Search results for: catalytic decomposition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 447

Search results for: catalytic decomposition

57 Nano-Bioremediation of Contaminated Industrial Wastewater Using Biosynthesized AgNPs and Their Nano-Composite

Authors: Osama M. Darwesh, Sahar H. Hassan, Abd El-Raheem R. El-Shanshoury, Shawky Z. Sabae

Abstract:

Nanotechnology as multidisciplinary technology is growing rapidly with important applications in several sectors. Also, nanobiotechnology is known for the use of microorganisms for the synthesis of targeted nanoparticles. The present study deals with the green synthesis of silver nanoparticles using aquatic bacteria and the development of a biogenic nanocomposite for environmental applications. 20 morphologically different colonies were isolated from the collected water samples from eight different locations at the Rosetta branch of the Nile Delta, Egypt. The obtained results illustrated that the most effective bacterial isolate (produced the higher amount of AgNPs after 24 h of incubation time) is isolate R3. Bacillus tequilensis was the strongest extracellular bio-manufactory of AgNPs. Biosynthesized nanoparticles had a spherical shape with a mean diameter of 2.74 to 28.4 nm. The antimicrobial activity of silver nanoparticles against many pathogenic microbes indicated that the produced AgNPs had high activity against all tested multi-antibiotic resistant pathogens. Also, the stabilized prepared AgNPs-SA nanocomposite has greater catalytic activity for the decolourization of some dyes like Methylene blue (MB) and Crystal violet. Such results represent a promising stage for producing eco-friendly, cost-effective, and easy-to-handle devices for the bioremediation of contaminated industrial wastewater.

Keywords: Bioremediation, AgNPs, AgNPs-SA nanocomposite, Bacillus tequilensis, nanobiotechnology.

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56 Growth of Multi-Layered Graphene Using Organic Solvent-PMMA Film as the Carbon Source under Low Temperature Conditions

Authors: Alaa Y. Ali, Natalie P. Holmes, John Holdsworth, Warwick Belcher, Paul Dastoor, Xiaojing Zhou

Abstract:

Multi-layered graphene has been produced under low temperature chemical vapour deposition (CVD) growth conditions by utilizing an organic solvent and polymer film source. Poly(methylmethacrylate) (PMMA) was dissolved in chlorobenzene solvent and used as a drop-cast film carbon source on a quartz slide. A source temperature (Tsource) of 180 °C provided sufficient carbon to grow graphene, as identified by Raman spectroscopy, on clean copper foil catalytic surfaces.  Systematic variation of hydrogen gas (H2) flow rate from 25 standard cubic centimeters per minute (sccm) to 100 sccm and CVD temperature (Tgrowth) from 400 to 800 °C, yielded graphene films of varying quality as characterized by Raman spectroscopy. The optimal graphene growth parameters were found to occur with a hydrogen flow rate of 75 sccm sweeping the 180 °C source carbon past the Cu foil at 600 °C for 1 min. The deposition at 600 °C with a H2 flow rate of 75 sccm yielded a 2D band peak with ~53.4 cm-1 FWHM and a relative intensity ratio of the G to 2D bands (IG/I2D) of 0.21. This recipe fabricated a few layers of good quality graphene.

Keywords: Graphene, chemical vapour deposition, carbon source, low temperature growth.

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55 Spatial and Temporal Variability of Fog Over the Indo-Gangetic Plains, India

Authors: Sanjay Kumar Srivastava, Anu Rani Sharma, Kamna Sachdeva

Abstract:

The aim of the paper is to analyze the characteristics of winter fog in terms of its trend and spatial-temporal variability over Indo-Gangetic plains. The study reveals that during last four and half decades (1971-2015), an alarming increasing trend in fog frequency has been observed during the winter months of December and January over the study area. The frequency of fog has increased by 118.4% during the peak winter months of December and January. It has also been observed that on an average central part of IGP has 66.29% fog days followed by west IGP with 41.94% fog days. Further, Empirical Orthogonal Function (EOF) decomposition and Mann-Kendall variation analysis are used to analyze the spatial and temporal patterns of winter fog. The findings have significant implications for the further research of fog over IGP and formulate robust strategies to adapt the fog variability and mitigate its effects. The decision by Delhi Government to implement odd-even scheme to restrict the use of private vehicles in order to reduce pollution and improve quality of air may result in increasing the alarming increasing trend of fog over Delhi and its surrounding areas regions of IGP.

Keywords: Fog, climatology, spatial variability, temporal variability, empirical orthogonal function, visibility, Mann-Kendall test, variation point.

