Search results for: Adaptive beam forming
869 Microbiological Contamination of Outdoor Air in Marine Durres's Harbour, Albania
Authors: Laura Gjyli, Pirro Prifti, Lindita Mukli, Silvana Gjyli, Irida Ikonomi, Jerina Kolitari
Abstract:
Microbial air contamination of the outdoor air in Marine Durres-s Harbour (Durres, Albania) was estimated by sedimentation technique in August-October 2008. The sampling areas were: Ferry Terminal (FT), Fishery Harbor (FH), East Zone (EZ), Fuel Quay (FQ) and Apollonian Beach (AB). The aim of this study was to measure the number of aerobic plate count (mesophilic aerobic bacteria) and fungi (yeasts and molds) in the outdoor air in these areas. The number of colonies that were formed determines the number of cells at the moment in the outdoor air; respectively the number of mesophilic aerobic bacteria and yeasts and molds. The measure of bacteria and fungi used is CFU (Colony Forming Units) per Petri dish. It is said that marine harbours are very polluted areas. The aim of study was the definition of mesophilic aerobic bacteria and yeasts and molds number, and the comparison of microorganisms number in air sampling areas.
Keywords: Air microbiology, colony forming units, Marine Durres's Harbour, mesophilic aerobic bacteria, outdoor air, yeasts and molds.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2742868 Mamdani Model based Adaptive Neural Fuzzy Inference System and its Application
Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang
Abstract:
Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5244867 A Method for 3D Mesh Adaptation in FEA
Authors: S. Sfarni, E. Bellenger, J. Fortin, M. Guessasma
Abstract:
The use of the mechanical simulation (in particular the finite element analysis) requires the management of assumptions in order to analyse a real complex system. In finite element analysis (FEA), two modeling steps require assumptions to be able to carry out the computations and to obtain some results: the building of the physical model and the building of the simulation model. The simplification assumptions made on the analysed system in these two steps can generate two kinds of errors: the physical modeling errors (mathematical model, domain simplifications, materials properties, boundary conditions and loads) and the mesh discretization errors. This paper proposes a mesh adaptive method based on the use of an h-adaptive scheme in combination with an error estimator in order to choose the mesh of the simulation model. This method allows us to choose the mesh of the simulation model in order to control the cost and the quality of the finite element analysis.
Keywords: Finite element, discretization errors, adaptivity.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1478866 Nonlinear Dynamic Modeling and Active Vibration Control of a System with Fuel Sloshing
Authors: A. A. Jafari, A. M. Khoshnood, J. Roshanian
Abstract:
Attitude control of aerospace system with liquid containers may face to a problem associate with fuel sloshing. The sloshing phenomena can degrade the stability of control system and in the worst case, interaction between the attitude control system and fuel vibration leading to resonance. In this paper, a full process of nonlinear dynamic modeling of an aerospace launch vehicle with fuel sloshing is given. Then, a new control system based on model reference adaptive filter is proposed and its algorithm is extracted. This controller implemented on the main attitude control system. Finally, numerical simulation of nonlinear model and control system is carried out to examine the performance of the new controller. Results of simulations show that the inconvenient effects of the fuel sloshing by augmenting this control system are reduced and attitude control system performs, satisfactorily.
