Search results for: predetermined motion time system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 13166

Search results for: predetermined motion time system

7316 Dialect and Gender Variations in the Place and Manner of Articulation of the Korean Fricatives

Authors: Kyung-Im Han

Abstract:

This study examines dialect and gender variations in the place and manner of articulation between the two Korean fricatives, /s/ and /s’/, as produced by speakers of the Daegu and Jeju dialects. The acoustic parameters of center of gravity and skewness for the place of articulation, and the rise time and the amplitude rise slope for the manner of articulation were measured. The study results revealed a gender effect, but no dialect effect, for the center of gravity and the skewness. No main effect for either the gender or dialect was found for the rise time and the amplitude rise slope. These findings indicated that, with regard to the place of articulation, Korean fricative sound differences are a gender distinction, not a dialectal one.

Keywords: Dialect, gender, Korean fricative, manner of articulation, place of articulation, spectral moments.

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7315 Data Acquisition from Cell Phone using Logical Approach

Authors: Keonwoo Kim, Dowon Hong, Kyoil Chung, Jae-Cheol Ryou

Abstract:

Cell phone forensics to acquire and analyze data in the cellular phone is nowadays being used in a national investigation organization and a private company. In order to collect cellular phone flash memory data, we have two methods. Firstly, it is a logical method which acquires files and directories from the file system of the cell phone flash memory. Secondly, we can get all data from bit-by-bit copy of entire physical memory using a low level access method. In this paper, we describe a forensic tool to acquire cell phone flash memory data using a logical level approach. By our tool, we can get EFS file system and peek memory data with an arbitrary region from Korea CDMA cell phone.

Keywords: Forensics, logical method, acquisition, cell phone, flash memory.

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7314 Inhibiting Gene for a Late-Heading Gene Responsible for Photoperiod Sensitivity in Rice (Oryza sativa)

Authors: Amol Dahal, Shunsuke Hori, Haruki Nakazawa, Kazumitsu Onishi, Toshio Kawano, Masayuki Murai

Abstract:

Two indica varieties, IR36 and ‘Suweon 258’ (“S”) are middle-heading in southern Japan. 36U, also middle-heading, is an isogenic line of IR36 carrying Ur1 (Undulate rachis-1) gene. However, late-heading plants segregated in the F2 population from the F1 of S × 36U, and so did in the following generations. The concerning lateness gene is designated as Ex. From the F8 generation, isogenic-line pair of early-heading and late-heading lines, denoted by “E” (ex/ex) and “L” (Ex/Ex), were developed. Genetic analyses of heading time were conducted, using F1s and F2s among L, E, S and 36U. The following inferences were drawn from the experimental results: 1) L, and both of E and 36U harbor Ex and ex, respectively; 2) Besides Ex, S harbors an inhibitor gene to it, i.e. I-Ex which is a novel finding of the present study. 3) Ex is a dominant allele at the E1 locus.

Keywords: Basic vegetative phase, heading time, lateness gene, photoperiod-sensitive phase.

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7313 Visual Odometry and Trajectory Reconstruction for UAVs

Authors: Sandro Bartolini, Alessandro Mecocci, Alessio Medaglini

Abstract:

The growing popularity of systems based on Unmanned Aerial Vehicles (UAVs) is highlighting their vulnerability particularly in relation to the positioning system used. Typically, UAV architectures use the civilian GPS which is exposed to a number of different attacks, such as jamming or spoofing. This is why it is important to develop alternative methodologies to accurately estimate the actual UAV position without relying on GPS measurements only. In this paper we propose a position estimate method for UAVs based on monocular visual odometry. We have developed a flight control system capable of keeping track of the entire trajectory travelled, with a reduced dependency on the availability of GPS signal. Moreover, the simplicity of the developed solution makes it applicable to a wide range of commercial drones. The final goal is to allow for safer flights in all conditions, even under cyber-attacks trying to deceive the drone.

Keywords: Visual odometry, autonomous UAV, position measurement, autonomous outdoor flight.