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54 Simulation-Based Optimization of a Non-Uniform Piezoelectric Energy Harvester with Stack Boundary

Authors: Alireza Keshmiri, Shahriar Bagheri, Nan Wu

Abstract:

This research presents an analytical model for the development of an energy harvester with piezoelectric rings stacked at the boundary of the structure based on the Adomian decomposition method. The model is applied to geometrically non-uniform beams to derive the steady-state dynamic response of the structure subjected to base motion excitation and efficiently harvest the subsequent vibrational energy. The in-plane polarization of the piezoelectric rings is employed to enhance the electrical power output. A parametric study for the proposed energy harvester with various design parameters is done to prepare the dataset required for optimization. Finally, simulation-based optimization technique helps to find the optimum structural design with maximum efficiency. To solve the optimization problem, an artificial neural network is first trained to replace the simulation model, and then, a genetic algorithm is employed to find the optimized design variables. Higher geometrical non-uniformity and length of the beam lowers the structure natural frequency and generates a larger power output.

Keywords: Piezoelectricity, energy harvesting, simulation-based optimization, artificial neural network, genetic algorithm.

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53 Comparative Study in Evaluating the Antioxidation Efficiency for Native Types Antioxidants Extracted from Crude Oil with the Synthesized Class

Authors: Mohammad Jamil Abd AlGhani

Abstract:

The natural native antioxidants N,N-P-methyl phenyl acetone and N,N-phenyl acetone were isolated from the Iraqi crude oil region of Kirkuk by ion exchange and their structure was characterized by spectral and chemical analysis methods. Tetraline was used as a liquid hydrocarbon to detect the efficiency of isolated molecules at elevated temperature (393 K) that it has physicochemical specifications and structure closed to hydrocarbons fractionated from crude oil. The synthesized universal antioxidant 2,6-ditertiaryisobutyl-p-methyl phenol (Unol) with known stochiometric coefficient of inhibition equal to (2) was used as a model for comparative evaluation at the same conditions. Modified chemiluminescence method was used to find the amount of absorbed oxygen and the induction periods in and without the existence of isolated antioxidants molecules. The results of induction periods and quantity of absorbed oxygen during the oxidation process were measured by manometric installation. It was seen that at specific equal concentrations of N,N-phenyl acetone and N, N-P-methyl phenyl acetone in comparison with Unol at 393 K were with (2) and (2.5) times efficient than do Unol. It means that they had the ability to inhibit the formation of new free radicals and prevent the chain reaction to pass from the propagation to the termination step rather than decomposition of formed hydroperoxides.

Keywords: Antioxidants, chemiluminescence, inhibition, unol.

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52 In Search of an SVD and QRcp Based Optimization Technique of ANN for Automatic Classification of Abnormal Heart Sounds

Authors: Samit Ari, Goutam Saha

Abstract:

Artificial Neural Network (ANN) has been extensively used for classification of heart sounds for its discriminative training ability and easy implementation. However, it suffers from overparameterization if the number of nodes is not chosen properly. In such cases, when the dataset has redundancy within it, ANN is trained along with this redundant information that results in poor validation. Also a larger network means more computational expense resulting more hardware and time related cost. Therefore, an optimum design of neural network is needed towards real-time detection of pathological patterns, if any from heart sound signal. The aims of this work are to (i) select a set of input features that are effective for identification of heart sound signals and (ii) make certain optimum selection of nodes in the hidden layer for a more effective ANN structure. Here, we present an optimization technique that involves Singular Value Decomposition (SVD) and QR factorization with column pivoting (QRcp) methodology to optimize empirically chosen over-parameterized ANN structure. Input nodes present in ANN structure is optimized by SVD followed by QRcp while only SVD is required to prune undesirable hidden nodes. The result is presented for classifying 12 common pathological cases and normal heart sound.

Keywords: ANN, Classification of heart diseases, murmurs, optimization, Phonocardiogram, QRcp, SVD.

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51 Single-Walled Carbon Nanotube Synthesis by Chemical Vapor Deposition Using Platinum-Group Metal Catalysts

Authors: T. Maruyama, T. Saida, S. Naritsuka, S. Iijima

Abstract:

Single-walled carbon nanotubes (SWCNTs) are generally synthesized by chemical vapor deposition (CVD) using Fe, Co, and Ni as catalysts. However, due to the Ostwald ripening of metal catalysts, the diameter distribution of the grown SWCNTs is considerably wide (>2 nm), which is not suitable for electronics applications. In addition, reduction in the growth temperature is desirable for fabricating SWCNT devices compatible with the LSI process. Herein, we performed SWCNT growth by alcohol catalytic CVD using platinum-group metal catalysts (Pt, Rh, and Pd) because these metals have high melting points, and the reduction in the Ostwald ripening of catalyst particles is expected. Our results revealed that web-like SWCNTs were obtained from Pt and Rh catalysts at growth temperature between 500 °C and 600 °C by optimizing the ethanol pressure. The SWCNT yield from Pd catalysts was considerably low. By decreasing the growth temperature, the diameter and chirality distribution of SWCNTs from Pt and Rh catalysts became small and narrow. In particular, the diameters of most SWCNTs grown using Pt catalysts were below 1 nm and their diameter distribution was considerably narrow. On the contrary, SWCNTs can grow from Rh catalysts even at 300 °C by optimizing the growth condition, which is the lowest temperature recorded for SWCNT growth. Our results demonstrated that platinum-group metals are useful for the growth of small-diameter SWCNTs and facilitate low-temperature growth.