Keywords: nonlinear dynamic modeling, fuel sloshing, vibration control, model reference, adaptive filter
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2298865 Simulating Discrete Time Model Reference Adaptive Control System with Great Initial Error
Authors: Bubaker M. F. Bushofa, Abdel Hafez A. Azab
Abstract:
This article is based on the technique which is called Discrete Parameter Tracking (DPT). First introduced by A. A. Azab [8] which is applicable for less order reference model. The order of the reference model is (n-l) and n is the number of the adjustable parameters in the physical plant. The technique utilizes a modified gradient method [9] where the knowledge of the exact order of the nonadaptive system is not required, so, as to eliminate the identification problem. The applicability of the mentioned technique (DPT) was examined through the solution of several problems. This article introduces the solution of a third order system with three adjustable parameters, controlled according to second order reference model. The adjustable parameters have great initial error which represent condition. Computer simulations for the solution and analysis are provided to demonstrate the simplicity and feasibility of the technique.Keywords: Adaptive Control System, Discrete Parameter Tracking, Discrete Time Model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1066864 Approach for an Integrative Technology Assessment Method Combining Product Design and Manufacturing Process
Authors: Guenther Schuh, Sebastian Woelk, Daniel Schraknepper, Anders Such
Abstract:
The systematic evaluation of manufacturing technologies with regard to the potential for product designing constitutes a major challenge. Until now, conventional evaluation methods primarily consider the costs of manufacturing technologies. Thus, the potential of manufacturing technologies for achieving additional product design features is not completely captured. To compensate this deficit, final evaluations of new technologies are mainly intuitive in practice. Therefore, an additional evaluation dimension is needed which takes the potential of manufacturing technologies for specific realizable product designs into account. In this paper, we present the approach of an evaluation method for selecting manufacturing technologies with regard to their potential for product designing. This research is done within the Fraunhofer innovation cluster »AdaM« (Adaptive Manufacturing) which targets the development of resource efficient and adaptive manufacturing technology processes for complex turbomachinery components.
Keywords: Manufacturing, product design, production, technology assessment, technology management.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2200863 A Novel Reversible Watermarking Method based on Adaptive Thresholding and Companding Technique
Authors: Nisar Ahmed Memon
Abstract:
Embedding and extraction of a secret information as well as the restoration of the original un-watermarked image is highly desirable in sensitive applications like military, medical, and law enforcement imaging. This paper presents a novel reversible data-hiding method for digital images using integer to integer wavelet transform and companding technique which can embed and recover the secret information as well as can restore the image to its pristine state. The novel method takes advantage of block based watermarking and iterative optimization of threshold for companding which avoids histogram pre and post-processing. Consequently, it reduces the associated overhead usually required in most of the reversible watermarking techniques. As a result, it keeps the distortion small between the marked and the original images. Experimental results show that the proposed method outperforms the existing reversible data hiding schemes reported in the literature.Keywords: Adaptive Thresholding, Companding Technique, Integer Wavelet Transform, Reversible Watermarking
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1869862 Human Facial Expression Recognition using MANFIS Model
Authors: V. Gomathi, Dr. K. Ramar, A. Santhiyaku Jeevakumar
Abstract:
Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 94.29% of classification accuracy.Keywords: Adaptive neuro-fuzzy inference system, Facialexpression, Local binary pattern, Uniform Histogram
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2103861 Effect of Atmospheric Turbulence on AcquisitionTime of Ground to Deep Space Optical Communication System
Authors: Hemani Kaushal, V.K.Jain, Subrat Kar
Abstract:
The performance of ground to deep space optical communication systems is degraded by distortion of the beam as it propagates through the turbulent atmosphere. Turbulence causes fluctuations in the intensity of the received signal which ultimately affects the acquisition time required to acquire and locate the spaceborne target using narrow laser beam. In this paper, performance of free-space optical (FSO) communication system in atmospheric turbulence has been analyzed in terms of acquisition time for coherent and non-coherent modulation schemes. Numerical results presented in graphical and tabular forms show that the acquisition time increases with the increase in turbulence level. This is true for both schemes. The BPSK has lowest acquisition time among all schemes. In non-coherent schemes, M-PPM performs better than the other schemes. With the increase in M, acquisition time becomes lower, but at the cost of increase in system complexity.Keywords: Atmospheric Turbulence, Acquisition Time, BinaryPhase Shift Keying (BPSK), Free-Space Optical (FSO)Communication System, M-ary Pulse Position Modulation (M-PPM), Coherent/Non-coherent Modulation Schemes.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1779860 Analytical Proposal to Damage Assessment of Buried Continuous Pipelines during External Blast Loading
Authors: Danesh Nourzadeh, Sepideh Khorshid, Shiro Takada, Khosrow Bargi
Abstract:
In this paper, transversal vibration of buried pipelines during loading induced by underground explosions is analyzed. The pipeline is modeled as an infinite beam on an elastic foundation, so that soil-structure interaction is considered by means of transverse linear springs along the pipeline. The pipeline behavior is assumed to be ideal elasto-plastic which an ultimate strain value limits the plastic behavior. The blast loading is considered as a point load, considering the affected length at some point of the pipeline, in which the magnitude decreases exponentially with time. A closed-form solution for the quasi-static problem is carried out for both elastic and elasticperfect plastic behaviors of pipe materials. At the end, a comparative study on steel and polyethylene pipes with different sizes buried in various soil conditions, affected by a predefined underground explosion is conducted, in which effect of each parameter is discussed.Keywords: Beam on elastic foundation, Buried pipelines, External explosion, Non-linear quasi-static solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2323859 Clubs Forming on Crazyvote -The Blurred Social Boundary Between Online Communities and the Real World
Authors: Ko-Hsun Huang, Hsiao-Chen You, Yi-Shin Deng
Abstract:
With the rapid growth and development of information and communication technology, the Internet has played a definite and irreplaceable role in people-s social lives in Taiwan like in other countries. In July 2008, on a general social website, an unexpected phenomenon was noticed – that there were more than one hundred users who started forming clubs voluntarily and having face-to-face gatherings for specific purposes. In this study, it-s argued whether or not teenagers- social contact on the Internet is involved in their life context, and tried to reveal the teenagers- social preferences, values, and needs, which merge with and influence teenagers- social activities. Therefore, the study conducts multiple user experience research methods, which include practical observations and qualitative analysis by contextual inquiries and in-depth interviews. Based on the findings, several design implications for software related to social interactions and cultural inheritance are offered. It is concluded that the inherent values of a social behaviors might be a key issue in developing computer-mediated communication or interaction designs in the future.
Keywords: Social Computing, Social Interaction, User-centered Design, Contextual Inquiry.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1604858 Combined Beamforming and Channel Estimation in WCDMA Communication Systems
Authors: Nermin A. Mohamed, Mohamed F. Madkour
Abstract:
We address the problem of joint beamforming and multipath channel parameters estimation in Wideband Code Division Multiple Access (WCDMA) communication systems that employ Multiple-Access Interference (MAI) suppression techniques in the uplink (from mobile to base station). Most of the existing schemes rely on time multiplex a training sequence with the user data. In WCDMA, the channel parameters can also be estimated from a code multiplexed common pilot channel (CPICH) that could be corrupted by strong interference resulting in a bad estimate. In this paper, we present new methods to combine interference suppression together with channel estimation when using multiple receiving antennas by using adaptive signal processing techniques. Computer simulation is used to compare between the proposed methods and the existing conventional estimation techniques.
Keywords: Adaptive arrays, channel estimation, interferencecancellation, wideband code division multiple access (WCDMA).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2315857 Soft Computing Based Cluster Head Selection in Wireless Sensor Network Using Bacterial Foraging Optimization Algorithm
Authors: A. Rajagopal, S. Somasundaram, B. Sowmya, T. Suguna
Abstract:
Wireless Sensor Networks (WSNs) enable new applications and need non-conventional paradigms for the protocol because of energy and bandwidth constraints, In WSN, sensor node’s life is a critical parameter. Research on life extension is based on Low-Energy Adaptive Clustering Hierarchy (LEACH) scheme, which rotates Cluster Head (CH) among sensor nodes to distribute energy consumption over all network nodes. CH selection in WSN affects network energy efficiency greatly. This study proposes an improved CH selection for efficient data aggregation in sensor networks. This new algorithm is based on Bacterial Foraging Optimization (BFO) incorporated in LEACH.Keywords: Bacterial Foraging Optimization (BFO), Cluster Head (CH), Data-aggregation protocols, Low-Energy Adaptive Clustering Hierarchy (LEACH).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3479856 Modulation Identification Algorithm for Adaptive Demodulator in Software Defined Radios Using Wavelet Transform
Authors: P. Prakasam, M. Madheswaran
Abstract:
A generalized Digital Modulation Identification algorithm for adaptive demodulator has been developed and presented in this paper. The algorithm developed is verified using wavelet Transform and histogram computation to identify QPSK and QAM with GMSK and M–ary FSK modulations. It has been found that the histogram peaks simplifies the procedure for identification. The simulated results show that the correct modulation identification is possible to a lower bound of 5 dB and 12 dB for GMSK and QPSK respectively. When SNR is above 5 dB the throughput of the proposed algorithm is more than 97.8%. The receiver operating characteristics (ROC) has been computed to measure the performance of the proposed algorithm and the analysis shows that the probability of detection (Pd) drops rapidly when SNR is 5 dB and probability of false alarm (Pf) is smaller than 0.3. The performance of the proposed algorithm has been compared with existing methods and found it will identify all digital modulation schemes with low SNR.
