Search results for: Plant information management system
2087 Multimodal Database of Emotional Speech, Video and Gestures
Authors: Tomasz Sapiński, Dorota Kamińska, Adam Pelikant, Egils Avots, Cagri Ozcinar, Gholamreza Anbarjafari
Abstract:
People express emotions through different modalities. Integration of verbal and non-verbal communication channels creates a system in which the message is easier to understand. Expanding the focus to several expression forms can facilitate research on emotion recognition as well as human-machine interaction. In this article, the authors present a Polish emotional database composed of three modalities: facial expressions, body movement and gestures, and speech. The corpora contains recordings registered in studio conditions, acted out by 16 professional actors (8 male and 8 female). The data is labeled with six basic emotions categories, according to Ekman’s emotion categories. To check the quality of performance, all recordings are evaluated by experts and volunteers. The database is available to academic community and might be useful in the study on audio-visual emotion recognition.Keywords: Body movement, emotion recognition, emotional corpus, facial expressions, gestures, multimodal database, speech.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11382086 A Hybrid System of Hidden Markov Models and Recurrent Neural Networks for Learning Deterministic Finite State Automata
Authors: Pavan K. Rallabandi, Kailash C. Patidar
Abstract:
In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence/pattern recognition/classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.Keywords: Hybrid systems, Hidden Markov Models, Recurrent neural networks, Deterministic finite state automata.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28922085 Utilization of Demolished Concrete Waste for New Construction
Authors: Asif Husain, Majid Matouq Assas
Abstract:
In recent years demolished concrete waste handling and management is the new primary challenging issue faced by the countries all over the world. It is very challenging and hectic problem that has to be tackled in an indigenous manner, it is desirable to completely recycle demolished concrete waste in order to protect natural resources and reduce environmental pollution. In this research paper an experimental study is carried out to investigate the feasibility and recycling of demolished waste concrete for new construction. The present investigation to be focused on recycling demolished waste materials in order to reduce construction cost and resolving housing problems faced by the low income communities of the world. The crushed demolished concrete wastes is segregated by sieving to obtain required sizes of aggregate, several tests were conducted to determine the aggregate properties before recycling it into new concrete. This research shows that the recycled aggregate that are obtained from site make good quality concrete. The compressive strength test results of partial replacement and full recycled aggregate concrete and are found to be higher than the compressive strength of normal concrete with new aggregate.
Keywords: Demolished, concrete waste, recycle, new concrete, fresh coarse aggregate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 58542084 Mathematical Modeling of SISO based Timoshenko Structures – A Case Study
Authors: T.C. Manjunath, Student Member, B. Bandyopadhyay
Abstract:
This paper features the mathematical modeling of a single input single output based Timoshenko smart beam. Further, this mathematical model is used to design a multirate output feedback based discrete sliding mode controller using Bartoszewicz law to suppress the flexural vibrations. The first 2 dominant vibratory modes is retained. Here, an application of the discrete sliding mode control in smart systems is presented. The algorithm uses a fast output sampling based sliding mode control strategy that would avoid the use of switching in the control input and hence avoids chattering. This method does not need the measurement of the system states for feedback as it makes use of only the output samples for designing the controller. Thus, this methodology is more practical and easy to implement.
Keywords: Smart structure, Timoshenko beam theory, Discretesliding mode control, Bartoszewicz law, Finite Element Method, State space model, Vibration control, Mathematical model, SISO.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24002083 Hydrologic Balance and Surface Water Resources of the Cheliff-Zahrez Basin
Authors: Mehaiguene Madjid, Touhari Fadhila, Meddi Mohamed
Abstract:
The Cheliff basin offers a good hydrological example for the possibility of studying the problem which elucidated in the future, because of the unclearity in several aspects and hydraulic installation. Thus, our study of the Cheliff basin is divided into two principal parts: The spatial evaluation of the precipitation: also, the understanding of the modes of the reconstitution of the resource in water supposes a good knowledge of the structuring of the precipitation fields in the studied space. In the goal of a good knowledge of revitalizes them in water and their management integrated one judged necessary to establish a precipitation card of the Cheliff basin for a good understanding of the evolution of the resource in water in the basin and that goes will serve as basis for all study of hydraulic planning in the Cheliff basin. Then, the establishment of the precipitation card of the Cheliff basin answered a direct need of setting to the disposition of the researchers for the region and a document of reference that will be completed therefore and actualized. The hydrological study, based on the statistical hydrometric data processing will lead us to specify the hydrological terms of the assessment hydrological and to clarify the fundamental aspects of the annual flow, seasonal, extreme and thus of their variability and resources surface water.