Keywords: Carbon nanotube, chemical vapor deposition, catalyst, Pt, Rh, Pd.

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50 A Systems Approach to Gene Ranking from DNA Microarray Data of Cervical Cancer

Authors: Frank Emmert Streib, Matthias Dehmer, Jing Liu, Max Mühlhauser

Abstract:

In this paper we present a method for gene ranking from DNA microarray data. More precisely, we calculate the correlation networks, which are unweighted and undirected graphs, from microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to progression of the tumor. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth and, hence, indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, DNA microarray data, cancer.

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49 Topographic Arrangement of 3D Design Components on 2D Maps by Unsupervised Feature Extraction

Authors: Stefan Menzel

Abstract:

As a result of the daily workflow in the design development departments of companies, databases containing huge numbers of 3D geometric models are generated. According to the given problem engineers create CAD drawings based on their design ideas and evaluate the performance of the resulting design, e.g. by computational simulations. Usually, new geometries are built either by utilizing and modifying sets of existing components or by adding single newly designed parts to a more complex design. The present paper addresses the two facets of acquiring components from large design databases automatically and providing a reasonable overview of the parts to the engineer. A unified framework based on the topographic non-negative matrix factorization (TNMF) is proposed which solves both aspects simultaneously. First, on a given database meaningful components are extracted into a parts-based representation in an unsupervised manner. Second, the extracted components are organized and visualized on square-lattice 2D maps. It is shown on the example of turbine-like geometries that these maps efficiently provide a wellstructured overview on the database content and, at the same time, define a measure for spatial similarity allowing an easy access and reuse of components in the process of design development.

Keywords: Design decomposition, topographic non-negative matrix factorization, parts-based representation, self-organization, unsupervised feature extraction.

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48 Fast Wavelet Image Denoising Based on Local Variance and Edge Analysis

Authors: Gaoyong Luo

Abstract:

The approach based on the wavelet transform has been widely used for image denoising due to its multi-resolution nature, its ability to produce high levels of noise reduction and the low level of distortion introduced. However, by removing noise, high frequency components belonging to edges are also removed, which leads to blurring the signal features. This paper proposes a new method of image noise reduction based on local variance and edge analysis. The analysis is performed by dividing an image into 32 x 32 pixel blocks, and transforming the data into wavelet domain. Fast lifting wavelet spatial-frequency decomposition and reconstruction is developed with the advantages of being computationally efficient and boundary effects minimized. The adaptive thresholding by local variance estimation and edge strength measurement can effectively reduce image noise while preserve the features of the original image corresponding to the boundaries of the objects. Experimental results demonstrate that the method performs well for images contaminated by natural and artificial noise, and is suitable to be adapted for different class of images and type of noises. The proposed algorithm provides a potential solution with parallel computation for real time or embedded system application.

Keywords: Edge strength, Fast lifting wavelet, Image denoising, Local variance.

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47 The Effects of Cow Manure Treated by Fruit Beetle Larvae, Waxworms and Tiger Worms on Plant Growth in Relation to Its Use as Potting Compost

Authors: Waleed S. Alwaneen

Abstract:

Dairy industry is flourishing in world to provide milk and milk products to local population. Besides milk products, dairy industries also generate a substantial amount of cow manure that significantly affects the environment. Moreover, heat produced during the decomposition of the cow manure adversely affects the crop germination. Different companies are producing vermicompost using different species of worms/larvae to overcome the harmful effects using fresh manure. Tiger worm treatment enhanced plant growth, especially in the compost-manure ratio (75% compost, 25% cow manure), followed by a ratio of 50% compost, 50% cow manure.  Results also indicated that plant growth in Waxworm treated manure was weak as compared to plant growth in compost treated with Fruit Beetle (FB), Waxworms (WW), and Control (C) especially in the compost (25% compost, 75% cow manure) and 100% cow manure where there was no growth at all. Freshplant weight, fresh leaf weight and fresh root weight were significantly higher in the compost treated with Tiger worms in (75% compost, 25% cow manure); no evidence was seen for any significant differences in the dry root weight measurement between FB, Tiger worms (TW), WW, Control (C) in all composts. TW produced the best product, especially at the compost ratio of 75% compost, 25% cow manure followed by 50% compost, 50% cow manure.

Keywords: Fruit beetle, tiger worms, waxworms, control.

