Search results for: solar cells.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 958

Search results for: solar cells.

88 FPGA Implementation of Generalized Maximal Ratio Combining Receiver Diversity

Authors: Rafic Ayoubi, Jean-Pierre Dubois, Rania Minkara

Abstract:

In this paper, we study FPGA implementation of a novel supra-optimal receiver diversity combining technique, generalized maximal ratio combining (GMRC), for wireless transmission over fading channels in SIMO systems. Prior published results using ML-detected GMRC diversity signal driven by BPSK showed superior bit error rate performance to the widely used MRC combining scheme in an imperfect channel estimation (ICE) environment. Under perfect channel estimation conditions, the performance of GMRC and MRC were identical. The main drawback of the GMRC study was that it was theoretical, thus successful FPGA implementation of it using pipeline techniques is needed as a wireless communication test-bed for practical real-life situations. Simulation results showed that the hardware implementation was efficient both in terms of speed and area. Since diversity combining is especially effective in small femto- and picocells, internet-associated wireless peripheral systems are to benefit most from GMRC. As a result, many spinoff applications can be made to the hardware of IP-based 4th generation networks.

Keywords: Femto-internet cells, field-programmable gate array, generalized maximal-ratio combining, Lyapunov fractal dimension, pipelining technique, wireless SIMO channels.

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87 Optimal Design of a PV/Diesel Hybrid System for Decentralized Areas through Economic Criteria

Authors: D. Tsuanyo, D. Aussel, Y. Azoumah, P. Neveu

Abstract:

An innovative concept called “Flexy-Energy” is developing at 2iE. This concept aims to produce electricity at lower cost by smartly mix different available energy sources in accordance to the load profile of the region. With a higher solar irradiation and due to the fact that Diesel generator are massively used in sub-Saharan rural areas, PV/Diesel hybrid systems could be a good application of this concept and a good solution to electrify this region, provided they are reliable, cost effective and economically attractive to investors. Presentation of the developed approach is the aims of this paper. The PV/Diesel hybrid system designed consists to produce electricity and/or heat from a coupling between Diesel Diesel generators and PV panels without batteries storage, while ensuring the substitution of gasoil by bio-fuels available in the area where the system will be installed. The optimal design of this system is based on his technical performances; the Life Cycle Cost (LCC) and Levelized Cost of Energy are developed and use as economic criteria. The Net Present Value (NPV), the internal rate of return (IRR) and the discounted payback (DPB) are also evaluated according to dual electricity pricing (in sunny and unsunny hours). The PV/Diesel hybrid system obtained is compared to the standalone Diesel Diesel generators. The approach carried out in this paper has been applied to Siby village in Mali (Latitude 12 ° 23'N 8 ° 20'W) with 295 kWh as daily demand.This approach provides optimal physical characteristics (size of the components, number of component) and dynamical characteristics in real time (number of Diesel generator on, their load rate, fuel specific consumptions, and PV penetration rate) of the system. The system obtained is slightly cost effective; but could be improved with optimized tariffing strategies.

Keywords: Investments criteria, Optimization, PV hybrid, Sizing, Rural electrification.

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86 Utilization of 3-N-trimethylamino-1-propanol by Rhodococcus sp. strain A4 isolated from Natural Soil

Authors: Isam A. Mohamed Ahmed, Jiro Arima, Tsuyoshi Ichiyanagi, Emi Sakuno, Nobuhiro Mori

Abstract:

The aim of this study was to screen for microorganism that able to utilize 3-N-trimethylamino-1-propanol (homocholine) as a sole source of carbon and nitrogen. The aerobic degradation of homocholine has been found by a gram-positive Rhodococcus sp. bacterium isolated from soil. The isolate was identified as Rhodococcus sp. strain A4 based on the phenotypic features, physiologic and biochemical characteristics, and phylogenetic analysis. The cells of the isolated strain grown on both basal-TMAP and nutrient agar medium displayed elementary branching mycelia fragmented into irregular rod and coccoid elements. Comparative 16S rDNA sequencing studies indicated that the strain A4 falls into the Rhodococcus erythropolis subclade and forms a monophyletic group with the type-strains of R. opacus, and R. wratislaviensis. Metabolites analysis by capillary electrophoresis, fast atom bombardment-mass spectrometry, and gas chromatography- mass spectrometry, showed trimethylamine (TMA) as the major metabolite beside β-alanine betaine and trimethylaminopropionaldehyde. Therefore, the possible degradation pathway of trimethylamino propanol in the isolated strain is through consequence oxidation of alcohol group (-OH) to aldehyde (-CHO) and acid (-COOH), and thereafter the cleavage of β-alanine betaine C-N bonds yielded trimethylamine and alkyl chain.

Keywords: Homocholine, 3-N-trimethylamino-1-propanol, Quaternary ammonium compounds, 16S rDNA gene sequence.