Keywords: Hydrological assessment, surface water resources, Cheliff, Algeria.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10542082 Dynamic Analysis of Transmission Line Towers
Authors: Srikanth L., Neelima Satyam D.
Abstract:
The transmission line towers are one of the important life line structures in the distribution of power from the source to the various places for several purposes. The predominant external loads which act on these towers are wind and earthquake loads. In this present study tower is analyzed using Indian Standards IS: 875:1987(Wind Load), IS: 802:1995(Structural steel), IS:1893:2002 (Earthquake) and dynamic analysis of tower has been performed considering ground motion of 2001 Bhuj Earthquake (India). The dynamic analysis was performed considering a tower system consisting two towers spaced 800m apart and 35m height each. This analysis has been performed using numerical time stepping finite difference method which is central difference method were employed by a developed MATLAB program to get the normalized ground motion parameters includes acceleration, frequency, velocity which are important in designing the tower. The tower is analyzed using response spectrum analysis.
Keywords: Response Spectra, Dynamic Analysis, Central Difference Method, Transmission Tower.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 40932081 A Fuzzy Approach to Liver Tumor Segmentation with Zernike Moments
Authors: Abder-Rahman Ali, Antoine Vacavant, Manuel Grand-Brochier, Adélaïde Albouy-Kissi, Jean-Yves Boire
Abstract:
In this paper, we present a new segmentation approach for liver lesions in regions of interest within MRI (Magnetic Resonance Imaging). This approach, based on a two-cluster Fuzzy CMeans methodology, considers the parameter variable compactness to handle uncertainty. Fine boundaries are detected by a local recursive merging of ambiguous pixels with a sequential forward floating selection with Zernike moments. The method has been tested on both synthetic and real images. When applied on synthetic images, the proposed approach provides good performance, segmentations obtained are accurate, their shape is consistent with the ground truth, and the extracted information is reliable. The results obtained on MR images confirm such observations. Our approach allows, even for difficult cases of MR images, to extract a segmentation with good performance in terms of accuracy and shape, which implies that the geometry of the tumor is preserved for further clinical activities (such as automatic extraction of pharmaco-kinetics properties, lesion characterization, etc.).Keywords: Defuzzification, floating search, fuzzy clustering, Zernike moments.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20592080 Efficacy and Stability of Ceramic Powder to Inactivate Avian Influenza Virus
Authors: Chanathip Thammakarn, Misato Tsujimura, Keisuke Satoh, Tomomi Hasegawa, Miho Tamura, Akinobu Kawamura, Yuki Ishida, Atsushi Suguro, Hakimullah Hakim, Sakchai Ruenphet, , Kazuaki Takehara
Abstract:
This experiment aims to demonstrate the efficacy of ceramic powder derived from various sources to inactivate avian influenza virus and its possibility to use in the environment. The ceramics used in the present experiment were derived from chicken feces (CF), scallop shell (SS), polyvinyl chloride (PVC) and soybean (SB). All ceramics were mixed with low pathogenic AIV (LPAIV) H7N1, and then kept at room temperature. The recovered virus was titrated onto Madin-Darby canine kidney (MDCK) cells. All ceramics were assessed the inactivation stability in the environment by keeping under sunlight and under wet-dry condition until reached 7 week or 7 resuspension times respectively. The results indicate that all ceramics have excellent efficacy to inactivate LPAIV. This efficacy can be maintained under the simulated condition. The ceramics are expected to be the good materials for application in the biosecurity system at farms.