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46 Stability and Kinetic Analysis during Vermicomposting of Sewage Sludge

Authors: Ashish Kumar Nayak, Dhamodharan K., Ajay S. Kalamdhad

Abstract:

The present study is aimed at alteration of sewage sludge into stable compost product using vermicomposting of sewage sludge mixed with cattle manure and saw dust in five different proportions based on C/N ratios (C/N 15 (R1), 20 (R2), 25 (R3) and 30 (R4); and control (R5)) by employing an epigeic earthworm Eisenia fetida. Higher reductions in C/N ratio, CO2 evolution and OUR were observed in R4 demonstrated the compost stability. In addition, R4 proved to be best combination for the growth of the earthworms. In order to observe the optimal degradation, kinetics for degradation of organic matter in vermicomposting were quantitatively evaluated. An approach model was developed by assuming that composting process is carried out in a homogeneous way and the kinetics for decomposition reaction is represented by a Monod-type equation. The results exhibit comparable variations in the kinetic constants Km and K3 under varying parameters during vermicomposting process. Results suggested that higher R2 value in R4, enhanced suitability towards Lineweaver-Burke plot. R4 yields higher degradability coefficient (K) reveals that the occurrence of optimal nutrient balance, which not only enhanced the affinity of enzymes towards substrate but also improved its degradation process. Therefore, it can be proved that R4 provided to be the best feed combination for vermicomposting process as compared to other reactors.

Keywords: Vermicomposting, Eisenia fetida, Sewage sludge, C/N ratio, Stability, Enzyme kinetics concept.

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45 Comparative Analysis of Various Multiuser Detection Techniques in SDMA-OFDM System Over the Correlated MIMO Channel Model for IEEE 802.16n

Authors: Susmita Das, Kala Praveen Bagadi

Abstract:

SDMA (Space-Division Multiple Access) is a MIMO (Multiple-Input and Multiple-Output) based wireless communication network architecture which has the potential to significantly increase the spectral efficiency and the system performance. The maximum likelihood (ML) detection provides the optimal performance, but its complexity increases exponentially with the constellation size of modulation and number of users. The QR decomposition (QRD) MUD can be a substitute to ML detection due its low complexity and near optimal performance. The minimum mean-squared-error (MMSE) multiuser detection (MUD) minimises the mean square error (MSE), which may not give guarantee that the BER of the system is also minimum. But the minimum bit error rate (MBER) MUD performs better than the classic MMSE MUD in term of minimum probability of error by directly minimising the BER cost function. Also the MBER MUD is able to support more users than the number of receiving antennas, whereas the rest of MUDs fail in this scenario. In this paper the performance of various MUD techniques is verified for the correlated MIMO channel models based on IEEE 802.16n standard.

Keywords: Multiple input multiple output, multiuser detection, orthogonal frequency division multiplexing, space division multiple access, Bit error rate

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44 Thermo-Mechanical Characterization of MWCNTs-Modified Epoxy Resin

Authors: M. Dehghan, R. Al-Mahaidi, I. Sbarski

Abstract:

An industrial epoxy adhesive used in Carbon Fiber Reinforced Polymer (CFRP) strengthening systems was modified by dispersing multi-walled carbon nanotubes (MWCNTs). Nanocomposites were fabricated using the solvent-assisted dispersion method and ultrasonic mixing. Thermogravimetric analysis (TGA), dynamic mechanical analysis (DMA) and tensile tests were conducted to study the effect of nanotubes dispersion on the thermal and mechanical properties of the epoxy composite. Experimental results showed a substantial enhancement in the decomposition temperature and tensile properties of epoxy composite, while, the glass transition temperature (Tg) was slightly reduced due to the solvent effect. The morphology of the epoxy nanocomposites was investigated by SEM. It was proved that using solvent improves the nanotubes dispersion. However, at contents higher than 2 wt. %, nanotubes started to re-bundle in the epoxy matrix which negatively affected the final properties of epoxy composite.

Keywords: Carbon Fiber Reinforced Polymer, Epoxy, Multi-Walled Carbon Nanotube, Glass Transition Temperature.

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43 Dynamic Clustering Estimation of Tool Flank Wear in Turning Process using SVD Models of the Emitted Sound Signals

Authors: A. Samraj, S. Sayeed, J. E. Raja., J. Hossen, A. Rahman

Abstract:

Monitoring the tool flank wear without affecting the throughput is considered as the prudent method in production technology. The examination has to be done without affecting the machining process. In this paper we proposed a novel work that is used to determine tool flank wear by observing the sound signals emitted during the turning process. The work-piece material we used here is steel and aluminum and the cutting insert was carbide material. Two different cutting speeds were used in this work. The feed rate and the cutting depth were constant whereas the flank wear was a variable. The emitted sound signal of a fresh tool (0 mm flank wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely worn tool (0.4mm and above flank wear) during turning process were recorded separately using a high sensitive microphone. Analysis using Singular Value Decomposition was done on these sound signals to extract the feature sound components. Observation of the results showed that an increase in tool flank wear correlates with an increase in the values of SVD features produced out of the sound signals for both the materials. Hence it can be concluded that wear monitoring of tool flank during turning process using SVD features with the Fuzzy C means classification on the emitted sound signal is a potential and relatively simple method.

Keywords: Fuzzy c means, Microphone, Singular ValueDecomposition, Tool Flank Wear.