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7312 Development of Reliable Web-Based Laboratories for Developing Countries

Authors: Teyana S. Sapula, Damian D. Haule

Abstract:

In online context, the design and implementation of effective remote laboratories environment is highly challenging on account of hardware and software needs. This paper presents the remote laboratory software framework modified from ilab shared architecture (ISA). The ISA is a framework which enables students to remotely acccess and control experimental hardware using internet infrastructure. The need for remote laboratories came after experiencing problems imposed by traditional laboratories. Among them are: the high cost of laboratory equipment, scarcity of space, scarcity of technical personnel along with the restricted university budget creates a significant bottleneck on building required laboratory experiments. The solution to these problems is to build web-accessible laboratories. Remote laboratories allow students and educators to interact with real laboratory equipment located anywhere in the world at anytime. Recently, many universities and other educational institutions especially in third world countries rely on simulations because they do not afford the experimental equipment they require to their students. Remote laboratories enable users to get real data from real-time hand-on experiments. To implement many remote laboratories, the system architecture should be flexible, understandable and easy to implement, so that different laboratories with different hardware can be deployed easily. The modifications were made to enable developers to add more equipment in ISA framework and to attract the new developers to develop many online laboratories.

Keywords: Batched, ISA, labserver, servicebroker.

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7311 Intelligent Rescheduling Trains for Air Pollution Management

Authors: Kainat Affrin, P. Reshma, G. Narendra Kumar

Abstract:

Optimization of timetable is the need of the day for the rescheduling and routing of trains in real time. Trains are scheduled in parallel with the road transport vehicles to the same destination. As the number of trains is restricted due to single track, customers usually opt for road transport to use frequently. The air pollution increases as the density of vehicles on road transport is increased. Use of an alternate mode of transport like train helps in reducing air-pollution. This paper mainly aims at attracting the passengers to Train transport by proper rescheduling of trains using hybrid of stop-skip algorithm and iterative convex programming algorithm. Rescheduling of train bi-directionally is achieved on a single track with dynamic dual time and varying stops. Introduction of more trains attract customers to use rail transport frequently, thereby decreasing the pollution. The results are simulated using Network Simulator (NS-2).

Keywords: Air pollution, routing protocol, network simulator, rescheduling.

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7310 Detection and Pose Estimation of People in Images

Authors: Mousa Mojarrad, Amir Masoud Rahmani, Mehrab Mohebi

Abstract:

Detection, feature extraction and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes and the high dimensionality of articulated body models and also the important field in Image, Signal and Vision Computing in recent years. In this paper, four types of people in 2D dimension image will be tested and proposed. The system will extract the size and the advantage of them (such as: tall fat, short fat, tall thin and short thin) from image. Fat and thin, according to their result from the human body that has been extract from image, will be obtained. Also the system extract every size of human body such as length, width and shown them in output.

Keywords: Analysis of Image Processing, Canny Edge Detection, Human Body Recognition, Measurement, Pose Estimation, 2D Human Dimension.

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7309 Performance Evaluation for Weightlifting Lifter by Barbell Trajectory

Authors: Ying-Chen Lin, Ching-Ting Hsu, Wei-Hua Ho

Abstract:

The purpose of this study is to investigate the kinematic characteristics and differences of the snatch barbell trajectory of 53 kg class female weight lifters. We take the 2014 Taiwan College Cup players as examples, and tend to make kinematic applications through the proven weightlifting barbell track system. The competition videos are taken by consumer camcorder with a tripod which set up at the side of the lifter. The results will be discussed in three parts, the first part is various lifting phase, the second part is the compare lifting between success and unsuccessful, and the third part is to compare the outstanding player with the general. Conclusion through the barbell can be used to observe the trajectories of our players lifting the usual process cannot be observed in the presence of malfunction or habits, so that the coach can find the problem and guide the players more accurately. Our system can be applied in practice and competition to increase the resilience of the lifter on the field.

