Search results for: laser propagation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1578

Search results for: laser propagation

618 Ontology-Based Backpropagation Neural Network Classification and Reasoning Strategy for NoSQL and SQL Databases

Authors: Hao-Hsiang Ku, Ching-Ho Chi

Abstract:

Big data applications have become an imperative for many fields. Many researchers have been devoted into increasing correct rates and reducing time complexities. Hence, the study designs and proposes an Ontology-based backpropagation neural network classification and reasoning strategy for NoSQL big data applications, which is called ON4NoSQL. ON4NoSQL is responsible for enhancing the performances of classifications in NoSQL and SQL databases to build up mass behavior models. Mass behavior models are made by MapReduce techniques and Hadoop distributed file system based on Hadoop service platform. The reference engine of ON4NoSQL is the ontology-based backpropagation neural network classification and reasoning strategy. Simulation results indicate that ON4NoSQL can efficiently achieve to construct a high performance environment for data storing, searching, and retrieving.

Keywords: Hadoop, NoSQL, ontology, back propagation neural network, high distributed file system

Procedia PDF Downloads 248
617 Forming-Free Resistive Switching Effect in ZnₓTiᵧHfzOᵢ Nanocomposite Thin Films for Neuromorphic Systems Manufacturing

Authors: Vladimir Smirnov, Roman Tominov, Vadim Avilov, Oleg Ageev

Abstract:

The creation of a new generation micro- and nanoelectronics elements opens up unlimited possibilities for electronic devices parameters improving, as well as developing neuromorphic computing systems. Interest in the latter is growing up every year, which is explained by the need to solve problems related to the unstructured classification of data, the construction of self-adaptive systems, and pattern recognition. However, for its technical implementation, it is necessary to fulfill a number of conditions for the basic parameters of electronic memory, such as the presence of non-volatility, the presence of multi-bitness, high integration density, and low power consumption. Several types of memory are presented in the electronics industry (MRAM, FeRAM, PRAM, ReRAM), among which non-volatile resistive memory (ReRAM) is especially distinguished due to the presence of multi-bit property, which is necessary for neuromorphic systems manufacturing. ReRAM is based on the effect of resistive switching – a change in the resistance of the oxide film between low-resistance state (LRS) and high-resistance state (HRS) under an applied electric field. One of the methods for the technical implementation of neuromorphic systems is cross-bar structures, which are ReRAM cells, interconnected by cross data buses. Such a structure imitates the architecture of the biological brain, which contains a low power computing elements - neurons, connected by special channels - synapses. The choice of the ReRAM oxide film material is an important task that determines the characteristics of the future neuromorphic system. An analysis of literature showed that many metal oxides (TiO2, ZnO, NiO, ZrO2, HfO2) have a resistive switching effect. It is worth noting that the manufacture of nanocomposites based on these materials allows highlighting the advantages and hiding the disadvantages of each material. Therefore, as a basis for the neuromorphic structures manufacturing, it was decided to use ZnₓTiᵧHfzOᵢ nanocomposite. It is also worth noting that the ZnₓTiᵧHfzOᵢ nanocomposite does not need an electroforming, which degrades the parameters of the formed ReRAM elements. Currently, this material is not well studied, therefore, the study of the effect of resistive switching in forming-free ZnₓTiᵧHfzOᵢ nanocomposite is an important task and the goal of this work. Forming-free nanocomposite ZnₓTiᵧHfzOᵢ thin film was grown by pulsed laser deposition (Pioneer 180, Neocera Co., USA) on the SiO2/TiN (40 nm) substrate. Electrical measurements were carried out using a semiconductor characterization system (Keithley 4200-SCS, USA) with W probes. During measurements, TiN film was grounded. The analysis of the obtained current-voltage characteristics showed a resistive switching from HRS to LRS resistance states at +1.87±0.12 V, and from LRS to HRS at -2.71±0.28 V. Endurance test shown that HRS was 283.21±32.12 kΩ, LRS was 1.32±0.21 kΩ during 100 measurements. It was shown that HRS/LRS ratio was about 214.55 at reading voltage of 0.6 V. The results can be useful for forming-free nanocomposite ZnₓTiᵧHfzOᵢ films in neuromorphic systems manufacturing. This work was supported by RFBR, according to the research project № 19-29-03041 mk. The results were obtained using the equipment of the Research and Education Center «Nanotechnologies» of Southern Federal University.