Keywords: Avian Influenza, Ceramics, Efficacy, Stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18322079 Increasing The Speed of Convergence of an Artificial Neural Network based ARMA Coefficients Determination Technique
Authors: Abiodun M. Aibinu, Momoh J. E. Salami, Amir A. Shafie, Athaur Rahman Najeeb
Abstract:
In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introducing sequential and batch method of weight initialization, batch method of weight and coefficient update, adaptive momentum and learning rate technique gives more accurate result and significant reduction in convergence time when compared t the traditional method of back propagation algorithm, thereby making FFBPNN an appropriate technique for online ARMA coefficient determination.Keywords: Adaptive Learning rate, Adaptive momentum, Autoregressive, Modeling, Neural Network.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15042078 PID Control Design Based on Genetic Algorithm with Integrator Anti-Windup for Automatic Voltage Regulator and Speed Governor of Brushless Synchronous Generator
Authors: O. S. Ebrahim, M. A. Badr, Kh. H. Gharib, H. K. Temraz
Abstract:
This paper presents a methodology based on genetic algorithm (GA) to tune the parameters of proportional-integral-differential (PID) controllers utilized in the automatic voltage regulator (AVR) and speed governor of a brushless synchronous generator driven by three-stage steam turbine. The parameter tuning is represented as a nonlinear optimization problem solved by GA to minimize the integral of absolute error (IAE). The problem of integral windup due to physical system limitations is solved using simple anti-windup scheme. The obtained controllers are compared to those designed using classical Ziegler-Nichols technique and constrained optimization. Results show distinct superiority of the proposed method.
Keywords: Brushless synchronous generator, Genetic Algorithm, GA, Proportional-Integral-Differential control, PID control, automatic voltage regulator, AVR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3142077 A New Self-Tuning Fuzzy PD Controller of a BDFIG for Wind Energy Conversion
Authors: Zoheir Tir, Rachid Abdessemed
Abstract:
This paper presents a new control scheme to control a brushless doubly fed induction generator (BDFIG) using back-to-back PWM converters for wind power generation. The proposed control scheme is a New Self-Tuning Fuzzy Proportional-Derivative Controller (NSTFPDC). The goal of BDFIG control is to achieve a similar dynamic performance to the doubly fed induction generator (DFIG), exploiting the well-known induction machine vector control philosophy. The performance of NSTFPDC controller has been investigated and compared with the two controllers, called Proportional–Integral (PI) and PD-like Fuzzy Logic controller (PD-like FLC) based BDFIG. The simulation results demonstrate the effectiveness and the robustness of the NSTFPDC controller.