Keywords: Computer aided sport training, Kinematic, Trajectory, Weightlifting.

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7308 An Approach Based on Statistics and Multi-Resolution Representation to Classify Mammograms

Authors: Nebi Gedik

Abstract:

One of the significant and continual public health problems in the world is breast cancer. Early detection is very important to fight the disease, and mammography has been one of the most common and reliable methods to detect the disease in the early stages. However, it is a difficult task, and computer-aided diagnosis (CAD) systems are needed to assist radiologists in providing both accurate and uniform evaluation for mass in mammograms. In this study, a multiresolution statistical method to classify mammograms as normal and abnormal in digitized mammograms is used to construct a CAD system. The mammogram images are represented by wave atom transform, and this representation is made by certain groups of coefficients, independently. The CAD system is designed by calculating some statistical features using each group of coefficients. The classification is performed by using support vector machine (SVM).

Keywords: Wave atom transform, statistical features, multi-resolution representation, mammogram.

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7307 Glutamic Acid Production from Potato by Brevibacterium linens

Authors: Marzieh Moosavi-Nasab, Masoumeh Izadi, Sara Hosseinpour

Abstract:

In this study, the possibility of using potato as a substrate for glutamic acid production by Brevibacterium linens was investigated. For preparation of fermentation medium, potato was hydrolyzed by hydrochloridric acid. The medium contained potato hydrolysate, tween 80, mineral solution, glucose, and potassium hydrogen phosphate. The initial pH of the medium was adjusted to 7-7.5. For achieving the optimum time with maximum yield, the beakers containing the medium and the inoculums were incubated in a rotary water bath flask shaker for one to five days. Thin layer choromatography was used for quantitative and qualitative assay of the glutamic acid produced. The results revealed that as fermentation time increased, pH of the fermentation medium significantly decreased (P<0.05). Furthermore, glutamic acid concentration in fermentation medium increased significantly (P<0.05). The highest amount of the glutamic acid obtained was 5.6 g/l on the forth day of fermentation.

Keywords: Brevibacterium linens, Fermentation, Glutamicacid, Thin layer choromatography

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7306 Non-Chronological Approach in Crane Girder and Composite Steel Beam Installation: Case Study

Authors: Govindaraj Ramanathan

Abstract:

The time delay and the structural stability are major issues in big size projects due to several factors. Improper planning and poor coordination lead to delay in construction, which sometimes result in reworking or rebuilding. This definitely increases the cost and time of project. This situation stresses the structural engineers to plan out of the limits of contemporary technology utilizing non-chronological approach with creative ideas. One of the strategies to solve this issue is through structural integrity solutions in a cost-effective way. We have faced several problems in a project worth 470 million USD, and one such issue is crane girder installation with composite steel beams. We have applied structural integrity approach with the proper and revised planning schedule to solve the problem efficiently with minimal expenses.

Keywords: Construction management, delay, non-chronological approach, composite beam, structural integrity.

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7305 Solving Stochastic Eigenvalue Problem of Wick Type

Authors: Hassan Manouzi, Taous-Meriem Laleg-Kirati

Abstract:

In this paper we study mathematically the eigenvalue problem for stochastic elliptic partial differential equation of Wick type. Using the Wick-product and the Wiener-Itô chaos expansion, the stochastic eigenvalue problem is reformulated as a system of an eigenvalue problem for a deterministic partial differential equation and elliptic partial differential equations by using the Fredholm alternative. To reduce the computational complexity of this system, we shall use a decomposition method using the Wiener-Itô chaos expansion. Once the approximation of the solution is performed using the finite element method for example, the statistics of the numerical solution can be easily evaluated.

Keywords: Eigenvalue problem, Wick product, SPDEs, finite element, Wiener-Itô chaos expansion.