Keywords: Bit Error rate, Receiver Operating Characteristics, Software Defined Radio, Wavelet Transform.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2424855 Adaptive Bidirectional Flow for Image Interpolation and Enhancement
Authors: Shujun Fu, Qiuqi Ruan, Wenqia Wang
Abstract:
Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually the effects of blurred edges and jagged artifacts in the image to some extent. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to sharpen edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (“jaggies") along the tangent directions. In order to preserve image features such as edges, corners and textures, the nonlinear diffusion coefficients are locally adjusted according to the directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Keywords: anisotropic diffusion, bidirectional flow, directional derivatives, edge enhancement, image interpolation, inverse flow, shock filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1538854 Self-Tuning Power System Stabilizer Based on Recursive Least Square Identification and Linear Quadratic Regulator
Authors: J. Ritonja
Abstract:
Available commercial applications of power system stabilizers assure optimal damping of synchronous generator’s oscillations only in a small part of operating range. Parameters of the power system stabilizer are usually tuned for the selected operating point. Extensive variations of the synchronous generator’s operation result in changed dynamic characteristics. This is the reason that the power system stabilizer tuned for the nominal operating point does not satisfy preferred damping in the overall operation area. The small-signal stability and the transient stability of the synchronous generators have represented an attractive problem for testing different concepts of the modern control theory. Of all the methods, the adaptive control has proved to be the most suitable for the design of the power system stabilizers. The adaptive control has been used in order to assure the optimal damping through the entire synchronous generator’s operating range. The use of the adaptive control is possible because the loading variations and consequently the variations of the synchronous generator’s dynamic characteristics are, in most cases, essentially slower than the adaptation mechanism. The paper shows the development and the application of the self-tuning power system stabilizer based on recursive least square identification method and linear quadratic regulator. Identification method is used to calculate the parameters of the Heffron-Phillips model of the synchronous generator. On the basis of the calculated parameters of the synchronous generator’s mathematical model, the synthesis of the linear quadratic regulator is carried-out. The identification and the synthesis are implemented on-line. In this way, the self-tuning power system stabilizer adapts to the different operating conditions. A purpose of this paper is to contribute to development of the more effective power system stabilizers, which would replace currently used linear stabilizers. The presented self-tuning power system stabilizer makes the tuning of the controller parameters easier and assures damping improvement in the complete operating range. The results of simulations and experiments show essential improvement of the synchronous generator’s damping and power system stability.
Keywords: Adaptive control, linear quadratic regulator, power system stabilizer, recursive least square identification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1123853 Characterising Effects of Applied Loads on the Mechanical Properties of Formed Steel Sheets
Authors: Esther T. Akinlabi, Stephen A. Akinlabi
Abstract:
The purpose of this research study is to investigate the manner in which various loads affect the mechanical properties of the formed mild steel plates. The investigation focuses on examining the cross-sectional area of the metal plate at the centre of the formed mild steel plate. Six mild steel plates were deformed with different loads. The loads applied on the plates had a magnitude of 5 kg, 10 kg, 15 kg, 20 kg, 25 kg and 30 kg. The radius of the punching die was 120 mm and the loads were applied at room temperature. The investigations established that the applied load causes the Vickers microhardness at the cross-sectional area of the plate to increase due to strain hardening. Hence, the percentage increase of the hardness due to the load was found to be directly proportional to the increase in the load. Furthermore, the tensile test results for the parent material showed that the average Ultimate Tensile Strength (UTS) for the three samples was 308 MPa while the average Yield Strength and Percentage Elongation were 227 MPa and 38 % respectively. Similarly, the UTS of the formed components increased after the deformation of the plate, as such it can be concluded that the forming loads alter the mechanical properties of the materials by improving and strengthening the material properties.
