Search results for: Adaptive GOP structure
3077 Study and Evaluation of Added Stresses under Foundation due to Adjacent Structure
Authors: Alireza M. goltabar, Issa shooshpasha , Reza Shamstabar kami , Mostafa Habibi
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Added stresses due to adjacent structure should be considered in foundation design and stress control in soil under the structure. This case is considered less than other cases in design and calculation whereas stresses in implementation are greater than analytical stress. Structure load are transmitted to earth by foundation and role of foundation is propagation of load on the continuous and half extreme soil. This act cause that, present stresses lessen to allowable strength of soil. Some researchers such as Boussinesq and westergaurd by using of some assumption studied on this issue, theorically. Target of this paper is study and evaluation of added stresses under structure due to adjacent structure. For this purpose, by using of assumption, theoric relation and numeral methods, effects of adjacent structure with 4 to 10 storeys on the main structure with 4 storeys are studied and effect of parameters and sensitivity of them are evaluated.Keywords: stress, soil, adjacent structure, foundation, loading.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14143076 Hybrid Feature and Adaptive Particle Filter for Robust Object Tracking
Authors: Xinyue Zhao, Yutaka Satoh, Hidenori Takauji, Shun'ichi Kaneko
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A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera. The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental results show the good performance of the proposed method.Keywords: Hybrid feature, adaptive Particle Filter, robust Object Tracking, Grayscale Arranging Pairs (GAP) feature.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14843075 Performance Analysis and Optimization for Diagonal Sparse Matrix-Vector Multiplication on Machine Learning Unit
Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu
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Efficient matrix-vector multiplication with diagonal sparse matrices is pivotal in a multitude of computational domains, ranging from scientific simulations to machine learning workloads. When encoded in the conventional Diagonal (DIA) format, these matrices often induce computational overheads due to extensive zero-padding and non-linear memory accesses, which can hamper the computational throughput, and elevate the usage of precious compute and memory resources beyond necessity. The ’DIA-Adaptive’ approach, a methodological enhancement introduced in this paper, confronts these challenges head-on by leveraging the advanced parallel instruction sets embedded within Machine Learning Units (MLUs). This research presents a thorough analysis of the DIA-Adaptive scheme’s efficacy in optimizing Sparse Matrix-Vector Multiplication (SpMV) operations. The scope of the evaluation extends to a variety of hardware architectures, examining the repercussions of distinct thread allocation strategies and cluster configurations across multiple storage formats. A dedicated computational kernel, intrinsic to the DIA-Adaptive approach, has been meticulously developed to synchronize with the nuanced performance characteristics of MLUs. Empirical results, derived from rigorous experimentation, reveal that the DIA-Adaptive methodology not only diminishes the performance bottlenecks associated with the DIA format but also exhibits pronounced enhancements in execution speed and resource utilization. The analysis delineates a marked improvement in parallelism, showcasing the DIA-Adaptive scheme’s ability to adeptly manage the interplay between storage formats, hardware capabilities, and algorithmic design. The findings suggest that this approach could set a precedent for accelerating SpMV tasks, thereby contributing significantly to the broader domain of high-performance computing and data-intensive applications.
Keywords: Adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1383074 A Study of Adaptive Fault Detection Method for GNSS Applications
Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee
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This study is purposed to develop an efficient fault detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive noise covariance estimation. Due to the dependence on radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. In the proposed method, the pseudorange and carrier-phase measurement noise covariances are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. The test statistics for fault detection are generated by the estimated measurement noise covariances. To evaluate the fault detection capability, intentional faults were added to the filed-collected measurements. The experiment result shows that the proposed method is efficient in detecting unhealthy measurements and improves GNSS positioning accuracy against fault occurrences.
