Search results for: Characteristic function

Authors: S. M. Nigdeli, M. H. Boduroglu

Abstract:

In this study, active tendons with Proportional Integral Derivation type controllers were applied to a SDOF and a MDOF building model. Physical models of buildings were constituted with virtual springs, dampers and rigid masses. After that, equations of motion of all degrees of freedoms were obtained. Matlab Simulink was utilized to obtain the block diagrams for these equations of motion. Parameters for controller actions were found by using a trial method. After earthquake acceleration data were applied to the systems, building characteristics such as displacements, velocities, accelerations and transfer functions were analyzed for all degrees of freedoms. Comparisons on displacement vs. time, velocity vs. time, acceleration vs. time and transfer function (Db) vs. frequency (Hz) were made for uncontrolled and controlled buildings. The results show that the method seems feasible.

Keywords: Active Tendons, Proportional Integral DerivationType Controllers, SDOF, MDOF, Earthquake, Building.

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Authors: Thu Le Thi Bao

Abstract:

Industrial parks have both active roles in promoting economic development, and source of appearance of boarding houses and slums in the adjacent area, lacking infrastructure, causing many social matters. The context of recent pandemic and climate change on a global scale pose issues that need to be resolved for sustainable development. Ho Chi Minh city aims to develop housing for migrant workers to stabilize human resources and at the same time, solve problems of social evils caused by poor living conditions. The paper focuses on the content of renovating existing industrial parks and worker accommodation in Ho Chi Minh city to propose appropriate models, contributing to the goal of urban embellishment and solutions for industrial parks to adapt to decree 29/2008/ND-CP abnormal impact conditions such as pandemics, climate change, crises.

Keywords: Industrial park, social housing, accommodation, distribution centre.

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Authors: Hamza Nejib, Okba Taouali

Abstract:

This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.

Keywords: KLMS, online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS.

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Authors: Toshiaki Yanada, Kazumi Ishikawa

Abstract:

The present paper deals with the analysis and development of noise-reduction transformer that has a filter function for conductive noise transmission. Two types of prototype noise-reduction transformers with two different output voltages are proposed. To determine an optimum design for the noise-reduction transformer, noise attenuation characteristics are discussed based on the experiments and the equivalent circuit analysis. The analysis gives a relation between the circuit parameters and the noise attenuation. High performance step-down noise-reduction transformer for direct power supply to electronics equipment is developed. The input voltage of the transformer is 100 V and the output voltage is 5 V. Frequency characteristics of noise attenuation are discussed, and prevention of pulse noise transmission is demonstrated. Normal mode noise attenuation of this transformer is –80 dB, and common mode exceeds –90 dB. The step-down noise-reduction transformer eliminates pulse noise efficiently.

Keywords: conductive noise, EMC, EMI, noise attenuation, transformer.

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Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

Abstract:

Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN.

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Authors: Broderick Crawford, Ricardo Soto, Natalia Berrios, Eduardo Olguin

Abstract:

In this paper, we present a binary cat swarm optimization for solving the Set covering problem. The set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behavior of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. We illustrate this approach with 65 instances of the problem from the OR-Library. Moreover, we solve this problem with 40 new binarization techniques and we select the technical with the best results obtained. Finally, we make a comparison between results obtained in previous studies and the new binarization technique, that is, with roulette wheel as transfer function and V3 as discretization technique.

Keywords: Binary cat swarm optimization, set covering problem, metaheuristic, binarization methods.

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Authors: M. Alauddin, T. Tsujimoto

Abstract:

Dynamicity of stream channels along with environmental concern is the key issue to address in lowland rivers like Jamuna in Bangladesh. The groins are important structures in attaining the improved river environment, but their effective functioning is not evident yet with the present design. Considering the present demands, an approach through modification of groin configurations is planned to function more natural way in dynamic lowland rivers. Four different configurations including the conventional one are considered in the study, and the changes in hydro- and morpho-dynamics affected by various structures are investigated in the laboratory. Results show that the modified combined groin favors gradual deceleration of flow towards the channel side and minimizes local scour noticeably. This favors stable regular channel and improve environmental functions.

Keywords: Lowland river, dynamicity, river environment, groin configuration, local scour.

