Search results for: living and learning conditions
3581 Multi-Enterprise Tie and Co-Operation Mechanism in Mexican Agro Industry SME's
Authors: Tania Elena González Alvarado, Ma. Antonieta Martín Granados
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The aim of this paper is to explain what a multienterprise tie is, what evidence its analysis provides and how does the cooperation mechanism influence the establishment of a multienterprise tie. The study focuses on businesses of smaller dimension, geographically dispersed and whose businessmen are learning to cooperate in an international environment. The empirical evidence obtained at this moment permits to conclude the following: The tie is not long-lasting, it has an end; opportunism is an opportunity to learn; the multi-enterprise tie is a space to learn about the cooperation mechanism; the local tie permits a businessman to alternate between competition and cooperation strategies; the disappearance of a tie is an experience of learning for a businessman, diminishing the possibility of failure in the next tie; the cooperation mechanism tends to eliminate hierarchical relations; the multienterprise tie diminishes the asymmetries and permits SME-s to have a better position when they negotiate with large companies; the multi-enterprise tie impacts positively on the local system. The collection of empirical evidence was done trough the following instruments: direct observation in a business encounter to which the businesses attended in 2003 (202 Mexican agro industry SME-s), a survey applied in 2004 (129), a questionnaire applied in 2005 (86 businesses), field visits to the businesses during the period 2006-2008 and; a survey applied by telephone in 2008 (55 Mexican agro industry SME-s).
Keywords: Cooperation, multi-enterprise tie, links, networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12793580 System Identification with General Dynamic Neural Networks and Network Pruning
Authors: Christian Endisch, Christoph Hackl, Dierk Schröder
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This paper presents an exact pruning algorithm with adaptive pruning interval for general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The structure of the plant is unknown, so the identification process is started with a larger network architecture than necessary. During parameter optimization with the Levenberg- Marquardt (LM) algorithm irrelevant weights of the dynamic neural network are deleted in order to find a model for the plant as simple as possible. The weights to be pruned are found by direct evaluation of the training data within a sliding time window. The influence of pruning on the identification system depends on the network architecture at pruning time and the selected weight to be deleted. As the architecture of the model is changed drastically during the identification and pruning process, it is suggested to adapt the pruning interval online. Two system identification examples show the architecture selection ability of the proposed pruning approach.Keywords: System identification, dynamic neural network, recurrentneural network, GDNN, optimization, Levenberg Marquardt, realtime recurrent learning, network pruning, quasi-online learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19413579 2D Spherical Spaces for Face Relighting under Harsh Illumination
Authors: Amr Almaddah, Sadi Vural, Yasushi Mae, Kenichi Ohara, Tatsuo Arai
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In this paper, we propose a robust face relighting technique by using spherical space properties. The proposed method is done for reducing the illumination effects on face recognition. Given a single 2D face image, we relight the face object by extracting the nine spherical harmonic bases and the face spherical illumination coefficients. First, an internal training illumination database is generated by computing face albedo and face normal from 2D images under different lighting conditions. Based on the generated database, we analyze the target face pixels and compare them with the training bootstrap by using pre-generated tiles. In this work, practical real time processing speed and small image size were considered when designing the framework. In contrast to other works, our technique requires no 3D face models for the training process and takes a single 2D image as an input. Experimental results on publicly available databases show that the proposed technique works well under severe lighting conditions with significant improvements on the face recognition rates.Keywords: Face synthesis and recognition, Face illumination recovery, 2D spherical spaces, Vision for graphics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17613578 Features of Soil Formation in the North of Western Siberia in Cryogenic Conditions
Authors: Tatiana V. Raudina, Sergey P. Kulizhskiy
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A large part of Russia is located in permafrost areas. These areas are widely used because there are concentrated valuable natural resources. Therefore to explore of cryosols it is important due to the significant increase of anthropogenic stress as well as the problem of global climate change. In the north of Western Siberia permafrost phenomena is widespread. Permafrost as a factor of soil formation and cryogenesis as a process have a great impact on the soil formation of these areas. Based on the research results of permafrost-affected soils tundra landscapes formed in the central part of the Tazovskiy Peninsula in cryogenic conditions, data were obtained which characterize the morphological features of soils. The specificity of soil cover distribution and manifestation of soil-forming processes within the study area are noted. Permafrost features such as frost cracking, cryoturbation, thixotropy, movement of humus are formed. The formation of these features is increased with the development of the territory. As a consequence, there is a change in the components of the environment and the destruction of the soil cover.