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42 Effect of Biomass Feedstocks on the Production of Hydrogenated Biodiesel

Authors: Panatcha Bovornseripatai, Siriporn Jongpatiwut, Somchai Osuwan, Suchada Butnark

Abstract:

Hydrogenated biodiesel is one of the most promising renewable fuels. It has many advantages over conventional biodiesel, including higher cetane number, higher heating value, lower viscosity, and lower corrosiveness due to its absence of oxygen. From previous work, Pd/TiO2 gave high conversion and selectivity in hydrogenated biodiesel. In this work, the effect of biomass feedstocks (i.e. beef fat, chicken fat, pork fat, and jatropha oil) on the production of hydrogenated biodiesel over Pd/TiO2 has been studied. Biomass feedstocks were analyzed by ICP-OES (inductively coupled plasma optical emission spectrometry) to identify the content of impurities (i.e. P, K, Ca, Na, and Mg). The deoxygenation catalyst, Pd/TiO2, was prepared by incipient wetness impregnation (IWI) and tested in a continuous flow packed-bed reactor at 500 psig, 325°C, H2/feed molar ratio of 30, and LHSV of 4 h-1 for its catalytic activity and selectivity in hydrodeoxygenation. All feedstocks gave high selectivity in diesel specification range hydrocarbons and the main hydrocarbons were n-pentadecane (n-C15) and n-heptadecane (n- C17), resulting from the decarbonylation/decarboxylation reaction. Intermediates such as oleic acid, stearic acid, palmitic acid, and esters were also detected in minor amount. The conversion of triglycerides in jatropha oil is higher than those of chicken fat, pork fat, and beef fat, respectively. The higher concentration of metal impurities in feedstock, the lower conversion of feedstock.

Keywords: Hydrogenated biodiesel, hydrodeoxygenation, Pd/TiO2, biomass feedstock

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41 Electric Field Impact on the Biomass Gasification and Combustion Dynamics

Authors: M. Zake, I. Barmina, A. Kolmickovs, R. Valdmanis

Abstract:

Experimental investigations of the DC electric field effect on thermal decomposition of biomass, formation of the axial flow of volatiles (CO, H2, CxHy), mixing of volatiles with swirling airflow at low swirl intensity (S ≈ 0.2-0.35), their ignition and on formation of combustion dynamics are carried out with the aim to understand the mechanism of electric field influence on biomass gasification, combustion of volatiles and heat energy production. The DC electric field effect on combustion dynamics was studied by varying the positive bias voltage of the central electrode from 0.6 kV to 3 kV, whereas the ion current was limited to 2 mA. The results of experimental investigations confirm the field-enhanced biomass gasification with enhanced release of volatiles and the development of endothermic processes at the primary stage of thermochemical conversion of biomass determining the field-enhanced heat energy consumption with the correlating decrease of the flame temperature and heat energy production at this stage of flame formation. Further, the field-enhanced radial expansion of the flame reaction zone correlates with a more complete combustion of volatiles increasing the combustion efficiency by 3% and decreasing the mass fraction of CO, H2 and CxHy in the products, whereas by 10% increases the average volume fraction of CO2 and the heat energy production downstream the combustor increases by 5-10% 

Keywords: Biomass, combustion, electrodynamic control, gasification.

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40 Continuous Feature Adaptation for Non-Native Speech Recognition

Authors: Y. Deng, X. Li, C. Kwan, B. Raj, R. Stern

Abstract:

The current speech interfaces in many military applications may be adequate for native speakers. However, the recognition rate drops quite a lot for non-native speakers (people with foreign accents). This is mainly because the nonnative speakers have large temporal and intra-phoneme variations when they pronounce the same words. This problem is also complicated by the presence of large environmental noise such as tank noise, helicopter noise, etc. In this paper, we proposed a novel continuous acoustic feature adaptation algorithm for on-line accent and environmental adaptation. Implemented by incremental singular value decomposition (SVD), the algorithm captures local acoustic variation and runs in real-time. This feature-based adaptation method is then integrated with conventional model-based maximum likelihood linear regression (MLLR) algorithm. Extensive experiments have been performed on the NATO non-native speech corpus with baseline acoustic model trained on native American English. The proposed feature-based adaptation algorithm improved the average recognition accuracy by 15%, while the MLLR model based adaptation achieved 11% improvement. The corresponding word error rate (WER) reduction was 25.8% and 2.73%, as compared to that without adaptation. The combined adaptation achieved overall recognition accuracy improvement of 29.5%, and WER reduction of 31.8%, as compared to that without adaptation.