Keywords: nanotechnology, nanocomposites, neuromorphic systems, RRAM, pulsed laser deposition, resistive switching effect

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616 Forecasting Electricity Spot Price with Generalized Long Memory Modeling: Wavelet and Neural Network

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

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615 Investigation of Arson Fire Incident in Textile Garment Building Using Fire Dynamic Simulation

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 70
614 Cancer Stem Cell-Associated Serum Proteins Obtained by Maldi TOF/TOF Mass Spectrometry in Women with Triple-Negative Breast Cancer

Authors: Javier Enciso-Benavides, Fredy Fabian, Carlos Castaneda, Luis Alfaro, Alex Choque, Aparicio Aguilar, Javier Enciso

Abstract:

Background: The use of biomarkers in breast cancer diagnosis, therapy, and prognosis has gained increasing interest. Cancer stem cells (CSCs) are a subpopulation of tumor cells that can drive tumor initiation and may cause relapse. Therefore, due to the importance of diagnosis, therapy, and prognosis, several biomarkers that characterize CSCs have been identified; however, in treatment-naïve triple-negative breast tumors, there is an urgent need to identify new biomarkers and therapeutic targets. According to this, the aim of this study was to identify serum proteins associated with cancer stem cells and pluripotency in women with triple-negative breast tumors in order to subsequently identify a biomarker for this type of breast tumor. Material and Methods: Whole blood samples from 12 women with histopathologically diagnosed triple-negative breast tumors were used after obtaining informed consent from the patient. Blood serum was obtained by conventional procedure and frozen at -80ºC. Identification of cancer stem cell-associated proteins was performed by matrix-assisted laser desorption/ionisation-assisted laser desorption/ionisation mass spectrometry (MALDI-TOF MS), protein analysis was obtained using the AB Sciex TOF/TOF™ 5800 system (AB Sciex, USA). Sequences not aligned by ProteinPilot™ software were analyzed by Protein BLAST. Results: The following proteins related to pluripotency and cancer stem cells were identified by MALDI TOF/TOF mass spectrometry: A-chain, Serpin A12 [Homo sapiens], AIEBP [Homo sapiens], Alpha-one antitrypsin, AT {internal fragment} [human, partial peptide, 20 aa] [Homo sapiens], collagen alpha 1 chain precursor variant [Homo sapiens], retinoblastoma-associated protein variant [Homo sapiens], insulin receptor, CRA_c isoform [Homo sapiens], Hydroxyisourate hydrolase [Streptomyces scopuliridis], MUCIN-6 [Macaca mulatta], Alpha-actinin-3 [Chrysochloris asiatica], Polyprotein M, CRA_d isoform, partial [Homo sapiens], Transcription factor SOX-12 [Homo sapiens]. Recommendations: The serum proteins identified in this study should be investigated in the exosome of triple-negative breast cancer stem cells and in the blood serum of women without breast cancer. Subsequently, proteins found only in the blood serum of women with triple-negative breast cancer should be identified in situ in triple-negative breast cancer tissue in order to identify a biomarker to study the evolution of this type of cancer, or that could be a therapeutic target. Conclusions: Eleven cancer stem cell-related serum proteins were identified in 12 women with triple-negative breast cancer, of which MUCIN-6, retinoblastoma-associated protein variant, transcription factor SOX-12, and collagen alpha 1 chain are the most representative and have not been studied so far in this type of breast tumor. Acknowledgement: This work was supported by Proyecto CONCYTEC–Banco Mundial “Mejoramiento y Ampliacion de los Servicios del Sistema Nacional de Ciencia Tecnología e Innovacion Tecnologica” 8682-PE (104-2018-FONDECYT-BM-IADT-AV).

