eddy currents, mass decrease after chemical stripping, optical microscopy, electron microscopy, beta particles backscattering, double-beam interference microscopy, and electrical breakdown voltage. A robust solution is obtained, confirmed by sensitivity analysis, indicating eddy currents and optical microscopy, as dominant alternatives.

Fuzzy fault tree analysis as a means for computer aided technology transfer to small/medium anodizers

Abstract Computer aided technology transfer to Small/Medium Anodizers (SMAs) can be provided either by an Anodizing department of a Large Company (ALC) or by a Technology Center designed for this purpose. In this work, a full cycle of this process is presented, including mainly Diagnostic Knowledge Base (DKB) enrichment, fuzzy Fault Tree Analysis (FTA), application of a simple expert system for pre-filtering alternative solutions to the problem, and fuzzy multicriteria analysis (MCA), all performing on a quasi online/real-time basis. The utility/applicability of this computer aided integrated scheme was proved by successfully analysing a real industrial problem referring to the appearance of defected articles in aluminium anodizing when medium/high thickness/porosity oxide layers were produced within a sulphuric acid bath.

Computer Aided Neuro-fuzzy Control in Anodizing of Aluminium

Abstract A combination of neuro-fuzzy networking and independent cluster analysis has been used to control alkaline etching in the sequence of aluminium anodizing processes. The objective was to avoid (a) failure or specific defects during a certain process and (b) creating an effect that might cause failure/defect during another downstream process. The fuzzy variables or input neurons used are the concentration of caustic soda, the bath temperature and the retention time. The defects under examination (namely, matness, etch staining, and inadequate cleaning) form the pattern classes of the neuro-fuzzy network. The independent clustering is based on (a) raw data and (b) specifications of the product, set by the client or the market. The algorithmic procedure applied herein can be used in other similar semi-continuous chemical processes, especially in the field of surface treatment of metals.