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85 Optimization of Proton Exchange Membrane Fuel Cell Parameters Based on Modified Particle Swarm Algorithms

Authors: M. Dezvarei, S. Morovati

Abstract:

In recent years, increasing usage of electrical energy provides a widespread field for investigating new methods to produce clean electricity with high reliability and cost management. Fuel cells are new clean generations to make electricity and thermal energy together with high performance and no environmental pollution. According to the expansion of fuel cell usage in different industrial networks, the identification and optimization of its parameters is really significant. This paper presents optimization of a proton exchange membrane fuel cell (PEMFC) parameters based on modified particle swarm optimization with real valued mutation (RVM) and clonal algorithms. Mathematical equations of this type of fuel cell are presented as the main model structure in the optimization process. Optimized parameters based on clonal and RVM algorithms are compared with the desired values in the presence and absence of measurement noise. This paper shows that these methods can improve the performance of traditional optimization methods. Simulation results are employed to analyze and compare the performance of these methodologies in order to optimize the proton exchange membrane fuel cell parameters.

Keywords: Clonal algorithm, proton exchange membrane fuel cell, particle swarm optimization, real valued mutation.

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84 Transformations of Spatial Distributions of Bio-Polymers and Nanoparticles in Water Suspensions Induced by Resonance-Like Low Frequency Electrical Fields

Authors: A. A. Vasin, N. V. Klassen, A. M. Likhter

Abstract:

Water suspensions of in-organic (metals and oxides) and organic nano-objects (chitozan and collagen) were subjected to the treatment of direct and alternative electrical fields. In addition to quasi-periodical spatial patterning resonance-like performance of spatial distributions of these suspensions has been found at low frequencies of alternating electrical field. These resonances are explained as the result of creation of equilibrium states of groups of charged nano-objects with opposite signs of charges at the interparticle distances where the forces of Coulomb attraction are compensated by the repulsion forces induced by relatively negative polarization of hydrated regions surrounding the nanoparticles with respect to pure water. The low frequencies of these resonances are explained by comparatively big distances between the particles and their big masses with t\respect to masses of atoms constituting molecules with high resonance frequencies. These new resonances open a new approach to detailed modeling and understanding of mechanisms of the influence of electrical fields on the functioning of internal organs of living organisms at the level of cells and neurons.

Keywords: Bio-polymers, chitosan, collagen, nanoparticles, coulomb attraction, polarization repulsion, periodical patterning, electrical low frequency resonances, transformations.

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83 Influence of Culture Conditions on the Growth and Fatty Acid Composition of Green Microalgae Oocystis rhomboideus, Scenedesmus obliquus, Dictyochlorella globosa

Authors: Tatyana A. Karpenyuk, Saltanat B. Orazova, Yana S. Tzurkan, Alla V. Goncharova, Bakytzhan K. Kairat, Togzhan D. Mukasheva, Ludmila V. Ignatova, Ramza Z. Berzhanova

Abstract:

Microalgae due to the ability to accumulate high levels of practically valuable polyunsaturated fatty acids attract attention as a promising raw material for commercial products. The features of the growth processes of cells green protococcal microalgae Oocystis rhomboideus, Scenedesmus obliquus, Dictyochlorella globosa at cultivation in different nutritional mediums were determined. For the rapid accumulation of biomass, combined with high productivity of total lipids fraction yield recommended to use the Fitzgerald medium (Scenodesmus obliquus, Oocystis rhomboideus) and/or Bold medium (Dictyochlorella globosa). Productivity of lipids decreased in sequence Dictyochlorella globosa > Scenodesmus obliquus > Oocystis rhomboideus. The bulk of fatty acids fraction of the total lipids is unsaturated fatty acids, which ac­counts for 70 to 83% of the total number of fatty acids. The share of monoenic acids accounts from 18 to 34%, while the share of unsaturated fatty acids - from 44 to 62% of the total number of unsaturated fatty acids fraction. Among the un­saturated acids dominate α-linolenic acid (C18:3n-3), hexadecatetraenic acid (C16:4) and linoleic acid (C18:2).

Keywords: Fatty acids, lipids, microalgae.

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82 Decision Tree Based Scheduling for Flexible Job Shops with Multiple Process Plans

Authors: H.-H. Doh, J.-M. Yu, Y.-J. Kwon, J.-H. Shin, H.-W. Kim, S.-H. Nam, D.-H. Lee

Abstract:

This paper suggests a decision tree based approach for flexible job shop scheduling with multiple process plans, i.e. each job can be processed through alternative operations, each of which can be processed on alternative machines. The main decision variables are: (a) selecting operation/machine pair; and (b) sequencing the jobs assigned to each machine. As an extension of the priority scheduling approach that selects the best priority rule combination after many simulation runs, this study suggests a decision tree based approach in which a decision tree is used to select a priority rule combination adequate for a specific system state and hence the burdens required for developing simulation models and carrying out simulation runs can be eliminated. The decision tree based scheduling approach consists of construction and scheduling modules. In the construction module, a decision tree is constructed using a four-stage algorithm, and in the scheduling module, a priority rule combination is selected using the decision tree. To show the performance of the decision tree based approach suggested in this study, a case study was done on a flexible job shop with reconfigurable manufacturing cells and a conventional job shop, and the results are reported by comparing it with individual priority rule combinations for the objectives of minimizing total flow time and total tardiness.

Keywords: Flexible job shop scheduling, Decision tree, Priority rules, Case study.

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81 On Combining Support Vector Machines and Fuzzy K-Means in Vision-based Precision Agriculture

Authors: A. Tellaeche, X. P. Burgos-Artizzu, G. Pajares, A. Ribeiro

Abstract:

One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.

Keywords: Fuzzy k-Means, Precision agriculture, SupportVectors Machines, Weed detection.