Keywords: Adaptive estimation, fault detection, GNSS, residual.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25053073 Elitist Self-Adaptive Step-Size Search in Optimum Sizing of Steel Structures
Authors: Oğuzhan Hasançebi, Saeid Kazemzadeh Azad
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Keywords: Structural design optimization, optimal sizing, metaheuristics, self-adaptive step-size search, steel trusses, steel frames.}
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13853072 Vibration Suppression of Timoshenko Beams with Embedded Piezoelectrics Using POF
Authors: T. C. Manjunath, B. Bandyopadhyay
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This paper deals with the design of a periodic output feedback controller for a flexible beam structure modeled with Timoshenko beam theory, Finite Element Method, State space methods and embedded piezoelectrics concept. The first 3 modes are considered in modeling the beam. The main objective of this work is to control the vibrations of the beam when subjected to an external force. Shear piezoelectric sensors and actuators are embedded into the top and bottom layers of a flexible aluminum beam structure, thus making it intelligent and self-adaptive. The composite beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. 4 state space SISO models are thus developed. Periodic Output Feedback (POF) Controllers are designed for the 4 SISO models of the same plant to control the flexural vibrations. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Conclusions are finally drawn.Keywords: Smart structure, Timoshenko beam theory, Periodic output feedback control, Finite Element Method, State space model, SISO, Embedded sensors and actuators, Vibration control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20923071 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
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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 14553070 A Family of Affine Projection Adaptive Filtering Algorithms With Selective Regressors
Authors: Mohammad Shams Esfand Abadi, Nader Hadizadeh Kashani, Vahid Mehrdad
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In this paper we present a general formalism for the establishment of the family of selective regressor affine projection algorithms (SR-APA). The SR-APA, the SR regularized APA (SR-RAPA), the SR partial rank algorithm (SR-PRA), the SR binormalized data reusing least mean squares (SR-BNDR-LMS), and the SR normalized LMS with orthogonal correction factors (SR-NLMS-OCF) algorithms are established by this general formalism. We demonstrate the performance of the presented algorithms through simulations in acoustic echo cancellation scenario.Keywords: Adaptive filter, affine projection, selective regressor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15313069 Adaptive Score Normalization: A Novel Approach for Multimodal Biometric Systems
Authors: Anouar Ben Khalifa, Sami Gazzah, Najoua Essoukri BenAmara
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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 35103068 MARTI and MRSD: Newly Developed Isolation-Damping Devices with Adaptive Hardening for Seismic Protection of Structures
Authors: Murat Dicleli, Ali Salem Milani
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In this paper, a summary of analytical and experimental studies into the behavior of a new hysteretic damper, designed for seismic protection of structures is presented. The Multidirectional Torsional Hysteretic Damper (MRSD) is a patented invention in which a symmetrical arrangement of identical cylindrical steel cores is so configured as to yield in torsion while the structure experiences planar movements due to earthquake shakings. The new device has certain desirable properties. Notably, it is characterized by a variable and controllable-via-design post-elastic stiffness. The mentioned property is a result of MRSD’s kinematic configuration which produces this geometric hardening, rather than being a secondary large-displacement effect. Additionally, the new system is capable of reaching high force and displacement capacities, shows high levels of damping, and very stable cyclic response. The device has gone through many stages of design refinement, multiple prototype verification tests and development of design guide-lines and computer codes to facilitate its implementation in practice. Practicality of the new device, as offspring of an academic sphere, is assured through extensive collaboration with industry in its final design stages, prototyping and verification test programs.Keywords: Seismic, isolation, damper, adaptive stiffness.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19493067 Adaptive E-Learning System Using Fuzzy Logic and Concept Map
Authors: Mesfer Al Duhayyim, Paul Newbury
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This paper proposes an effective adaptive e-learning system that uses a coloured concept map to show the learner's knowledge level for each concept in the chosen subject area. A Fuzzy logic system is used to evaluate the learner's knowledge level for each concept in the domain, and produce a ranked concept list of learning materials to address weaknesses in the learner’s understanding. This system obtains information on the learner's understanding of concepts by an initial pre-test before the system is used for learning and a post-test after using the learning system. A Fuzzy logic system is used to produce a weighted concept map during the learning process. The aim of this research is to prove that such a proposed novel adapted e-learning system will enhance learner's performance and understanding. In addition, this research aims to increase participants' overall understanding of their learning level by providing a coloured concept map of understanding followed by a ranked concepts list of learning materials.
