Search results for: Arabic Information extraction
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4536

Search results for: Arabic Information extraction

4206 Phase Error Accumulation Methodology for On-Chip Cell Characterization

Authors: Chang Soo Kang, In Ho Im, Sergey Churayev, Timour Paltashev

Abstract:

This paper describes the design of new method of propagation delay measurement in micro and nanostructures during characterization of ASIC standard library cell. Providing more accuracy timing information about library cell to the design team we can improve a quality of timing analysis inside of ASIC design flow process. Also, this information could be very useful for semiconductor foundry team to make correction in technology process. By comparison of the propagation delay in the CMOS element and result of analog SPICE simulation. It was implemented as digital IP core for semiconductor manufacturing process. Specialized method helps to observe the propagation time delay in one element of the standard-cell library with up-to picoseconds accuracy and less. Thus, the special useful solutions for VLSI schematic to parameters extraction, basic cell layout verification, design simulation and verification are announced.

Keywords: phase error accumulation methodology, gatepropagation delay, Processor Testing, MEMS Testing

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4205 Fast Facial Feature Extraction and Matching with Artificial Face Models

Authors: Y. H. Tsai, Y. W. Chen

Abstract:

Facial features are frequently used to represent local properties of a human face image in computer vision applications. In this paper, we present a fast algorithm that can extract the facial features online such that they can give a satisfying representation of a face image. It includes one step for a coarse detection of each facial feature by AdaBoost and another one to increase the accuracy of the found points by Active Shape Models (ASM) in the regions of interest. The resulted facial features are evaluated by matching with artificial face models in the applications of physiognomy. The distance measure between the features and those in the fate models from the database is carried out by means of the Hausdorff distance. In the experiment, the proposed method shows the efficient performance in facial feature extractions and online system of physiognomy.

Keywords: Facial feature extraction, AdaBoost, Active shapemodel, Hausdorff distance

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4204 Leaching Behaviour of a Low-grade South African Nickel Laterite

Authors: Catherine K. Thubakgale, Richard K.K. Mbaya, Kaby Kabongo

Abstract:

The morphology, mineralogical and chemical composition of a low-grade nickel ore from Mpumalanga, South Africa, were studied by scanning electron microscope (SEM), X-ray diffraction (XRD) and X-ray fluorescence (XRF), respectively. The ore was subjected to atmospheric agitation leaching using sulphuric acid to investigate the effects of acid concentration, leaching temperature, leaching time and particle size on extraction of nickel and cobalt. Analyses results indicated the ore to be a saprolitic nickel laterite belonging to the serpentine group of minerals. Sulphuric acid was found to be able to extract nickel from the ore. Increased acid concentration and temperature only produced low amounts of nickel but improved cobalt extraction. As high as 77.44% Ni was achieved when leaching a -106+75μm fraction with 4.0M acid concentration at 25oC. The kinetics of nickel leaching from the saprolitic ore were studied and the activation energy was determined to be 18.16kJ/mol. This indicated that nickel leaching reaction was diffusion controlled.

Keywords: Laterite, sulphuric acid, atmospheric leaching, nickel.

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4203 The Use of Microorganisms in the Bioleaching of Soils Polluted with Heavy Metals

Authors: I. M. Sur, A. M. Chirila-Babau, T. Gabor, V. Micle

Abstract:

This paper shows researches in order to extract Cr, Cu and Ni from the polluted soils. Research is based on preliminary studies regarding the usage of Thiobacillus ferrooxidans bacterium (9K medium) for bioleaching of soil polluted with heavy metal (Cu, Cr and Ni). The microorganisms (Thiobacillus ferooxidans) selected directly from polluted soil samples were used in this experimental work. Soil samples used in the experimental research were taken from an area polluted with heavy metals from Romania. The soil samples are subjected to the cleaning process using the 9K medium solution (20 mL and 40 mL, respectively), stirred 200 rpm for 20 hours at a controlled temperature (30 ˚C). During the experiment (0, 2, 4, 8 and 20 h), liquid samples have been extracted and analyzed using the Atomic Absorption Spectrophotometer AA-6800 (AAS) in order to determine the Cr, Cu and Ni concentration. Experiments led to the conclusion that these soils can be depolluted by bioleaching, being a biological treatment method involving the use of microorganisms to favor the extraction of Cr, Cu and Ni from polluted soils.

Keywords: Bioleaching, extraction, microorganisms, polluted soil, Thiobacillus ferooxidans.