Keywords: Applied load, forming and Mechanical Properties.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1428852 Evaluating Generative Neural Attention Weights-Based Chatbot on Customer Support Twitter Dataset
Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli
Abstract:
Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are increasingly important in automated customer service. These models, adept at recognizing complex relationships between input and output sequences, are essential for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the model’s focus during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the context of chatbots utilizing the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Using the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k = 3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k = 3). These findings emphasize the crucial influence of selecting an appropriate attention-scoring function to enhance the performance of seq2seq models for chatbots, particularly highlighting the model integrating tanh activation as a promising approach to improving chatbot quality in customer support contexts.
Keywords: Attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 90851 Innovative Design Considerations for Adaptive Spacecraft
Authors: K. Parandhama Gowd
Abstract:
Space technologies have changed the way we live in the present day society and manage many aspects of our daily affairs through Remote sensing, Navigation & Communications. Further, defense and military usage of spacecraft has increased tremendously along with civilian purposes. The number of satellites deployed in space in Low Earth Orbit (LEO), Medium Earth Orbit (MEO), and the Geostationary Orbit (GEO) has gone up. The dependency on remote sensing and operational capabilities are most invariably to be exploited more and more in future. Every country is acquiring spacecraft in one way or other for their daily needs, and spacecraft numbers are likely to increase significantly and create spacecraft traffic problems. The aim of this research paper is to propose innovative design concepts for adaptive spacecraft. The main idea here is to improve existing design methods of spacecraft design and development to further improve upon design considerations for futuristic adaptive spacecraft with inbuilt features for automatic adaptability and self-protection. In other words, the innovative design considerations proposed here are to have future spacecraft with self-organizing capabilities for orbital control and protection from anti-satellite weapons (ASAT). Here, an attempt is made to propose design and develop futuristic spacecraft for 2030 and beyond due to tremendous advancements in VVLSI, miniaturization, and nano antenna array technologies, including nano technologies are expected.
Keywords: Satellites, low earth orbit, medium earth orbit, geostationary earth orbit, self-organizing control system, anti-satellite weapons, orbital control, radar warning receiver, missile warning receiver, laser warning receiver, attitude and orbit control systems, command and data handling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 999850 A Self Adaptive Genetic Based Algorithm for the Identification and Elimination of Bad Data
Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy
Abstract:
The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1346849 Feature Preserving Image Interpolation and Enhancement Using Adaptive Bidirectional Flow
Authors: Shujun Fu, Qiuqi Ruan, Wenqia Wang
Abstract:
Image interpolation is a common problem in imaging applications. However, most interpolation algorithms in existence suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This paper presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines (edges), while a normal diffusion is done to remove artifacts (''jaggies'') along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first and second order directional derivatives of the image. Experimental results on synthetic images and nature images demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.
Keywords: anisotropic diffusion, bidirectional flow, directionalderivatives, edge enhancement, image interpolation, inverse flow, shock filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1498848 Development of Underactuated Robot Hand Using Cross Section Deformation Spring
Authors: Naoki Saito, Daisuke Kon, Toshiyuki Sato
Abstract:
This paper describes an underactuated robot hand operated by low-power actuators. It can grasp objects of various shapes using easy operations. This hand is suitable for use as a lightweight prosthetic hand that can grasp various objects using few input channels. To realize operations using a low-power actuator, a cross section deformation spring is proposed. The design procedure of the underactuated robot finger is proposed to realize an adaptive grasping movement. The validity of this mechanism and design procedure are confirmed through an object grasping experiment. Results demonstrate the effectiveness of across section deformation spring in reducing the actuator power. Moreover, adaptive grasping movement is realized by an easy operation.