Keywords: Gleyed and nongleyed soils, permafrost, soil cryogenesis (pedocryogenesis), soil-forming macroprocesses.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20653577 Numerical Analysis of Plate Heat Exchanger Performance in Co-Current Fluid Flow Configuration
Authors: H. Dardour, S. Mazouz, A. Bellagi
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For many industrial applications plate heat exchangers are demonstrating a large superiority over the other types of heat exchangers. The efficiency of such a device depends on numerous factors the effect of which needs to be analysed and accurately evaluated. In this paper we present a theoretical analysis of a cocurrent plate heat exchanger and the results of its numerical simulation. Knowing the hot and the cold fluid streams inlet temperatures, the respective heat capacities mCp and the value of the overall heat transfer coefficient, a 1-D mathematical model based on the steady flow energy balance for a differential length of the device is developed resulting in a set of N first order differential equations with boundary conditions where N is the number of channels.For specific heat exchanger geometry and operational parameters, the problem is numerically solved using the shooting method. The simulation allows the prediction of the temperature map in the heat exchanger and hence, the evaluation of its performances. A parametric analysis is performed to evaluate the influence of the R-parameter on the e-NTU values. For practical purposes effectiveness-NTU graphs are elaborated for specific heat exchanger geometry and different operating conditions.Keywords: Plate heat exchanger, thermal performance, NTU, effectiveness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 96573576 Probiotic Potential and Antimicrobial Activity of Enterococcus faecium Isolated from Chicken Caecal and Fecal Samples
Authors: Salma H. Abu Hafsa, A. Mendonca, B. Brehm-Stecher, A. A. Hassan, S. A. Ibrahim
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Enterococci are important inhabitants of the animal intestine and are widely used in probiotic products. A probiotic strain is expected to possess several desirable properties in order to exert beneficial effects. Therefore, the objective of this study was to isolate, characterize and identify Enterococcus sp. from chicken cecal and fecal samples to determine potential probiotic properties. Enterococci were isolated from chicken ceca and feces of thirty three clinically healthy chickens from a local farm. In vitro studies were performed to assess antibacterial activity of the isolated LAB (using agar well diffusion and cell free supernatant broth technique against Salmonella enterica serotype Enteritidis), survival in acidic conditions, resistance to bile salts, and their survival during simulated gastric juice conditions at pH 2.5. Isolates were identified by biochemical carbohydrate fermentation patterns using an API 50 CHL kit and API ZYM kits and by sequenced 16S rDNA. An isolate belonging to E. faecium species exhibited inhibitory effect against S. enteritidis. This isolate producing a clear zone as large as 10.30 mm or greater and was able to grow in the coculture medium and at the same time, inhibited the growth S. enteritidis. In addition, E. faecium exhibited significant resistance under highly acidic conditions at pH 2.5 for 8 h and survived well in bile salt at 0.2% for 24 h and showing ability to survive in the presence of simulated gastric juice at pH 2.5. Based on these results, E. faecium isolate fulfills some of the criteria to be considered as a probiotic strain and therefore, could be used as a feed additive with good potential for controlling S. Enteritidis in chickens. However, in vivo studies are needed to determine the safety of the strain.
Keywords: Acid tolerance, antimicrobial activity, Enterococcus faecium, probiotic.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28953575 Effects of Gamification on Lower Secondary School Students’ Motivation and Engagement
Authors: Goh Yung Hong, Mona Masood
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This paper explores the effects of gamification on lower secondary school students’ motivation and engagement in the classroom. Two-group posttest-only experimental design were employed to study the influence of gamification teaching method (GTM) when compared with conventional teaching method (CTM) on 60 lower secondary school students. The Student Engagement Instrument (SEI) and Intrinsic Motivation Inventory (IMI) were used to assess students’ intrinsic motivation and engagement level towards the respective teaching method. Finding indicates that students who completed the GTM lesson were significantly higher in intrinsic motivation to learn than those from the CTM. Although the result were insignificant and only marginal difference in the engagement mean, GTM still show better potential in raising student’s engagement in class when compared with CTM. This finding proves that the GTM is likely to solve the current issue of low motivation to learn and low engagement in class among lower secondary school students in Malaysia. On the other hand, despite being not significant, higher mean indicates that CTM positively contribute to higher peer support for learning and better teacher and student relationship when compared with GTM. As a conclusion, gamification approach is flexible and can be adapted into many learning content to enhance the intrinsic motivation to learn and to some extent, encourage better student engagement in class.
Keywords: Conventional teaching method, Gamification teaching method, Motivation, Engagement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 58263574 Physiological and Performance Effects of Glycerol Hyperhydration for World Championship Distance Duathlons in Hot Conditions
Authors: John McCullagh, Jaclyn Munge, NivanWeerakkody, Kerrie Gamble
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The aim of this study was to evaluate the effect of preexercise glycerol hyperhydration on endurance performance in a heat chamber designed to simulate the World Championship Distance (WCD) duathlon (10km run, 40km ride, 5 km run). Duathlons are often performed in hot and humid conditions and as a result hydration is a major issue. Glycerol enhances the body’s capacity for fluid retention by inducing hyperhydration, which is theorized to improve thermoregulatory and cardiovascular responses, and thereby improve performance. Six well-trained athletes completed the testing protocol in a heat chamber at the La Trobe University Exercise Physiology Laboratory. Each testing session was approximately 4.5 hours in duration (2 hours of pre-exercise glycerol hyper-hydration followed by approximately 2.5 hours of exercise). The results showed an increased water retention pre-exercise and an improved overall performance of 2.04% was achieved by subjects ingesting the glycerol solution.
Keywords: Endurance performance, glycerol hyperhydration, heat chamber.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23853573 Periodic Control of a Wastewater Treatment Process to Improve Productivity
Authors: Muhammad Rizwan Azhar, Emadadeen Ali
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In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.
Keywords: Dilution rate, nonlinear model predictive control, sinusoidal function, wastewater treatment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22133572 Preparing Data for Calibration of Mechanistic-Empirical Pavement Design Guide in Central Saudi Arabia
Authors: Abdulraaof H. Alqaili, Hamad A. Alsoliman
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Through progress in pavement design developments, a pavement design method was developed, which is titled the Mechanistic Empirical Pavement Design Guide (MEPDG). Nowadays, the evolution in roads network and highways is observed in Saudi Arabia as a result of increasing in traffic volume. Therefore, the MEPDG currently is implemented for flexible pavement design by the Saudi Ministry of Transportation. Implementation of MEPDG for local pavement design requires the calibration of distress models under the local conditions (traffic, climate, and materials). This paper aims to prepare data for calibration of MEPDG in Central Saudi Arabia. Thus, the first goal is data collection for the design of flexible pavement from the local conditions of the Riyadh region. Since, the modifying of collected data to input data is needed; the main goal of this paper is the analysis of collected data. The data analysis in this paper includes processing each: Trucks Classification, Traffic Growth Factor, Annual Average Daily Truck Traffic (AADTT), Monthly Adjustment Factors (MAFi), Vehicle Class Distribution (VCD), Truck Hourly Distribution Factors, Axle Load Distribution Factors (ALDF), Number of axle types (single, tandem, and tridem) per truck class, cloud cover percent, and road sections selected for the local calibration. Detailed descriptions of input parameters are explained in this paper, which leads to providing of an approach for successful implementation of MEPDG. Local calibration of MEPDG to the conditions of Riyadh region can be performed based on the findings in this paper.
Keywords: Mechanistic-empirical pavement design guide, traffic characteristics, materials properties, climate, Riyadh.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12313571 Removal of a Reactive Dye by Adsorption Utilizing Waste Aluminium Hydroxide Sludge as an Adsorbent
Authors: R. Songur, E. Bayraktar, U. Mehmetoglu
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Removal of a reactive dye (Reactive blue 4) by adsorption utilizing waste aluminium hydroxide sludge as an adsorbent was investigated. The removal of the dye was optimized using response surface methodology (RSM). In the RSM experiments; initial dye concentration, adsorbent concentration and contact time were critical parameters. RSM experiments were performed at the range of initial dye concentration 31.82-368.18 mg/L, adsorbent concentration 3.18-36.82 g/L, contact time 15.82- 56.18 h. Optimum initial dye concentration, adsorbent concentration and contact time were obtained as 108.83 mg/L, 29.36 g/L and 33.57 h respectively. At these conditions, maximum removal of the dye was obtained as 95%. The experiments were performed at the optimum conditions to verify these results and the same results were obtained.Keywords: Adsorption, Reactive blue 4, Response surface methodology (RSM), Waste aluminium hydroxide sludge
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19873570 Calibrations and Effect of Different Operating Conditions on the Performance of a Fluid Power Control System with Servo Solenoid Valve
Authors: Tahany W. Sadak, Fouly, A. Anwer, M. Rizk
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The current investigation presents a study on the hydraulic performance of an electro-hydraulic servo solenoid valve controlled linear piston used in hydraulic systems. Advanced methods have been used to measure and record laboratory experiments, to ensure accurate analysis and evaluation. Experiments have been conducted under different values of temperature (28, 40 and 50 °C), supply pressure (10, 20, 30, 40 and 50 bar), system stiffness (32 N/mm), and load (0.0 & 5560 N). It is concluded that increasing temperature of hydraulic oil increases the quantity of flow rate, so it achieves an increase of the quantity of flow by 5.75 % up to 48.8 % depending on operating conditions. The values of pressure decay at low temperature are less than the values at high temperature. The frequency increases with the increase of the temperature. When we connect the springs to the system, it decreases system frequency. These results are very useful in the process of packing and manufacturing of fluid products, where the properties are not affected by 50 °C, so energy and time are saved.
Keywords: Electro Hydraulic Servo Valve, fluid power control system, system stiffness, static and dynamic performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6893569 A Study of the Variables in the Optimisation of a Platinum Precipitation Process
Authors: Tebogo Phetla, Edison Muzenda, M Belaid
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This study investigated possible ways to improve the efficiency of the platinum precipitation process using ammonium chloride by reducing the platinum content reporting to the effluent. The ore treated consist of five platinum group metals namely, ruthenium, rhodium, iridium, platinum, palladium and a precious metal gold. Gold, ruthenium, rhodium and iridium were extracted prior the platinum precipitation process. Temperature, reducing agent, flow rate and potential difference were the variables controlled to determine the operation conditions for optimum platinum precipitation efficiency. Hydrogen peroxide was added as the oxidizing agent at the temperature of 85-90oC and potential difference of 700-850mV was the variable used to check the oxidizing state of platinum. The platinum was further purified at temperature between 60-65oC, potential difference above 700 mV, ammonium chloride of 200 l, and at these conditions the platinum content reporting to the effluent was reduced to less than 300ppm, resulting in optimum platinum precipitation efficiency and purity of 99.9%.Keywords: Platinum Group Metals (PGM), Potential difference, Precipitation, Redox reactions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 47943568 Ensemble Learning with Decision Tree for Remote Sensing Classification
Authors: Mahesh Pal
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In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.Keywords: Ensemble learning, decision tree, remote sensingclassification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25933567 The Residual Effects of Different Doses of Atrazine+Alachlor and Foramsulfuron on the Growth and Physiology of Rapeseed (Brassica napus L.)
Authors: S. Peyvastegan, A. Farahbakhsh
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A pot experiment was carried out under controlled conditions to evaluate the residual effects of different doses of atrazine+alachlor and foramsulfuron used in corn fields on the growth and physiology of rapeseed (Brassica napus L.). A split-plot experiment in CRD with 4 replications was used. The main plots consisted of herbicide type (atrazine+alachlor mixture and foramsulfuron) and the sub-plots were different residual doses of the herbicides (0, 1%, 5%, 10%, 20%, 40%, 50% and 100%). 7 cm diameter pots were filled with a virgin soil and seeds of rapeseed cv. Hayola were planted in them. The pots were kept under controlled conditions for 8 weeks after germination. At harvest, the growth parameters and the chlorophyll contents of the leaves were determined. The results showed that the growth of rapeseed plants was completely prevented at the highest residual doses of the herbicides (50 and 100 %). The growth parameters of rapeseed plants were affected by all doses of both types of the herbicide as compared to the controls. The residual effects of atrazine+alachlor mixture in reducing the growth parameters of rapeseed were more pronounced as compared to the residual effects of foramsulfuron alone.Keywords: Atrazine+alachlor, foramsulfuron, rapeseed, residual
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21283566 A Study of Geographic Information System Combining with GPS and 3G for Parking Guidance and Information System
Authors: Yu-Chi Shiue, Jyong Lin, Shih-Chang Chen
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With the increase of economic behavior and the upgrade of living standar, the ratio for people in Taiwan who own automobiles and motorcycles have recently increased with multiples. Therefore, parking issues will be a big challenge to facilitate traffic network and ensure urban life quality. The Parking Guidance and Information System is one of important systems for Advanced Traveler Information Services (ATIS). This research proposes a parking guidance and information system which integrates GPS and 3G network for a map on the Geographic Information System to solution inadequate of roadside information kanban. The system proposed in this study mainly includes Parking Host, Parking Guidance and Information Server, Geographic Map and Information System as well as Parking Guidance and Information Browser. The study results show this system can increase driver-s efficiency to find parking space and efficiently enhance parking convenience in comparison with roadside kanban system.Keywords: Geographic Information System, 3G, GPS, parkinginformation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18203565 Recent Advances in the Valorization of Goat Milk: Nutritional Properties and Production Sustainability
Authors: A. M. Tarola, R. Preti, A. M. Girelli, P. Campana
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Goat dairy products are gaining popularity worldwide. In developing countries, but also in many marginal regions of the Mediterranean area, goats represent a great part of the economy and ensure food security. In fact, these small ruminants are able to convert efficiently poor weedy plants and small trees into traditional products of high nutritional quality, showing great resilience to different climatic and environmental conditions. In developed countries, goat milk is appreciated for the presence of health-promoting compounds, bioactive compounds such as conjugated linoleic acids, oligosaccharides, sphingolipids and polyammines. This paper focuses on the recent advances in literature on the nutritional properties of goat milk and on innovative techniques to improve its quality as to become a promising functional food. The environmental sustainability of different methodologies of production has also been examined. Goat milk is valued today as a food of high nutritional value and functional properties as well as small environmental footprint. It is widely consumed in many countries due to high nutritional value, lower allergenic potential, and better digestibility when compared to bovine milk, that makes this product suitable for infants, elderly or sensitive patients. The main differences in chemical composition between a cow and goat milk rely on fat globules that in goat milk are smaller and in fatty acids that present a smaller chain length, while protein, fat, and lactose concentration are comparable. Milk nutritional properties have demonstrated to be strongly influenced by animal diet, genotype, and welfare, but also by season and production systems. Furthermore, there is a growing interest in the dairy industry in goat milk for its relatively high concentration of prebiotics and a good amount of probiotics, which have recently gained importance for their therapeutic potential. Therefore, goat milk is studied as a promising matrix to develop innovative functional foods. In addition to the economic and nutritional value, goat milk is considered a sustainable product for its small environmental footprint, as they require relatively little water and land, and less medical treatments, compared to cow, these characteristics make its production naturally vocated to organic farming. Organic goat milk production has becoming more and more interesting both for farmers and consumers as it can answer to several concerns like environment protection, animal welfare and economical sustainment of rural populations living in marginal lands. These evidences make goat milk an ancient food with novel properties and advantages to be valorized and exploited.
Keywords: Goat milk, nutritional quality, bioactive compounds, sustainable production.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11313564 Clamped-clamped Boundary Conditions for Analysis Free Vibration of Functionally Graded Cylindrical Shell with a Ring based on Third Order Shear Deformation Theory
Authors: M.Pourmahmoud, M.Salmanzadeh, M.Mehrani, M.R.Isvandzibaei
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In this paper a study on the vibration of thin cylindrical shells with ring supports and made of functionally graded materials (FGMs) composed of stainless steel and nickel is presented. Material properties vary along the thickness direction of the shell according to volume fraction power law. The cylindrical shells have ring supports which are arbitrarily placed along the shell and impose zero lateral deflections. The study is carried out based on third order shear deformation shell theory (T.S.D.T). The analysis is carried out using Hamilton-s principle. The governing equations of motion of FGM cylindrical shells are derived based on shear deformation theory. Results are presented on the frequency characteristics, influence of ring support position and the influence of boundary conditions. The present analysis is validated by comparing results with those available in the literature.Keywords: Vibration, FGM, Cylindrical shell, Hamilton'sprinciple, Ring support.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16173563 Influence of the Flow Rate Ratio in a Jet Pump on the Size of Air Bubbles
Authors: L. Grinis, N. Lubashevsky, Y. Ostrovski
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In wastewater treatment processes, aeration introduces air into a liquid. In these systems, air is introduced by different devices submerged in the wastewater. Smaller bubbles result in more bubble surface area per unit of volume and higher oxygen transfer efficiency. Jet pumps are devices that use air bubbles and are widely used in wastewater treatment processes. The principle of jet pumps is their ability to transfer energy of one fluid, called primary or motive, into a secondary fluid or gas. These pumps have no moving parts and are able to work in remote areas under extreme conditions. The objective of this work is to study experimentally the characteristics of the jet pump and the size of air bubbles in the laboratory water tank. The effect of flow rate ratio on pump performance is investigated in order to have a better understanding about pump behavior under various conditions, in order to determine the efficiency of receiving air bubbles different sizes. The experiments show that we should take care when increasing the flow rate ratio while seeking to decrease bubble size in the outlet flow. This study will help improve and extend the use of the jet pump in many practical applications.Keywords: Jet pump, air bubbles size, retention time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29933562 Modelling the Photovoltaic Pump Output Using Empirical Data from Local Conditions in the Vhembe District
Authors: C. Matasane, C. Dwarika, R. Naidoo
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The mathematical analysis on radiation obtained and the development of the solar photovoltaic (PV) array groundwater pumping is needed in the rural areas of Thohoyandou for sizing and power performance subject to the climate conditions within the area. A simple methodology approach is developed for the directed coupled solar, controller and submersible ground water pump system. The system consists of a PV array, pump controller and submerged pump, battery backup and charger controller. For this reason, the theoretical solar radiation is obtained for optimal predictions and system performance in order to achieve different design and operating parameters. Here the examination of the PV schematic module in a Direct Current (DC) application is used for obtainable maximum solar power energy for water pumping. In this paper, a simple efficient photovoltaic water pumping system is presented with its theoretical studies and mathematical modeling of photovoltaics (PV) system.
Keywords: Renewable energy sources, solar groundwater pumping, theoretical and mathematical analysis of photovoltaic (PV) system, theoretical solar radiation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25273561 Influence of Tool Geometry on Surface Roughness and Tool Wear When Turning AISI 304L Using Taguchi Optimisation Methodology
Authors: Salah Gariani, Taher Dao, Ahmed Lajili
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This paper presents an experimental optimisation of surface roughness (Ra) and tool wear in the precision turning of AISI 304L alloy using a wiper and conventional cutting tools under wet cutting conditions. The machining trials were conducted based on Taguchi methodology employing an L9 orthogonal array design with four process parameters: feed rate, spindle speed, depth of cut, and cutting tool type. The experimental results were utilised to characterise the main factors affecting Ra and tool wear using the analyses of means (AOM) and variance (ANOVA). The results show that the wiper tools outperformed conventional tools in terms of surface quality and tool wear at optimal cutting conditions. The ANOVA results indicate that the main factors contributing to lower Ra are cutting tool type and feed rate, with percentage contribution ratios (PCRs) of 58.69% and 25.18% respectively. This confirms that tool type is the most significant factor affecting surface quality when turning AISI 304L. Additionally, a substantial reduction in tool wear was observed when a wiper insert was used, whereas noticeable increases in tool wear occurred when higher cutting speeds were employed for both tool types. These trends confirm the ANOVA outcomes that cutting speed has a significant effect on tool wear, with a PCR value of 39.22%, followed by tool type with a PCR of 27.40%. All machining trials generated similar continuous spiral or curl-shaped chips. A noticeable difference was found in the radius of the produced curl-shaped chips at different cutting speeds when turning AISI 304L under wet cutting conditions.
Keywords: AISI 304L alloy, conventional and wiper carbide tools, wet turning, average surface roughness, tool wear.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1643560 Intensification of Ethyl Esters Synthesis Using a Packed-Bed Tubular Reactor at Supercritical Conditions
Authors: Camila da Silva, Simone Belorte de Andrade, Vitor Augusto dos Santos Garcia, Vladimir Ferreira Cabral, J. Vladimir Oliveira Lúcio Cardozo-Filho
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In the present study, the non-catalytic transesterification of soybean oil in continuous mode using supercritical ethanol were investigated. Experiments were performed in a packed-bed tubular reactor (PBTR) and variable studied were reaction temperature (523 K to 598 K), pressure (10 MPa to 20 MPa), oil to ethanol molar ratio (1:10 to 1:40) and water concentration (0 wt% to 10 wt% in ethanol). Results showed that ethyl esters yields obtained in the PBTR were higher (> 20 wt%) than those verified in a tubular reactor (TR), due to improved mass transfer conditions attained in the PBTR. Results demonstrated that temperature, pressure, oil to ethanol molar ratio and water concentration had a positive effect on fatty acid ethyl esters (FAEE) production in the experimental range investigated, with appreciable reaction yields (90 wt%) achieved at 598 K, 20 MPa, oil to ethanol molar ratio of 1:40 and 10 wt% of water concentration.
Keywords: Packed bed reactor, ethyl esters, continuous process, catalyst-free process.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12993559 Micropropagation and in vitro Conservation via Slow Growth Techniques of Prunus webbii (Spach) Vierh: An Endangered Plant Species in Albania
Authors: Valbona Sota, Efigjeni Kongjika
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Wild almond is a woody species, which is difficult to propagate either generatively by seed or by vegetative methods (grafting or cuttings) and also considered as Endangered (EN) in Albania based on IUCN criteria. As a wild relative of cultivated fruit trees, this species represents a source of genetic variability and can be very important in breeding programs and cultivation. For this reason, it would be of interest to use an effective method of in vitro mid-term conservation, which involves strategies to slow plant growth through physicochemical alterations of in vitro growth conditions. Multiplication of wild almond was carried out using zygotic embryos, as primary explants, with the purpose to develop a successful propagation protocol. Results showed that zygotic embryos can proliferate through direct or indirect organogenesis. During subculture, stage was obtained a great number of new plantlets identical to mother plants derived from the zygotic embryos. All in vitro plantlets obtained from subcultures underwent in vitro conservation by minimal growth in low temperature (4ºC) and darkness. The efficiency of this technique was evaluated for 3, 6, and 10 months of conservation period. Maintenance in these conditions reduced micro cuttings growth. Survival and regeneration rates for each period were evaluated and resulted that the maximal time of conservation without subculture on 4ºC was 10 months, but survival and regeneration rates were significantly reduced, specifically 15.6% and 7.6%. An optimal period of conservation in these conditions can be considered the 5-6 months storage, which can lead to 60-50% of survival and regeneration rates. This protocol may be beneficial for mass propagation, mid-term conservation, and for genetic manipulation of wild almond.
Keywords: Micropropagation, minimal growth, storage, wild almond.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8013558 An Anomaly Detection Approach to Detect Unexpected Faults in Recordings from Test Drives
Authors: Andreas Theissler, Ian Dear
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In the automotive industry test drives are being conducted during the development of new vehicle models or as a part of quality assurance of series-production vehicles. The communication on the in-vehicle network, data from external sensors, or internal data from the electronic control units is recorded by automotive data loggers during the test drives. The recordings are used for fault analysis. Since the resulting data volume is tremendous, manually analysing each recording in great detail is not feasible. This paper proposes to use machine learning to support domainexperts by preventing them from contemplating irrelevant data and rather pointing them to the relevant parts in the recordings. The underlying idea is to learn the normal behaviour from available recordings, i.e. a training set, and then to autonomously detect unexpected deviations and report them as anomalies. The one-class support vector machine “support vector data description” is utilised to calculate distances of feature vectors. SVDDSUBSEQ is proposed as a novel approach, allowing to classify subsequences in multivariate time series data. The approach allows to detect unexpected faults without modelling effort as is shown with experimental results on recordings from test drives.
Keywords: Anomaly detection, fault detection, test drive analysis, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24803557 Study on Nitrite Accumulation Characteristics and Nitrifying Population Dynamics at Different Growth Environments
Authors: Yunxia Zhang, Jiti Zhou, Jianbo Guo, Xiuhong Zhang, Lihong Zhao, Shouzhi Yuan
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Novel nitrogen removal technologies via nitrite pathway attract increasing interest in recent years. In this study, batch experiments were performed to investigate nitrite accumulation characteristics and shifts in nitrifying community structure at different growth environments including ammonia concentration, pH and alkalinity. It was found that nitrite accumulation ratios were maintained at around 95% at studied conditions, and the optimum pH and Alk/N (ratio between alkalinity and nitrogen) for ammonium oxidization were 8.5 and 8.33, respectively. Fluorescence in situ hybridization analysis of nitrifying bacteria showed that high free ammonia (from influent ammonium or caused by high pH) significantly altered the structure of nitrifying community, leading to abundance of ammonia-oxidizing bacteria (AOB), especially Nitrososmonas, and inhibition of nitrite-oxidizing bacteria (NOB). The results suggest that free ammonia plays more important role than other studied conditions on nitrite accumulation.Keywords: Partial nitrification, Nitrite accumulation, Nitrifyingbacteria, Fluorescence in situ hybridization (FISH).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20393556 Dimensionality Reduction in Modal Analysis for Structural Health Monitoring
Authors: Elia Favarelli, Enrico Testi, Andrea Giorgetti
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Autonomous structural health monitoring (SHM) of many structures and bridges became a topic of paramount importance for maintenance purposes and safety reasons. This paper proposes a set of machine learning (ML) tools to perform automatic feature selection and detection of anomalies in a bridge from vibrational data and compare different feature extraction schemes to increase the accuracy and reduce the amount of data collected. As a case study, the Z-24 bridge is considered because of the extensive database of accelerometric data in both standard and damaged conditions. The proposed framework starts from the first four fundamental frequencies extracted through operational modal analysis (OMA) and clustering, followed by time-domain filtering (tracking). The fundamental frequencies extracted are then fed to a dimensionality reduction block implemented through two different approaches: feature selection (intelligent multiplexer) that tries to estimate the most reliable frequencies based on the evaluation of some statistical features (i.e., entropy, variance, kurtosis), and feature extraction (auto-associative neural network (ANN)) that combine the fundamental frequencies to extract new damage sensitive features in a low dimensional feature space. Finally, one-class classification (OCC) algorithms perform anomaly detection, trained with standard condition points, and tested with normal and anomaly ones. In particular, principal component analysis (PCA), kernel principal component analysis (KPCA), and autoassociative neural network (ANN) are presented and their performance are compared. It is also shown that, by evaluating the correct features, the anomaly can be detected with accuracy and an F1 score greater than 95%.
Keywords: Anomaly detection, dimensionality reduction, frequencies selection, modal analysis, neural network, structural health monitoring, vibration measurement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7153555 Complex-Valued Neural Network in Signal Processing: A Study on the Effectiveness of Complex Valued Generalized Mean Neuron Model
Authors: Anupama Pande, Ashok Kumar Thakur, Swapnoneel Roy
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A complex valued neural network is a neural network which consists of complex valued input and/or weights and/or thresholds and/or activation functions. Complex-valued neural networks have been widening the scope of applications not only in electronics and informatics, but also in social systems. One of the most important applications of the complex valued neural network is in signal processing. In Neural networks, generalized mean neuron model (GMN) is often discussed and studied. The GMN includes a new aggregation function based on the concept of generalized mean of all the inputs to the neuron. This paper aims to present exhaustive results of using Generalized Mean Neuron model in a complex-valued neural network model that uses the back-propagation algorithm (called -Complex-BP-) for learning. Our experiments results demonstrate the effectiveness of a Generalized Mean Neuron Model in a complex plane for signal processing over a real valued neural network. We have studied and stated various observations like effect of learning rates, ranges of the initial weights randomly selected, error functions used and number of iterations for the convergence of error required on a Generalized Mean neural network model. Some inherent properties of this complex back propagation algorithm are also studied and discussed.Keywords: Complex valued neural network, Generalized Meanneuron model, Signal processing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17353554 Statistical Optimization of Adsorption of a Harmful Dye from Aqueous Solution
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Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.
Keywords: Acid Orange 10, Activated carbon, Optimum conditions, Statistical design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13583553 MIMO-OFDM Channel Tracking Using a Dynamic ANN Topology
Authors: Manasjyoti Bhuyan, Kandarpa Kumar Sarma
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All the available algorithms for blind estimation namely constant modulus algorithm (CMA), Decision-Directed Algorithm (DDA/DFE) suffer from the problem of convergence to local minima. Also, if the channel drifts considerably, any DDA looses track of the channel. So, their usage is limited in varying channel conditions. The primary limitation in such cases is the requirement of certain overhead bits in the transmit framework which leads to wasteful use of the bandwidth. Also such arrangements fail to use channel state information (CSI) which is an important aid in improving the quality of reception. In this work, the main objective is to reduce the overhead imposed by the pilot symbols, which in effect reduces the system throughput. Also we formulate an arrangement based on certain dynamic Artificial Neural Network (ANN) topologies which not only contributes towards the lowering of the overhead but also facilitates the use of the CSI. A 2×2 Multiple Input Multiple Output (MIMO) system is simulated and the performance variation with different channel estimation schemes are evaluated. A new semi blind approach based on dynamic ANN is proposed for channel tracking in varying channel conditions and the performance is compared with perfectly known CSI and least square (LS) based estimation.
Keywords: MIMO, Artificial Neural Network (ANN), CMA, LS, CSI.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23763552 Properties of Biodiesel Produced by Enzymatic Transesterification of Lipids Extracted from Microalgae in Supercritical Carbon Dioxide Medium
Authors: Hanifa Taher, Sulaiman Al-Zuhair, Ali H. Al-Marzouqi, Yousef Haik, Mohammed Farid
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Biodiesel, as an alternative renewable fuel, has been receiving increasing attention due to the limited supply of fossil fuels and the increasing need for energy. Microalgae are promising source for lipids, which can be converted to biodiesel. The biodiesel production from microalgae lipids using lipase catalyzed reaction in supercritical CO2 medium has several advantages over conventional production processes. However, identifying the optimum microalgae lipid extraction and transesterification conditions is still a challenge. In this study, the quality of biodiesel produced from lipids extracted from Scenedesmus sp. and their enzymatic transesterification using supercritical carbon dioxide have been investigated. At the optimum conditions, the highest biodiesel production yield was found to be 82%. The fuel properties of the produced biodiesel, without any separation step, at optimum reaction condition, were determined and compared to ASTM standards. The properties were found to comply with the limits, and showed a low glycerol content, without any separation step.Keywords: Biodiesel, fuel standards, lipase, microalgae, Supercritical CO2.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2514