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80 Microbial Oil Production by Mixed Culture of Microalgae Chlorella sp. KKU-S2 and Yeast Torulaspora maleeae Y30

Authors: Ratanaporn Leesing, Rattanaporn Baojungharn, Thidarat Papone

Abstract:

Compared to oil production from microorganisms, little work has been performed for mixed culture of microalgae and yeast. In this article it is aimed to show high oil accumulation potential of mixed culture of microalgae Chlorella sp. KKU-S2 and oleaginous yeast Torulaspora maleeae Y30 using sugarcane molasses as substrate. The monoculture of T. maleeae Y30 grew faster than that of microalgae Chlorella sp. KKU-S2. In monoculture of yeast, a biomass of 6.4g/L with specific growth rate (m) of 0.265 (1/d) and lipid yield of 0.466g/L were obtained, while 2.53g/L of biomass with m of 0.133 (1/d) and lipid yield of 0.132g/L were obtained for monoculture of Chlorella sp. KKU-S2. The biomass concentration in the mixed culture of T. maleeae Y30 with Chlorella sp. KKU-S2 increased faster and was higher compared with that in the monoculture and mixed culture of microalgae. In mixed culture of microalgae Chlorella sp. KKU-S2 and C. vulgaris TISTR8580, a biomass of 3.47g/L and lipid yield of 0.123 g/L were obtained. In mixed culture of T. maleeae Y30 with Chlorella sp. KKU-S2, a maximum biomass of 7.33 g/L and lipid yield of 0.808g/L were obtained. Maximum cell yield coefficient (YX/S, 0.229g/L), specific yield of lipid (YP/X, 0.11g lipid/g cells) and volumetric lipid production rate (QP, 0.115 g/L/d) were obtained in mixed culture of yeast and microalgae. Clearly, T. maleeae Y30 and Chlorella sp. KKU-S2 use sugarcane molasses as organic nutrients efficiently in mixed culture under mixotrophic growth. The biomass productivity and lipid yield are notably enhanced in comparison with monoculture.

Keywords: Microbial oil, Chlorella sp. KKU-S2, Chlorella vulgaris, Torulaspora maleeae Y30, mixed culture, biodiesel.

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79 Biochemical and Multiplex PCR Analysis of Toxic Crystal Proteins to Determine Genes in Bacillus thuringiensis Mutants

Authors: Fatma N. Talkhan, H. H. Abo-Assy, K. A. Soliman, Marwa M. Azzam, A. Z. E. Abdelsalam, A. S. Abdel-Razek

Abstract:

The Egyptian Bacillus thuringiensis isolate (M5) produce crystal proteins that is toxic against insects was irradiated with UV light to induce mutants. Upon testing 10 of the resulting mutants for their toxicity against cotton leafworm larvae, the three mutants 62, 64 and 85 proved to be the most toxic ones. Upon testing these mutants along with their parental isolate by SDS-PAGE analysis of spores-crystals proteins as well as vegetative cells proteins, new induced bands appeared in the three mutants by UV radiation and also they showed disappearance of some other bands as compared with the wild type isolate. Multiplex PCR technique, with five sets of specific primers, was used to detect the three types of cryI genes cryIAa, cryIAb and cryIAc. Results showed that these three genes exist, as distinctive bands, in the wild type isolate (M5) as well as in mutants 62 and 85, while the mutant 64 had two distinctive bands of cryIAb and cryIAc genes, and a faint band of cryI Aa gene. Finally, these results revealed that mutant 62 is considered as the promising mutant since it is UV resistant, highly toxic against Spodoptera littoralis and active against a wide range of Lepidopteran insects.

Keywords: Bacillus thuringiensis, biological control, cry1 genes, multiplex PC, SDS- PAGE analysis.

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78 A Model to Study the Effect of Excess Buffers and Na+ Ions on Ca2+ Diffusion in Neuron Cell

Authors: Vikas Tewari, Shivendra Tewari, K. R. Pardasani

Abstract:

Calcium is a vital second messenger used in signal transduction. Calcium controls secretion, cell movement, muscular contraction, cell differentiation, ciliary beating and so on. Two theories have been used to simplify the system of reaction-diffusion equations of calcium into a single equation. One is excess buffer approximation (EBA) which assumes that mobile buffer is present in excess and cannot be saturated. The other is rapid buffer approximation (RBA), which assumes that calcium binding to buffer is rapid compared to calcium diffusion rate. In the present work, attempt has been made to develop a model for calcium diffusion under excess buffer approximation in neuron cells. This model incorporates the effect of [Na+] influx on [Ca2+] diffusion,variable calcium and sodium sources, sodium-calcium exchange protein, Sarcolemmal Calcium ATPase pump, sodium and calcium channels. The proposed mathematical model leads to a system of partial differential equations which have been solved numerically using Forward Time Centered Space (FTCS) approach. The numerical results have been used to study the relationships among different types of parameters such as buffer concentration, association rate, calcium permeability.

Keywords: Excess buffer approximation, Na+ influx, sodium calcium exchange protein, sarcolemmal calcium atpase pump, forward time centred space.