Keywords: Brushless Doubly Fed Induction Generator (BDFIG), PI controller, PD-like Fuzzy Logic controller, New Self-Tuning Fuzzy Proportional-Derivative Controller (NSTFPDC), Scaling factor, back-to-back PWM converters, wind energy system.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23962076 OCIRS: An Ontology-based Chinese Idioms Retrieval System
Authors: Hu Haibo, Tu Chunmei, Fu Chunlei, Fu Li, Mao Fan, Ma Yuan
Abstract:
Chinese Idioms are a type of traditional Chinese idiomatic expressions with specific meanings and stereotypes structure which are widely used in classical Chinese and are still common in vernacular written and spoken Chinese today. Currently, Chinese Idioms are retrieved in glossary with key character or key word in morphology or pronunciation index that can not meet the need of searching semantically. OCIRS is proposed to search the desired idiom in the case of users only knowing its meaning without any key character or key word. The user-s request in a sentence or phrase will be grammatically analyzed in advance by word segmentation, key word extraction and semantic similarity computation, thus can be mapped to the idiom domain ontology which is constructed to provide ample semantic relations and to facilitate description logics-based reasoning for idiom retrieval. The experimental evaluation shows that OCIRS realizes the function of searching idioms via semantics, obtaining preliminary achievement as requested by the users.Keywords: Chinese idiom, idiom retrieval, semantic searching, ontology, semantics similarity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17252075 Modelling of Powered Roof Supports Work
Authors: Marcin Michalak
Abstract:
Due to the increasing efforts on saving our natural environment a change in the structure of energy resources can be observed - an increasing fraction of a renewable energy sources. In many countries traditional underground coal mining loses its significance but there are still countries, like Poland or Germany, in which the coal based technologies have the greatest fraction in a total energy production. This necessitates to make an effort to limit the costs and negative effects of underground coal mining. The longwall complex is as essential part of the underground coal mining. The safety and the effectiveness of the work is strongly dependent of the diagnostic state of powered roof supports. The building of a useful and reliable diagnostic system requires a lot of data. As the acquisition of a data of any possible operating conditions it is important to have a possibility to generate a demanded artificial working characteristics. In this paper a new approach of modelling a leg pressure in the single unit of powered roof support. The model is a result of the analysis of a typical working cycles.Keywords: Machine modelling, underground mining, coal mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19332074 A Study on the Location and Range of Obstacle Region in Robot's Point Placement Task based on the Vision Control Algorithm
Authors: Jae Kyung Son, Wan Shik Jang, Sung hyun Shim, Yoon Gyung Sung
Abstract:
This paper is concerned with the application of the vision control algorithm for robot's point placement task in discontinuous trajectory caused by obstacle. The presented vision control algorithm consists of four models, which are the robot kinematic model, vision system model, parameters estimation model, and robot joint angle estimation model.When the robot moves toward a target along discontinuous trajectory, several types of obstacles appear in two obstacle regions. Then, this study is to investigate how these changes will affect the presented vision control algorithm.Thus, the practicality of the vision control algorithm is demonstrated experimentally by performing the robot's point placement task in discontinuous trajectory by obstacle.
Keywords: Vision control algorithm, location of obstacle region, range of obstacle region, point placement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14092073 Automatic Number Plate Recognition System Based on Deep Learning
Authors: T. Damak, O. Kriaa, A. Baccar, M. A. Ben Ayed, N. Masmoudi
Abstract:
In the last few years, Automatic Number Plate Recognition (ANPR) systems have become widely used in the safety, the security, and the commercial aspects. Forethought, several methods and techniques are computing to achieve the better levels in terms of accuracy and real time execution. This paper proposed a computer vision algorithm of Number Plate Localization (NPL) and Characters Segmentation (CS). In addition, it proposed an improved method in Optical Character Recognition (OCR) based on Deep Learning (DL) techniques. In order to identify the number of detected plate after NPL and CS steps, the Convolutional Neural Network (CNN) algorithm is proposed. A DL model is developed using four convolution layers, two layers of Maxpooling, and six layers of fully connected. The model was trained by number image database on the Jetson TX2 NVIDIA target. The accuracy result has achieved 95.84%.
Keywords: Automatic number plate recognition, character segmentation, convolutional neural network, CNN, deep learning, number plate localization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12972072 Cost Sensitive Feature Selection in Decision-Theoretic Rough Set Models for Customer Churn Prediction: The Case of Telecommunication Sector Customers
Authors: Emel Kızılkaya Aydogan, Mihrimah Ozmen, Yılmaz Delice
Abstract:
In recent days, there is a change and the ongoing development of the telecommunications sector in the global market. In this sector, churn analysis techniques are commonly used for analysing why some customers terminate their service subscriptions prematurely. In addition, customer churn is utmost significant in this sector since it causes to important business loss. Many companies make various researches in order to prevent losses while increasing customer loyalty. Although a large quantity of accumulated data is available in this sector, their usefulness is limited by data quality and relevance. In this paper, a cost-sensitive feature selection framework is developed aiming to obtain the feature reducts to predict customer churn. The framework is a cost based optional pre-processing stage to remove redundant features for churn management. In addition, this cost-based feature selection algorithm is applied in a telecommunication company in Turkey and the results obtained with this algorithm.