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4202 A Study of Geographic Information System Combining with GPS and 3G for Parking Guidance and Information System

Authors: Yu-Chi Shiue, Jyong Lin, Shih-Chang Chen

Abstract:

With the increase of economic behavior and the upgrade of living standar, the ratio for people in Taiwan who own automobiles and motorcycles have recently increased with multiples. Therefore, parking issues will be a big challenge to facilitate traffic network and ensure urban life quality. The Parking Guidance and Information System is one of important systems for Advanced Traveler Information Services (ATIS). This research proposes a parking guidance and information system which integrates GPS and 3G network for a map on the Geographic Information System to solution inadequate of roadside information kanban. The system proposed in this study mainly includes Parking Host, Parking Guidance and Information Server, Geographic Map and Information System as well as Parking Guidance and Information Browser. The study results show this system can increase driver-s efficiency to find parking space and efficiently enhance parking convenience in comparison with roadside kanban system.

Keywords: Geographic Information System, 3G, GPS, parkinginformation

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4201 On-line Handwritten Character Recognition: An Implementation of Counterpropagation Neural Net

Authors: Muhammad Faisal Zafar, Dzulkifli Mohamad, Razib M. Othman

Abstract:

On-line handwritten scripts are usually dealt with pen tip traces from pen-down to pen-up positions. Time evaluation of the pen coordinates is also considered along with trajectory information. However, the data obtained needs a lot of preprocessing including filtering, smoothing, slant removing and size normalization before recognition process. Instead of doing such lengthy preprocessing, this paper presents a simple approach to extract the useful character information. This work evaluates the use of the counter- propagation neural network (CPN) and presents feature extraction mechanism in full detail to work with on-line handwriting recognition. The obtained recognition rates were 60% to 94% using the CPN for different sets of character samples. This paper also describes a performance study in which a recognition mechanism with multiple thresholds is evaluated for counter-propagation architecture. The results indicate that the application of multiple thresholds has significant effect on recognition mechanism. The method is applicable for off-line character recognition as well. The technique is tested for upper-case English alphabets for a number of different styles from different peoples.

Keywords: On-line character recognition, character digitization, counter-propagation neural networks, extreme coordinates.

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4200 Data Preprocessing for Supervised Leaning

Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

Abstract:

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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4199 A Semantic Web Based Ontology in the Financial Domain

Authors: S. Banerjee

Abstract:

The paper describes design of an ontology in the financial domain for mutual funds. The design of this ontology consists of four steps, namely, specification, knowledge acquisition, implementation and semantic query. Specification includes a description of the taxonomy and different types mutual funds and their scope. Knowledge acquisition involves the information extraction from heterogeneous resources. Implementation describes the conceptualization and encoding of this data. Finally, semantic query permits complex queries to integrated data, mapping of these database entities to ontological concepts.

Keywords: Ontology, Semantic Web, Mutual Funds.

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4198 Identification of Coauthors in Scientific Database

Authors: Thiago M. R Dias, Gray F. Moita

Abstract:

The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: Extraction and data integration, Information Retrieval, Scientific Collaboration.

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4197 Institutional Aspects of Information Security in Russian Economy

Authors: Mingaleva Zhanna, Kapuskina Tatiana

Abstract:

The article touches upon questions of information security in Russian Economy. It covers theoretical bases of information security and causes of its development. The theory is proved by the analysis of business activities and the main tendencies of information security development. Perm region has been chosen as the bases for the analysis, being the fastestdeveloping region that uses methods of information security in managing it economy. As a result of the study the authors of the given article have formulated their own vision of the problem of information security in various branches of economy and stated prospects of information security development and its growing role in Russian economy

Keywords: security of business, management of information security, institutional analyses.

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4196 Towards Automatic Recognition and Grading of Ganoderma Infection Pattern Using Fuzzy Systems

Authors: Mazliham Mohd Su'ud, Pierre Loonis, Idris Abu Seman

Abstract:

This paper deals with the extraction of information from the experts to automatically identify and recognize Ganoderma infection in oil palm stem using tomography images. Expert-s knowledge are used as rules in a Fuzzy Inference Systems to classify each individual patterns observed in he tomography image. The classification is done by defining membership functions which assigned a set of three possible hypotheses : Ganoderma infection (G), non Ganoderma infection (N) or intact stem tissue (I) to every abnormalities pattern found in the tomography image. A complete comparison between Mamdani and Sugeno style,triangular, trapezoids and mixed triangular-trapezoids membership functions and different methods of aggregation and defuzzification is also presented and analyzed to select suitable Fuzzy Inference System methods to perform the above mentioned task. The results showed that seven out of 30 initial possible combination of available Fuzzy Inference methods in MATLAB Fuzzy Toolbox were observed giving result close to the experts estimation.