Keywords: Adaptive e-learning system, coloured concept map, fuzzy logic, ranked concept list.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10403066 Identifying Dynamic Structural Parameters of Soil-Structure System Based on Data Recorded during Strong Earthquakes
Authors: Vahidreza Mahmoudabadi, Omid Bahar, Mohammad Kazem Jafari
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In many applied engineering problems, structural analysis is usually conducted by assuming a rigid bed, while imposing the effect of structure bed flexibility can affect significantly on the structure response. This article focuses on investigation and evaluation of the effects arising from considering a soil-structure system in evaluation of dynamic characteristics of a steel structure with respect to elastic and inelastic behaviors. The recorded structure acceleration during Taiwan’s strong Chi-Chi earthquake on different floors of the structure was our evaluation criteria. The respective structure is an eight-story steel bending frame structure designed using a displacement-based direct method assuring weak beam - strong column function. The results indicated that different identification methods i.e. reverse Fourier transform or transfer functions, is capable to determine some of the dynamic parameters of the structure precisely, rather than evaluating all of them at once (mode frequencies, mode shapes, structure damping, structure rigidity, etc.). Response evaluation based on the input and output data elucidated that the structure first mode is not significantly affected, even considering the soil-structure interaction effect, but the upper modes have been changed. Also, it was found that the response transfer function of the different stories, in which plastic hinges have occurred in the structure components, provides similar results.
Keywords: System identification, dynamic characteristics, soil-structure system, bending steel frame structure, displacement-based design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9103065 Discrete and Stationary Adaptive Sub-Band Threshold Method for Improving Image Resolution
Authors: P. Joyce Beryl Princess, Y. Harold Robinson
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Image Processing is a structure of Signal Processing for which the input is the image and the output is also an image or parameter of the image. Image Resolution has been frequently referred as an important aspect of an image. In Image Resolution Enhancement, images are being processed in order to obtain more enhanced resolution. To generate highly resoluted image for a low resoluted input image with high PSNR value. Stationary Wavelet Transform is used for Edge Detection and minimize the loss occurs during Downsampling. Inverse Discrete Wavelet Transform is to get highly resoluted image. Highly resoluted output is generated from the Low resolution input with high quality. Noisy input will generate output with low PSNR value. So Noisy resolution enhancement technique has been used for adaptive sub-band thresholding is used. Downsampling in each of the DWT subbands causes information loss in the respective subbands. SWT is employed to minimize this loss. Inverse Discrete wavelet transform (IDWT) is to convert the object which is downsampled using DWT into a highly resoluted object. Used Image denoising and resolution enhancement techniques will generate image with high PSNR value. Our Proposed method will improve Image Resolution and reached the optimized threshold.Keywords: Image Processing, Inverse Discrete wavelet transform, PSNR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17503064 Performance Analysis of an Adaptive Threshold Hybrid Double-Dwell System with Antenna Diversity for Acquisition in DS-CDMA Systems
Authors: H. Krouma, M. Barkat, K. Kemih, M. Benslama, Y. Yacine
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In this paper, we consider the analysis of the acquisition process for a hybrid double-dwell system with antenna diversity for DS-CDMA (direct sequence-code division multiple access) using an adaptive threshold. Acquisition systems with a fixed threshold value are unable to adapt to fast varying mobile communications environments and may result in a high false alarm rate, and/or low detection probability. Therefore, we propose an adaptively varying threshold scheme through the use of a cellaveraging constant false alarm rate (CA-CFAR) algorithm, which is well known in the field of radar detection. We derive exact expressions for the probabilities of detection and false alarm in Rayleigh fading channels. The mean acquisition time of the system under consideration is also derived. The performance of the system is analyzed and compared to that of a hybrid single dwell system.Keywords: Adaptive threshold, hybrid double-dwell system, CA-CFAR algorithm, DS-CDMA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16703063 A New Hybrid RMN Image Segmentation Algorithm
Authors: Abdelouahab Moussaoui, Nabila Ferahta, Victor Chen
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The development of aid's systems for the medical diagnosis is not easy thing because of presence of inhomogeneities in the MRI, the variability of the data from a sequence to the other as well as of other different source distortions that accentuate this difficulty. A new automatic, contextual, adaptive and robust segmentation procedure by MRI brain tissue classification is described in this article. A first phase consists in estimating the density of probability of the data by the Parzen-Rozenblatt method. The classification procedure is completely automatic and doesn't make any assumptions nor on the clusters number nor on the prototypes of these clusters since these last are detected in an automatic manner by an operator of mathematical morphology called skeleton by influence zones detection (SKIZ). The problem of initialization of the prototypes as well as their number is transformed in an optimization problem; in more the procedure is adaptive since it takes in consideration the contextual information presents in every voxel by an adaptive and robust non parametric model by the Markov fields (MF). The number of bad classifications is reduced by the use of the criteria of MPM minimization (Maximum Posterior Marginal).Keywords: Clustering, Automatic Classification, SKIZ, MarkovFields, Image segmentation, Maximum Posterior Marginal (MPM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13723062 Channel Estimation/Equalization with Adaptive Modulation and Coding over Multipath Faded Channels for WiMAX
Authors: B. Siva Kumar Reddy, B. Lakshmi
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Different order modulations combined with different coding schemes, allow sending more bits per symbol, thus achieving higher throughputs and better spectral efficiencies. However, it must also be noted that when using a modulation technique such as 64- QAM with less overhead bits, better signal-to-noise ratios (SNRs) are needed to overcome any Inter symbol Interference (ISI) and maintain a certain bit error ratio (BER). The use of adaptive modulation allows wireless technologies to yielding higher throughputs while also covering long distances. The aim of this paper is to implement an Adaptive Modulation and Coding (AMC) features of the WiMAX PHY in MATLAB and to analyze the performance of the system in different channel conditions (AWGN, Rayleigh and Rician fading channel) with channel estimation and blind equalization. Simulation results have demonstrated that the increment in modulation order causes to increment in throughput and BER values. These results derived a trade-off among modulation order, FFT length, throughput, BER value and spectral efficiency. The BER changes gradually for AWGN channel and arbitrarily for Rayleigh and Rician fade channels.
