On the reduction of repetitive processes into singular and non-singular Roesser models

Multidimensional Systems and Signal Processing - In this paper we present new methods for the reduction of a polynomial system matrix describing a discrete linear repetitive process, to equivalent...     

Behavior-based detection and classification of malicious software utilizing structural characteristics of group sequence graphs

Journal of Computer Virology and Hacking Techniques - In this work we present a graph-based approach for behavior-based malware detection and classification utilizing the Group Relation Graphs...     

Microbiological and physicochemical characterisation of green table olives of Halkidiki and Conservolea varieties processed by the Spanish method on industrial scale

The microbiological and physicochemical changes of industrially fermented Halkidiki and Conservolea green table olives were determined. Samples were analysed to monitor the population of lactic acid bacteria (LAB), yeasts and Enterobacteriaceae, together with changes in pH, acidity, salinity, colour, lactic acid, acetic acid and ethanol. LAB and yeast species diversity was evaluated at the beginning (1 day), middle (75 days) and final (135 days) stages of fermentation by RAPD-PCR genomic fingerprinting. Results revealed vigorous lactic acid processes as indicated by the dominance of LAB over yeasts. No Enterobacteriaceae could be detected after 30 days. Lactiplantibacillus plantarum (formerly Lactobacillus plantarum) dominated in the beginning of fermentation in both varieties. In the end, Lactiplantibacillus pentosus (formerly Lactobacillus pentosus) and Pediococcus ethanolidurans prevailed in Halkidiki and Conservolea varieties, respectively. As for yeasts, Kluyveromyces lactis/marxianus and Pichia manshurica prevailed at the onset of fermentation in Halkidiki and Conservolea varieties, whereas in the end Pichia membranifaciens dominated in both varieties.     

Volatile fraction of commercial thyme honeys produced in Mediterranean regions and key volatile compounds for geographical discrimination: A chemometric approach

The aim of the present study was to investigate the volatile fraction and discriminate 34 commercial thyme honeys from Morocco, Egypt, Spain, and Greece according to geographical origin, using key volatile compounds in combination with chemometrics. Sixty-two volatile compounds belonging to different classes were identified and semi-quantified using headspace solid phase micro-extraction coupled to gas chromatography/mass spectrometry (HS-SPME-GC/MS). Applying chemometric analyses to 17 volatiles (p < 0.05), honeys were successfully discriminated according to geographical origin. Correct classification rate was 88.2% using the cross-validation method. Volatile compounds proved to be a powerful tool for discriminating commercial thyme honeys from different countries.     

Tokens vs. Signals: On Conformance between Formal Models of Dataflow and Hardware

Designing hardware often involves several types of modeling and analysis, e.g., in order to check system correctness, to derive performance properties such as throughput, to optimize resource usages (e.g., buffer sizes), and to synthesize parts of a circuit (e.g., control logic). Working directly with low-level hardware models such as finite-state machines (FSMs) to answer such questions is often infeasible, e.g., due to state explosion. Instead, designers often use dataflow models such as SDF and CSDF, which are more abstract than FSMs, and less expensive to use since they come with more efficient analysis algorithms. However, dataflow models are only abstractions of the real hardware, and often omit critical information. This raises the question, when can one say that a certain dataflow model faithfully captures a given piece of hardware? The question is of more than simply academic interest. Indeed, as illustrated in this paper, dataflow-based analysis outcomes may sometimes be defensive (e.g., buffers that are too big) or even incorrect (e.g., buffers that are too small). To answer the question of faithfully capturing hardware using dataflow models, we develop a formal conformance relation between the heterogeneous formalisms of (1) finite-state machines with synchronous semantics, typically used to model synchronous hardware, and (2) asynchronous processes communicating via queues, used as a formal model for dataflow. The conformance relation preserves performance properties such as worst-case throughput and latency.     

Comparative Analysis of Synthetic Natural Gas versus Hydrogen Production from Bagasse

A rigorous and comparative evaluation of two biomass‐to‐gases (BtG) conversion routes was performed and, according to this outcome, it is suggested which of the options evaluated is most desirable. These options, the hydrogen and synthetic natural gas (SNG) production, were designed in Aspen Plus process simulation software. Sugar cane bagasse was considered as feedstock. Mass and energy balance data were extracted from the simulations, and consequently thermodynamic (exergy analysis), economic (financial and uncertainty analysis), and environmental (CO₂ emissions) evaluations were carried out. Exergy and environmental analysis favor the SNG production while the hydrogen route provides higher profits.     

Electric vehicle charging in stochastic smart microgrid operation with fuel cell and RES units

Plug-in electric vehicles increasingly augment their share in the global market as they appear to be an economic and emission-free alternative to modern means of transportation. As their presence strengthens, ways that will ensure economic charge along with uninterrupted grid operation are necessary to be found. This paper aims to approach the economic optimization problem that includes several Electric Vehicles (EVs) within a Low Voltage (LV) network comprising various Distributed Energy Resources (DER) as fuel cell, Renewable Energy Sources (RES), (photovoltaics, wind turbine) etc. via a scenario based simulation. The purpose is to investigate the main variables of the grid, such as its operating cost, charging patterns, power injection from the upstream network, resulting from the coordinated control of DER in Smart Microgrid operation in conjunction to the flexible load the controlled EV charging introduces. The base case study is that of absence of EVs, and therefore the demand is met only by the upstream network and the DER units. Subsequently, EVs are introduced as controllable loads and finally as dispatchable storage units incorporating a Vehicle to Grid (V2G) capability to the Smart Microgrid. Furthermore, the problem is not tackled deterministically and although forecasts for all network parameters are assumed to be known, forecasting errors and stochastic driver patterns cannot be ignored. Thus, for each imposed policy, a scenario based approach is implemented to determine operating cost in various cases along to DER utilization and the effect EVs bear on these results.     

Kefir Immobilized on Corn Grains as Biocatalyst for Lactic Acid Fermentation and Sourdough Bread Making

Abstract: The natural mixed culture kefir was immobilized on boiled corn grains to produce an efficient biocatalyst for lactic acid fermentation with direct applications in food production, such as sourdough bread making. The immobilized biocatalyst was initially evaluated for its efficiency for lactic acid production by fermentation of cheese whey at various temperatures. The immobilized cells increased the fermentation rate and enhanced lactic acid production compared to free kefir cells. Maximum lactic acid yield (68.8 g/100 g) and lactic acid productivity (12.6 g/L per day) were obtained during fermentation by immobilized cells at 37 °C. The immobilized biocatalyst was then assessed as culture for sourdough bread making. The produced sourdough breads had satisfactory specific loaf volumes and good sensory characteristics. Specifically, bread made by addition of 60% w/w sourdough containing kefir immobilized on corn was more resistant regarding mould spoilage (appearance during the 11^th day), probably due to higher lactic acid produced (2.86 g/Kg of bread) compared to the control samples. The sourdough breads made with the immobilized biocatalyst had aroma profiles similar to that of the control samples as shown by headspace SPME GC‐MS analysis.