Keywords: Fuzzy Inference Systems, Tomography analysis, Modelizationof expert's information, Ganoderma Infection pattern recognition

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4195 Information Needs and Information Usage of the Older Person Club’s Members in Bangkok

Authors: Siriporn Poolsuwan

Abstract:

This research aims to explore the information needs, information usages, and problems of information usage of the older people club’s members in Dusit district, Bangkok. There are 12 clubs and 746 club’s members in this district. The research results use for older person service in this district. Data is gathered from 252 club’s members by using questionnaires. The quantitative approach uses in research by percentage, means and standard deviation. The results are as follows (1) The older people need Information for entertainment, occupation and academic in the field of short story, computer work, and religion and morality. (2) The participants use Information from various sources. (3) The Problem of information usage is their language skills because of the older people’s literacy problem.

Keywords: Information Behavior, Older Person, Information Seeking.

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4194 On-line Speech Enhancement by Time-Frequency Masking under Prior Knowledge of Source Location

Authors: Min Ah Kang, Sangbae Jeong, Minsoo Hahn

Abstract:

This paper presents the source extraction system which can extract only target signals with constraints on source localization in on-line systems. The proposed system is a kind of methods for enhancing a target signal and suppressing other interference signals. But, the performance of proposed system is superior to any other methods and the extraction of target source is comparatively complete. The method has a beamforming concept and uses an improved time-frequency (TF) mask-based BSS algorithm to separate a target signal from multiple noise sources. The target sources are assumed to be in front and test data was recorded in a reverberant room. The experimental results of the proposed method was evaluated by the PESQ score of real-recording sentences and showed a noticeable speech enhancement.

Keywords: Beam forming, Non-stationary noise reduction, Source separation, TF mask.

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4193 Methods of Forming Informational Culture Students

Authors: Altynbek Moshkalov

Abstract:

Along with the basic features of students\' culture information, with its widely usage oriented on implementation of the new information technologies in educational process that determines the search for ways of pointing to the similarity of interdisciplinary connections content, aims and objectives of the study. In this regard, the article questions about students\' information culture, and also presented information about the aims and objectives of the information culture process among students. In the formation of a professional interest in relevant information, which is an opportunity to assist in informing the professional activities of the essence of effective use of interactive methods and innovative technologies in the learning process. The result of the experiment proves the effectiveness of the information culture process of students in training the system of higher education based on the credit technology. The main purpose of this paper is a comprehensive review of students\' information culture.

Keywords: Information culture, methods of information culture of students, educational system of the credit technology, distance learning, information of interest, information and communication technologies and tools.

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4192 Optimization of Some Process Parameters to Produce Raisin Concentrate in Khorasan Region of Iran

Authors: Peiman Ariaii, Hamid Tavakolipour, Mohsen Pirdashti, Rabehe Izadi Amoli

Abstract:

Raisin Concentrate (RC) are the most important products obtained in the raisin processing industries. These RC products are now used to make the syrups, drinks and confectionery productions and introduced as natural substitute for sugar in food applications. Iran is a one of the biggest raisin exporter in the world but unfortunately despite a good raw material, no serious effort to extract the RC has been taken in Iran. Therefore, in this paper, we determined and analyzed affected parameters on extracting RC process and then optimizing these parameters for design the extracting RC process in two types of raisin (round and long) produced in Khorasan region. Two levels of solvent (1:1 and 2:1), three levels of extraction temperature (60°C, 70°C and 80°C), and three levels of concentration temperature (50°C, 60°C and 70°C) were the treatments. Finally physicochemical characteristics of the obtained concentrate such as color, viscosity, percentage of reduction sugar, acidity and the microbial tests (mould and yeast) were counted. The analysis was performed on the basis of factorial in the form of completely randomized design (CRD) and Duncan's multiple range test (DMRT) was used for the comparison of the means. Statistical analysis of results showed that optimal conditions for production of concentrate is round raisins when the solvent ratio was 2:1 with extraction temperature of 60°C and then concentration temperature of 50°C. Round raisin is cheaper than the long one, and it is more economical to concentrate production. Furthermore, round raisin has more aromas and the less color degree with increasing the temperature of concentration and extraction. Finally, according to mentioned factors the concentrate of round raisin is recommended.

