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Synthesis of regional networks for biomass and biofuel production
Hon Loong Lam, 2010, dissertation

Abstract: This thesis presents two different approaches to the synthesis of regional networks for biomass and biofuel production and supply: Mathematical Programming and Graph Theoretic approach. The optimisation criterion for both approaches is the maximisation of profit. The first approach is based on a generic optimisation model of biomass production and supply networks. This superstructure approach is based on a flexible number of network layers: plantation, collection using a pre-treatment, process, and consumption. A Mixed Integer Linear Programming (MILP) model has been successfully developed during this work. However, the solution of this biomass production network model is very challenging due to the large sizes of the networks and the number of interconnections. The huge number of redundant variables reduces model efficiency (time taken to solve the model and the interpretation of the results). This model when representing very large size networks cannot be solved over a reasonable time even by professional mathematical programming software tools. Several model-size reduction techniques are therefore proposed for the solution of large-scale networks. In particular, methods are proposed for (i) reducing the connectivity within a biomass supply chain network by setting the maximum allowable distance between the supply zones to the collection centres, (ii) eliminating unnecessary variables and constrains to reduce the zero-flows in the full model, and (iii) aggregating the network and hence the synthesis process by merging the collection centres. The network synthesis is also carried out by P-graph (Process Graph) tools. P-graph is a directed bipartite graph, having two types of vertices — one for operating units and another for those objects representing material or energy flows/quantities. In this procedure, firstly a maximum feasible superstructure for biomass production network is generated from which the optimal structure is then selected by the Branch and Bound method. This graph-based method clearly shows where, how, and what kind of material and energy carriers will be transferred from one supply chain layer to another. In order to test the efficiency of the model, a small regional renewable network problem was solved using both methods. Their performances were tested and the results confirmed the applicability on a regional scale. The proposed model-size reduction techniques were also tested. A large-scale regional case study was created to demonstrate these techniques. The results are very positive and some suggestions for future work are given in the conclusion.
Keywords: Biomass and bioenergy network synthesis, Model-size reduction techniques, Mathematical Programming, MILP, P-Graph
Published: 06.01.2011; Views: 2469; Downloads: 83
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Fuzzy Logic Model for the performance benchmarking of sugar plants by considering best available techniques
Damjan Krajnc, Miro Mele, Peter Glavič, 2007, original scientific article

Abstract: This paper deals with the problem of performance benchmarking of traditional beet sugar plants, by considering Best Available Techniques (BAT) for beet sugar production, as determined by the Integrated Pollution Prevention and Control (IPPC) Directive. A Fuzzy Logic Model, based on fuzzy set theory, was constructed for this purpose, in order to compare the performances of sugar plants within the sector's best standards, as expressed in the Reference Document on BAT. The effectiveness of the model was tested in the case study,in which three sugar plants were benchmarked against the BAT regarding the consumption of energy, water, raw materials and the production of wastes, wastewater, by-products and the main product. The model was recognized as helpful for the benchmarking needs of sugar plants. In addition, by integrating BAT Reference Document analysis into the model, it provides IPPC permitting authorities with an objective method and uniform BAT benchmarks to manage permitting process.
Keywords: chemical processing, beet sugar production, sugar industry, clean technologies, performance benchmarking, IPPC Directive, technology performance assessment, fuzzy set theory, best available techniques, IPPC permitting process
Published: 31.05.2012; Views: 1557; Downloads: 34
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A model of data flow in lower CIM levels
Igor Drstvenšek, Ivo Pahole, Jože Balič, 2004, original scientific article

Abstract: After years of work in fields of computer-integrated manufacturing (CIM), flexible manufacturing systems (FMS), and evolutionary optimisation techniques, several models of production automation were developed in our laboratories. The last model pools the discoveries that proved their effectiveness in the past models. It is based on the idea of five levels CIM hierarchy where the technological database (TDB) represents a backbone of the system. Further on the idea of work operation determination by an analyse of the production system is taken out of a model for FMS control system, and finally the approach to the optimisation of production is supported by the results of evolutionary based techniques such as genetic algorithms and genetic programming.
Keywords: computer integrated manufacturing, flexible manufacturing systems, evolutionary optimisation techniques, production automation, CIM hierarchy, technological databases, production optimisation, genetic algorithms, genetic programming
Published: 01.06.2012; Views: 1066; Downloads: 31
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Stability of ranked gene lists in large microarray analysis studies
Gregor Štiglic, Peter Kokol, 2010, original scientific article