Keywords: triple-negative breast cancer, MALDI TOF/TOF MS, serum proteins, cancer stem cells

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613 Coaxial Helix Antenna for Microwave Coagulation Therapy in Liver Tissue Simulations

Authors: M. Chaichanyut, S. Tungjitkusolmun

Abstract:

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

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612 N-Type GaN Thinning for Enhancing Light Extraction Efficiency in GaN-Based Thin-Film Flip-Chip Ultraviolet (UV) Light Emitting Diodes (LED)

Authors: Anil Kawan, Soon Jae Yu, Jong Min Park

Abstract:

GaN-based 365 nm wavelength ultraviolet (UV) light emitting diodes (LED) have various applications: curing, molding, purification, deodorization, and disinfection etc. However, their usage is limited by very low output power, because of the light absorption in the GaN layers. In this study, we demonstrate a method utilizing removal of 365 nm absorption layer buffer GaN and thinning the n-type GaN so as to improve the light extraction efficiency of the GaN-based 365 nm UV LED. The UV flip chip LEDs of chip size 1.3 mm x 1.3 mm were fabricated using GaN epilayers on a sapphire substrate. Via-hole n-type contacts and highly reflective Ag metal were used for efficient light extraction. LED wafer was aligned and bonded to AlN carrier wafer. To improve the extraction efficiency of the flip chip LED, sapphire substrate and absorption layer buffer GaN were removed by using laser lift-off and dry etching, respectively. To further increase the extraction efficiency of the LED, exposed n-type GaN thickness was reduced by using inductively coupled plasma etching.

Keywords: extraction efficiency, light emitting diodes, n-GaN thinning, ultraviolet

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611 An Integrated Approach to Find the Effect of Strain Rate on Ultimate Tensile Strength of Randomly Oriented Short Glass Fiber Composite in Combination with Artificial Neural Network

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

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610 Profit-Based Artificial Neural Network (ANN) Trained by Migrating Birds Optimization: A Case Study in Credit Card Fraud Detection

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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609 Verification and Application of Finite Element Model Developed for Flood Routing in Rivers

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

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608 Finite Element Simulation for Preliminary Study on Microorganism Detection System

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

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607 Low Density Parity Check Codes

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

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606 Damage Assessment of Reinforced Concrete Slabs Subjected to Blast Loading

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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605 Mitigation of Electromagnetic Interference Generated by GPIB Control-Network in AC-DC Transfer Measurement System

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 278
604 Simple Finite-Element Procedure for Modeling Crack Propagation in Reinforced Concrete Bridge Deck under Repetitive Moving Truck Wheel Loads

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

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603 New Isolate of Cucumber Mosaic Virus Infecting Banana

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

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602 Digital Holographic Interferometric Microscopy for the Testing of Micro-Optics