Keywords: speaker adaptation; environment adaptation; robust speech recognition; SVD; non-native speech recognition

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39 Variation of Streamwise and Vertical Turbulence Intensity in a Smooth and Rough Bed Open Channel Flow

Authors: Md Abdullah Al Faruque, Ram Balachandar

Abstract:

An experimental study with four different types of bed conditions was carried out to understand the effect of roughness in open channel flow at two different Reynolds numbers. The bed conditions include a smooth surface and three different roughness conditions, which were generated using sand grains with a median diameter of 2.46 mm. The three rough conditions include a surface with distributed roughness, a surface with continuously distributed roughness and a sand bed with a permeable interface. A commercial two-component fibre-optic LDA system was used to conduct the velocity measurements. The variables of interest include the mean velocity, turbulence intensity, correlation between the streamwise and the wall normal turbulence, Reynolds shear stress and velocity triple products. Quadrant decomposition was used to extract the magnitude of the Reynolds shear stress of the turbulent bursting events. The effect of roughness was evident throughout the flow depth. The results show that distributed roughness has the greatest roughness effect followed by the sand bed and the continuous roughness. Compared to the smooth bed, the streamwise turbulence intensity reduces but the vertical turbulence intensity increases at a location very close to the bed due to the introduction of roughness. Although the same sand grain is used to create the three different rough bed conditions, the difference in the turbulence intensity is an indication that the specific geometry of the roughness has an influence on turbulence structure.

Keywords: Open channel flow, smooth bed, rough bed, Reynolds number, turbulence.

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38 Automatic Detection of Defects in Ornamental Limestone Using Wavelets

Authors: Maria C. Proença, Marco Aniceto, Pedro N. Santos, José C. Freitas

Abstract:

A methodology based on wavelets is proposed for the automatic location and delimitation of defects in limestone plates. Natural defects include dark colored spots, crystal zones trapped in the stone, areas of abnormal contrast colors, cracks or fracture lines, and fossil patterns. Although some of these may or may not be considered as defects according to the intended use of the plate, the goal is to pair each stone with a map of defects that can be overlaid on a computer display. These layers of defects constitute a database that will allow the preliminary selection of matching tiles of a particular variety, with specific dimensions, for a requirement of N square meters, to be done on a desktop computer rather than by a two-hour search in the storage park, with human operators manipulating stone plates as large as 3 m x 2 m, weighing about one ton. Accident risks and work times are reduced, with a consequent increase in productivity. The base for the algorithm is wavelet decomposition executed in two instances of the original image, to detect both hypotheses – dark and clear defects. The existence and/or size of these defects are the gauge to classify the quality grade of the stone products. The tuning of parameters that are possible in the framework of the wavelets corresponds to different levels of accuracy in the drawing of the contours and selection of the defects size, which allows for the use of the map of defects to cut a selected stone into tiles with minimum waste, according the dimension of defects allowed.

Keywords: Automatic detection, wavelets, defects, fracture lines.

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37 Locating Cultural Centers in Shiraz (Iran) Applying Geographic Information System (GIS)

Authors: R. Mokhtari Malekabadi, S. Ghaed Rahmati, S. Aram

Abstract:

Optimal cultural site selection is one of the ways that can lead to the promotion of citizenship culture in addition to ensuring the health and leisure of city residents. This study examines the social and cultural needs of the community and optimal cultural site allocation and after identifying the problems and shortcomings, provides a suitable model for finding the best location for these centers where there is the greatest impact on the promotion of citizenship culture. On the other hand, non-scientific methods cause irreversible impacts to the urban environment and citizens. But modern efficient methods can reduce these impacts. One of these methods is using geographical information systems (GIS). In this study, Analytical Hierarchy Process (AHP) method was used to locate the optimal cultural site. In AHP, three principles (decomposition), (comparative analysis), and (combining preferences) are used. The objectives of this research include providing optimal contexts for passing time and performing cultural activities by Shiraz residents and also proposing construction of some cultural sites in different areas of the city. The results of this study show the correct positioning of cultural sites based on social needs of citizens. Thus, considering the population parameters and radii access, GIS and AHP model for locating cultural centers can meet social needs of citizens.

Keywords: Analytical Hierarchy Process (AHP), geographical information systems (GIS), Cultural site, locating, Shiraz.

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36 Strategic Development for a Diverse Population in the Urban Core

Authors: Andreas L. Savvides

Abstract:

These This paper looks into frameworks which aim at furthering the discussion of the role of regenerative design practices in a city-s historic core and the tool of urban design to achieve urban revitalization on the island of Cyprus. It also examines the region-s demographic mix, the effectiveness of its governmental coordination and the strategies of adaptive reuse and strategic investments in older areas with existing infrastructure. The two main prongs of investigation will consider the effect of the existing and proposed changes in the physical infrastructure and fabric of the city, as well as the catalytic effect of sustainable urban design practices. Through this process, the work hopes to integrate the contained potential within the existing historic core and the contributions and participation of the migrant and immigrant populations to the local economy. It also examines ways in which this coupling of factors can bring to the front the positive effects of this combined effort on an otherwise sluggish local redevelopment effort. The data for this study is being collected and organized as part of ongoing urban design and development student workshop efforts in urban planning and design education. The work is presented in graphic form and includes data collected from interviews with study area organizations and the community at large. Planning work is also based on best practices initiated by the staff of the Nicosia Master Plan task force, which coordinates holistic planning efforts for the historic center of the city of Nicosia.