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7304 Low Resolution Face Recognition Using Mixture of Experts

Authors: Fatemeh Behjati Ardakani, Fatemeh Khademian, Abbas Nowzari Dalini, Reza Ebrahimpour

Abstract:

Human activity is a major concern in a wide variety of applications, such as video surveillance, human computer interface and face image database management. Detecting and recognizing faces is a crucial step in these applications. Furthermore, major advancements and initiatives in security applications in the past years have propelled face recognition technology into the spotlight. The performance of existing face recognition systems declines significantly if the resolution of the face image falls below a certain level. This is especially critical in surveillance imagery where often, due to many reasons, only low-resolution video of faces is available. If these low-resolution images are passed to a face recognition system, the performance is usually unacceptable. Hence, resolution plays a key role in face recognition systems. In this paper we introduce a new low resolution face recognition system based on mixture of expert neural networks. In order to produce the low resolution input images we down-sampled the 48 × 48 ORL images to 12 × 12 ones using the nearest neighbor interpolation method and after that applying the bicubic interpolation method yields enhanced images which is given to the Principal Component Analysis feature extractor system. Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in low resolution face recognition that is the recognition rate of 100% for the training set and 96.5% for the test set.

Keywords: Low resolution face recognition, Multilayered neuralnetwork, Mixture of experts neural network, Principal componentanalysis, Bicubic interpolation, Nearest neighbor interpolation.

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7303 Stock Price Forecast by Using Neuro-Fuzzy Inference System

Authors: Ebrahim Abbasi, Amir Abouec

Abstract:

In this research, the researchers have managed to design a model to investigate the current trend of stock price of the "IRAN KHODRO corporation" at Tehran Stock Exchange by utilizing an Adaptive Neuro - Fuzzy Inference system. For the Longterm Period, a Neuro-Fuzzy with two Triangular membership functions and four independent Variables including trade volume, Dividend Per Share (DPS), Price to Earning Ratio (P/E), and also closing Price and Stock Price fluctuation as an dependent variable are selected as an optimal model. For the short-term Period, a neureo – fuzzy model with two triangular membership functions for the first quarter of a year, two trapezoidal membership functions for the Second quarter of a year, two Gaussian combination membership functions for the third quarter of a year and two trapezoidal membership functions for the fourth quarter of a year were selected as an optimal model for the stock price forecasting. In addition, three independent variables including trade volume, price to earning ratio, closing Stock Price and a dependent variable of stock price fluctuation were selected as an optimal model. The findings of the research demonstrate that the trend of stock price could be forecasted with the lower level of error.

Keywords: Stock Price forecast, membership functions, Adaptive Neuro-Fuzzy Inference System, trade volume, P/E, DPS.

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7302 A Review on Stormwater Harvesting and Reuse

Authors: Fatema Akram, Mohammad G. Rasul, M. Masud K. Khan, M. Sharif I. I. Amir

Abstract:

Australia is a country of some 7,700 million square kilometers with a population of about 22.6 million. At present water security is a major challenge for Australia. In some areas the use of water resources is approaching and in some parts it is exceeding the limits of sustainability. A focal point of proposed national water conservation programs is the recycling of both urban stormwater and treated wastewater. But till now it is not widely practiced in Australia, and particularly stormwater is neglected. In Australia, only 4% of stormwater and rainwater is recycled, whereas less than 1% of reclaimed wastewater is reused within urban areas. Therefore, accurately monitoring, assessing and predicting the availability, quality and use of this precious resource are required for better management. As stormwater is usually of better quality than untreated sewage or industrial discharge, it has better public acceptance for recycling and reuse, particularly for non-potable use such as irrigation, watering lawns, gardens, etc. Existing stormwater recycling practice is far behind of research and no robust technologies developed for this purpose. Therefore, there is a clear need for using modern technologies for assessing feasibility of stormwater harvesting and reuse. Numerical modeling has, in recent times, become a popular tool for doing this job. It includes complex hydrological and hydraulic processes of the study area. The hydrologic model computes stormwater quantity to design the system components, and the hydraulic model helps to route the flow through stormwater infrastructures. Nowadays water quality module is incorporated with these models. Integration of Geographic Information System (GIS) with these models provides extra advantage of managing spatial information. However for the overall management of a stormwater harvesting project, Decision Support System (DSS) plays an important role incorporating database with model and GIS for the proper management of temporal information. Additionally DSS includes evaluation tools and Graphical user interface. This research aims to critically review and discuss all the aspects of stormwater harvesting and reuse such as available guidelines of stormwater harvesting and reuse, public acceptance of water reuse, the scopes and recommendation for future studies. In addition to these, this paper identifies, understand and address the importance of modern technologies capable of proper management of stormwater harvesting and reuse.