Abstract: This paper presents an empirical study that aims to explain the relationship between the number of samples and stability of different gene selection techniques for microarray datasets. Unlike other similar studies where number of genes in a ranked gene list is variable, this study uses an alternative approach where stability is observed at different number of samples that are used for gene selection. Three different metrics of stability, including a novel metric in bioinformatics, were used to estimate the stability of the ranked gene lists. Results of this study demonstrate that the univariate selection methods produce significantly more stable ranked gene lists than themultivariate selection methods used in this study. More specifically, thousands of samples are needed for these multivariate selection methods to achieve the same level of stability any given univariate selection method can achieve with only hundreds.
Keywords: gene selection techniques, microarray, analysis studies
Published: 05.06.2012; Views: 848; Downloads: 101
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Mojca Ješe, 2015, undergraduate thesis

Abstract: Translating scientific texts is crucial for dissiminating scietific knowledge and consequently for the progress of specific scientific fields. This thesis focuses on the issue of translating mathematical texts. The first chapter presents basic characteristics of scientific texts which will serve as a basic model. In the second chapter those common basic characteristics of mathematical texts are presented which distinguish themselves from other texts at different levels of semiotic structure, as well as through symbolism and visual images. Specific aspects of individual systems and their intersemiotic relations are presented through multisemiotic mechanisms. In the third chapter the basic model for translating scientific texts is given, as well as a description of some of the traslation techniques we can use when translating. The fourth and final chapter presents an analysis of the first and third chapters of the book 17 Lectures on Fermat Numbers and its translation into Slovene based on theoretical knowledge in the first three chapters. The techniques for translation of the selected mathematical text are analyzed through specific characterictics of scientific and mathematical texts.
Keywords: Scientific translation, intersemiotic text, mathematical text, translation techniques, 17 Lectures on Fermat Numbers
Published: 07.10.2015; Views: 449; Downloads: 50
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Postmodern Elements in Luhrmann's Adaptation of The Great Gatsby
Nina Kresnik, 2014, undergraduate thesis

Abstract: The aim of this diploma thesis was to find postmodern elements in Luhrman’s film adaptation of F. Scott Fitzgerald’s novel The Great Gatsby. Since The Great Gatsby is a modernist novel, published in 1925 and the aim was to find postmodern elements in the movie adaptation, modernism and postmodernism are explained first. Then the novel with its content, themes, motifs and symbols is examined thoroughly in order to explain how postmodern elements in the movie make the novel’s story interesting for today’s generation. Finally the postmodern elements in the movie are examined and connected to the novel’s story, themes, motifs and symbols. I came to the conclusion that postmodern elements in the movie are the reason why the movie adaptation of the novel, published almost ninety years ago, is so interesting to today’s generation.
Keywords: modernism, postmodernism, The Great Gatsby, 1920s, postmodern elements in the movie, cinematic techniques, the music, the fashion.
Published: 18.06.2014; Views: 1517; Downloads: 143
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Characterization of Slovenian wines using multidimensional data analysis from simple enological descriptors
Adriána Bednárová, Roman Kranvogl, Darinka Brodnjak-Vončina, Tjaša Jug, Ernest Beinrohr, 2013, original scientific article

Abstract: Determination of the product's origin is one of the primary requirements when certifying a wine's authenticity. Significant research has described the possibilities of predicting a wine's origin using efficient methods of wine components' analyses connected with multivariate data analysis. The main goal of this study was to examine the discrimination ability of simple enological descriptors for the classification of Slovenian red and white wine samples according to their varieties and geographical origins. Another task was to investigate the inter-relations available among descriptors such as relative density, content of total acids, non-volatile acids and volatile acids, ash, reducing sugars, sugar-free extract, $SO_2$, ethanol, pH, and an important additional variable - the sensorial quality of the wine, using correlation analysis, principal component analysis (PCA), and cluster analysis (CLU). 739 red and white wine samples were scanned on a Wine Scan FT 120, from wave numbers 926 $cm^{–1}$ to 5012 $cm^{–1}$. The applied methods of linear discriminant analysis (LDA), general discriminant analysis (GDA), and artificial neural networks (ANN), demonstrated their power for authentication purposes.
Keywords: wine authentication, enological descriptors, classification techniques, ANN
Published: 10.07.2015; Views: 845; Downloads: 13
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Optimiranje značilnih parametrov frezanja z uporabo razvojne tehnike optimizacije jate delcev
Uroš Župerl, Franc Čuš, Valentina Gečevska, 2007, original scientific article