Keywords: Raisin concentrate, optimization, process parameters, round raisin, Iran.

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4191 Non-Invasive Data Extraction from Machine Display Units Using Video Analytics

Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

Abstract:

Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: Human machine interface, industrial internet of things, internet of things, optical character recognition, video analytic.

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4190 Analysis of Roasted and Ground Grains on the Seoul (Korea) Market for Their Contaminants of Aflatoxins, Ochratoxin A and Fusarium Toxins by LC-MS/MS

Authors: So-young Jung, Bu-chuhl Choe, Gi-young Shin, Jung-hun Kim, Young-zoo Chae

Abstract:

A sensitive and specific method for quantitative determination of aflatoxins(B1, B2, G1,G2), deoxynivalenol, fumonisin(B1,B2), ochratoxin A, zearalenone, T-2 and HT-2 in roasted and ground grains using liquid chromatography combined with tandem mass spectrometry. A double extraction using a phosphate buffer solution followed by methanol was applied to achieve effective co extraction of 11 mycotoxins. A multitoxin immunoaffinity column for all these mycotoxins was used to clean up the extract. The LODs of mycotoxins were 0.1~6.1 μg/kg, LOQs were 0.3~18.4 μg/kg. Forty seven samples collected from Seoul (Korea) for mycotoxin contamination monitoring. The results showed that the occurrence of zearalenone and deoxynivalenol were frequent. Zearalenone was detected in all samples and deoxynivalenol was detected in 80.9 % samples in the range 0.626 ~ 29.264 μg/kg and N.D ~ 48.332 μg/kg respectively. Fumonisins and ochratoxin A were detected in 46.8% samples and 17 % samples respectively, aflatoxins and T-2/HT-2 toxins were not detected all samples.

Keywords: LC-MS/MS, mycotoxins, roasted and ground grains.

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4189 Space Telemetry Anomaly Detection Based on Statistical PCA Algorithm

Authors: B. Nassar, W. Hussein, M. Mokhtar

Abstract:

The critical concern of satellite operations is to ensure the health and safety of satellites. The worst case in this perspective is probably the loss of a mission, but the more common interruption of satellite functionality can result in compromised mission objectives. All the data acquiring from the spacecraft are known as Telemetry (TM), which contains the wealth information related to the health of all its subsystems. Each single item of information is contained in a telemetry parameter, which represents a time-variant property (i.e. a status or a measurement) to be checked. As a consequence, there is a continuous improvement of TM monitoring systems to reduce the time required to respond to changes in a satellite's state of health. A fast conception of the current state of the satellite is thus very important to respond to occurring failures. Statistical multivariate latent techniques are one of the vital learning tools that are used to tackle the problem above coherently. Information extraction from such rich data sources using advanced statistical methodologies is a challenging task due to the massive volume of data. To solve this problem, in this paper, we present a proposed unsupervised learning algorithm based on Principle Component Analysis (PCA) technique. The algorithm is particularly applied on an actual remote sensing spacecraft. Data from the Attitude Determination and Control System (ADCS) was acquired under two operation conditions: normal and faulty states. The models were built and tested under these conditions, and the results show that the algorithm could successfully differentiate between these operations conditions. Furthermore, the algorithm provides competent information in prediction as well as adding more insight and physical interpretation to the ADCS operation.

Keywords: Space telemetry monitoring, multivariate analysis, PCA algorithm, space operations.

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4188 The Place and Effects of Information Management in Corporate Identity

Authors: H. Buluthan Cetintas

Abstract:

Corporate identity, which has several advantages such that the employees become integrated with their corporations, corporation is distinguished from its competitors and it is recognized by the masses, is the total of the distinctive corporate features that and corporation has. That the information takes part in production as a more important component than labor and capital has required that the corporations are reorganized as information-based. Therefore, information and its management have reached a basic and prevalent position in having sustainable competitive advantage. Thanks to the information management which regulates the information and makes it reachable and available, information will be produced in line with a specific purpose in the corporations and be used in all the corporate processes. As an auxiliary power for increase in the economic potential, efficiency and productivity of the corporation, corporate identity consists of four components. These are corporate philosophy, corporate design, corporate behavior and corporate communication. In this study, the effects of the information management on corporate identity are discussed from the point of these four elements.

Keywords: Corporate identity, information management.