Keywords: AMC, CSI, CMA, OFDM, OFDMA, WiMAX.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30563061 An Incomplete Factorization Preconditioner for LMS Adaptive Filter
Authors: Shazia Javed, Noor Atinah Ahmad
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In this paper an efficient incomplete factorization preconditioner is proposed for the Least Mean Squares (LMS) adaptive filter. The proposed preconditioner is approximated from a priori knowledge of the factors of input correlation matrix with an incomplete strategy, motivated by the sparsity patter of the upper triangular factor in the QRD-RLS algorithm. The convergence properties of IPLMS algorithm are comparable with those of transform domain LMS(TDLMS) algorithm. Simulation results show efficiency and robustness of the proposed algorithm with reduced computational complexity.
Keywords: Autocorrelation matrix, Cholesky's factor, eigenvalue spread, Markov input.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17483060 A Study on Fuzzy Adaptive Control of Enteral Feeding Pump
Authors: Seungwoo Kim, Hyojune Chae, Yongrae Jung, Jongwook Kim
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Recent medical studies have investigated the importance of enteral feeding and the use of feeding pumps for recovering patients unable to feed themselves or gain nourishment and nutrients by natural means. The most of enteral feeding system uses a peristaltic tube pump. A peristaltic pump is a form of positive displacement pump in which a flexible tube is progressively squeezed externally to allow the resulting enclosed pillow of fluid to progress along it. The squeezing of the tube requires a precise and robust controller of the geared motor to overcome parametric uncertainty of the pumping system which generates due to a wide variation of friction and slip between tube and roller. So, this paper proposes fuzzy adaptive controller for the robust control of the peristaltic tube pump. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system. Finally, the good control performance, accurate dose rate and robust system stability, of the developed feeding pump is confirmed through experimental and clinic testing.
Keywords: Enteral Feeding Pump, Peristaltic Tube Pump, Fuzzy Adaptive Control, Fuzzy Multi-layered Controller, Look-up Table..
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16133059 Adaptive Helmholtz Resonator in a Hydraulic System
Authors: Lari Kela
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An adaptive Helmholtz resonator was designed and adapted to hydraulics. The resonator was controlled by open- and closed-loop controls so that 20 dB attenuation of the peak-to-peak value of the pulsating pressure was maintained. The closed-loop control was noted to be better, albeit it was slower because of its low pressure and temperature variation, which caused variation in the effective bulk modulus of the hydraulic system. Low-pressure hydraulics contains air, which affects the stiffness of the hydraulics, and temperature variation changes the viscosity of the oil. Thus, an open-loop control loses its efficiency if a condition such as temperature or the amount of air changes after calibration. The instability of the low-pressure hydraulic system reduced the operational frequency range of the Helmholtz resonator when compared with the results of an analytical model. Different dampers for hydraulics are presented. Then analytical models of a hydraulic pipe and a hydraulic pipe with a Helmholtz resonator are presented. The analytical models are based on the wave equation of sound pressure. Finally, control methods and the results of experiments are presented.Keywords: adaptive, damper, hydraulics, pressure, pulsating
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 42713058 Adaptive Conjoint Analysis of Professionals’ Job Preferences
Authors: N. Scheidegger, A. Mueller
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Job preferences are a well-developed research field. Many studies analyze the preferences using simple ratings with a sample of university graduates. The current study analyzes the preferences with a mixed method approach of a qualitative preliminary study and adaptive conjoint-analysis. Preconditions of accepting job offers are clarified for professionals in the industrial sector. It could be shown that, e.g. wages above the average are critical and that career opportunities must be seen broader than merely a focus on formal personnel development programs. The results suggest that, to be effective with their recruitment efforts, employers must take into account key desirable job attributes of their target group.