Keywords: Stormwater Management, Stormwater Harvesting and Reuse, Numerical Modeling, Geographic Information System (GIS), Decision Support System (DSS), Database.

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7301 Classification Based on Deep Neural Cellular Automata Model

Authors: Yasser F. Hassan

Abstract:

Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: Cellular automata, neural cellular automata, deep learning, classification.

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7300 Physical Modeling of Oil Well Fire Extinguishing Using a Turbojet on a Barge

Authors: M. Abbaspour, D. Mansouri, N. Mansouri

Abstract:

There are reports of gas and oil wells fire due to different accidents. Many different methods are used for fire fighting in gas and oil industry. Traditional fire extinguishing techniques are mostly faced with many problems and are usually time consuming and needs lots of equipments. Besides, they cause damages to facilities, and create health and environmental problems. This article proposes innovative approach in fire extinguishing techniques in oil and gas industry, especially applicable for burning oil wells located offshore. Fire extinguishment employing a turbojet is a novel approach which can help to extinguishment the fire in short period of time. Divergent and convergent turbojets modeled in laboratory scale along with a high pressure flame were used. Different experiments were conducted to determine the relationship between output discharges of trumpet and oil wells. The results were corrected and the relationship between dimensionless parameters of flame and fire extinguishment distances and also the output discharge of turbojet and oil wells in specified distances are demonstrated by specific curves.

Keywords: Burning well, fire extinguishment, gas/oil industry, simulation.

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7299 A Review of the Theoretical Context of the Role of Innovation in Economic Development

Authors: Maria E. Eggink

Abstract:

It is the aim of this paper to place the role of innovation in economic development in its theoretical context through a literature review. The review compares classical economic theory and the neoclassical theories of “equilibrium in the markets” and “perfectly competitive markets” with the Schumpeterian theory. It was found that Schumpeter’s role in contributing towards economic development theories, and by creating awareness of the role of innovation in these theories is of immeasurable importance. His contribution led to a change in economic thinking, although this was only realized much later than when his theories were first published. The neo-Schumpeterian thinking expanded on the Schumpeterian theory by studying innovation within a system of interaction among different role players. Studies on innovation should be founded in the neo-Schumpeterian school of thought in order to accommodate the complexity of the innovation system concept.

Keywords: Economic development, evolutionary economics, innovation, Schumpeter.

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7298 An Approach for Blind Source Separation using the Sliding DFT and Time Domain Independent Component Analysis

Authors: Koji Yamanouchi, Masaru Fujieda, Takahiro Murakami, Yoshihisa Ishida

Abstract:

''Cocktail party problem'' is well known as one of the human auditory abilities. We can recognize the specific sound that we want to listen by this ability even if a lot of undesirable sounds or noises are mixed. Blind source separation (BSS) based on independent component analysis (ICA) is one of the methods by which we can separate only a special signal from their mixed signals with simple hypothesis. In this paper, we propose an online approach for blind source separation using the sliding DFT and the time domain independent component analysis. The proposed method can reduce calculation complexity in comparison with conventional methods, and can be applied to parallel processing by using digital signal processors (DSPs) and so on. We evaluate this method and show its availability.

Keywords: Cocktail party problem, blind Source Separation(BSS), independent component analysis, sliding DFT, onlineprocessing.