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4187 Predicting Protein-Protein Interactions from Protein Sequences Using Phylogenetic Profiles

Authors: Omer Nebil Yaveroglu, Tolga Can

Abstract:

In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Keywords: Protein Interaction Prediction, Phylogenetic Profile, SVM , ReliefF, Decision Trees, Random Forest Classification

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4186 A Relationship Extraction Method from Literary Fiction Considering Korean Linguistic Features

Authors: Hee-Jeong Ahn, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The knowledge of the relationship between characters can help readers to understand the overall story or plot of the literary fiction. In this paper, we present a method for extracting the specific relationship between characters from a Korean literary fiction. Generally, methods for extracting relationships between characters in text are statistical or computational methods based on the sentence distance between characters without considering Korean linguistic features. Furthermore, it is difficult to extract the relationship with direction from text, such as one-sided love, because they consider only the weight of relationship, without considering the direction of the relationship. Therefore, in order to identify specific relationships between characters, we propose a statistical method considering linguistic features, such as syntactic patterns and speech verbs in Korean. The result of our method is represented by a weighted directed graph of the relationship between the characters. Furthermore, we expect that proposed method could be applied to the relationship analysis between characters of other content like movie or TV drama.

Keywords: Data mining, Korean linguistic feature, literary fiction, relationship extraction.

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4185 Control Chart Pattern Recognition Using Wavelet Based Neural Networks

Authors: Jun Seok Kim, Cheong-Sool Park, Jun-Geol Baek, Sung-Shick Kim

Abstract:

Control chart pattern recognition is one of the most important tools to identify the process state in statistical process control. The abnormal process state could be classified by the recognition of unnatural patterns that arise from assignable causes. In this study, a wavelet based neural network approach is proposed for the recognition of control chart patterns that have various characteristics. The procedure of proposed control chart pattern recognizer comprises three stages. First, multi-resolution wavelet analysis is used to generate time-shape and time-frequency coefficients that have detail information about the patterns. Second, distance based features are extracted by a bi-directional Kohonen network to make reduced and robust information. Third, a back-propagation network classifier is trained by these features. The accuracy of the proposed method is shown by the performance evaluation with numerical results.

Keywords: Control chart pattern recognition, Multi-resolution wavelet analysis, Bi-directional Kohonen network, Back-propagation network, Feature extraction.

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4184 The Autoregresive Analysis for Wind Turbine Signal Postprocessing

Authors: Daniel Pereiro, Felix Martinez, Iker Urresti, Ana Gomez Gonzalez

Abstract:

Today modern simulations solutions in the wind turbine industry have achieved a high degree of complexity and detail in result. Limitations exist when it is time to validate model results against measurements. Regarding Model validation it is of special interest to identify mode frequencies and to differentiate them from the different excitations. A wind turbine is a complex device and measurements regarding any part of the assembly show a lot of noise. Input excitations are difficult or even impossible to measure due to the stochastic nature of the environment. Traditional techniques for frequency analysis or features extraction are widely used to analyze wind turbine sensor signals, but have several limitations specially attending to non stationary signals (Events). A new technique based on autoregresive analysis techniques is introduced here for a specific application, a comparison and examples related to different events in the wind turbine operations are presented.

Keywords: Wind turbine, signal processing, mode extraction.

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4183 Determinants of Information Security Affecting Adoption of Web-based Integrated Information Systems

Authors: Jaehun Joo, Mie-jung Kim, Ismatilla Normatov, Lyunhwa Kim

Abstract:

The purpose of this paper is to analyze determinants of information security affecting adoption of the Web-based integrated information systems (IIS). We introduced Web-based information systems which are designed to formulate strategic plans for Peruvian government. Theoretical model is proposed to test impact of organizational factors (deterrent efforts and severity; preventive efforts) and individual factors (information security threat; security awareness) on intentions to proactively use the Web-based IIS .Our empirical study results highlight that deterrent efforts and deterrent severity have no significant influence on the proactive use intentions of IIS, whereas, preventive efforts play an important role in proactive use intentions of IIS. Thus, we suggest that organizations need to do preventive efforts by introducing various information security solutions, and try to improve information security awareness while reducing the perceived information security threats.

Keywords: Information security, Deterrent efforts, deterrentseverity, preventive efforts, information security awareness, information security threats, integrated information systems

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4182 Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

Authors: R.Anita, V.Ganga Bharani, N.Nityanandam, Pradeep Kumar Sahoo

Abstract:

The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based approach for extracting data from the deep web. Deep iCrawl splits the process into two phases. The first phase includes Query analysis and Query translation and the second covers vision-based extraction of data from the dynamically created deep web pages. There are several established approaches for the extraction of deep web pages but the proposed method aims at overcoming the inherent limitations of the former. This paper also aims at comparing the data items and presenting them in the required order.