Authors: Varun Kumar, Chandra Shakher

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Micro-optical components such as microlenses and microlens array have numerous engineering and industrial applications for collimation of laser diodes, imaging devices for sensor system (CCD/CMOS, document copier machines etc.), for making beam homogeneous for high power lasers, a critical component in Shack-Hartmann sensor, fiber optic coupling and optical switching in communication technology. Also micro-optical components have become an alternative for applications where miniaturization, reduction of alignment and packaging cost are necessary. The compliance with high-quality standards in the manufacturing of micro-optical components is a precondition to be compatible on worldwide markets. Therefore, high demands are put on quality assurance. For quality assurance of these lenses, an economical measurement technique is needed. For cost and time reason, technique should be fast, simple (for production reason), and robust with high resolution. The technique should provide non contact, non-invasive and full field information about the shape of micro- optical component under test. The interferometric techniques are noncontact type and non invasive and provide full field information about the shape of the optical components. The conventional interferometric technique such as holographic interferometry or Mach-Zehnder interferometry is available for characterization of micro-lenses. However, these techniques need more experimental efforts and are also time consuming. Digital holography (DH) overcomes the above described problems. Digital holographic microscopy (DHM) allows one to extract both the amplitude and phase information of a wavefront transmitted through the transparent object (microlens or microlens array) from a single recorded digital hologram by using numerical methods. Also one can reconstruct the complex object wavefront at different depths due to numerical reconstruction. Digital holography provides axial resolution in nanometer range while lateral resolution is limited by diffraction and the size of the sensor. In this paper, Mach-Zehnder based digital holographic interferometric microscope (DHIM) system is used for the testing of transparent microlenses. The advantage of using the DHIM is that the distortions due to aberrations in the optical system are avoided by the interferometric comparison of reconstructed phase with and without the object (microlens array). In the experiment, first a digital hologram is recorded in the absence of sample (microlens array) as a reference hologram. Second hologram is recorded in the presence of microlens array. The presence of transparent microlens array will induce a phase change in the transmitted laser light. Complex amplitude of object wavefront in presence and absence of microlens array is reconstructed by using Fresnel reconstruction method. From the reconstructed complex amplitude, one can evaluate the phase of object wave in presence and absence of microlens array. Phase difference between the two states of object wave will provide the information about the optical path length change due to the shape of the microlens. By the knowledge of the value of the refractive index of microlens array material and air, the surface profile of microlens array is evaluated. The Sag of microlens and radius of curvature of microlens are evaluated and reported. The sag of microlens agrees well within the experimental limit as provided in the specification by the manufacturer.

Keywords: micro-optics, microlens array, phase map, digital holographic interferometric microscopy

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601 Application of Artificial Neural Network for Prediction of Load-Haul-Dump Machine Performance Characteristics

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

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600 Novel CFRP Adhesive Joints and Structures for Offshore Application

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

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599 A Phase Field Approach to Model Crack Interface Interaction in Ceramic Matrix Composites

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

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598 The Application of Artificial Neural Networks for the Performance Prediction of Evacuated Tube Solar Air Collector with Phase Change Material

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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597 A Neural Network Modelling Approach for Predicting Permeability from Well Logs Data

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

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596 Application of Artificial Neural Network Technique for Diagnosing Asthma

Authors: Azadeh Bashiri

Abstract:

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

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595 Interesting Behavior of Non-Thermal Plasma Photonic Crystals

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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594 Waste Egg Albumin Derived Small Peptides Stimulate Photosynthetic Electron Transport

Authors: Seungwon Han, Sung young Yoo, Tae Wan Kim

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The objective of this study was to measure the changes in the photochemical response in the leaves of red pepper (Capsium annuum L.) after foliar fertilization of amino acid and small peptides derived from the waste egg. As a nitrogen fertilizer, waste eggs were incubated over one 1week and then degraded as amino acids and small peptides. The smaller peptides less than 20 kDa were identified by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF-MS). MALDI-TOF-MS as a rapid analysis method was to show the molecular mass of degraded egg protein. The sequences of peptides were identified as follows; γ-Glu- Cys-γ-Glu-Cys-γ-Glu-Cys)-Ser and γ-Glu-Cys-γ-Glu-Cys-γ-Glu- Cys)-Gly. It was clearly illuminated that the parameters related to quantum yields for PSI electron transport (ΦRE1O, ΨRE1O, δRE1O) and RC/ABS have increased tendency by small peptide application. On the other hand, phenomenological energy fluxes (ABSO/CSM, TRO/CSM, ET2O/CSM, RE1O/CSM, DIO/CSM) have considerably fluctuated with foliar fertilization of small peptides. In conclusion, the small peptides can enhance the photochemical activities from photosystem II to photosystem I. This study was financially supported by RDA Agenda Project PJ 016196012022.