Keywords: Robot hand, Underactuated mechanism, Cross section deformation spring, Prosthetic hand.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1667847 Microwave LNA Design Based On Adaptive Network Fuzzy Inference and Evolutionary Optimization
Authors: Samad Nejatian, Vahideh Rezaie, Vahid Asadpour
Abstract:
This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN.Keywords: fuzzy system, low noise amplifier, microwaveamplifier, space mapping
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1796846 A Preliminary Study on the Suitability of Data Driven Approach for Continuous Water Level Modeling
Authors: Muhammad Aqil, Ichiro Kita, Moses Macalinao
Abstract:
Reliable water level forecasts are particularly important for warning against dangerous flood and inundation. The current study aims at investigating the suitability of the adaptive network based fuzzy inference system for continuous water level modeling. A hybrid learning algorithm, which combines the least square method and the back propagation algorithm, is used to identify the parameters of the network. For this study, water levels data are available for a hydrological year of 2002 with a sampling interval of 1-hour. The number of antecedent water level that should be included in the input variables is determined by two statistical methods, i.e. autocorrelation function and partial autocorrelation function between the variables. Forecasting was done for 1-hour until 12-hour ahead in order to compare the models generalization at higher horizons. The results demonstrate that the adaptive networkbased fuzzy inference system model can be applied successfully and provide high accuracy and reliability for river water level estimation. In general, the adaptive network-based fuzzy inference system provides accurate and reliable water level prediction for 1-hour ahead where the MAPE=1.15% and correlation=0.98 was achieved. Up to 12-hour ahead prediction, the model still shows relatively good performance where the error of prediction resulted was less than 9.65%. The information gathered from the preliminary results provide a useful guidance or reference for flood early warning system design in which the magnitude and the timing of a potential extreme flood are indicated.Keywords: Neural Network, Fuzzy, River, Forecasting
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1289845 A Study of Dynamic Clustering Method to Extend the Lifetime of Wireless Sensor Network
Authors: Wernhuar Tarng, Kun-Jie Huang, Li-Zhong Deng, Kun-Rong Hsie, Mingteh Chen
Abstract:
In recent years, the research in wireless sensor network has increased steadily, and many studies were focusing on reducing energy consumption of sensor nodes to extend their lifetimes. In this paper, the issue of energy consumption is investigated and two adaptive mechanisms are proposed to extend the network lifetime. This study uses high-energy-first scheme to determine cluster heads for data transmission. Thus, energy consumption in each cluster is balanced and network lifetime can be extended. In addition, this study uses cluster merging and dynamic routing mechanisms to further reduce energy consumption during data transmission. The simulation results show that the proposed method can effectively extend the lifetime of wireless sensor network, and it is suitable for different base station locations.Keywords: Wireless sensor network, high-energy-first scheme, adaptive mechanisms, network lifetime
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1538844 Face Recognition Based On Vector Quantization Using Fuzzy Neuro Clustering
Authors: Elizabeth B. Varghese, M. Wilscy
Abstract:
A face recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame. A lot of algorithms have been proposed for face recognition. Vector Quantization (VQ) based face recognition is a novel approach for face recognition. Here a new codebook generation for VQ based face recognition using Integrated Adaptive Fuzzy Clustering (IAFC) is proposed. IAFC is a fuzzy neural network which incorporates a fuzzy learning rule into a competitive neural network. The performance of proposed algorithm is demonstrated by using publicly available AT&T database, Yale database, Indian Face database and a small face database, DCSKU database created in our lab. In all the databases the proposed approach got a higher recognition rate than most of the existing methods. In terms of Equal Error Rate (ERR) also the proposed codebook is better than the existing methods.