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77 Effect of Loop Diameter, Height and Insulation on a High Temperature CO2 Based Natural Circulation Loop

Authors: S. Sadhu, M. Ramgopal, S. Bhattacharyya

Abstract:

Natural circulation loops (NCLs) are buoyancy driven flow systems without any moving components. NCLs have vast applications in geothermal, solar and nuclear power industry where reliability and safety are of foremost concern. Due to certain favorable thermophysical properties, especially near supercritical regions, carbon dioxide can be considered as an ideal loop fluid in many applications. In the present work, a high temperature NCL that uses supercritical carbon dioxide as loop fluid is analysed. The effects of relevant design and operating variables on loop performance are studied. The system operating under steady state is modelled taking into account the axial conduction through loop fluid and loop wall, and heat transfer with surroundings. The heat source is considered to be a heater with controlled heat flux and heat sink is modelled as an end heat exchanger with water as the external cold fluid. The governing equations for mass, momentum and energy conservation are normalized and are solved numerically using finite volume method. Results are obtained for a loop pressure of 90 bar with the power input varying from 0.5 kW to 6.0 kW. The numerical results are validated against the experimental results reported in the literature in terms of the modified Grashof number (Grm) and Reynolds number (Re). Based on the results, buoyancy and friction dominated regions are identified for a given loop. Parametric analysis has been done to show the effect of loop diameter, loop height, ambient temperature and insulation. The results show that for the high temperature loop, heat loss to surroundings affects the loop performance significantly. Hence this conjugate heat transfer between the loop and surroundings has to be considered in the analysis of high temperature NCLs.

Keywords: Conjugate heat transfer, heat loss, natural circulation loop, supercritical carbon dioxide.

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76 Hybrid Weighted Multiple Attribute Decision Making Handover Method for Heterogeneous Networks

Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

Abstract:

Small cell deployment in 5G networks is a promising technology to enhance the capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision problem using Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), and propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting policy, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method show better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: Handover, HetNets, interference, MADM, small cells, TOPSIS, weight.

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75 Action Potential Propagation in Inhomogeneous 2D Mouse Ventricular Tissue Model

Authors: Mouse, cardiac myocytes, computer simulation, action potential.

Abstract:

Heterogeneous repolarization causes dispersion of the T-wave and has been linked to arrhythmogenesis. Such heterogeneities appear due to differential expression of ionic currents in different regions of the heart, both in healthy and diseased animals and humans. Mice are important animals for the study of heart diseases because of the ability to create transgenic animals. We used our previously reported model of mouse ventricular myocytes to develop 2D mouse ventricular tissue model consisting of 14,000 cells (apical or septal ventricular myocytes) and to study the stability of action potential propagation and Ca2+ dynamics. The 2D tissue model was implemented as a FORTRAN program code for highperformance multiprocessor computers that runs on 36 processors. Our tissue model is able to simulate heterogeneities not only in action potential repolarization, but also heterogeneities in intracellular Ca2+ transients. The multicellular model reproduced experimentally observed velocities of action potential propagation and demonstrated the importance of incorporation of realistic Ca2+ dynamics for action potential propagation. The simulations show that relatively sharp gradients of repolarization are predicted to exist in 2D mouse tissue models, and they are primarily determined by the cellular properties of ventricular myocytes. Abrupt local gradients of channel expression can cause alternans at longer pacing basic cycle lengths than gradual changes, and development of alternans depends on the site of stimulation.

Keywords: Mouse, cardiac myocytes, computer simulation, action potential

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74 Similitude for Thermal Scale-up of a Multiphase Thermolysis Reactor in the Cu-Cl Cycle of a Hydrogen Production

Authors: Mohammed W. Abdulrahman

Abstract:

The thermochemical copper-chlorine (Cu-Cl) cycle is considered as a sustainable and efficient technology for a hydrogen production, when linked with clean-energy systems such as nuclear reactors or solar thermal plants. In the Cu-Cl cycle, water is decomposed thermally into hydrogen and oxygen through a series of intermediate reactions. This paper investigates the thermal scale up analysis of the three phase oxygen production reactor in the Cu-Cl cycle, where the reaction is endothermic and the temperature is about 530 oC. The paper focuses on examining the size and number of oxygen reactors required to provide enough heat input for different rates of hydrogen production. The type of the multiphase reactor used in this paper is the continuous stirred tank reactor (CSTR) that is heated by a half pipe jacket. The thermal resistance of each section in the jacketed reactor system is studied to examine its effect on the heat balance of the reactor. It is found that the dominant contribution to the system thermal resistance is from the reactor wall. In the analysis, the Cu-Cl cycle is assumed to be driven by a nuclear reactor where two types of nuclear reactors are examined as the heat source to the oxygen reactor. These types are the CANDU Super Critical Water Reactor (CANDU-SCWR) and High Temperature Gas Reactor (HTGR). It is concluded that a better heat transfer rate has to be provided for CANDU-SCWR by 3-4 times than HTGR. The effect of the reactor aspect ratio is also examined in this paper and is found that increasing the aspect ratio decreases the number of reactors and the rate of decrease in the number of reactors decreases by increasing the aspect ratio. Finally, a comparison between the results of heat balance and existing results of mass balance is performed and is found that the size of the oxygen reactor is dominated by the heat balance rather than the material balance.

Keywords: Clean energy, Cu-Cl cycle, heat transfer, sustainable energy.