Keywords: Churn prediction, data mining, decision-theoretic rough set, feature selection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17672071 Sound Absorption of Arenga Pinnata Natural Fiber
Authors: Lindawati Ismail, Mohd. Imran Ghazali, Shahruddin Mahzan, Ahmad Mujahid Ahmad Zaidi
Abstract:
Arenga pinnata is an abundantly natural fiber that can be used for sound proof material. However, the scientific data of acoustics properties of Arenga pinnata was not available yet. In this study the sound absorption of pure arenga pinnata was measured. The thickness of Arenga pinnata was varied in 10 mm, 20 mm, 30mm, and 40mm. This work was carried out to investigate the potential of using Arenga pinnata fiber as raw material for sound absorbing material. Impedance Tube Method was used to measure sound absorption coefficient (α). The Measurements was done in accordance with ASTM E1050-98, that is the standard test method for impedance and absorption of acoustical materials using a tube, two microphones and a digital frequency analysis system . The results showed that sound absorption coefficients of Arenga pinnata were good from 2000 Hz to 5000 Hz within the range of 0.75 – 0.90. The optimum sound absorption coefficient was obtained from the thickness of 40 mm. These results indicated that Arenga pinnata fiber is promising to be used as raw material of sound absorbing material with low cost, light, and biodegradable.
Keywords: Sound absorption, Arenga pinnata, raw material.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 36312070 Analysis of Building Response from Vertical Ground Motions
Authors: George C. Yao, Chao-Yu Tu, Wei-Chung Chen, Fung-Wen Kuo, Yu-Shan Chang
Abstract:
Building structures are subjected to both horizontal and vertical ground motions during earthquakes, but only the horizontal ground motion has been extensively studied and considered in design. Most of the prevailing seismic codes assume the vertical component to be 1/2 to 2/3 of the horizontal one. In order to understand the building responses from vertical ground motions, many earthquakes records are studied in this paper. System identification methods (ARX Model) are used to analyze the strong motions and to find out the characteristics of the vertical amplification factors and the natural frequencies of buildings. Analysis results show that the vertical amplification factors for high-rise buildings and low-rise building are 1.78 and 2.52 respectively, and the average vertical amplification factor of all buildings is about 2. The relationship between the vertical natural frequency and building height was regressed to a suggested formula in this study. The result points out an important message; the taller the building is, the greater chance of resonance of vertical vibration on the building will be.
Keywords: Vertical ground motion, vertical amplification factor, natural frequency, component.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10732069 Reusing Assessments Tests by Generating Arborescent Test Groups Using a Genetic Algorithm
Authors: Ovidiu Domşa, Nicolae Bold
Abstract:
Using Information and Communication Technologies (ICT) notions in education and three basic processes of education (teaching, learning and assessment) can bring benefits to the pupils and the professional development of teachers. In this matter, we refer to these notions as concepts taken from the informatics area and apply them to the domain of education. These notions refer to genetic algorithms and arborescent structures, used in the specific process of assessment or evaluation. This paper uses these kinds of notions to generate subtrees from a main tree of tests related between them by their degree of difficulty. These subtrees must contain the highest number of connections between the nodes and the lowest number of missing edges (which are subtrees of the main tree) and, in the particular case of the non-existence of a subtree with no missing edges, the subtrees which have the lowest (minimal) number of missing edges between the nodes, where a node is a test and an edge is a direct connection between two tests which differs by one degree of difficulty. The subtrees are represented as sequences. The tests are the same (a number coding a test represents that test in every sequence) and they are reused for each sequence of tests.