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7297 Optimized Brain Computer Interface System for Unspoken Speech Recognition: Role of Wernicke Area

Authors: Nassib Abdallah, Pierre Chauvet, Abd El Salam Hajjar, Bassam Daya

Abstract:

In this paper, we propose an optimized brain computer interface (BCI) system for unspoken speech recognition, based on the fact that the constructions of unspoken words rely strongly on the Wernicke area, situated in the temporal lobe. Our BCI system has four modules: (i) the EEG Acquisition module based on a non-invasive headset with 14 electrodes; (ii) the Preprocessing module to remove noise and artifacts, using the Common Average Reference method; (iii) the Features Extraction module, using Wavelet Packet Transform (WPT); (iv) the Classification module based on a one-hidden layer artificial neural network. The present study consists of comparing the recognition accuracy of 5 Arabic words, when using all the headset electrodes or only the 4 electrodes situated near the Wernicke area, as well as the selection effect of the subbands produced by the WPT module. After applying the articial neural network on the produced database, we obtain, on the test dataset, an accuracy of 83.4% with all the electrodes and all the subbands of 8 levels of the WPT decomposition. However, by using only the 4 electrodes near Wernicke Area and the 6 middle subbands of the WPT, we obtain a high reduction of the dataset size, equal to approximately 19% of the total dataset, with 67.5% of accuracy rate. This reduction appears particularly important to improve the design of a low cost and simple to use BCI, trained for several words.

Keywords: Brain-computer interface, speech recognition, electroencephalography EEG, Wernicke area, artificial neural network.

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7296 Using Combination of Optimized Recurrent Neural Network with Design of Experiments and Regression for Control Chart Forecasting

Authors: R. Behmanesh, I. Rahimi

Abstract:

recurrent neural network (RNN) is an efficient tool for modeling production control process as well as modeling services. In this paper one RNN was combined with regression model and were employed in order to be checked whether the obtained data by the model in comparison with actual data, are valid for variable process control chart. Therefore, one maintenance process in workshop of Esfahan Oil Refining Co. (EORC) was taken for illustration of models. First, the regression was made for predicting the response time of process based upon determined factors, and then the error between actual and predicted response time as output and also the same factors as input were used in RNN. Finally, according to predicted data from combined model, it is scrutinized for test values in statistical process control whether forecasting efficiency is acceptable. Meanwhile, in training process of RNN, design of experiments was set so as to optimize the RNN.

Keywords: RNN, DOE, regression, control chart.

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7295 Baseline Performance of Notebook Computer under Various Environmental and Usage Conditions for Prognostics

Authors: Sachin Kumar, Michael Pecht

Abstract:

A study was conducted to formally characterize notebook computer performance under various environmental and usage conditions. Software was developed to collect data from the operating system of the computer. An experiment was conducted to evaluate the performance parameters- variations, trends, and correlations, as well as the extreme value they can attain in various usage and environmental conditions. An automated software script was written to simulate user activity. The variability of each performance parameter was addressed by establishing the empirical relationship between performance parameters. These equations were presented as baseline estimates for performance parameters, which can be used to detect system deviations from normal operation and for prognostic assessment. The effect of environmental factors, including different power sources, ambient temperatures, humidity, and usage, on performance parameters of notebooks was studied.

Keywords: Health monitoring, Electronic prognostics, Reliability, Usage monitoring, Notebook computer.

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7294 Heuristic Continuous-time Associative Memories

Authors: Truong Quang Dang Khoa, Masahiro Nakagawa

Abstract:

In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.

Keywords: Artificial Intelligent, Soft Computing, NeuralNetworks, Genetic Algorithms, Hopfield Neural Networks, andAssociative Memories.