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Authors: Muhammad Mujtaba Asad, Razali Bin Hassan, Fahad Sherwani, Insaf Ali Siming

Abstract:

This paper discusses about the findings of preliminary survey on MATLAB software learning among power electronics students. One of the main focuses of power electronics course is on DC to DC boost convertors, because boost convertors are generally used in different industrial and non industrial applications. Population samples of this study were randomly selected final year bachelor of electronics and electrical engineering students from University Tun Hussein Onn Malaysia (UTHM).As per the results from the survey questioner analysis, almost eighty percent students are facing problem and difficulties in Dc to Dc boost convertors experimental understanding without using MATLAB simulink package. As per finding of this study it is clear that MATLAB play an effective and efficient function for better understanding of boost convertors experimental work among power electronics learners.

Keywords: MATLAB, Simulation, Power Electronics, Experimental Work.

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Authors: M. F. Omar, R. A. Salam, R. Abdullah, N. A. Rashid

Abstract:

Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.

Keywords: Simulated annealing, genetic algorithm, sequence alignment, multiple sequence alignment.

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Authors: N. P. Waweru, D. B. O. Konditi, P. K. Langat

Abstract:

Direction of Arrival estimation refers to defining a mathematical function called a pseudospectrum that gives an indication of the angle a signal is impinging on the antenna array. This estimation is an efficient method of improving the quality of service in a communication system by focusing the reception and transmission only in the estimated direction thereby increasing fidelity with a provision to suppress interferers. This improvement is largely dependent on the performance of the algorithm employed in the estimation. Many DOA algorithms exists amongst which are MUSIC, Root-MUSIC and ESPRIT. In this paper, performance of these three algorithms is analyzed in terms of complexity, accuracy as assessed and characterized by the CRLB and memory requirements in various environments and array sizes. It is found that the three algorithms are high resolution and dependent on the operating environment and the array size. 

Keywords: Direction of Arrival, Autocorrelation matrix, Eigenvalue decomposition, MUSIC, ESPRIT, CRLB.

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Authors: B.M.N. Nik Hisyamudin, S. Yokoyama, M. Umemoto

Abstract:

In the current study, we have conducted an experimental investigation on the utilization of electronic arc furnace (EAF) reducing slag for the absorption of CO2 via wet grinding method. It was carried out by various grinding conditions. The slag was ground in the vibrating ball mill in the presence of CO2 and pure water under ambient temperature. The reaction behavior was monitored with constant pressure method, and the changes of experimental systems volume as a function of grinding time were measured. It was found that the CO2 absorption occurred as soon as the grinding started. The CO2 absorption was significantly increased in the case of wet grinding compare to the dry grinding. Generally, the amount of CO2 absorption increased as the amount of water, weight of slag and initial pressure increased. However, it was decreased when the amount of water exceeds 200ml and when smaller balls were used. The absorption of CO2 occurred simultaneously with the start of the grinding and it stopped when the grinding was stopped. According to this research, the CO2 reacted with the CaO inside the slag, forming CaCO3.

Keywords: CO2 absorption, EAF reducing slag, vibration ball mill, wet grinding.

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Authors: Rana M. Zeina, Laila AL-Ayadhi, Shahid Bashir

Abstract:

Cognitive symptoms and behavioral symptoms may, in fact, overlap and be related to the level of the general cognitive function. We have measured the behavioral aspects of autism and its correlation to the cognitive ability in 30 children with ASD. We used a neuropsychological Battery CANTAB eclipse to evaluate the ASD children's cognitive ability. Individuals with ASD and challenging behaviors showed significant correlation between some cognitive abilities and Motor aspects. Based on these findings, we can conclude that the motor behavioral problems in autism affect specific cognitive abilities in ASDs such as comprehension, learning, reversal, acquisition, attention set shifting, and speed of reaction to one stimulus. Future researches should also focus on the relationship between motor stereotypes and other subtypes of repetitive behaviors, such as verbal stereotypes, ritual routine adherence, and the use of different types of CANTAB tests.

Keywords: Autism, Cognitive ability, Motor Behavior, and Neuropsychological battery.

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Authors: Karim Kemih, Yacine Yaiche, Malek Benslama

Abstract:

To establish optical communication between any two satellites, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is the use of very small transmitter beam divergence angles of too narrow divergence angle is that the transmitter beam may sometimes miss the receiver satellite, due to pointing vibrations. In this paper we propose the use of genetic algorithm to optimize the BER as function of transmitter optics aperture.