Keywords: Chromosome, genetic algorithm, subtree, test.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7212068 Adaptive Score Normalization: A Novel Approach for Multimodal Biometric Systems
Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara
Abstract:
Multimodal biometric systems integrate the data presented by multiple biometric sources, hence offering a better performance than the systems based on a single biometric modality. Although the coupling of biometric systems can be done at different levels, the fusion at the scores level is the most common since it has been proven effective than the rest of the fusion levels. However, the scores from different modalities are generally heterogeneous. A step of normalizing the scores is needed to transform these scores into a common domain before combining them. In this paper, we study the performance of several normalization techniques with various fusion methods in a context relating to the merger of three unimodal systems based on the face, the palmprint and the fingerprint. We also propose a new adaptive normalization method that takes into account the distribution of client scores and impostor scores. Experiments conducted on a database of 100 people show that the performances of a multimodal system depend on the choice of the normalization method and the fusion technique. The proposed normalization method has given the best results.
Keywords: Multibiometrics, Fusion, Score level, Score normalization, Adaptive normalization.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35612067 Total Lipid of Mutant Synechococcus sp. PCC 7002
Authors: Azlin S Azmi, Mus’ab Zainal, Sarina Sulaiman, Azura Amid, Zaki Zainudin
Abstract:
Microalgae lipid is a promising feedstock for biodiesel production. The objective of this work was to study growth factors affecting marine mutant Synechococcus sp. (PCC 7002) for high lipid production. Four growth factors were investigated; nitrogen-phosporus-potassium (NPK) concentration, light intensity, temperature and NaNO3 concentration on mutant strain growth and lipid production were studied. Design Expert v8.0 was used to design the experimental and analyze the data. The experimental design selected was Min-Run Res IV which consists of 12 runs and the response surfaces measured were specific growth rate and lipid concentration. The extraction of lipid was conducted by chloroform/methanol solvents system. Based on the study, mutant Synechococcus sp. PCC 7002 gave the highest specific growth rate of 0.0014 h-1 at 0% NPK, 2500 lux, 40oC and 0% NaNO3. On the other hand, the highest lipid concentration was obtained at 0% NPK, 3500 lux, 30oC and 1% NaNO3.
Keywords: Cyanobacteria, lipid, mutant, marine Synechococcus sp. PCC 7002, specific growth rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26802066 A Neural-Network-Based Fault Diagnosis Approach for Analog Circuits by Using Wavelet Transformation and Fractal Dimension as a Preprocessor
Abstract:
This paper presents a new method of analog fault diagnosis based on back-propagation neural networks (BPNNs) using wavelet decomposition and fractal dimension as preprocessors. The proposed method has the capability to detect and identify faulty components in an analog electronic circuit with tolerance by analyzing its impulse response. Using wavelet decomposition to preprocess the impulse response drastically de-noises the inputs to the neural network. The second preprocessing by fractal dimension can extract unique features, which are the fed to a neural network as inputs for further classification. A comparison of our work with [1] and [6], which also employs back-propagation (BP) neural networks, reveals that our system requires a much smaller network and performs significantly better in fault diagnosis of analog circuits due to our proposed preprocessing techniques.
Keywords: Analog circuits, fault diagnosis, tolerance, wavelettransform, fractal dimension, box dimension.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22052065 Dimensionality Reduction of PSSM Matrix and its Influence on Secondary Structure and Relative Solvent Accessibility Predictions
Authors: Rafał Adamczak
Abstract:
State-of-the-art methods for secondary structure (Porter, Psi-PRED, SAM-T99sec, Sable) and solvent accessibility (Sable, ACCpro) predictions use evolutionary profiles represented by the position specific scoring matrix (PSSM). It has been demonstrated that evolutionary profiles are the most important features in the feature space for these predictions. Unfortunately applying PSSM matrix leads to high dimensional feature spaces that may create problems with parameter optimization and generalization. Several recently published suggested that applying feature extraction for the PSSM matrix may result in improvements in secondary structure predictions. However, none of the top performing methods considered here utilizes dimensionality reduction to improve generalization. In the present study, we used simple and fast methods for features selection (t-statistics, information gain) that allow us to decrease the dimensionality of PSSM matrix by 75% and improve generalization in the case of secondary structure prediction compared to the Sable server.