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73 An ACO Based Algorithm for Distribution Networks Including Dispersed Generations

Authors: B. Bahmani Firouzi, T. Niknam, M. Nayeripour

Abstract:

With Power system movement toward restructuring along with factors such as life environment pollution, problems of transmission expansion and with advancement in construction technology of small generation units, it is expected that small units like wind turbines, fuel cells, photovoltaic, ... that most of the time connect to the distribution networks play a very essential role in electric power industry. With increase in developing usage of small generation units, management of distribution networks should be reviewed. The target of this paper is to present a new method for optimal management of active and reactive power in distribution networks with regard to costs pertaining to various types of dispersed generations, capacitors and cost of electric energy achieved from network. In other words, in this method it-s endeavored to select optimal sources of active and reactive power generation and controlling equipments such as dispersed generations, capacitors, under load tapchanger transformers and substations in a way that firstly costs in relation to them are minimized and secondly technical and physical constraints are regarded. Because the optimal management of distribution networks is an optimization problem with continuous and discrete variables, the new evolutionary method based on Ant Colony Algorithm has been applied. The simulation results of the method tested on two cases containing 23 and 34 buses exist and will be shown at later sections.

Keywords: Distributed Generation, Optimal Operation Management of distribution networks, Ant Colony Optimization(ACO).

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72 Classification of Potential Biomarkers in Breast Cancer Using Artificial Intelligence Algorithms and Anthropometric Datasets

Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

Abstract:

Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: Breast cancer, health diagnosis, Machine Learning, biomarker classification, Neural Network.

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71 Selecting Negative Examples for Protein-Protein Interaction

Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

Abstract:

Proteomics is one of the largest areas of research for bioinformatics and medical science. An ambitious goal of proteomics is to elucidate the structure, interactions and functions of all proteins within cells and organisms. Predicting Protein-Protein Interaction (PPI) is one of the crucial and decisive problems in current research. Genomic data offer a great opportunity and at the same time a lot of challenges for the identification of these interactions. Many methods have already been proposed in this regard. In case of in-silico identification, most of the methods require both positive and negative examples of protein interaction and the perfection of these examples are very much crucial for the final prediction accuracy. Positive examples are relatively easy to obtain from well known databases. But the generation of negative examples is not a trivial task. Current PPI identification methods generate negative examples based on some assumptions, which are likely to affect their prediction accuracy. Hence, if more reliable negative examples are used, the PPI prediction methods may achieve even more accuracy. Focusing on this issue, a graph based negative example generation method is proposed, which is simple and more accurate than the existing approaches. An interaction graph of the protein sequences is created. The basic assumption is that the longer the shortest path between two protein-sequences in the interaction graph, the less is the possibility of their interaction. A well established PPI detection algorithm is employed with our negative examples and in most cases it increases the accuracy more than 10% in comparison with the negative pair selection method in that paper.

Keywords: Interaction graph, Negative training data, Protein-Protein interaction, Support vector machine.

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70 Finite Volume Method for Flow Prediction Using Unstructured Meshes

Authors: Juhee Lee, Yongjun Lee

Abstract:

In designing a low-energy-consuming buildings, the heat transfer through a large glass or wall becomes critical. Multiple layers of the window glasses and walls are employed for the high insulation. The gravity driven air flow between window glasses or wall layers is a natural heat convection phenomenon being a key of the heat transfer. For the first step of the natural heat transfer analysis, in this study the development and application of a finite volume method for the numerical computation of viscous incompressible flows is presented. It will become a part of the natural convection analysis with high-order scheme, multi-grid method, and dual-time step in the future. A finite volume method based on a fully-implicit second-order is used to discretize and solve the fluid flow on unstructured grids composed of arbitrary-shaped cells. The integrations of the governing equation are discretised in the finite volume manner using a collocated arrangement of variables. The convergence of the SIMPLE segregated algorithm for the solution of the coupled nonlinear algebraic equations is accelerated by using a sparse matrix solver such as BiCGSTAB. The method used in the present study is verified by applying it to some flows for which either the numerical solution is known or the solution can be obtained using another numerical technique available in the other researches. The accuracy of the method is assessed through the grid refinement.

Keywords: Finite volume method, fluid flow, laminar flow, unstructured grid.

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69 A Cross-Disciplinary Educational Model in Biomanufacturing to Sustain a Competitive Workforce Ecosystem

Authors: Rosa Buxeda, Lorenzo Saliceti-Piazza, Rodolfo J. Romañach, Luis Ríos, Sandra L. Maldonado-Ramírez

Abstract:

Biopharmaceuticals manufacturing is one of the major economic activities worldwide. Ninety-three percent of the workforce in a biomanufacturing environment concentrates in production-related areas. As a result, strategic collaborations between industry and academia are crucial to ensure the availability of knowledgeable workforce needed in an economic region to become competitive in biomanufacturing. In the past decade, our institution has been a key strategic partner with multinational biotechnology companies in supplying science and engineering graduates in the field of industrial biotechnology. Initiatives addressing all levels of the educational pipeline, from K-12 to college to continued education for company employees have been established along a ten-year span. The Amgen BioTalents Program was designed to provide undergraduate science and engineering students with training in biomanufacturing. The areas targeted by this educational program enhance their academic development, since these topics are not part of their traditional science and engineering curricula. The educational curriculum involved the process of producing a biomolecule from the genetic engineering of cells to the production of an especially targeted polypeptide, protein expression and purification, to quality control, and validation. This paper will report and describe the implementation details and outcomes of the first sessions of the program.