Keywords: Urban Design, Urban Development, Urban Regeneration, Historic Core, Cultural Planning.

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35 Microwave Assisted Solvent-Free Catalytic Transesterification of Glycerol to Glycerol Carbonate

Authors: Wai Keng Teng, Gek Cheng Ngoh, Rozita Yusoff, Mohamed Kheireddine Aroua, Joe Shen Heng

Abstract:

As a by-product of the biodiesel industries, glycerol has been vastly generated which surpasses the market demand. It is imperative to develop an efficient glycerol valorization processes in minimizing the net energy requirement and intensifying the biodiesel production. In this study, base-catalyzed transesterification of glycerol with dimethyl carbonate using microwave irradiation as heating method to produce glycerol carbonate was conducted by varying grades of glycerol, i.e. 70%, 86% and 99% purity, that is obtained from biodiesel plant. Metal oxide catalysts were used with varying operating parameters including reaction time, DMC/glycerol molar ratio, catalyst weight %, temperature and stirring speed. From the study on the effect of different operating parameters it was found that the type of catalyst used has the most significant effect on the transesterification reaction. Amidst the metal oxide catalysts examined, CaO gave the best performance. This study indicates the feasibility of producing glycerol carbonate using different grade of glycerol in both conventional thermal activation and microwave irradiation with CaO as catalyst. Microwave assisted transesterification (MAT) of glycerol into glycerol carbonate has demonstrated itself as an energy efficient route by achieving 94.2% yield of GC at 65°C, 5 minutes reaction time, 1 wt% CaO and DMC/glycerol molar ratio of 2. The advantages of MAT transesterification route has made the direct utilization of bioglycerol from biodiesel production without the need of purification. This has marked a more economical and less-energy intensive glycerol carbonate synthesis route.

Keywords: Biodiesel, glycerol, glycerol carbonate, microwave irradiation.

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34 Automatic Detection of Breast Tumors in Sonoelastographic Images Using DWT

Authors: A. Sindhuja, V. Sadasivam

Abstract:

Breast Cancer is the most common malignancy in women and the second leading cause of death for women all over the world. Earlier the detection of cancer, better the treatment. The diagnosis and treatment of the cancer rely on segmentation of Sonoelastographic images. Texture features has not considered for Sonoelastographic segmentation. Sonoelastographic images of 15 patients containing both benign and malignant tumorsare considered for experimentation.The images are enhanced to remove noise in order to improve contrast and emphasize tumor boundary. It is then decomposed into sub-bands using single level Daubechies wavelets varying from single co-efficient to six coefficients. The Grey Level Co-occurrence Matrix (GLCM), Local Binary Pattern (LBP) features are extracted and then selected by ranking it using Sequential Floating Forward Selection (SFFS) technique from each sub-band. The resultant images undergo K-Means clustering and then few post-processing steps to remove the false spots. The tumor boundary is detected from the segmented image. It is proposed that Local Binary Pattern (LBP) from the vertical coefficients of Daubechies wavelet with two coefficients is best suited for segmentation of Sonoelastographic breast images among the wavelet members using one to six coefficients for decomposition. The results are also quantified with the help of an expert radiologist. The proposed work can be used for further diagnostic process to decide if the segmented tumor is benign or malignant.

Keywords: Breast Cancer, Segmentation, Sonoelastography, Tumor Detection.

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33 Siding Mode Control of Pitch-Rate of an F-16 Aircraft

Authors: Ekprasit Promtun, Sridhar Seshagiri

Abstract:

This paper considers the control of the longitudinal flight dynamics of an F-16 aircraft. The primary design objective is model-following of the pitch rate q, which is the preferred system for aircraft approach and landing. Regulation of the aircraft velocity V (or the Mach-hold autopilot) is also considered, but as a secondary objective. The problem is challenging because the system is nonlinear, and also non-affine in the input. A sliding mode controller is designed for the pitch rate, that exploits the modal decomposition of the linearized dynamics into its short-period and phugoid approximations. The inherent robustness of the SMC design provides a convenient way to design controllers without gain scheduling, with a steady-state response that is comparable to that of a conventional polynomial based gain-scheduled approach with integral control, but with improved transient performance. Integral action is introduced in the sliding mode design using the recently developed technique of “conditional integrators", and it is shown that robust regulation is achieved with asymptotically constant exogenous signals, without degrading the transient response. Through extensive simulation on the nonlinear multiple-input multiple-output (MIMO) longitudinal model of the F-16 aircraft, it is shown that the conditional integrator design outperforms the one based on the conventional linear control, without requiring any scheduling.

Keywords: Sliding-mode Control, Integral Control, Model Following, F-16 Longitudinal Dynamics, Pitch-Rate Control.