Keywords: Crawler, Deep web, Web Database

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4181 GA Based Optimal Feature Extraction Method for Functional Data Classification

Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai

Abstract:

Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.

Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.

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4180 Effect of Different pH on Canthaxanthin Degradation

Authors: N. Seyedrazi, S. H. Razavi, Z. Emam-Djomeh

Abstract:

In this research, natural canthaxanthin as one of the most important carotenoids was extracted from Dietzia natronolimnaea HS-1. The changes of canthaxanthin enriched in oilin- water emulsions with vegetable oil (5 mg/ 100 mL), Arabic gum (5 mg/100 mL), and potassium sorbate (0.5 g/100 mL) was investigated. The effects of different pH (3, 5 and 7), as well as, time treatment (3, 18 and 33 days) in the environmental temperature (24°C) on the degradation were studied by response surface methodology (RSM). The Hunter values (L*, a*, and b*) and the concentration of canthaxanthin (C, mg/L) illustrated more degradation of this pigment at low pHs (pH≤ 4) by passing the time (days≥10) with R² 97.00%, 91.31%, 97.60%, and 99.54% for C, L*, a*, and b* respectively. The predicted model were found to be significant (p<0.05).

Keywords: Degradation, Emulsion, Response SurfaceMethodology (RSM)

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4179 Supercritical Carbon Dioxide Extraction of Phenolics and Tocopherols Enriched Oil from Wheat Bran

Authors: Kyung-Tae Kwon, Md. Salim Uddin, Go-Woon Jung, Jeong-Eun Sim, Byung-Soo Chun

Abstract:

Supercritical carbon dioxide (SC-CO2) was used as a solvent to extract oil from wheat bran. Extractions were carried out in a semi-batch process at temperatures ranging from 40 to 60ºC and pressures ranging from 10 to 30 MPa, with a carbon dioxide (CO2) flow rate of 26.81 g/min. The oil obtained from wheat bran at different extraction conditions was quantitatively measured to investigate the solubility of oil in SC-CO2. The solubility of wheat bran oil was found to be enhanced in high temperature and pressure. The composition of fatty acids in wheat bran oil was measured by gas chromatography (GC). Linoleic, palmitic, oleic and γ-linolenic acid were the major fatty acids of wheat bran oil. Tocopherol contents in oil were analyzed by high performance liquid chromatography (HPLC). The highest amount of phenolics and tocopherols (α and β) were found at temperature of 60ºC and pressure of 30 MPa.

Keywords: Supercritical carbon dioxide, Tocopherols, Totalphenolic content, Wheat bran oil

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4178 Neural Network Based Speech to Text in Malay Language

Authors: H. F. A. Abdul Ghani, R. R. Porle

Abstract:

Speech to text in Malay language is a system that converts Malay speech into text. The Malay language recognition system is still limited, thus, this paper aims to investigate the performance of ten Malay words obtained from the online Malay news. The methodology consists of three stages, which are preprocessing, feature extraction, and speech classification. In preprocessing stage, the speech samples are filtered using pre emphasis. After that, feature extraction method is applied to the samples using Mel Frequency Cepstrum Coefficient (MFCC). Lastly, speech classification is performed using Feedforward Neural Network (FFNN). The accuracy of the classification is further investigated based on the hidden layer size. From experimentation, the classifier with 40 hidden neurons shows the highest classification rate which is 94%.  

Keywords: Feed-Forward Neural Network, FFNN, Malay speech recognition, Mel Frequency Cepstrum Coefficient, MFCC, speech-to-text.

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4177 A Physical Theory of Information vs. a Mathematical Theory of Communication

Authors: Manouchehr Amiri

Abstract:

This article presents a general notion of physical bit information that is compatible with the basics of quantum mechanics and incorporates the Shannon entropy as a special case. This notion of physical information leads to the Binary Data Matrix model (BDM), which predicts the basic results of quantum mechanics, general relativity, and black hole thermodynamics. The compatibility of the model with holographic, information conservation, and Landauer’s principle is investigated. After deriving the “Bit Information principle” as a consequence of BDM, the fundamental equations of Planck, De Broglie, Bekenstein, and mass-energy equivalence are derived.

Keywords: Physical theory of information, binary data matrix model, Shannon information theory, bit information principle.

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