Keywords: Secondary structure prediction, feature selection, position specific scoring matrix.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19462064 Optimisation of Polycyclic AromaticHydrocarbon Removal from Contaminated Soilusing Modified Fenton Treatment
Authors: Venny, S. Gan, H. K. Ng
Abstract:
The performance of modified Fenton (MF) treatment to promote PAH oxidation in artificially contaminated soil was investigated in packed soil column with a hydrogen peroxide (H2O2) delivery system simulating in situ injection. Soil samples were spiked with phenanthrene (low molecular weight PAH) and fluoranthene (high molecular weight PAH) to an initial concentration of 500 mg/kg dried soil each. The effectiveness of process parameters H2O2/soil, iron/soil, chelating agent/soil weight ratios and reaction time were studied using a 24 three level factorial design experiments. Statistically significant quadratic models were developed using Response Surface Methodology (RSM) for degrading PAHs from the soil samples. Optimum operating condition was achieved at mild range of H2O2/soil, iron/soil and chelating agent/soil weight ratios, indicating cost efficient method for treating highly contaminated lands.Keywords: Fenton, polycyclic aromatic hydrocarbon, chelate, response surface methodology
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17182063 Power Flow Control with UPFC in Power Transmission System
Authors: Samina Elyas Mubeen, R. K. Nema, Gayatri Agnihotri
Abstract:
In this paper the performance of unified power flow controller is investigated in controlling the flow of po wer over the transmission line. Voltage sources model is utilized to study the behaviour of the UPFC in regulating the active, reactive power and voltage profile. This model is incorporated in Newton Raphson algorithm for load flow studies. Simultaneous method is employed in which equations of UPFC and the power balance equations of network are combined in to one set of non-linear algebraic equations. It is solved according to the Newton raphson algorithm. Case studies are carried on standard 5 bus network. Simulation is done in Matlab. The result of network with and without using UPFC are compared in terms of active and reactive power flows in the line and active and reactive power flows at the bus to analyze the performance of UPFC.Keywords: Newton-Raphson algorithm, Load flow, Unified power flow controller, Voltage source model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42952062 The Biomechanics of Cycling with a Transtibial Prosthesis: A Case Study of a Professional Cyclist
Authors: D. Koutny, D. Palousek, P. Stoklasek, J. Rosicky, L. Tepla, M. Prochazkova, Z. Svoboda, P. Krejci
Abstract:
The article deals with biomechanics of cyclist with unilateral transtibial amputation. Transtibial amputation completely removes ankle and part of muscles of a lower leg which are responsible for production of force during pedaling and causes significant geometric and power asymmetry between the limbs during cycling movement. The primary goal of this work is to assess the effects of length adjustment of the crank on the kinematics and muscle activity of cyclist. The paper presents experimental work, which aims to find a suitable ratio of the length of kinematic components to improve overall athletic performance. The study presents the results of the kinematic analysis of the cycling movement with different crank length realized by tracking camera system together with the results of muscle activity measurements captured by electromyography and measurement of forces in the cranks by strain gauges.