Keywords: Face Recognition, Vector Quantization, Integrated Adaptive Fuzzy Clustering, Self Organization Map.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2241843 Adaptive Digital Watermarking Integrating Fuzzy Inference HVS Perceptual Model
Authors: Sherin M. Youssef, Ahmed Abouelfarag, Noha M. Ghatwary
Abstract:
An adaptive Fuzzy Inference Perceptual model has been proposed for watermarking of digital images. The model depends on the human visual characteristics of image sub-regions in the frequency multi-resolution wavelet domain. In the proposed model, a multi-variable fuzzy based architecture has been designed to produce a perceptual membership degree for both candidate embedding sub-regions and strength watermark embedding factor. Different sizes of benchmark images with different sizes of watermarks have been applied on the model. Several experimental attacks have been applied such as JPEG compression, noises and rotation, to ensure the robustness of the scheme. In addition, the model has been compared with different watermarking schemes. The proposed model showed its robustness to attacks and at the same time achieved a high level of imperceptibility.Keywords: Watermarking, The human visual system (HVS), Fuzzy Inference System (FIS), Local Binary Pattern (LBP), Discrete Wavelet Transform (DWT).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1818842 Effect of Interior Brick-infill Partitions on the Progressive Collapse Potential of a RC Building: Linear Static Analysis Results
Authors: Meng-Hao Tsai, Tsuei-Chiang Huang
Abstract:
Interior brick-infill partitions are usually considered as non-structural components, and only their weight is accounted for in practical structural design. In this study, the brick-infill panels are simulated by compression struts to clarify their effect on the progressive collapse potential of an earthquake-resistant RC building. Three-dimensional finite element models are constructed for the RC building subjected to sudden column loss. Linear static analyses are conducted to investigate the variation of demand-to-capacity ratio (DCR) of beam-end moment and the axial force variation of the beams adjacent to the removed column. Study results indicate that the brick-infill effect depends on their location with respect to the removed column. As they are filled in a structural bay with a shorter span adjacent to the column-removed line, more significant reduction of DCR may be achieved. However, under certain conditions, the brick infill may increase the axial tension of the two-span beam bridging the removed column.Keywords: Progressive collapse, brick-infill partition, compression strut.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2215841 An Efficient Adaptive Thresholding Technique for Wavelet Based Image Denoising
Authors: D.Gnanadurai, V.Sadasivam
Abstract:
This frame work describes a computationally more efficient and adaptive threshold estimation method for image denoising in the wavelet domain based on Generalized Gaussian Distribution (GGD) modeling of subband coefficients. In this proposed method, the choice of the threshold estimation is carried out by analysing the statistical parameters of the wavelet subband coefficients like standard deviation, arithmetic mean and geometrical mean. The noisy image is first decomposed into many levels to obtain different frequency bands. Then soft thresholding method is used to remove the noisy coefficients, by fixing the optimum thresholding value by the proposed method. Experimental results on several test images by using this method show that this method yields significantly superior image quality and better Peak Signal to Noise Ratio (PSNR). Here, to prove the efficiency of this method in image denoising, we have compared this with various denoising methods like wiener filter, Average filter, VisuShrink and BayesShrink.Keywords: Wavelet Transform, Gaussian Noise, ImageDenoising, Filter Banks and Thresholding.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2907840 Opportunistic Routing with Secure Coded Wireless Multicast Using MAS Approach
Authors: E. Golden Julie, S. Tamil Selvi, Y. Harold Robinson
Abstract:
Many Wireless Sensor Network (WSN) applications necessitate secure multicast services for the purpose of broadcasting delay sensitive data like video files and live telecast at fixed time-slot. This work provides a novel method to deal with end-to-end delay and drop rate of packets. Opportunistic Routing chooses a link based on the maximum probability of packet delivery ratio. Null Key Generation helps in authenticating packets to the receiver. Markov Decision Process based Adaptive Scheduling algorithm determines the time slot for packet transmission. Both theoretical analysis and simulation results show that the proposed protocol ensures better performance in terms of packet delivery ratio, average end-to-end delay and normalized routing overhead.
Keywords: Delay-sensitive data, Markovian Decision Process based Adaptive Scheduling, Opportunistic Routing, Digital Signature authentication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1957