Keywords: Biomanufacturing curriculum, interdisciplinary learning, workforce development, industry-academia partnering.

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68 Computable Difference Matrix for Synonyms in the Holy Quran

Authors: Mohamed Ali AlShaari, Khalid M. ElFitori

Abstract:

In the field of Quran Studies known as GHAREEB AL QURAN (The study of the meanings of strange words and structures in Holy Quran), it is difficult to distinguish some pragmatic meanings from conceptual meanings. One who wants to study this subject may need to look for a common usage between any two words or more; to understand general meaning, and sometimes may need to look for common differences between them, even if there are synonyms (word sisters).

Some of the distinguished scholars of Arabic linguistics believe that there are no synonym words, they believe in varieties of meaning and multi-context usage. Based on this viewpoint, our method was designedto look for synonyms of a word, then the differences that distinct the word and their synonyms.

There are many available books that use such a method e.g. synonyms books, dictionaries, glossaries, and some books on the interpretations of strange vocabulary of the Holy Quran, but it is difficult to look up words in these written works.

For that reason, we proposed a logical entity, which we called Differences Matrix (DM).

DM groups the synonyms words to extract the relations between them and to know the general meaning, which defines the skeleton of all word synonyms; this meaning is expressed by a word of its sisters.

In Differences Matrix, we used  the sisters(words) as titles for rows and columns, and in the obtained  cells we tried to define the row title (word) by using column title (her sister), so the relations between sisters appear, the expected result is well defined groups of sisters for each word. We represented the obtained results formally, and used the defined groups as a base for building the ontology of the Holy Quran synonyms.

Keywords: Quran, synonyms, Differences Matrix, ontology

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67 A Novel VLSI Architecture for Image Compression Model Using Low power Discrete Cosine Transform

Authors: Vijaya Prakash.A.M, K.S.Gurumurthy

Abstract:

In Image processing the Image compression can improve the performance of the digital systems by reducing the cost and time in image storage and transmission without significant reduction of the Image quality. This paper describes hardware architecture of low complexity Discrete Cosine Transform (DCT) architecture for image compression[6]. In this DCT architecture, common computations are identified and shared to remove redundant computations in DCT matrix operation. Vector processing is a method used for implementation of DCT. This reduction in computational complexity of 2D DCT reduces power consumption. The 2D DCT is performed on 8x8 matrix using two 1-Dimensional Discrete cosine transform blocks and a transposition memory [7]. Inverse discrete cosine transform (IDCT) is performed to obtain the image matrix and reconstruct the original image. The proposed image compression algorithm is comprehended using MATLAB code. The VLSI design of the architecture is implemented Using Verilog HDL. The proposed hardware architecture for image compression employing DCT was synthesized using RTL complier and it was mapped using 180nm standard cells. . The Simulation is done using Modelsim. The simulation results from MATLAB and Verilog HDL are compared. Detailed analysis for power and area was done using RTL compiler from CADENCE. Power consumption of DCT core is reduced to 1.027mW with minimum area[1].

Keywords: Discrete Cosine Transform (DCT), Inverse DiscreteCosine Transform (IDCT), Joint Photographic Expert Group (JPEG), Low Power Design, Very Large Scale Integration (VLSI) .

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66 The Role of Chemerin and Myostatin after Physical Activity

Authors: M. J. Pourvaghar, M. E. Bahram

Abstract:

Obesity and overweight is one of the most common metabolic disorders in industrialized countries and in developing countries. One consequence of pathological obesity is cardiovascular disease and metabolic syndrome. Chemerin is an adipocyne that plays a role in the regulation of the adipocyte function and the metabolism of glucose in the liver and musculoskeletal system. Most likely, chemerin is involved in obesity-related disorders such as type 2 diabetes and cardiovascular disease. Aerobic exercises reduce the level of chemerin and cause macrophage penetration into fat cells and inflammatory factors. Several efforts have been made to clarify the cellular and molecular mechanisms of hypertrophy and muscular atrophy. Myostatin, a new member of the TGF-β family, is a transforming growth factor β that its expression negatively regulates the growth of the skeletal muscle; and the increase of this hormone has been observed in conditions of muscular atrophy. While in response to muscle overload, its levels decrease after the atrophy period, TGF-β is the most important cytokine in the development of skeletal muscle. Myostatin plays an important role in muscle control, and animal and human studies show a negative role of myostatin in the growth of skeletal muscle. Separation of myostatin from Golgi begins on the ninth day of the onset period and continues until birth at all times of muscle growth. Higher levels of myostatin are found in obese people. Resistance training for 10 weeks could reduce levels of plasma myostatin.

Keywords: Chemerin, myostatin, obesity, physical activity.