Keywords: Optical Satellite Communication, Genetic Algorithm, Transmitter Optics Aperture

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Authors: G.H. Farrahi, S.A. Faghidian, D.J. Smith

Abstract:

A thin layer on the component surface can be found with high tensile residual stresses, due to turning operations, which can dangerously affect the fatigue performance of the component. In this paper an analytical approach is presented to reconstruct the residual stress field from a limited incomplete set of measurements. Airy stress function is used as the primary unknown to directly solve the equilibrium equations and satisfying the boundary conditions. In this new method there exists the flexibility to impose the physical conditions that govern the behavior of residual stress to achieve a meaningful complete stress field. The analysis is also coupled to a least squares approximation and a regularization method to provide stability of the inverse problem. The power of this new method is then demonstrated by analyzing some experimental measurements and achieving a good agreement between the model prediction and the results obtained from residual stress measurement.

Keywords: Residual stress, Limited measurements, Inverse problems, Turning process.

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Authors: Tariq T. Darabseh

Abstract:

The transient thermoelastic response of thick hollow cylinder made of functionally graded material under thermal loading is studied. The generalized coupled thermoelasticity based on the Green-Lindsay model is used. The thermal and mechanical properties of the functionally graded material are assumed to be varied in the radial direction according to a power law variation as a function of the volume fractions of the constituents. The thermal and elastic governing equations are solved by using Galerkin finite element method. All the finite element calculations were done by using commercial finite element program FlexPDE. The transient temperature, radial displacement, and thermal stresses distribution through the radial direction of the cylinder are plotted.

Keywords: Finite element method, thermal stresses, Green-Lindsay theory, functionally graded material.

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Authors: Mehmet Bozca

Abstract:

Singular value decomposition based optimisation of geometric design parameters of a 5-speed gearbox is studied. During the optimisation, a four-degree-of freedom torsional vibration model of the pinion gear-wheel gear system is obtained and the minimum singular value of the transfer matrix is considered as the objective functions. The computational cost of the associated singular value problems is quite low for the objective function, because it is only necessary to compute the largest and smallest singular values (μmax and μmin) that can be achieved by using selective eigenvalue solvers; the other singular values are not needed. The design parameters are optimised under several constraints that include bending stress, contact stress and constant distance between gear centres. Thus, by optimising the geometric parameters of the gearbox such as, the module, number of teeth and face width it is possible to obtain a light-weight-gearbox structure. It is concluded that the all optimised geometric design parameters also satisfy all constraints.

Keywords: Singular value, optimisation, gearbox, torsional vibration.

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Authors: Yury Nikulin

Abstract:

A multicriteria linear programming problem with integer variables and parameterized optimality principle "from lexicographic to Slater" is considered. A situation in which initial coefficients of penalty cost functions are not fixed but may be potentially a subject to variations is studied. For any efficient solution, appropriate measures of the quality are introduced which incorporate information about variations of penalty cost function coefficients. These measures correspond to the so-called stability and accuracy functions defined earlier for efficient solutions of a generic multicriteria combinatorial optimization problem with Pareto and lexicographic optimality principles. Various properties of such functions are studied and maximum norms of perturbations for which an efficient solution preserves the property of being efficient are calculated.

Keywords: Stability and accuracy, multicriteria optimization, lexicographic optimality.

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Authors: S. Sarumathi, N. Shanthi, P. Ranjetha

Abstract:

Data mining is the procedure of determining interesting patterns from the huge amount of data. With the intention of accessing the data faster the most supporting processes needed is clustering. Clustering is the process of identifying similarity between data according to the individuality present in the data and grouping associated data objects into clusters. Cluster ensemble is the technique to combine various runs of different clustering algorithms to obtain a general partition of the original dataset, aiming for consolidation of outcomes from a collection of individual clustering outcomes. The performances of clustering ensembles are mainly affecting by two principal factors such as diversity and quality. This paper presents the overview about the different cluster ensemble algorithm along with their methods used in cluster ensemble to improve the diversity and quality in the several cluster ensemble related papers and shows the comparative analysis of different cluster ensemble also summarize various cluster ensemble methods. Henceforth this clear analysis will be very useful for the world of clustering experts and also helps in deciding the most appropriate one to determine the problem in hand.

Keywords: Cluster Ensemble, Consensus Function, CSPA, Diversity, HGPA, MCLA.