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7293 Analytical Model Based Evaluation of Human Machine Interfaces Using Cognitive Modeling

Authors: Belkacem Chikhaoui, Helene Pigot

Abstract:

Cognitive models allow predicting some aspects of utility and usability of human machine interfaces (HMI), and simulating the interaction with these interfaces. The action of predicting is based on a task analysis, which investigates what a user is required to do in terms of actions and cognitive processes to achieve a task. Task analysis facilitates the understanding of the system-s functionalities. Cognitive models are part of the analytical approaches, that do not associate the users during the development process of the interface. This article presents a study about the evaluation of a human machine interaction with a contextual assistant-s interface using ACTR and GOMS cognitive models. The present work shows how these techniques may be applied in the evaluation of HMI, design and research by emphasizing firstly the task analysis and secondly the time execution of the task. In order to validate and support our results, an experimental study of user performance is conducted at the DOMUS laboratory, during the interaction with the contextual assistant-s interface. The results of our models show that the GOMS and ACT-R models give good and excellent predictions respectively of users performance at the task level, as well as the object level. Therefore, the simulated results are very close to the results obtained in the experimental study.

Keywords: HMI, interface evaluation, Analytical evaluation, cognitivemodeling, user modeling, user performance.

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7292 Real-Time Implementation of STANAG 4539 High-Speed HF Modem

Authors: S. Saraç, F. Kara, C.Vural

Abstract:

High-frequency (HF) communications have been used by military organizations for more than 90 years. The opportunity of very long range communications without the need for advanced equipment makes HF a convenient and inexpensive alternative of satellite communications. Besides the advantages, voice and data transmission over HF is a challenging task, because the HF channel generally suffers from Doppler shift and spread, multi-path, cochannel interference, and many other sources of noise. In constructing an HF data modem, all these effects must be taken into account. STANAG 4539 is a NATO standard for high-speed data transmission over HF. It allows data rates up to 12800 bps over an HF channel of 3 kHz. In this work, an efficient implementation of STANAG 4539 on a single Texas Instruments- TMS320C6747 DSP chip is described. The state-of-the-art algorithms used in the receiver and the efficiency of the implementation enables real-time high-speed data / digitized voice transmission over poor HF channels.

Keywords: High frequency, modem, STANAG 4539.

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7291 Binary Mixture of Copper-Cobalt Ions Uptake by Zeolite using Neural Network

Authors: John Kabuba, Antoine Mulaba-Bafubiandi, Kim Battle

Abstract:

In this study a neural network (NN) was proposed to predict the sorption of binary mixture of copper-cobalt ions into clinoptilolite as ion-exchanger. The configuration of the backpropagation neural network giving the smallest mean square error was three-layer NN with tangent sigmoid transfer function at hidden layer with 10 neurons, linear transfer function at output layer and Levenberg-Marquardt backpropagation training algorithm. Experiments have been carried out in the batch reactor to obtain equilibrium data of the individual sorption and the mixture of coppercobalt ions. The obtained modeling results have shown that the used of neural network has better adjusted the equilibrium data of the binary system when compared with the conventional sorption isotherm models.

Keywords: Adsorption isotherm, binary system, neural network; sorption

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7290 The Study on the Development of Ornamentation in the Architecture of Safavid Dynasty

Authors: N. Utaberta, H. Mamamni, M. Surat, A. I. Che-Ani, N.A.G. Abdullah

Abstract:

The architecture of Safavid Dynasty can be considered the epitome of Iranian architectural beauty. Safavid dynasty (1501- 1722 AC) along with Ottoman in Turkey and Mughal Empire in India were the three great Islamic nations of their time (1500 AC) often known as the last Islamic countries with international authority up to the 20th Century. This era approximately coincide with Renaissance in Europe. In this era, large European countries begin amassing power thanks to significant scientific, cultural and religious revolutions of that time and colonizing nations such as England, Spain and Portugal began to influence international trends with in an increasing while other non-industrial nations diminished. The main objective of this paper is to give a typological overview of the development of decoration and ornament in the architecture of Safafid Dynasty in Iran. It is expected that it can start a wider discussion to enrich this nation-s heritage and contribute to the development of Islamic ornament in general.