Keywords: Conjoint analysis, employer attractiveness, job preferences, personnel marketing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9203057 Relaxing Convergence Constraints in Local Priority Hysteresis Switching Logic
Authors: Mubarak Alhajri
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This paper addresses certain inherent limitations of local priority hysteresis switching logic. Our main result establishes that under persistent excitation assumption, it is possible to relax constraints requiring strict positivity of local priority and hysteresis switching constants. Relaxing these constraints allows the adaptive system to reach optimality which implies the performance improvement. The unconstrained local priority hysteresis switching logic is examined and conditions for global convergence are derived.Keywords: Adaptive control, convergence, hysteresis constant, hysteresis switching.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8423056 Model to Support Synchronous and Asynchronous in the Learning Process with An Adaptive Hypermedia System
Authors: Francisca Grimón, Marylin Giugni, Josep Monguet F., Joaquín Fernández, Luis León G.
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In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.
Keywords: Blended Learning, System Adaptive, Model, Clustering Algorithms.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18083055 CompPSA: A Component-Based Pairwise RNA Secondary Structure Alignment Algorithm
Authors: Ghada Badr, Arwa Alturki
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The biological function of an RNA molecule depends on its structure. The objective of the alignment is finding the homology between two or more RNA secondary structures. Knowing the common functionalities between two RNA structures allows a better understanding and a discovery of other relationships between them. Besides, identifying non-coding RNAs -that is not translated into a protein- is a popular application in which RNA structural alignment is the first step A few methods for RNA structure-to-structure alignment have been developed. Most of these methods are partial structure-to-structure, sequence-to-structure, or structure-to-sequence alignment. Less attention is given in the literature to the use of efficient RNA structure representation and the structure-to-structure alignment methods are lacking. In this paper, we introduce an O(N2) Component-based Pairwise RNA Structure Alignment (CompPSA) algorithm, where structures are given as a component-based representation and where N is the maximum number of components in the two structures. The proposed algorithm compares the two RNA secondary structures based on their weighted component features rather than on their base-pair details. Extensive experiments are conducted illustrating the efficiency of the CompPSA algorithm when compared to other approaches and on different real and simulated datasets. The CompPSA algorithm shows an accurate similarity measure between components. The algorithm gives the flexibility for the user to align the two RNA structures based on their weighted features (position, full length, and/or stem length). Moreover, the algorithm proves scalability and efficiency in time and memory performance.Keywords: Alignment, RNA secondary structure, pairwise, component-based, data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9283054 Adaptive Multiple Transforms Hardware Architecture for Versatile Video Coding
Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi
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The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.
Keywords: AMT, DCT II, hardware, transform, VVC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5313053 A Simplified Adaptive Decision Feedback Equalization Technique for π/4-DQPSK Signals
Authors: V. Prapulla, A. Mitra, R. Bhattacharjee, S. Nandi
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We present a simplified equalization technique for a π/4 differential quadrature phase shift keying ( π/4 -DQPSK) modulated signal in a multipath fading environment. The proposed equalizer is realized as a fractionally spaced adaptive decision feedback equalizer (FS-ADFE), employing exponential step-size least mean square (LMS) algorithm as the adaptation technique. The main advantage of the scheme stems from the usage of exponential step-size LMS algorithm in the equalizer, which achieves similar convergence behavior as that of a recursive least squares (RLS) algorithm with significantly reduced computational complexity. To investigate the finite-precision performance of the proposed equalizer along with the π/4 -DQPSK modem, the entire system is evaluated on a 16-bit fixed point digital signal processor (DSP) environment. The proposed scheme is found to be attractive even for those cases where equalization is to be performed within a restricted number of training samples.Keywords: Adaptive decision feedback equalizer, Fractionally spaced equalizer, π/4 DQPSK signal, Digital signal processor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 56893052 Tipover Stability Enhancement of Wheeled Mobile Manipulators Using an Adaptive Neuro- Fuzzy Inference Controller System
Authors: A. Ghaffari, A. Meghdari, D. Naderi, S. Eslami