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Authors: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: Mohammed S. ALSaidi, John P. Mo

Abstract:

Modern engineering assets are complex and very high in value. They are expected to function for years to come, with ability to handle the change in technology and ageing modification. The aging of an engineering asset and continues increase of vendors and contractors numbers forces the asset operation management (or Owner) to design an asset system which can capture these changes. Furthermore, an accurate performance measurement and risk evaluation processes are highly needed. Therefore, this paper explores the nature of the asset management system performance evaluation for an engineering asset based on the System Support Engineering (SSE) principles. The research work explores the asset support system from a range of perspectives, interviewing managers from across a refinery organization. The factors contributing to complexity of an asset management system are described in context which clusters them into several key areas. It is proposed that SSE framework may then be used as a tool for analysis and management of asset. The paper will conclude with discussion of potential application of the framework and opportunities for future research.

Keywords: Asset management, performance, evaluation.

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Authors: Saeed Mian Qaisar, Laurent Fesquet, Marc Renaudin

Abstract:

Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.

Keywords: Level Crossing Sampling, Activity Selection, Adaptive Resolution Analysis, Computational Complexity

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Authors: Mina Alibeigi, Sattar Hashemi, Ali Hamzeh

Abstract:

Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. In this paper, we propose a new unsupervised feature selection method which will remove redundant features from the original feature space by the use of probability density functions of various features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several datasets derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both classification accuracy and the number of selected features.

Keywords: Feature, Feature Selection, Filter, Probability Density Function

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Authors: Omid Borazjani, Mahmoud Roosta, Khodakhast Isapour, Ali Reza Rajabi

Abstract:

This paper presents an application of Artificial Neural Network (ANN) algorithm for improving power system voltage stability. The training data is obtained by solving several normal and abnormal conditions using the Linear Programming technique. The selected objective function gives minimum deviation of the reactive power control variables, which leads to the maximization of minimum Eigen value of load flow Jacobian. The considered reactive power control variables are switchable VAR compensators, OLTC transformers and excitation of generators. The method has been implemented on a modified IEEE 30-bus test system. The results obtain from the test clearly show that the trained neural network is capable of improving the voltage stability in power system with a high level of precision and speed.

Keywords: Artificial Neural Network (ANN), Load Flow, Voltage Stability, Power Systems.

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Authors: E T. Rakgati, E. Matlotse

Abstract:

In this paper the principle, basic torque theory and design optimisation of a six-phase reluctance dc machine are considered. A trapezoidal phase current waveform for the machine drive is proposed and evaluated to minimise ripple torque. Low cost normal laminated salient-pole rotors with and without slits and chamfered poles are investigated. The six-phase machine is optimised in multi-dimensions by linking the finite-element analysis method directly with an optimisation algorithm; the objective function is to maximise the torque per copper losses of the machine. The armature reaction effect is investigated in detail and found to be severe. The measured and calculated torque performances of a 35 kW optimum designed six-phase reluctance dc machine drive are presented.

Keywords: Reluctance dc machine, current waveform, design optimisation, finite element analysis, armature reaction effect.

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Authors: Nemat Abazari, Ilgin Sager

Abstract:

In this paper smooth trajectories are computed in the Lie group SO(2, 1) as a motion planning problem by assigning a Frenet frame to the rigid body system to optimize the cost function of the elastic energy which is spent to track a timelike curve in Minkowski space. A method is proposed to solve a motion planning problem that minimizes the integral of the Lorentz inner product of Darboux vector of a timelike curve. This method uses the coordinate free Maximum Principle of Optimal control and results in the theory of integrable Hamiltonian systems. The presence of several conversed quantities inherent in these Hamiltonian systems aids in the explicit computation of the rigid body motions.

Keywords: Optimal control, Hamiltonian vector field, Darboux vector, maximum principle, lie group, rigid body motion, Lorentz metric.

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Authors: Randy Gomez, Keisuke Nakamura, Kazuhiro Nakadai

Abstract:

Distant-talking voice-based HCI system suffers from performance degradation due to mismatch between the acoustic speech (runtime) and the acoustic model (training). Mismatch is caused by the change in the power of the speech signal as observed at the microphones. This change is greatly influenced by the change in distance, affecting speech dynamics inside the room before reaching the microphones. Moreover, as the speech signal is reflected, its acoustical characteristic is also altered by the room properties. In general, power mismatch due to distance is a complex problem. This paper presents a novel approach in dealing with distance-induced mismatch by intelligently sensing instantaneous voice power variation and compensating model parameters. First, the distant-talking speech signal is processed through microphone array processing, and the corresponding distance information is extracted. Distance-sensitive Gaussian Mixture Models (GMMs), pre-trained to capture both speech power and room property are used to predict the optimal distance of the speech source. Consequently, pre-computed statistic priors corresponding to the optimal distance is selected to correct the statistics of the generic model which was frozen during training. Thus, model combinatorics are post-conditioned to match the power of instantaneous speech acoustics at runtime. This results to an improved likelihood in predicting the correct speech command at farther distances. We experiment using real data recorded inside two rooms. Experimental evaluation shows voice recognition performance using our method is more robust to the change in distance compared to the conventional approach. In our experiment, under the most acoustically challenging environment (i.e., Room 2: 2.5 meters), our method achieved 24.2% improvement in recognition performance against the best-performing conventional method.

Keywords: Human Machine Interaction, Human Computer Interaction, Voice Recognition, Acoustic Model Compensation, Acoustic Speech Enhancement.

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Authors: Saleh H. Abud, Z. Hassan, F. K. Yam

Abstract:

Characteristics of MSM photodetector based on a porous In_0.08Ga_0.92N thin film were reported. Nanoporous structures of n-type In_0.08Ga_0.92N/AlN/Si thin films were synthesized by photoelectrochemical (PEC) etching at a ratio of 1:4 of HF:C₂H₅OH solution for 15min. The structural and optical properties of pre- and post-etched thin films were investigated. Field emission scanning electron microscope and atomic force microscope images showed that the pre-etched thin film has a sufficiently smooth surface over a large region and the roughness increased for porous film. Blue shift has been observed in photoluminescence emission peak at 300 K for porous sample. The photoluminescence intensity of the porous film indicated that the optical properties have been enhanced. A high work function metals (Pt and Ni) were deposited as a metal contact on the porous films. The rise and recovery times of the devices were investigated at 390nm chopped light. Finally, the sensitivity and quantum efficiency were also studied.

Keywords: Porous InGaN, photoluminescence, SMS photodetector.

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Authors: Rungnapa Taithai, Anant Oonsivilai

Abstract:

This paper presents optimal based damping controllers of Unified Power Flow Controller (UPFC) for improving the damping power system oscillations. The design problem of UPFC damping controller and system configurations is formulated as an optimization with time domain-based objective function by means of Adaptive Tabu Search (ATS) technique. The UPFC is installed in Single Machine Infinite Bus (SMIB) for the performance analysis of the power system and simulated using MATLAB-s simulink. The simulation results of these studies showed that designed controller has an tremendous capability in damping power system oscillations.

Keywords: Adaptive Tabu Search (ATS), damping controller, Single Machine Infinite Bus (SMIB), Unified Power Flow Controller (UPFC).

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Authors: Q. Niu, X. H. Zhou, W. Liu

Abstract:

The cooling channels of injection mould play a crucial role in determining the productivity of moulding process and the product quality. It’s not a simple task to design high quality cooling channels. In this paper, an intelligent cooling channels design system including automatic layout of cooling channels, interference checking and assembly of accessories is studied. Automatic layout of cooling channels using genetic algorithm is analyzed. Through integrating experience criteria of designing cooling channels, considering the factors such as the mould temperature and interference checking, the automatic layout of cooling channels is implemented. The method of checking interference based on distance constraint algorithm and the function of automatic and continuous assembly of accessories are developed and integrated into the system. Case studies demonstrate the feasibility and practicality of the intelligent design system.

Keywords: Injection mould, cooling channel, automatic layout, interference checking.

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Authors: Asim Kumar Pal, Debabrata Nath, Sumit Chakraborty

Abstract:

This paper presents an economic game for sybil detection in a distributed computing environment. Cost parameters reflecting impacts of different sybil attacks are introduced in the sybil detection game. The optimal strategies for this game in which both sybil and non-sybil identities are expected to participate are devised. A cost sharing economic mechanism called Discriminatory Rewarding Mechanism for Sybil Detection is proposed based on this game. A detective accepts a security deposit from each active agent, negotiates with the agents and offers rewards to the sybils if the latter disclose their identity. The basic objective of the detective is to determine the optimum reward amount for each sybil which will encourage the maximum possible number of sybils to reveal themselves. Maintaining privacy is an important issue for the mechanism since the participants involved in the negotiation are generally reluctant to share their private information. The mechanism has been applied to Tor by introducing a reputation scoring function.

Keywords: Game theory, Incentive mechanism, Reputation, Sybil Attack

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