Keywords: Amputation, electromyography, kinematics of cycling, leg asymmetry, motion capture, transtibial prosthesis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35862061 A Genetic Algorithm Based Classification Approach for Finding Fault Prone Classes
Authors: Parvinder S. Sandhu, Satish Kumar Dhiman, Anmol Goyal
Abstract:
Fault-proneness of a software module is the probability that the module contains faults. A correlation exists between the fault-proneness of the software and the measurable attributes of the code (i.e. the static metrics) and of the testing (i.e. the dynamic metrics). Early detection of fault-prone software components enables verification experts to concentrate their time and resources on the problem areas of the software system under development. This paper introduces Genetic Algorithm based software fault prediction models with Object-Oriented metrics. The contribution of this paper is that it has used Metric values of JEdit open source software for generation of the rules for the classification of software modules in the categories of Faulty and non faulty modules and thereafter empirically validation is performed. The results shows that Genetic algorithm approach can be used for finding the fault proneness in object oriented software components.Keywords: Genetic Algorithms, Software Fault, Classification, Object Oriented Metrics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22972060 Experimental Comparison of Combustion Characteristic and Pollutant Emission of Gas Oil and Biodiesel
Authors: S. Baghdar Hosseini, K. Bashirnezhad, A. R. Moghiman, Y. Khazraii, N. Nikoofal
Abstract:
The increasing industrialization and motorization of the world has led to a steep rise for the demand of petroleum-based fuels. Petroleum-based fuels are obtained from limited reserves. These finite reserves are highly concentrated in certain regions of the world. Therefore, those countries not having these resources are facing energy/foreign exchange crisis, mainly due to the import of crude petroleum. Hence, it is necessary to look for alternative fuels which can be produced from resources available locally within the country such as alcohol, biodiesel, vegetable oils etc. Biodiesel is a renewable, domestically produced fuel that has been shown to reduce particulate, hydrocarbon, and carbon monoxide emissions from combustion. In the present study an experimental investigation on emission characteristic of a liquid burner system operating on several percentage of biodiesel and gas oil is carried out. Samples of exhaust gas are analysed with Testo 350 Xl. The results show that biodiesel can lower some pollutant such as CO, CO2 and particulate matter emissions while NOx emission would increase in comparison with gas oil. The results indicate there may be benefits to using biodiesel in industrial processes.
Keywords: Biodiesel, combustion, gas oil, pollutant.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23632059 Fast Database Indexing for Large Protein Sequence Collections Using Parallel N-Gram Transformation Algorithm
Authors: Jehad A. H. Hammad, Nur'Aini binti Abdul Rashid
Abstract:
With the rapid development in the field of life sciences and the flooding of genomic information, the need for faster and scalable searching methods has become urgent. One of the approaches that were investigated is indexing. The indexing methods have been categorized into three categories which are the lengthbased index algorithms, transformation-based algorithms and mixed techniques-based algorithms. In this research, we focused on the transformation based methods. We embedded the N-gram method into the transformation-based method to build an inverted index table. We then applied the parallel methods to speed up the index building time and to reduce the overall retrieval time when querying the genomic database. Our experiments show that the use of N-Gram transformation algorithm is an economical solution; it saves time and space too. The result shows that the size of the index is smaller than the size of the dataset when the size of N-Gram is 5 and 6. The parallel N-Gram transformation algorithm-s results indicate that the uses of parallel programming with large dataset are promising which can be improved further.Keywords: Biological sequence, Database index, N-gram indexing, Parallel computing, Sequence retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21452058 Simulation of Thin Film Relaxation by Buried Misfit Networks
Authors: A. Derardja
Abstract:
The present work is motivated by the idea that the layer deformation in anisotropic elasticity can be estimated from the theory of interfacial dislocations. In effect, this work which is an extension of a previous approach given by one of the authors determines the anisotropic displacement fields and the critical thickness due to a complex biperiodic network of MDs lying just below the free surface in view of the arrangement of dislocations. The elastic fields of such arrangements observed along interfaces play a crucial part in the improvement of the physical properties of epitaxial systems. New results are proposed in anisotropic elasticity for hexagonal networks of MDs which contain intrinsic and extrinsic stacking faults. We developed, using a previous approach based on the relative interfacial displacement and a Fourier series formulation of the displacement fields, the expressions of elastic fields when there is a possible dissociation of MDs. The numerical investigations in the case of the observed system Si/(111)Si with low twist angles show clearly the effect of the anisotropy and thickness when the misfit networks are dissociated.Keywords: Angular misfit, dislocation networks, plane interfaces, stacking faults.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1498