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In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector and the vehicle. The controller creates proper configurations for the manipulator to prevent the robot from being overturned. The optimal configuration and thus the most favorable control are obtained through soft computing approaches including a combination of genetic algorithm, neural networks, and fuzzy logic. The proposed algorithm, in this paper, is that a look-up table is designed by employing the obtained values from the genetic algorithm in order to minimize the performance index and by using this data base, rule bases are designed for the ANFIS controller and will be exerted on the actuators to enhance the tipover stability of the mobile manipulator. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm.Keywords: Mobile Manipulator, Tipover Stability Enhancement, Adaptive Neuro-Fuzzy Inference Controller System, Soft Computing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19283051 Adaptive Filtering of Heart Rate Signals for an Improved Measure of Cardiac Autonomic Control
Authors: Desmond B. Keenan, Paul Grossman
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In order to provide accurate heart rate variability indices of sympathetic and parasympathetic activity, the low frequency and high frequency components of an RR heart rate signal must be adequately separated. This is not always possible by just applying spectral analysis, as power from the high and low frequency components often leak into their adjacent bands. Furthermore, without the respiratory spectra it is not obvious that the low frequency component is not another respiratory component, which can appear in the lower band. This paper describes an adaptive filter, which aids the separation of the low frequency sympathetic and high frequency parasympathetic components from an ECG R-R interval signal, enabling the attainment of more accurate heart rate variability measures. The algorithm is applied to simulated signals and heart rate and respiratory signals acquired from an ambulatory monitor incorporating single lead ECG and inductive plethysmography sensors embedded in a garment. The results show an improvement over standard heart rate variability spectral measurements.Keywords: Heart rate variability, vagal tone, sympathetic, parasympathetic, spectral analysis, adaptive filter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17093050 Protein Secondary Structure Prediction
Authors: Manpreet Singh, Parvinder Singh Sandhu, Reet Kamal Kaur
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Protein structure determination and prediction has been a focal research subject in the field of bioinformatics due to the importance of protein structure in understanding the biological and chemical activities of organisms. The experimental methods used by biotechnologists to determine the structures of proteins demand sophisticated equipment and time. A host of computational methods are developed to predict the location of secondary structure elements in proteins for complementing or creating insights into experimental results. However, prediction accuracies of these methods rarely exceed 70%.Keywords: Protein, Secondary Structure, Prediction, DNA, RNA.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13433049 Shot Detection Using Modified Dugad Model
Authors: Lenka Krulikovská, Jaroslav Polec
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In this paper we present a modification to existed model of threshold for shot cut detection, which is able to adapt itself to the sequence statistics and operate in real time, because it use for calculation only previously evaluated frames. The efficiency of proposed modified adaptive threshold scheme was verified through extensive test experiment with several similarity metrics and achieved results were compared to the results reached by the original model. According to results proposed threshold scheme reached higher accuracy than existed original model.
Keywords: Abrupt cut, shot cut detection, adaptive threshold.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14903048 Performance Evaluation of an ANC-based Hybrid Algorithm for Multi-target Wideband Active Sonar Echolocation System
Authors: Jason Chien-Hsun Tseng
Abstract:
This paper evaluates performances of an adaptive noise cancelling (ANC) based target detection algorithm on a set of real test data supported by the Defense Evaluation Research Agency (DERA UK) for multi-target wideband active sonar echolocation system. The hybrid algorithm proposed is a combination of an adaptive ANC neuro-fuzzy scheme in the first instance and followed by an iterative optimum target motion estimation (TME) scheme. The neuro-fuzzy scheme is based on the adaptive noise cancelling concept with the core processor of ANFIS (adaptive neuro-fuzzy inference system) to provide an effective fine tuned signal. The resultant output is then sent as an input to the optimum TME scheme composed of twogauge trimmed-mean (TM) levelization, discrete wavelet denoising (WDeN), and optimal continuous wavelet transform (CWT) for further denosing and targets identification. Its aim is to recover the contact signals in an effective and efficient manner and then determine the Doppler motion (radial range, velocity and acceleration) at very low signal-to-noise ratio (SNR). Quantitative results have shown that the hybrid algorithm have excellent performance in predicting targets- Doppler motion within various target strength with the maximum false detection of 1.5%.Keywords: Wideband Active Sonar Echolocation, ANC Neuro-Fuzzy, Wavelet Denoise, CWT, Hybrid Algorithm.
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