Keywords: electron transport, foliar fertilization, small peptide, waste egg

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593 Flow Visualization around a Rotationally Oscillating Cylinder

Authors: Cemre Polat, Mustafa Soyler, Bulent Yaniktepe, Coskun Ozalp

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In this study, it was aimed to control the flow actively by giving an oscillating rotational motion to a vertically placed cylinder, and flow characteristics were determined. In the study, firstly, the flow structure around the flat cylinder was investigated with dye experiments, and then the cylinders with different oscillation angles (θ = 60°, θ = 120°, and θ = 180°) and different rotation speeds (15 rpm and 30 rpm) the flow structure around it was examined. Thus, the effectiveness of oscillation and rotation speed in flow control has been investigated. In the dye experiments, the dye/water mixture obtained by mixing Rhodamine 6G in powder form with water, which shines under laser light and allows detailed observation of the flow structure, was used. During the experiments, the dye was injected into the flow with the help of a thin needle at a distance that would not affect the flow from the front of the cylinder. In dye experiments, 100 frames per second were taken with a Canon brand EOS M50 (24MP) digital mirrorless camera at a resolution of 1280 * 720 pixels. Then, the images taken were analyzed, and the pictures representing the flow structure for each experiment were obtained. As a result of the study, it was observed that no separation points were formed at 180° swing angle at 15 rpm speed, 120° and 180° swing angle at 30 rpm, and the flow was controlled according to the fixed cylinder.

Keywords: active flow control, cylinder, flow visualization rotationally oscillating

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592 Anomaly Detection with ANN and SVM for Telemedicine Networks

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

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591 Bacteriocinogenic Strains of Bacillus thuringiensis Isolated from Soil at Northern of Algeria

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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590 Development and Investigation of Sustainable Wireless Sensor Networks for forest Ecosystems

Authors: Shathya Duobiene, Gediminas Račiukaitis

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Solar-powered wireless sensor nodes work best when they operate continuously with minimal energy consumption. Wireless Sensor Networks (WSNs) are a new technology opens up wide studies, and advancements are expanding the prevalence of numerous monitoring applications and real-time aid for environments. The Selective Surface Activation Induced by Laser (SSAIL) technology is an exciting development that gives the design of WSNs more flexibility in terms of their shape, dimensions, and materials. This research work proposes a methodology for using SSAIL technology for forest ecosystem monitoring by wireless sensor networks. WSN monitoring the temperature and humidity were deployed, and their architectures are discussed. The paper presents the experimental outcomes of deploying newly built sensor nodes in forested areas. Finally, a practical method is offered to extend the WSN's lifespan and ensure its continued operation. When operational, the node is independent of the base station's power supply and uses only as much energy as necessary to sense and transmit data.

Keywords: internet of things (IoT), wireless sensor network, sensor nodes, SSAIL technology, forest ecosystem

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589 Indoor Localization by Pattern Matching Method Based on Extended Database

Authors: Gyumin Hwang, Jihong Lee

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This paper studied the CSS-based indoor localization system which is easy to implement, inexpensive to compose the systems, additionally CSS-based indoor localization system covers larger area than other system. However, this system has problem which is affected by reflected distance data. This problem in localization is caused by the multi-path effect. Error caused by multi-path is difficult to be corrected because the indoor environment cannot be described. In this paper, in order to solve the problem by multi-path, we have supplemented the localization system by using pattern matching method based on extended database. Thereby, this method improves precision of estimated. Also this method is verified by experiments in gymnasium. Database was constructed by 1 m intervals, and 16 sample data were collected from random position inside the region of DB points. As a result, this paper shows higher accuracy than existing method through graph and table.

Keywords: chirp spread spectrum, indoor localization, pattern-matching, time of arrival, multi-path, mahalanobis distance, reception rate, simultaneous localization and mapping, laser range finder

Procedia PDF Downloads 229