Abstract: Izbira rezalnih parametrov je najpomembnejši korak pri postopku načrtovanja proizvodnje, zato izdelamo novo tehniko razvojnega računanja za optimiranje procesa odrezovanja. V prispevku je uporabljena tehnika, ki oponaša dinamiko delcev v velikih skupinah (optimizacija PSO), za učinkovito in simultano optimiranje postopkov frezanja. V omenjenih postopkih smo soočeni s problemom več ciljnih dejavnikov. Najprej uporabimo umetno nevronsko mrežo (UNM) za napovedovanje rezalnih sil, nato z algoritmom PSO pridobimo optimalno rezalno hitrost in podajanja. Cilj optimizacije je, ob upoštevanju omejitev, določiti ekstrem ciljne funkcije (napovedna površina največjih sil). Med optimizacijo delci, s svojo inteligenco, letijo po prostoru rešitev in iščejo optimalne rezalne pogoje po strategiji algoritma PSO. Rezultati pokažejo, da je integriran sistem nevronskih mrež in kolektivne inteligence učinkovita metoda pri reševanju večciljnih optimizacijskih problemov. Njena velika učinkovitost na širokem območju rezalnih parametrov potrjuje, da sistem lahko praktično uporabimo v proizvodnji. Rezultati simulacij nakazujejo, da predlagan algoritem v primerjavi z rodovnimi algoritmi (GA) in simulacijskim (SA) ohlajanjem lahko poveča natančnost rešitve in konvergenco postopka. Nova tehnika razvojnega računanja ima nekoliko prednosti ter koristi in je primerna za uporabo v kombinaciji z modeli na osnovi umetnih nevronskih vezij, pri katerih niso na voljo izrecne relacije med vhodi in izhodi. Raziskava odpre vrata na področju obdelave z odrezovanjem za nov razred optimizacijskih tehnik, ki slonijo na razvojnem računanju.
Keywords: odrezovanje, končno frezanje, rezalni parametri, nevronske mreže, razvojne tehnike, optimizacija jate delcev, cutting, end-milling, cutting parameters, neural networks, evolution techniques, particle swarm optimization
Published: 10.07.2015; Views: 607; Downloads: 17
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A comprehensive noise robust speech parameterization algorithm using wavelet packet decomposition-based denoising and speech feature representation techniques
Bojan Kotnik, Zdravko Kačič, 2007, original scientific article

Abstract: This paper concerns the problem of automatic speech recognition in noise-intense and adverse environments. The main goal of the proposed work is the definition, implementation, and evaluation of a novel noise robust speech signal parameterization algorithm. The proposed procedure is based on time-frequency speech signal representation using wavelet packet decomposition. A new modified soft thresholding algorithm based on time-frequency adaptive threshold determination was developed to efficiently reduce the level of additive noise in the input noisy speech signal. A two-stage Gaussian mixture model (GMM)-based classifier was developed to perform speech/nonspeech as well as voiced/unvoiced classification. The adaptive topology of the wavelet packet decomposition tree based on voiced/unvoiced detection was introduced to separately analyze voiced and unvoiced segments of the speech signal. The main feature vector consists of a combination of log-root compressed wavelet packet parameters, and autoregressive parameters. The final output feature vector is produced using a two-staged feature vector postprocessing procedure. In the experimental framework, the noisy speech databases Aurora 2 and Aurora 3 were applied together with corresponding standardized acoustical model training/testing procedures. The automatic speech recognition performance achieved using the proposed noise robust speech parameterization procedure was compared to the standardized mel-frequency cepstral coefficient (MFCC) feature extraction procedures ETSI ES 201 108 and ETSI ES 202 050.
Keywords: speech parametrization, algorithm, speech techniques
Published: 26.06.2017; Views: 339; Downloads: 129
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