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65 Rapid Determination of Biochemical Oxygen Demand

Authors: Mayur Milan Kale, Indu Mehrotra

Abstract:

Biochemical Oxygen Demand (BOD) is a measure of the oxygen used in bacteria mediated oxidation of organic substances in water and wastewater. Theoretically an infinite time is required for complete biochemical oxidation of organic matter, but the measurement is made over 5-days at 20 0C or 3-days at 27 0C test period with or without dilution. Researchers have worked to further reduce the time of measurement. The objective of this paper is to review advancement made in BOD measurement primarily to minimize the time and negate the measurement difficulties. Survey of literature review in four such techniques namely BOD-BARTTM, Biosensors, Ferricyanidemediated approach, luminous bacterial immobilized chip method. Basic principle, method of determination, data validation and their advantage and disadvantages have been incorporated of each of the methods. In the BOD-BARTTM method the time lag is calculated for the system to change from oxidative to reductive state. BIOSENSORS are the biological sensing element with a transducer which produces a signal proportional to the analyte concentration. Microbial species has its metabolic deficiencies. Co-immobilization of bacteria using sol-gel biosensor increases the range of substrate. In ferricyanidemediated approach, ferricyanide has been used as e-acceptor instead of oxygen. In Luminous bacterial cells-immobilized chip method, bacterial bioluminescence which is caused by lux genes was observed. Physiological responses is measured and correlated to BOD due to reduction or emission. There is a scope to further probe into the rapid estimation of BOD.

Keywords: BOD, Four methods, Rapid estimation

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64 Oil Extraction from Microalgae Dunalliela sp. by Polar and Non-Polar Solvents

Authors: A. Zonouzi, M. Auli, M. Javanmard Dakheli, M. A. Hejazi

Abstract:

Microalgae are tiny photosynthetic plants. Nowadays, microalgae are being used as nutrient-dense foods and sources of fine chemicals. They have significant amounts of lipid, carotenoids, vitamins, protein, minerals, chlorophyll, and pigments. Oil extraction from algae is a hotly debated topic currently because introducing an efficient method could decrease the process cost. This can determine the sustainability of algae-based foods. Scientific research works show that solvent extraction using chloroform/methanol (2:1) mixture is one of the efficient methods for oil extraction from algal cells, but both methanol and chloroform are toxic solvents, and therefore, the extracted oil will not be suitable for food application. In this paper, the effect of two food grade solvents (hexane and hexane/ isopropanol) on oil extraction yield from microalgae Dunaliella sp. was investigated and the results were compared with chloroform/methanol (2:1) extraction yield. It was observed that the oil extraction yield using hexane, hexane/isopropanol (3:2) and chloroform/methanol (2:1) mixture were 5.4, 13.93, and 17.5 (% w/w, dry basis), respectively. The fatty acid profile derived from GC illustrated that the palmitic (36.62%), oleic (18.62%), and stearic acids (19.08%) form the main portion of fatty acid composition of microalgae Dunalliela sp. oil. It was concluded that, the addition of isopropanol as polar solvent could increase the extraction yield significantly. Isopropanol solves cell wall phospholipids and enhances the release of intercellular lipids, which improves accessing of hexane to fatty acids.

Keywords: Fatty acid profile, Microalgae, Oil extraction, Polar solvent.

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63 Design and Control of PEM Fuel Cell Diffused Aeration System using Artificial Intelligence Techniques

Authors: Doaa M. Atia, Faten H. Fahmy, Ninet M. Ahmed, Hassen T. Dorrah

Abstract:

Fuel cells have become one of the major areas of research in the academia and the industry. The goal of most fish farmers is to maximize production and profits while holding labor and management efforts to the minimum. Risk of fish kills, disease outbreaks, poor water quality in most pond culture operations, aeration offers the most immediate and practical solution to water quality problems encountered at higher stocking and feeding rates. Many units of aeration system are electrical units so using a continuous, high reliability, affordable, and environmentally friendly power sources is necessary. Aeration of water by using PEM fuel cell power is not only a new application of the renewable energy, but also, it provides an affordable method to promote biodiversity in stagnant ponds and lakes. This paper presents a new design and control of PEM fuel cell powered a diffused air aeration system for a shrimp farm in Mersa Matruh in Egypt. Also Artificial intelligence (AI) techniques control is used to control the fuel cell output power by control input gases flow rate. Moreover the mathematical modeling and simulation of PEM fuel cell is introduced. A comparison study is applied between the performance of fuzzy logic control (FLC) and neural network control (NNC). The results show the effectiveness of NNC over FLC.

Keywords: PEM fuel cell, Diffused aeration system, Artificialintelligence (AI) techniques, neural network control, fuzzy logiccontrol

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62 Microbial Oil Production by Monoculture and Mixed Cultures of Microalgae and Oleaginous Yeasts using Sugarcane Juice as Substrate

Authors: Thidarat Papone, Supaporn Kookkhunthod, Ratanaporn Leesing

Abstract:

Monoculture and mixed cultures of microalgae and the oleaginous yeast for microbial oil productions were investigated using sugarcane juice as carbon substrate. The monoculture of yeast Torulaspora maleeae Y30, Torulaspora globosa YU5/2 grew faster than that of microalgae Chlorella sp. KKU-S2. In monoculture of T. maleeae Y30, a biomass of 8.267g/L with lipid yield of 0.920g/L were obtained, while 8.333g/L of biomass with lipid yield of 1.141g/L were obtained for monoculture of T. globosa YU5/2. A biomass of 1.933g/L with lipid yield of 0.052g/L was found for monoculture of Chlorella sp. KKU-S2. The biomass concentration in the mixed culture of the oleaginous yeast with microalgae increased faster and was higher compared with that in the monocultures. A biomass of 8.733g/L with lipid yield of 1.564g/L was obtained for a mixed culture of T. maleeae Y30 with Chlorella sp. KKU-S2, while 8.010g/L of biomass with lipid yield of 2.424g/L was found for mixed culture of T. globosa YU5/2 with Chlorella sp. KKU-S2. Maximum cell yield coefficient (YX/S, g/L) was found of 0.323 in monoculture of Chlorella sp. KKU-S2 but low level of both specific yield of lipid (YP/X, g lipid/g cells) of 0.027 and volumetric lipid production rate (QP, g/L/d) of 0.003 were observed. While, maximum YP/X (0.303), QP (0.105) and maximum process product yield (YP/S, 0.061) were obtained in mixed culture of T. globosa YU5/2 with Chlorella sp. KKU-S2. The results obtained from the study shows that mixed culture of yeast with microalgae is a desirable cultivation process for microbial oil production.