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32 The Effects of TiO2 Nanoparticles on Tumor Cell Colonies: Fractal Dimension and Morphological Properties

Authors: T. Sungkaworn, W. Triampo, P. Nalakarn, D. Triampo, I. M. Tang, Y. Lenbury, P. Picha

Abstract:

Semiconductor nanomaterials like TiO2 nanoparticles (TiO2-NPs) approximately less than 100 nm in diameter have become a new generation of advanced materials due to their novel and interesting optical, dielectric, and photo-catalytic properties. With the increasing use of NPs in commerce, to date few studies have investigated the toxicological and environmental effects of NPs. Motivated by the importance of TiO2-NPs that may contribute to the cancer research field especially from the treatment prospective together with the fractal analysis technique, we have investigated the effect of TiO2-NPs on colony morphology in the dark condition using fractal dimension as a key morphological characterization parameter. The aim of this work is mainly to investigate the cytotoxic effects of TiO2-NPs in the dark on the growth of human cervical carcinoma (HeLa) cell colonies from morphological aspect. The in vitro studies were carried out together with the image processing technique and fractal analysis. It was found that, these colonies were abnormal in shape and size. Moreover, the size of the control colonies appeared to be larger than those of the treated group. The mean Df +/- SEM of the colonies in untreated cultures was 1.085±0.019, N= 25, while that of the cultures treated with TiO2-NPs was 1.287±0.045. It was found that the circularity of the control group (0.401±0.071) is higher than that of the treated group (0.103±0.042). The same tendency was found in the diameter parameters which are 1161.30±219.56 μm and 852.28±206.50 μm for the control and treated group respectively. Possible explanation of the results was discussed, though more works need to be done in terms of the for mechanism aspects. Finally, our results indicate that fractal dimension can serve as a useful feature, by itself or in conjunction with other shape features, in the classification of cancer colonies.

Keywords: Tumor growth, Cell colonies, TiO2, Nanoparticles, Fractal, Morphology, Aggregation.

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31 Ranking Genes from DNA Microarray Data of Cervical Cancer by a local Tree Comparison

Authors: Frank Emmert-Streib, Matthias Dehmer, Jing Liu, Max Muhlhauser

Abstract:

The major objective of this paper is to introduce a new method to select genes from DNA microarray data. As criterion to select genes we suggest to measure the local changes in the correlation graph of each gene and to select those genes whose local changes are largest. More precisely, we calculate the correlation networks from DNA microarray data of cervical cancer whereas each network represents a tissue of a certain tumor stage and each node in the network represents a gene. From these networks we extract one tree for each gene by a local decomposition of the correlation network. The interpretation of a tree is that it represents the n-nearest neighbor genes on the n-th level of a tree, measured by the Dijkstra distance, and, hence, gives the local embedding of a gene within the correlation network. For the obtained trees we measure the pairwise similarity between trees rooted by the same gene from normal to cancerous tissues. This evaluates the modification of the tree topology due to tumor progression. Finally, we rank the obtained similarity values from all tissue comparisons and select the top ranked genes. For these genes the local neighborhood in the correlation networks changes most between normal and cancerous tissues. As a result we find that the top ranked genes are candidates suspected to be involved in tumor growth. This indicates that our method captures essential information from the underlying DNA microarray data of cervical cancer.

Keywords: Graph similarity, generalized trees, graph alignment, DNA microarray data, cervical cancer.

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30 Recent Advances in Pulse Width Modulation Techniques and Multilevel Inverters

Authors: Satish Kumar Peddapelli

Abstract:

This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have became popular and considerable interest by researcher are given on them. A fast space-vector pulse width modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analyzed.

Keywords: Five-level inverter, Space vector pulse wide modulation, diode clamped inverter.

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29 Robust Integrated Design for a Mechatronic Feed Drive System of Machine Tools

Authors: Chin-Yin Chen, Chi-Cheng Cheng

Abstract:

This paper aims at to develop a robust optimization methodology for the mechatronic modules of machine tools by considering all important characteristics from all structural and control domains in one single process. The relationship between these two domains is strongly coupled. In order to reduce the disturbance caused by parameters in either one, the mechanical and controller design domains need to be integrated. Therefore, the concurrent integrated design method Design For Control (DFC), will be employed in this paper. In this connect, it is not only applied to achieve minimal power consumption but also enhance structural performance and system response at same time. To investigate the method for integrated optimization, a mechatronic feed drive system of the machine tools is used as a design platform. Pro/Engineer and AnSys are first used to build the 3D model to analyze and design structure parameters such as elastic deformation, nature frequency and component size, based on their effects and sensitivities to the structure. In addition, the robust controller,based on Quantitative Feedback Theory (QFT), will be applied to determine proper control parameters for the controller. Therefore, overall physical properties of the machine tool will be obtained in the initial stage. Finally, the technology of design for control will be carried out to modify the structural and control parameters to achieve overall system performance. Hence, the corresponding productivity is expected to be greatly improved.

Keywords: Machine tools, integrated structure and control design, design for control, multilevel decomposition, quantitative feedback theory.

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28 Optimized Brain Computer Interface System for Unspoken Speech Recognition: Role of Wernicke Area

Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

Abstract:

In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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