Keywords: Ornamentation, Architecture in Iran, Safavid Dynasty

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7289 Simulation of Ammonia-Water Two Phase Flow in Bubble Pump

Authors: Jemai Rabeb, Benhmidene Ali, Hidouri Khaoula, Chaouachi Bechir

Abstract:

The diffusion-absorption refrigeration cycle consists of a generator bubble pump, an absorber, an evaporator and a condenser, and usually operates with ammonia/water/ hydrogen or helium as the working fluid. The aim of this paper is to study the stability problem a bubble pump. In fact instability can caused a reduction of bubble pump efficiency. To achieve this goal, we have simulated the behaviour of two-phase flow in a bubble pump by using a drift flow model. Equations of a drift flow model are formulated in the transitional regime, non-adiabatic condition and thermodynamic equilibrium between the liquid and vapour phases. Equations resolution allowed to define void fraction, and liquid and vapour velocities, as well as pressure and mixing enthalpy. Ammonia-water mixing is used as working fluid, where ammonia mass fraction in the inlet is 0.6. Present simulation is conducted out for a heating flux of 2 kW/m² to 5 kW/m² and bubble pump tube length of 1 m and 2.5 mm of inner diameter. Simulation results reveal oscillations of vapour and liquid velocities along time. Oscillations decrease with time and with heat flux. For sufficient time the steady state is established, it is characterised by constant liquid velocity and void fraction values. However, vapour velocity does not have the same behaviour, it increases for steady state too. On the other hand, pressure drop oscillations are studied.

Keywords: Bubble pump, drift flow model, instability, simulation.

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7288 Fast Factored DCT-LMS Speech Enhancement for Performance Enhancement of Digital Hearing Aid

Authors: Sunitha. S.L., V. Udayashankara

Abstract:

Background noise is particularly damaging to speech intelligibility for people with hearing loss especially for sensorineural loss patients. Several investigations on speech intelligibility have demonstrated sensorineural loss patients need 5-15 dB higher SNR than the normal hearing subjects. This paper describes Discrete Cosine Transform Power Normalized Least Mean Square algorithm to improve the SNR and to reduce the convergence rate of the LMS for Sensory neural loss patients. Since it requires only real arithmetic, it establishes the faster convergence rate as compare to time domain LMS and also this transformation improves the eigenvalue distribution of the input autocorrelation matrix of the LMS filter. The DCT has good ortho-normal, separable, and energy compaction property. Although the DCT does not separate frequencies, it is a powerful signal decorrelator. It is a real valued function and thus can be effectively used in real-time operation. The advantages of DCT-LMS as compared to standard LMS algorithm are shown via SNR and eigenvalue ratio computations. . Exploiting the symmetry of the basis functions, the DCT transform matrix [AN] can be factored into a series of ±1 butterflies and rotation angles. This factorization results in one of the fastest DCT implementation. There are different ways to obtain factorizations. This work uses the fast factored DCT algorithm developed by Chen and company. The computer simulations results show superior convergence characteristics of the proposed algorithm by improving the SNR at least 10 dB for input SNR less than and equal to 0 dB, faster convergence speed and better time and frequency characteristics.

Keywords: Hearing Impairment, DCT Adaptive filter, Sensorineural loss patients, Convergence rate.

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7287 The Use of Ontology Framework for Automation Digital Forensics Investigation

Authors: Ahmad Luthfi

Abstract:

One of the main goals of a computer forensic analyst is to determine the cause and effect of the acquisition of a digital evidence in order to obtain relevant information on the case is being handled. In order to get fast and accurate results, this paper will discuss the approach known as Ontology Framework. This model uses a structured hierarchy of layers that create connectivity between the variant and searching investigation of activity that a computer forensic analysis activities can be carried out automatically. There are two main layers are used, namely Analysis Tools and Operating System. By using the concept of Ontology, the second layer is automatically designed to help investigator to perform the acquisition of digital evidence. The methodology of automation approach of this research is by utilizing Forward Chaining where the system will perform a search against investigative steps and atomically structured in accordance with the rules of the Ontology.

Keywords: Ontology, Framework, Automation, Forensics.

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