Keywords: Microbial oil, Chlorella sp. KKU-S2, Torulaspora maleeae Y30, Torulaspora globosa YU5/2, mixed culture, biodiesel.

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61 Nutrient Modelling to Fabricate Dairy Milk Constituents: Let Milk Serve More Than a Food Item

Authors: M.Aasif Shahzad, N.Mukhtar, M.Sarwar

Abstract:

Dietary macro and micro nutrients in their respective proportion and fractions present a practical potential tool to fabricate milk constituents since cells of lactating mammary glands obtain about 80 % of milk synthesis nutrients from blood, reflecting the existence of an isotonic equilibrium between blood and milk. Diverting milk biosynthetic activities through manipulation of nutrients towards producing milk not only keeping in view its significance as natural food but also as food item which prevents or dilutes the adverse effects of some diseases (like cardiovascular problem by saturated milk fat intake) has been area of interest in the last decade. Nutritional modification / supplementation has been reported to enhance conjugated linoleic acid, fatty acid type and concentration, essential fatty acid concentration, vitamin B12& C, Se, Cu, I and Fe which are involved to counter the health threats to human well being. Synchronizing dietary nutrients aimed to modify rumen dynamics towards synthesis of nutrients or their precursors to make their drive towards formulated milk constituents presents a practical option. Formulating dietary constituents to design milk constituents will let the farmers, consumers and investors know about the real potential and profit margins associated with this enterprise. This article briefly recapitulates the ways and means to modify milk constituents keeping an eye on human health and well being issues, which allows milk to serve more than a food item.

Keywords: Nutritional modification, fabricating milk composition, human health.

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60 Evaluation of Stent Performances using FEA considering a Realistic Balloon Expansion

Authors: Won-Pil Park, Seung-Kwan Cho, Jai-Young Ko, Anders Kristensson, S.T.S. Al-Hassani, Han-Sung Kim, Dohyung Lim

Abstract:

A number of previous studies were rarely considered the effects of transient non-uniform balloon expansion on evaluation of the properties and behaviors of stents during stent expansion, nor did they determine parameters to maximize the performances driven by mechanical characteristics. Therefore, in order to fully understand the mechanical characteristics and behaviors of stent, it is necessary to consider a realistic modeling of transient non-uniform balloon-stent expansion. The aim of the study is to propose design parameters capable of improving the ability of vascular stent through a comparative study of seven commercial stents using finite element analyses of a realistic transient non-uniform balloon-stent expansion process. In this study, seven representative commercialized stents were evaluated by finite element (FE) analysis in terms of the criteria based on the itemized list of Food and Drug Administration (FDA) and European Standards (prEN). The results indicate that using stents composed of opened unit cells connected by bend-shaped link structures and controlling the geometrical and morphological features of the unit cell strut or the link structure at the distal ends of stent may improve mechanical characteristics of stent. This study provides a better method at the realistic transient non-uniform balloon-stent expansion by investigating the characteristics, behaviors, and parameters capable of improving the ability of vascular stent.

Keywords: Finite Element Analysis, Mechanical Characteristic, Transient Non-uniform Balloon-Stent Expansion, Vascular Stent.

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59 Characterisation of Wind-Driven Ventilation in Complex Terrain Conditions

Authors: Daniel Micallef, Damien Bounaudet, Robert N. Farrugia, Simon P. Borg, Vincent Buhagiar, Tonio Sant

Abstract:

The physical effects of upstream flow obstructions such as vegetation on cross-ventilation phenomena of a building are important for issues such as indoor thermal comfort. Modelling such effects in Computational Fluid Dynamics simulations may also be challenging. The aim of this work is to establish the cross-ventilation jet behaviour in such complex terrain conditions as well as to provide guidelines on the implementation of CFD numerical simulations in order to model complex terrain features such as vegetation in an efficient manner. The methodology consists of onsite measurements on a test cell coupled with numerical simulations. It was found that the cross-ventilation flow is highly turbulent despite the very low velocities encountered internally within the test cells. While no direct measurement of the jet direction was made, the measurements indicate that flow tends to be reversed from the leeward to the windward side. Modelling such a phenomenon proves challenging and is strongly influenced by how vegetation is modelled. A solid vegetation tends to predict better the direction and magnitude of the flow than a porous vegetation approach. A simplified terrain model was also shown to provide good comparisons with observation. The findings have important implications on the study of cross-ventilation in complex terrain conditions since the flow direction does not remain trivial, as with the traditional isolated building case.

Keywords: Complex terrain, cross-ventilation, wind driven ventilation, Computational Fluid Dynamics (CFD), wind resource.

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