Search results for: Speaker identification

Authors: Rebecca Angeles

Abstract:

Radio frequency identification (RFID) has been recognized as a key enabler of efficient and effective supply chains. Recently, with increasing concern for environmental sustainability, researchers and practitioners have been exploring the role of RFID in supporting “green supply chains.” This qualitative study uses the technology-organization-environment framework of Tornatzky and Fleischer, and Zuboff’s concepts of automating-informating-transformating in analyzing two case studies involving RFID use: the recycling of Hewlett Packard inkjet printers and the garbage and recycling program of the City of Grand Rapids, Michigan.

Keywords: Environmental sustainability, green supply chain management, radio frequency identification, technology-organization-environment framework, Zuboff’automate-informate-transformate concepts.

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Authors: Tanuj Kanchan, Anadi Gupta, Kewal Krishan

Abstract:

Human skull is shown to exhibit numerous sexually dimorphic traits. Estimation of sex is a challenging task especially when a part of skull is brought for medicolegal investigation. The present research was planned to evaluate the sexing potential of the dimensions of foramen magnum in forensic identification by craniometric analysis. Length and breadth of the foramen magnum was measured using Vernier calipers and the area of foramen magnum was calculated. The length, breadth, and area of foramen magnum were found to be larger in males than females. Sexual dimorphism index was calculated to estimate the sexing potential of each variable. The study observations are suggestive of the limited utility of the craniometric analysis of foramen magnum during the examination of skull and its parts in estimation of sex.

Keywords: Forensic Anthropology, Skeletal remains, Identification, Sex estimation, Foramen magnum.

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Authors: Sh. A. Yousif, M. Bhave

Abstract:

There is strong evidence that water channel proteins 'aquaporins (AQPs)' are central components in plant-water relations as well as a number of other physiological parameters. We had previously reported the isolation of 24 plasma membrane intrinsic protein (PIP) type AQPs. However, the gene numbers in rice and the polyploid nature of bread wheat indicated a high probability of further genes in the latter. The present work focused on identification of further AQP isoforms in bread wheat. With the use of altered primer design, we identified five genes homologous, designated PIP1;5b, PIP2;9b, TaPIP2;2, TaPIP2;2a, TaPIP2;2b. Sequence alignments indicate PIP1;5b, PIP2;9b are likely to be homeologues of two previously reported genes while the other three are new genes and could be homeologs of each other. The results indicate further AQP diversity in wheat and the sequence data will enable physical mapping of these genes to identify their genomes as well as genetic to determine their association with any quantitative trait loci (QTLs) associated with plant-water relation such as salinity or drought tolerance.

Keywords: Aquaporins, homeologues, PIP, wheat

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Authors: Ali Serhan Koyuncugil, Nermin Ozgulbas

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In this paper, a data mining model to SMEs for detecting financial and operational risk indicators by data mining is presenting. The identification of the risk factors by clarifying the relationship between the variables defines the discovery of knowledge from the financial and operational variables. Automatic and estimation oriented information discovery process coincides the definition of data mining. During the formation of model; an easy to understand, easy to interpret and easy to apply utilitarian model that is far from the requirement of theoretical background is targeted by the discovery of the implicit relationships between the data and the identification of effect level of every factor. In addition, this paper is based on a project which was funded by The Scientific and Technological Research Council of Turkey (TUBITAK).

Keywords: Risk Management, Financial Risk, Operational Risk, Financial Early Warning System, Data Mining, CHAID Decision Tree Algorithm, SMEs.

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Authors: J. Dzugan, M. Spaniel, P. Konopík, J. Ruzicka, J. Kuzelka

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The modeling of inelastic behavior of plastic materials requires measurements providing information on material response to different multiaxial loading conditions. Different triaxiality conditions and values of Lode parameters have to be covered for complex description of the material plastic behavior. Samples geometries providing material plastic behavoiur over the range of interest are proposed with the use of FEM analysis. Round samples with 3 different notches and smooth surface are used together with butterfly type of samples tested at angle ranging for 0 to 90°. Identification of ductile damage parameters is carried out on the basis of obtained experimental data for austenitic stainless steel. The obtained material plastic damage parameters are subsequently applied to FEM simulation of notched CT normally samples used for fracture mechanics testing and results from the simulation are compared with real tests.

Keywords: baqus, austenitic steel, computer simulation, ductile damage, triaxiality

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Authors: Mohd Sidek Ahmad, Zainon Mohd Noor, Zaidah Zainal Ariffin

Abstract:

Fibrin degradation is an important part in prevention or treatment of intravascular thrombosis and cardiovascular diseases. Plasmin like fibrinolytic enzymes has given new hope to patient with cardiovascular diseases by treating fibrin aggregation related diseases with traditional plasminogen activator which have many side effects. Various researches involving wide range of sources for production of fibrinolytic proteases, from bacteria, fungi, insects and fermented foods. But few have looked into endophytic fungi as a potential source. Sixteen (16) endophytic fungi were isolated from Hibiscus sp. leaves from six different locations in Shah Alam, Selangor. Only two endophytic fungi, FH3 and S13 showed positive fibrinolytic protease activities. FH3 produced 5.78cm and S13 produced 4.48cm on Skim Milk Agar after 4 days of incubation at 27°C. Fibrinolytic activity was observed; 3.87cm and 1.82cm diameter clear zone on fibrin plate of FH3 and S13 respectively. 18srRNA was done for identification of the isolated fungi with positive fibrinolytic protease. S13 had the highest similarity (100%) to that of Penicillium citrinum strain TG2 and FH3 had the highest similarity (99%) to that of Fusarium sp. FW2PhC1, Fusarium sp. 13002, Fusarium sp. 08006, Fusarium equiseti strain Salicorn 8 and Fungal sp. FCASAn-2. Media composition variation showed the effects of carbon nitrogen on protein concentration, where the decrement of 50% of media composition caused drastic decrease in protease of FH3 from 1.081 to 0.056 and also S13 from 2.946 to 0.198.

Keywords: Isolation, identification, fibrinolytic protease, endophytic fungi, Hibiscus leaves.

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Authors: S. Safi, M. Frikel, M. M'Saad, A. Zeroual

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This paper describes a blind algorithm for estimating a time varying and frequency selective fading channel. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. In this paper, we have selected two theoretical frequency selective channels as the Proakis-s 'B' channel and the Macchi-s channel, and one practical frequency selective fading channel called Broadband Radio Access Network (BRAN A). The simulation results in noisy environment and for different data input channel, demonstrate that the proposed method could estimate the phase and magnitude of these channels blindly and without any information about the input, except that the input excitation is i.i.d (Identically and Independent Distributed) and non-Gaussian.

Keywords: Frequency response, system identification, higher order statistics, communication channels, phase estimation.

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Authors: Thaweesak Yingthawornsuk, Chusak Thanawattano

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Acoustical properties of speech have been shown to be related to mental states of speaker with symptoms: depression and remission. This paper describes way to address the issue of distinguishing depressed patients from remitted subjects based on measureable acoustics change of their spoken sound. The vocal-tract related frequency characteristics of speech samples from female remitted and depressed patients were analyzed via speech processing techniques and consequently, evaluated statistically by cross-validation with Support Vector Machine. Our results comparatively show the classifier's performance with effectively correct separation of 93% determined from testing with the subjectbased feature model and 88% from the frame-based model based on the same speech samples collected from hospital visiting interview sessions between patients and psychiatrists.

Keywords: Depression, SVM, Vocal Extract, Vocal Tract

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Authors: Sudipta Majumdar

Abstract:

This paper presents a method for identification of a linear time invariant (LTI) autonomous all pole system using singular value decomposition. The novelty of this paper is two fold: First, MUSIC algorithm for estimating complex frequencies from real measurements is proposed. Secondly, using the proposed algorithm, we can identify the coefficients of differential equation that determines the LTI system by switching off our input signal. For this purpose, we need only to switch off the input, apply our complex MUSIC algorithm and determine the coefficients as symmetric polynomials in the complex frequencies. This method can be applied to unstable system and has higher resolution as compared to time series solution when, noisy data are used. The classical performance bound, Cramer Rao bound (CRB), has been used as a basis for performance comparison of the proposed method for multiple poles estimation in noisy exponential signal.

Keywords: MUSIC algorithm, Cramer Rao bound, frequency estimation.

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Authors: S. Kotsiantis, E. Koumanakos, D. Tzelepis, V. Tampakas

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This paper explores the effectiveness of machine learning techniques in detecting firms that issue fraudulent financial statements (FFS) and deals with the identification of factors associated to FFS. To this end, a number of experiments have been conducted using representative learning algorithms, which were trained using a data set of 164 fraud and non-fraud Greek firms in the recent period 2001-2002. The decision of which particular method to choose is a complicated problem. A good alternative to choosing only one method is to create a hybrid forecasting system incorporating a number of possible solution methods as components (an ensemble of classifiers). For this purpose, we have implemented a hybrid decision support system that combines the representative algorithms using a stacking variant methodology and achieves better performance than any examined simple and ensemble method. To sum up, this study indicates that the investigation of financial information can be used in the identification of FFS and underline the importance of financial ratios.

Keywords: Machine learning, stacking, classifier.

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Authors: Y. V. Kim

Abstract:

This article presents an approach with regards to the Functional Testing of Space System (SS) that could be a space vehicle (spacecraft-S/C) and/or its equipment and components – S/C subsystems. This test should finalize the Space Qualification Tests (SQT) campaign. It could be considered as a generic test and used for a wide class of SS that, from the point of view of System Dynamics and Control Theory, may be described by the ordinary differential equations. The suggested methodology is based on using semi-natural experiment laboratory stand that does not require complicated, precise and expensive technological control-verification equipment. However, it allows for testing totally assembled system during Assembling, Integration and Testing (AIT) activities at the final phase of SQT, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data are then inserted in a laboratory computer, where it is post-experiment processed by the MATLAB/Simulink Identification Toolbox. It allows for estimating the system dynamics in the form of estimation of its differential equation coefficients through the verification experimental test and comparing them with expected mathematical model, prematurely verified by mathematical simulation during the design process. Mathematical simulation results presented in the article show that this approach could be applicable and helpful in SQT practice. Further semi-natural experiments should specify detail requirements for the test laboratory equipment and test-procedures.

Keywords: system dynamics, space system ground tests, space qualification, system dynamics identification, satellite attitude control, assembling integration and testing

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Authors: Matthew O. Ikuabe, Ayodeji E. Oke, Clinton O. Aigbavboa, Douglas O. Aghimien, Tshepo P. Mokori

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The use of technological innovations has been touted to be beneficial in the delivery of construction projects. Particularly, Radio Frequency Identification (RFID) technology is widely regarded to be of immense advantage for the management of construction projects. This study focused on evaluating the barriers to the use of RFID technology for the delivery of construction projects. Using Gauteng Province in South Africa as the study area, questionnaire was used in eliciting responses from construction professionals which made up the population of the study. Retrieved data were analyzed using Mean Item Score and One-Sample t-test. Findings from the study showed that the most significant barriers to the deployment of RFID for construction project delivery are high cost and lack of awareness. Conclusively, the study made recommendations that would aid in the abatement of the barriers to the use of RFID technology for construction project delivery.

Keywords: Barriers, construction, project delivery, RFID.

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Authors: Thamer Al-Rousan, Shahida Sulaiman, Rosalina Abdul Salam

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Risk management is an essential fraction of project management, which plays a significant role in project success. Many failures associated with Web projects are the consequences of poor awareness of the risks involved and lack of process models that can serve as a guideline for the development of Web based applications. To circumvent this problem, contemporary process models have been devised for the development of conventional software. This paper introduces the WPRiMA (Web Project Risk Management Assessment) as the tool, which is used to implement RIAP, the risk identification architecture pattern model, which focuses upon the data from the proprietor-s and vendor-s perspectives. The paper also illustrates how WPRiMA tool works and how it can be used to calculate the risk level for a given Web project, to generate recommendations in order to facilitate risk avoidance in a project, and to improve the prospects of early risk management.

Keywords: Architecture pattern model, risk factors, risk identification, web project, web project risk management assessment.

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Authors: Kamil Aida-zade, C. Ardil

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In this paper, some problem formulations of dynamic object parameters recovery described by non-autonomous system of ordinary differential equations with multipoint unshared edge conditions are investigated. Depending on the number of additional conditions the problem is reduced to an algebraic equations system or to a problem of quadratic programming. With this purpose the paper offers a new scheme of the edge conditions transfer method called by conditions shift. The method permits to get rid from differential links and multipoint unshared initially-edge conditions. The advantage of the proposed approach is concluded by capabilities of reduction of a parametric identification problem to essential simple problems of the solution of an algebraic system or quadratic programming.

Keywords: dynamic objects, ordinary differential equations, multipoint unshared edge conditions, quadratic programming, conditions shift

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Authors: Muhammad R. Ahmed, Xu Huang, Dharmendra Sharma

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Despite extensive study on wireless sensor network security, defending internal attacks and finding abnormal behaviour of the sensor are still difficult and unsolved task. The conventional cryptographic technique does not give the robust security or detection process to save the network from internal attacker that cause by abnormal behavior. The insider attacker or abnormally behaved sensor identificationand location detection framework using false massage detection and Time difference of Arrival (TDoA) is presented in this paper. It has been shown that the new framework can efficiently identify and detect the insider attacker location so that the attacker can be reprogrammed or subside from the network to save from internal attack.

Keywords: Insider Attaker identification, Abnormal Behaviour, Location detection, Time difference of Arrival (TDoA), Wireless sensor network

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Authors: Houshang Taghizadeh, Gholamreza Soltani Fesghandis

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Nowadays, without the awareness of consumer behavior and correct understanding of it, it is not possible for organizations to take appropriate measures to meet the consumer needs and demands. The aim of this paper is the identification and prioritization of the factors affecting the consumer behavior based on the product value. The population of the study includes all the consumers of furniture producing firms in East Azarbaijan province, Iran. The research sample includes 93 people selected by the sampling formula in unlimited population. The data collection instrument was a questionnaire, the validity of which was confirmed through face validity and the reliability of which was determined, using Cronbach's alpha coefficient. The Kolmogorov-Smironov test was used to test data normality, the t-test for identification of factors affecting the product value, and Friedman test for prioritizing the factors. The results show that quality, satisfaction, styling, price, finishing operation, performance, safety, worth, shape, use, and excellence are placed from 1 to 11 priorities, respectively.

Keywords: Consumer Behavior, Consumer Satisfaction, Product, Value

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Authors: H. Nouri, I. E. Achouri, A. Grimes, H. Ait Said, M. Aissou, Y. Zebboudj

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This paper aims to analysis the behavior of DC corona discharge in wire-to-plate electrostatic precipitators (ESP). Currentvoltage curves are particularly analyzed. Experimental results show that discharge current is strongly affected by the applied voltage. The proposed method of current identification is to use the method of least squares. Least squares problems that of into two categories: linear or ordinary least squares and non-linear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regression analysis; it has a closed-form solution. A closed-form solution (or closed form expression) is any formula that can be evaluated in a finite number of standard operations. The non-linear problem has no closed-form solution and is usually solved by iterative.

Keywords: Electrostatic precipitator, current-voltage characteristics, Least Squares method, electric field, magnetic field.

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Authors: R. A. Temah, L. A. Nkengla-Asi

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Planning for future disasters sets the stage for a variety of activities that may trigger multiple recurring operations and expose the community to opportunities to minimize risks. Local communities are increasingly embracing the necessity for planning based on local risks, but are also significantly challenged to effectively plan and response to disasters. This research examines basic risk-based disaster planning model and compares it with advanced risk-based planning that introduces the identification and alignment of varieties of local capabilities within and out of the local community that can be pivotal to facilitate the management of local risks and cascading effects prior to a disaster. A critical review shows that the identification and alignment of capabilities can potentially enhance risk-based disaster planning. A tailored holistic approach to risk based disaster planning is pivotal to enhance collective action and a reduction in disaster collective cost.

Keywords: Capabilities, disaster planning, hazards, local community, risk-based.

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Authors: A.K. Tangirala, S. Babji

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In the last few years, three multivariate spectral analysis techniques namely, Principal Component Analysis (PCA), Independent Component Analysis (ICA) and Non-negative Matrix Factorization (NMF) have emerged as effective tools for oscillation detection and isolation. While the first method is used in determining the number of oscillatory sources, the latter two methods are used to identify source signatures by formulating the detection problem as a source identification problem in the spectral domain. In this paper, we present a critical drawback of the underlying linear (mixing) model which strongly limits the ability of the associated source separation methods to determine the number of sources and/or identify the physical source signatures. It is shown that the assumed mixing model is only valid if each unit of the process gives equal weighting (all-pass filter) to all oscillatory components in its inputs. This is in contrast to the fact that each unit, in general, acts as a filter with non-uniform frequency response. Thus, the model can only facilitate correct identification of a source with a single frequency component, which is again unrealistic. To overcome this deficiency, an iterative post-processing algorithm that correctly identifies the physical source(s) is developed. An additional issue with the existing methods is that they lack a procedure to pre-screen non-oscillatory/noisy measurements which obscure the identification of oscillatory sources. In this regard, a pre-screening procedure is prescribed based on the notion of sparseness index to eliminate the noisy and non-oscillatory measurements from the data set used for analysis.

Keywords: non-negative matrix factorization, PCA, source separation, plant-wide diagnosis

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Authors: Carsten Röcker

Abstract:

This paper provides an introduction into the evolution of information and communication technology and illustrates its usage in the work domain. The paper is sub-divided into two parts. The first part gives an overview over the different phases of information processing in the work domain. It starts by charting the past and present usage of computers in work environments and shows current technological trends, which are likely to influence future business applications. The second part starts by briefly describing, how the usage of computers changed business processes in the past, and presents first Ambient Intelligence applications based on identification and localization information, which are already used in the production and retail sector. Based on current systems and prototype applications, the paper gives an outlook of how Ambient Intelligence technologies could change business processes in the future.

Keywords: Ambient Intelligence, Ubiquitous Computing, Business Applications, Radio Frequency Identification (RFID).

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Authors: Carsten Röcker

Abstract:

This paper provides an introduction into the evolution of information and communication technology and illustrates its usage in the work domain. The paper is sub-divided into two parts. The first part gives an overview over the different phases of information processing in the work domain. It starts by charting the past and present usage of computers in work environments and shows current technological trends, which are likely to influence future business applications. The second part starts by briefly describing, how the usage of computers changed business processes in the past, and presents first Ambient Intelligence applications based on identification and localization information, which are already used in the production and retail sector. Based on current systems and prototype applications, the paper gives an outlook of how Ambient Intelligence technologies could change business processes in the future.

Keywords: Ambient Intelligence, Ubiquitous Computing, Business Applications, Radio Frequency Identification (RFID)

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Authors: A. A. Hossam-Eldin, E. N. Abdallah, M. S. El-Nozahy

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The identification and elimination of bad measurements is one of the basic functions of a robust state estimator as bad data have the effect of corrupting the results of state estimation according to the popular weighted least squares method. However this is a difficult problem to handle especially when dealing with multiple errors from the interactive conforming type. In this paper, a self adaptive genetic based algorithm is proposed. The algorithm utilizes the results of the classical linearized normal residuals approach to tune the genetic operators thus instead of making a randomized search throughout the whole search space it is more likely to be a directed search thus the optimum solution is obtained at very early stages(maximum of 5 generations). The algorithm utilizes the accumulating databases of already computed cases to reduce the computational burden to minimum. Tests are conducted with reference to the standard IEEE test systems. Test results are very promising.

Keywords: Bad Data, Genetic Algorithms, Linearized Normal residuals, Observability, Power System State Estimation.

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Authors: Mahbobeh Hajirostamloo

Abstract:

Aquatic and semi aquatic birds as a group are suited to feed and breed in environments in which water forms a fundamental part. These birds are biological indicator in aquatic environment, because these birds belong to the top level of food chain in aquatic ecosystems. There are 61 species in 14 families of aquatic and semi aquatic birds in Iran. The birds of the Sattarkhan Lake belong to 16 species in 8 families which include 26.2 percent of total Aquatic and semi aquatic bird species and 57% of Aquatic and semi aquatic bird's family of Iran. Study was carried out monthly at Sattarkhan Lake show the existence of Phalacrocorax carbo, Ardea cinerea, Egretta alba, Egretta garzetta, