Search results for: flame propagation

Authors: K. Mohammed, M. Agarwal, J. Mewman, Y. Ren

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An optimum technic has been developed for extracting volatile organic compounds which contribute to the aroma of lime fruit (Citrus aurantifolia). The volatile organic compounds of healthy and infested lime fruit with California red scale Aonidiella aurantii were characterized using headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled flame ionization detection (FID) and gas chromatography with mass spectrometry (GC-MS) as a very simple, efficient and nondestructive extraction method. A three-phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing and fibre exposure time for volatiles reaching equilibrium from whole lime fruit in the headspace of the chamber was 16 and 4 hours respectively. 5 min was selected as desorption time of the three-phase fibre. Herbivorous activity induces indirect plant defenses, as the emission of herbivorous-induced plant volatiles (HIPVs), which could be used by natural enemies for host location. GC-MS analysis showed qualitative differences among volatiles emitted by infested and healthy lime fruit. The GC-MS analysis allowed the initial identification of 18 compounds, with similarities higher than 85%, in accordance with the NIST mass spectral library. One of these were increased by A. aurantii infestation, D-limonene, and three were decreased, Undecane, α-Farnesene and 7-epi-α-selinene. From an applied point of view, the application of the above-mentioned VOCs may help boost the efficiency of biocontrol programs and natural enemies’ production techniques.

Keywords: lime fruit, Citrus aurantifolia, California red scale, Aonidiella aurantii, VOCs, HS-SPME/GC-FID-MS

Procedia PDF Downloads 212

Authors: Souhir Ben Amor, Heni Boubaker, Lotfi Belkacem

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This aims of this paper is to forecast the electricity spot prices. First, we focus on modeling the conditional mean of the series so we adopt a generalized fractional -factor Gegenbauer process (k-factor GARMA). Secondly, the residual from the -factor GARMA model has used as a proxy for the conditional variance; these residuals were predicted using two different approaches. In the first approach, a local linear wavelet neural network model (LLWNN) has developed to predict the conditional variance using the Back Propagation learning algorithms. In the second approach, the Gegenbauer generalized autoregressive conditional heteroscedasticity process (G-GARCH) has adopted, and the parameters of the k-factor GARMA-G-GARCH model has estimated using the wavelet methodology based on the discrete wavelet packet transform (DWPT) approach. The empirical results have shown that the k-factor GARMA-G-GARCH model outperform the hybrid k-factor GARMA-LLWNN model, and find it is more appropriate for forecasts.

Keywords: electricity price, k-factor GARMA, LLWNN, G-GARCH, forecasting

Procedia PDF Downloads 231

Authors: Mohsin Ali Shaikh, Song Weiguo, Muhammad Kashan Surahio, Usman Shahid, Rehmat Karim

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This study investigated a catastrophic arson fire incident that occurred at a textile garment building in Karachi, Pakistan. Unfortunately, a catastrophic event led to the loss of 262 lives and caused 55 severe injuries. The primary objective is to analyze the aspects of the fire incident and understand the causes of arson fire disasters. The study utilized Fire Dynamic Simulation (F.D.S) was employed to simulate fire propagation, visibility, harmful gas concentration, fire temperature, and numerical results. The analysis report has determined the specific circumstances that created the unpleasant incident in the present study. The significance of the current findings lies in their potential to prevent arson fires, improve fire safety measures, and the development of safety plans in building design. The fire dynamic simulation findings can serve as a theoretical basis for the investigation of arson fires and evacuation planning in textile garment buildings.

Keywords: investigation, fire arson incident, textile garment, fire dynamic simulation (FDS)

Procedia PDF Downloads 90

Authors: M. Chaichanyut, S. Tungjitkusolmun

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This paper is concerned with microwave (MW) ablation for a liver cancer tissue by using helix antenna. The antenna structure supports the propagation of microwave energy at 2.45 GHz. A 1½ turn spiral catheter-based microwave antenna applicator has been developed. We utilize the three-dimensional finite element method (3D FEM) simulation to analyze where the tissue heat flux, lesion pattern and volume destruction during MW ablation. The configurations of helix antenna where Helix air-core antenna and Helix Dielectric-core antenna. The 3D FEMs solutions were based on Maxwell and bio-heat equations. The simulation protocol was power control (10 W, 300s). Our simulation result, both helix antennas have heat flux occurred around the helix antenna and that can be induced the temperature distribution similar (teardrop). The region where the temperature exceeds 50°C the microwave ablation was successful (i.e. complete destruction). The Helix air-core antenna and Helix Dielectric-core antenna, ablation zone or axial ratios (Widest/length) were respectively 0.82 and 0.85; the complete destructions were respectively 4.18 cm³ and 5.64 cm³.

Keywords: liver cancer, Helix antenna, finite element, microwave ablation

Procedia PDF Downloads 309

Authors: Ali Raza, Shafiq Ur Rehman Khan, Raja Sher Afgun Usmani, Asif Raza, Basit Umair

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Detection of Fake news and missing information is gaining popularity, especially after the advancement in social media and online news platforms. Social media platforms are the main and speediest source of fake news propagation, whereas online news websites contribute to fake news dissipation. In this study, we propose a framework to detect fake news using the temporal features of text and consider user feedback to identify whether the news is fake or not. In recent studies, the temporal features in text documents gain valuable consideration from Natural Language Processing and user feedback and only try to classify the textual data as fake or true. This research article indicates the impact of recurring and non-recurring events on fake and true news. We use two models BERT and Bi-LSTM to investigate, and it is concluded from BERT we get better results and 70% of true news are recurring and rest of 30% are non-recurring.

Keywords: natural language processing, fake news detection, machine learning, Bi-LSTM

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Authors: Sharad Shrivastava, Arun Jalan

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In this study tensile testing was performed on randomly oriented short glass fiber/epoxy resin composite specimens which were prepared using hand lay-up method. Samples were tested over a wide range of strain rate/loading rate from 2mm/min to 40mm/min to see the effect on ultimate tensile strength of the composite. A multi layered 'back propagation artificial neural network of supervised learning type' was used to analyze and predict the tensile properties with strain rate and temperature as given input and output as UTS to predict. Various network structures were designed and investigated with varying parameters and network sizes, and an optimized network structure was proposed to predict the UTS of short glass fiber/epoxy resin composite specimens with reasonably good accuracy.

Keywords: glass fiber composite, mechanical properties, strain rate, artificial neural network

Procedia PDF Downloads 437

Authors: Ashkan Zakaryazad, Ekrem Duman

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A typical classification technique ranks the instances in a data set according to the likelihood of belonging to one (positive) class. A credit card (CC) fraud detection model ranks the transactions in terms of probability of being fraud. In fact, this approach is often criticized, because firms do not care about fraud probability but about the profitability or costliness of detecting a fraudulent transaction. The key contribution in this study is to focus on the profit maximization in the model building step. The artificial neural network proposed in this study works based on profit maximization instead of minimizing the error of prediction. Moreover, some studies have shown that the back propagation algorithm, similar to other gradient–based algorithms, usually gets trapped in local optima and swarm-based algorithms are more successful in this respect. In this study, we train our profit maximization ANN using the Migrating Birds optimization (MBO) which is introduced to literature recently.

Keywords: neural network, profit-based neural network, sum of squared errors (SSE), MBO, gradient descent

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Authors: A. L. Qureshi, A. A. Mahessar, A. Baloch

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Flood wave propagation in river channel flow can be enunciated by nonlinear equations of motion for unsteady flow. However, it is difficult to find analytical solution of these complex non-linear equations. Hence, verification of the numerical model should be carried out against field data and numerical predictions. This paper presents the verification of developed finite element model applying for unsteady flow in the open channels. The results of a proposed model indicate a good matching with both Preissmann scheme and HEC-RAS model for a river reach of 29 km at both sites (15 km from upstream and at downstream end) for discharge hydrographs. It also has an agreeable comparison with the Preissemann scheme for the flow depth (stage) hydrographs. The proposed model has also been applying to forecast daily discharges at 400 km downstream from Sukkur barrage, which demonstrates accurate model predictions with observed daily discharges. Hence, this model may be utilized for predicting and issuing flood warnings about flood hazardous in advance.

Keywords: finite element method, Preissmann scheme, HEC-RAS, flood forecasting, Indus river

Procedia PDF Downloads 503

Authors: A. E. Mukhametov, M. T. Yerbulekova, D. R. Dautkanova, G. A. Tuyakova, G. Aitkhozhayeva

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The accumulation of heavy metals in food is a constant problem in many parts of the world. Vegetable oils are widely used, both for cooking and for processing in the food industry, meeting the main dietary requirements. One of the main chemical pollutants, heavy metals, is usually found in vegetable oils. These chemical pollutants are carcinogenic, teratogenic and immunotoxic, harmful to consumption and have a negative effect on human health even in trace amounts. Residues of these substances can easily accumulate in vegetable oil during cultivation, processing and storage. In this article, the content of the concentration of heavy metal ions in vegetable oils of Kazakhstan production is studied: sunflower, rapeseed, safflower and linseed oil. Heavy metals: arsenic, cadmium, lead and nickel, were determined in three repetitions by the method of flame atomic absorption. Analysis of vegetable oil samples revealed that the largest lead contamination (Pb) was determined to be 0.065 mg/kg in linseed oil. The content of cadmium (Cd) in the largest amount of 0.009 mg/kg was found in safflower oil. Arsenic (As) content was determined in rapeseed and safflower oils at 0.003 mg/kg, and arsenic (As) was not detected in linseed and sunflower oil. The nickel (Ni) content in the largest amount of 0.433 mg/kg was in linseed oil. The heavy metal contents in the test samples complied with the requirements of regulatory documents for vegetable oils. An assessment of the health risk of vegetable oils with a daily consumption of 36 g per day shows that all samples of vegetable oils produced in Kazakhstan are safe for consumption. But further monitoring is needed, since all these metals are toxic and their harmful effects become apparent only after several years of exposure.

Keywords: vegetable oil, sunflower oil, linseed oil, safflower oil, toxic metals, food safety, rape oil

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Authors: Muhammad Rosli Abdullah, Noor Hasmiza Harun

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A microorganism detection system has a potential to be used with the advancement in a biosensor development. The detection system requires an optical sensing system, microfluidic device and biological reagent. Although, the biosensors are available in the market, a label free and a lab-on-chip approach will promote a flexible solution. As a preliminary study of microorganism detection, three mechanisms such as Total Internal Reflection (TIR), Micro Fluidic Channel (MFC) and magnetic-electric field propagation were study and simulated. The objective are to identify the TIR angle, MFC parabolic flow and the wavelength for the microorganism detection. The simulation result indicates that evanescent wave is achieved when TIR angle > 42°, the corner and centre of a parabolic velocity are 0.02 m/s and 0.06 m/s respectively, and a higher energy distribution of a perfect electromagnetic scattering with dipole resonance radiation occurs at 500 nm. This simulation is beneficial to determine the components of the microorganism detection system that does not rely on classical microbiological, immunological and genetic methods which are laborious, time-consuming procedures and confined to specialized laboratories with expensive instrumentation equipment.

Keywords: microorganism, microfluidic, total internal reflection, lab on chip

Procedia PDF Downloads 277

Authors: Kassoul Ilyes

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The field of error correcting codes has been revolutionized by the introduction of iteratively decoded codes. Among these, LDPC codes are now a preferred solution thanks to their remarkable performance and low complexity. The binary version of LDPC codes showed even better performance, although it’s decoding introduced greater complexity. This thesis studies the performance of binary LDPC codes using simplified weighted decisions. Information is transported between a transmitter and a receiver by digital transmission systems, either by propagating over a radio channel or also by using a transmission medium such as the transmission line. The purpose of the transmission system is then to carry the information from the transmitter to the receiver as reliably as possible. These codes have not generated enough interest within the coding theory community. This forgetfulness will last until the introduction of Turbo-codes and the iterative principle. Then it was proposed to adopt Pearl's Belief Propagation (BP) algorithm for decoding these codes. Subsequently, Luby introduced irregular LDPC codes characterized by a parity check matrix. And finally, we study simplifications on binary LDPC codes. Thus, we propose a method to make the exact calculation of the APP simpler. This method leads to simplifying the implementation of the system.

Keywords: LDPC, parity check matrix, 5G, BER, SNR

Procedia PDF Downloads 153

Authors: Jagadeshvaran P. L., Kamlesh Panwar, Indumathi Ramakrishnan, Suryasarathi Bose

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The surge in the usage of wireless electronics and communication devices has engendered a different form of pollution, viz. the electromagnetic (EM) pollution and yet another serious issue, electromagnetic interference (EMI). There is a legitimate need to develop strategies and materials to combat this issue, otherwise leading to dreadful consequences. Functional textiles have emerged as the modern materials to help attenuate EM waves due to the numerous advantages – flexibility being the most important. In addition to this, there is an inherent advantage of multiple interfaces in coated fabrics that can engender significant attenuation. Herein we report a coating having multifunctional properties – capable of blocking both UV and EM radiation (predominantly of the microwave frequencies) with flame-retarding properties. The layer described here comprises iron titanate(FT) synthesized from its sustainable precursor – ilmenite sand and carbon nanotubes (CNT) dispersed in waterborne polyurethane. It is worth noting that FT's use as a multifunctional material is being reported for the first time. It was observed that a single layer of coated fabric shows EMI shielding effectiveness of -40 dB translating to 99.99% attenuation and similarly a UV blocking of 99.99% in the wavelength ranging from 200-400 nm. The microwave shielding properties of the fabric were demonstrated using a Bluetooth module – where the coated fabric was able to block the incoming Bluetooth signals to the module from a mobile phone. Besides, the coated fabrics exhibited phenomenal enhancement in thermal stability - a five percent increase in the limiting oxygen index (LOI) was observed upon the application of the coating. Such exceptional properties complement cotton fabrics' existing utility, thereby extending their use to specialty applications.

Keywords: multifunctional coatings, EMI shielding, UV blocking, iron titanate, CNT, waterborne polyurethane, cotton fabrics

Procedia PDF Downloads 116

Authors: W. Badla

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A numerical investigation has been carried out to examine the behaviour of reinforced concrete slabs to uniform blast loading. The aim of this work is to determine the effects of various parameters on the results. Finite element simulations were performed in the non linear dynamic range using an elasto-plastic damage model. The main parameters considered are: the negative phase of blast loading, time duration, equivalent weight of TNT, distance of the explosive and slab dimensions. Numerical modelling has been performed using ABAQUS/Explicit. The results obtained in terms of displacements and propagation of damage show that the above parameters influence considerably the nonlinear dynamic behaviour of reinforced concrete slabs under uniform blast loading.

Keywords: blast loading, reinforced concrete slabs, elasto-plastic damage model, negative phase, time duration, equivalent weight of TNT, explosive distance, slab dimensions

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Authors: M. M. Hlakola, E. Golovins, D. V. Nicolae

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The field of instrumentation electronics is undergoing an explosive growth, due to its wide range of applications. The proliferation of electrical devices in a close working proximity can negatively influence each other’s performance. The degradation in the performance is due to electromagnetic interference (EMI). This paper investigates the negative effects of electromagnetic interference originating in the General Purpose Interface Bus (GPIB) control-network of the ac-dc transfer measurement system. Remedial measures of reducing measurement errors and failure of range of industrial devices due to EMI have been explored. The ac-dc transfer measurement system was analyzed for the common-mode (CM) EMI effects. Further investigation of coupling path as well as more accurate identification of noise propagation mechanism has been outlined. To prevent the occurrence of common-mode (ground loops) which was identified between the GPIB system control circuit and the measurement circuit, a microcontroller-driven GPIB switching isolator device was designed, prototyped, programmed and validated. This mitigation technique has been explored to reduce EMI effectively.

Keywords: CM, EMI, GPIB, ground loops

Procedia PDF Downloads 288

Authors: Rajwanlop Kumpoopong, Sukit Yindeesuk, Pornchai Silarom

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Modeling cracks in concrete is complicated by its strain-softening behavior which requires the use of sophisticated energy criteria of fracture mechanics to assure stable and convergent solutions in the finite-element (FE) analysis particularly for relatively large structures. However, for small-scale structures such as beams and slabs, a simpler approach relies on retaining some shear stiffness in the cracking plane has been adopted in literature to model the strain-softening behavior of concrete under monotonically increased loading. According to the shear retaining approach, each element is assumed to be an isotropic material prior to cracking of concrete. Once an element is cracked, the isotropic element is replaced with an orthotropic element in which the new orthotropic stiffness matrix is formulated with respect to the crack orientation. The shear transfer factor of 0.5 is used in parallel to the crack plane. The shear retaining approach is adopted in this research to model cracks in RC bridge deck with some modifications to take into account the effect of repetitive moving truck wheel loads as they cause fatigue cracking of concrete. First modification is the introduction of fatigue tests of concrete and reinforcing steel and the Palmgren-Miner linear criterion of cumulative damage in the conventional FE analysis. For a certain loading, the number of cycles to failure of each concrete or RC element can be calculated from the fatigue or S-N curves of concrete and reinforcing steel. The elements with the minimum number of cycles to failure are the failed elements. For the elements that do not fail, the damage is accumulated according to Palmgren-Miner linear criterion of cumulative damage. The stiffness of the failed element is modified and the procedure is repeated until the deck slab fails. The total number of load cycles to failure of the deck slab can then be obtained from which the S-N curve of the deck slab can be simulated. Second modification is the modification in shear transfer factor. Moving loading causes continuous rubbing of crack interfaces which greatly reduces shear transfer mechanism. It is therefore conservatively assumed in this study that the analysis is conducted with shear transfer factor of zero for the case of moving loading. A customized FE program has been developed using the MATLAB software to accomodate such modifications. The developed procedure has been validated with the fatigue test of the 1/6.6-scale AASHTO bridge deck under the applications of both fixed-point repetitive loading and moving loading presented in the literature. Results are in good agreement both experimental vs. simulated S-N curves and observed vs. simulated crack patterns. Significant contribution of the developed procedure is a series of S-N relations which can now be simulated at any desired levels of cracking in addition to the experimentally derived S-N relation at the failure of the deck slab. This permits the systematic investigation of crack propagation or deterioration of RC bridge deck which is appeared to be useful information for highway agencies to prolong the life of their bridge decks.

Keywords: bridge deck, cracking, deterioration, fatigue, finite-element, moving truck, reinforced concrete

Procedia PDF Downloads 257

Authors: Abdelsabour G. A. Khaled, Ahmed W. A. Abdalla And Sabry Y. M. Mahmoud

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Banana plants showing typical mosaic and yellow stripes on leaves as symptoms were collected from Assiut Governorate in Egypt. The causal agent was identified as Cucumber mosaic virus (CMV) on the basis of symptoms, transmission, serology, transmission electron microscopy and reverse transcription polymerase chain reaction (RT-PCR). Coat protein (CP) gene was amplified using gene specific primers for coat protein (CP), followed by cloning into desired cloning vector for sequencing. In this study the CMV was transmitted into propagation host either by aphid or mechanically. The transmission was confirmed through Direct Antigen Coating Enzyme Linked Immuno Sorbent Assay (DAC-ELISA). Analysis of the 120 deduced amino acid sequence of the coat protein gene revealed that the EG-A strain of CMV shared from 97.50 to 98.33% with those strains belonging to subgroup IA. The cluster analysis grouped the Egyptian isolate with strains Fny and Ri8 belonging sub-group IA. It appears that there occurs a high incidence of CMV infecting banana belonging to IA subgroup in most parts of Egypt.

Keywords: banana, CMV, transmission, CP gene, RT-PCR

Procedia PDF Downloads 341

Authors: J. Balaraju, M. Govinda Raj, C. S. N. Murthy

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Every industry is constantly looking for enhancement of its day to day production and productivity. This can be possible only by maintaining the men and machinery at its adequate level. Prediction of performance characteristics plays an important role in performance evaluation of the equipment. Analytical and statistical approaches will take a bit more time to solve complex problems such as performance estimations as compared with software-based approaches. Keeping this in view the present study deals with an Artificial Neural Network (ANN) modelling of a Load-Haul-Dump (LHD) machine to predict the performance characteristics such as reliability, availability and preventive maintenance (PM). A feed-forward-back-propagation ANN technique has been used to model the Levenberg-Marquardt (LM) training algorithm. The performance characteristics were computed using Isograph Reliability Workbench 13.0 software. These computed values were validated using predicted output responses of ANN models. Further, recommendations are given to the industry based on the performed analysis for improvement of equipment performance.

Keywords: load-haul-dump, LHD, artificial neural network, ANN, performance, reliability, availability, preventive maintenance

Procedia PDF Downloads 150

Authors: M. R. Abusrea, Shiyi Jiang, Dingding Chen, Kazuo Arakawa

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Novel wind-lens turbine designs can augment power output. Vacuum-Assisted Resin Transfer Molding (VARTM) is used to form large and complex structures from a Carbon Fiber Reinforced Polymer (CFRP) composite. Typically, wind-lens turbine structures are fabricated in segments, and then bonded to form the final structure. This paper introduces five new adhesive joints, divided into two groups: One is constructed between dry carbon and CFRP fabrics, and the other is constructed with two dry carbon fibers. All joints and CFRP fabrics were made in our laboratory using VARTM manufacturing techniques. Specimens were prepared for tensile testing to measure joint performance. The results showed that the second group of joints achieved a higher tensile strength than the first group. On the other hand, the tensile fracture behavior of the two groups showed the same pattern of crack originating near the joint ends followed by crack propagation until fracture.

Keywords: adhesive joints, CFRP, VARTM, resin transfer molding

Procedia PDF Downloads 436

Authors: Dhaladhuli Pranavi, Amirtham Rajagopal

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There are various failure modes in ceramic matrix composites; notable ones are fiber breakage, matrix cracking and fiber matrix debonding. Crack nucleation and propagation in microstructure of such composites requires an understanding of interaction of crack with the multiple inclusion heterogeneous system and interfaces. In order to assess structural integrity, the material parameters especially of the interface that governs the crack growth should be determined. In the present work, a nonlocal phase field approach is proposed to model the crack interface interaction in such composites. Nonlocal approaches help in understanding the complex mechanisms of delamination growth and mitigation and operates at a material length scale. The performance of the proposed formulation is illustrated through representative numerical examples. The model proposed is implemented in the framework of the finite element method. Several parametric studies on interface crack interaction are conducted. The proposed model is easy and simple to implement and works very well in modeling fracture in composite systems.

Keywords: composite, interface, nonlocal, phase field

Procedia PDF Downloads 142

Authors: Sukhbir Singh

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This paper describes the modeling of novel solar air collector (NSAC) system by using artificial neural network (ANN) model. The objective of the study is to demonstrate the application of the ANN model to predict the performance of the NSAC with acetamide as a phase change material (PCM) storage. Input data set consist of time, solar intensity and ambient temperature wherever as outlet air temperature of NSAC was considered as output. Experiments were conducted between 9.00 and 24.00 h in June and July 2014 underneath the prevailing atmospheric condition of Kurukshetra (city of the India). After that, experimental results were utilized to train the back propagation neural network (BPNN) to predict the outlet air temperature of NSAC. The results of proposed algorithm show that the BPNN is effective tool for the prediction of responses. The BPNN predicted results are 99% in agreement with the experimental results.

Keywords: Evacuated tube solar air collector, Artificial neural network, Phase change material, solar air collector

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Authors: Chico Horacio Jose Sambo

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Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

Procedia PDF Downloads 403

Authors: Azadeh Bashiri

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Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 273

Authors: A. Mousavi, S. Sadegzadeh

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In this research, the effect of non-thermal micro plasma with non-Maxwellian distribution function on the one dimensional plasma photonic crystals containing alternate plasma-dielectric layers, has been studied. By using Kronig Penny model, the dispersion relation of electromagnetic modes for such a periodic structure is obtained. In this study we take two plasma photonic crystals with different dielectric layers: the first one with Silicon monoxide named PPCI, and the second one with Tellurium dioxide named PPCII. The effects of the plasma layer thickness and the material of the dielectric layer on the plasma photonic crystal band gaps have been illustrated in the dispersion relation and the group velocity figures. Results revealed that in such a system, the non-thermal plasma exerts stronger limit on the wave’s propagation. In another word, for the non-thermal plasma photonic crystals (NPPC), there are two distinct regions in the dispersion plot. The upper region consists of alternate band gaps in such a way that both width and length of the bands decrease gradually as the band gaps order increases. Whereas in the lower region where v_ph > 20 c (for PPCI), waves will not be allowed to propagate.

Keywords: band gap, dispersion relation, non-thermal plasma, plasma photonic crystal

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Authors: Edward Guillén, Jeisson Sánchez, Carlos Omar Ramos

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In recent years, a wide variety of applications are developed with Support Vector Machines -SVM- methods and Artificial Neural Networks -ANN-. In general, these methods depend on intrusion knowledge databases such as KDD99, ISCX, and CAIDA among others. New classes of detectors are generated by machine learning techniques, trained and tested over network databases. Thereafter, detectors are employed to detect anomalies in network communication scenarios according to user’s connections behavior. The first detector based on training dataset is deployed in different real-world networks with mobile and non-mobile devices to analyze the performance and accuracy over static detection. The vulnerabilities are based on previous work in telemedicine apps that were developed on the research group. This paper presents the differences on detections results between some network scenarios by applying traditional detectors deployed with artificial neural networks and support vector machines.

Keywords: anomaly detection, back-propagation neural networks, network intrusion detection systems, support vector machines

Procedia PDF Downloads 357

Authors: R. Gounina-Allouane, I. Moussaoui, N. Boukahel

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Bacillus antimicrobial metabolites, especially those of Bacillus thuringiensis (Bt), are of great interest for research because of health risks generated by the excessive use of chemical additives as well as the propagation of resistant microbial strains, caused by the massive treatment with antibiotics. The objective of this study was the selection of Bt strains producing antimicrobial peptides (bacteriocins), and the partial purification of the most powerful bacteriocins, then the determination of their spectra of antimicrobial action. A collection of twenty one Bt strains isolated from soil at Boumerdès (northern Algeria) was used for screening strains having an antagonistic activity against phylogenetically closed bacteria. Spectra of antagonistic activity of two selected strains was determined against other Bt strains, Gram positive and Gram negative bacterial strains of clinical origin and others from ATCC collection as well as yeasts isolated in human dermatology. Bacteriocins of these two strains were partially purified and their effect on the kinetics of growth of the most sensitive microbial strains was studied. The bacteriocinogenic strains were biochemically characterized and their sensitivity to antibiotics was studied.

Keywords: antimicrobial peptides, Bacillus thuringiensis, bacteriocin, partial purification

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Authors: M. Benachour, N. Benachour, M. Benguediab

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In this investigation, variation of cyclic loading effect on fatigue crack growth is studied. This study is performed on 2024 T351 and 7050-T74 aluminum alloys, used in aeronautical structures. The propagation model used in this study is NASGRO model. In constant amplitude loading (CA), the effect of stress ratio has been investigated. Fatigue life and fatigue crack growth rate were affected by this factor. Results showed an increasing in fatigue crack growth rates (FCGRs) with increasing stress ratio. Variable amplitude loading (VAL) can take many forms i.e with a single overload, overload band etc. The shape of these loads affects strongly the fracture life and FCGRs. The application of a single overload (ORL) decrease the FCGR and increase the delay crack length caused by the formation of a larger plastic zone compared to the plastic zone due without VAL. The fatigue behavior of the both material under single overload has been compared.

Keywords: fatigue crack growth, overload ratio, stress ratio, generalized willenborg model, retardation, al-alloys

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Authors: O. Onoriode Emoyan, E. Eyitemi Akporhonor, Charles Otobrise

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Polycyclic Aromatic Hydrocarbons (PAHs) are formed mainly as a result of incomplete combustion of organic materials during industrial, domestic activities or natural occurrence. Their toxicity and contamination of terrestrial and aquatic ecosystem have been established. Though with limited validity index, previous research has focused on PAHs isomer pair ratios of variable physicochemical properties in source identification. The objective of this investigation was to determine the empirical validity of Pearson correlation coefficient (PCC) and cluster analysis (CA) in PAHs source identification along soil samples of different land uses. Therefore, 16 PAHs grouped as endocrine disruption substances (EDSs) were determined in 10 sample stations in top and sub soils seasonally. PAHs was determined the use of Varian 300 gas chromatograph interfaced with flame ionization detector. Instruments and reagents used are of standard and chromatographic grades respectively. PCC and CA results showed that the classification of PAHs along kinetically and thermodyanamically-favoured and those derived directly from plants product through biologically mediated processes used in source signature is about the predominance PAHs are likely to be. Therefore the observed PAHs in the studied stations have trace quantities of the vast majority of the sixteen un-substituted PAHs which may ultimately inhabit the actual source signature authentication. Type and extent of bacterial metabolism, transformation products/substrates, and environmental factors such as: salinity, pH, oxygen concentration, nutrients, light intensity, temperature, co-substrates and environmental medium are hereby recommended as factors to be considered when evaluating possible sources of PAHs.

Keywords: comparative correlation, kinetically and thermodynamically-favored PAHs, pearson correlation coefficient, cluster analysis, sources evaluation

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Authors: W. Oudad, H. Fikirini, K. Boulenouar

Abstract:

Material fracture by opening (mode I) is not alone responsible for fracture propagation. Many industrial examples show the presence of mode II and mixed mode I + II. In the present work the three-dimensional and non-linear finite element method is used to estimate the performance of the bonded composite repair of metallic aircraft structures by analyzing the plastic zone size ahead of repaired cracks under mixed mode loading. The computations are made according to Von Mises and Tresca criteria. The extension of the plastic zone which takes place at the tip of a crack strictly depends on many variables, such as the yield stress of the material, the loading conditions, the crack size and the thickness of the cracked component, The obtained results show that the presence of the composite patch reduces considerably the size of the plastic zone ahead of the crack. The effects of the composite orientation layup (adhesive properties) and the patch thickness on the plastic zone size ahead of repaired cracks were analyzed.

Keywords: crack, elastic-plastic, J integral, patch, plastic zone

Procedia PDF Downloads 445

Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

Abstract:

Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

Procedia PDF Downloads 312

Authors: R. Gounina-Allouane, I. Moussaoui, N. Boukahel

Abstract:

Bacillus antimicrobial metabolites, especially those of Bacillus thuringiensis (Bt), are of great interest for research because of health risks generated by the excessive use of chemical additives as well as the propagation of resistant microbial strains, caused by the massive treatment with antibiotics. The objective of this study was the selection of Bt strains producing antimicrobial peptides (bacteriocins), and the partial purification of the most powerful bacteriocins, then the determination of their spectra of antimicrobial action. A collection of twenty one Bt strains isolated from soil at Boumerdès (northern of Algeria) was used for screening strains having an antagonistic activity against phylogenetically closed bacteria. Spectra of antagonistic activity of two selected strains was determined against other Bt strains, Gram positive and Gram negative bacterial strains of clinical origin and others from ATCC collection as well as yeasts isolated in human dermatology. Bacteriocins of these two strains were partially purified and their effect on the kinetics of growth of the most sensitive microbial strains was studied. The bacteriocinogenic strains were biochemically characterized and their sensitivity to antibiotics was studied.

Keywords: antimicrobial peptides, Bacillus thuringiensis, bacteriocin, partial purification

Procedia PDF Downloads 358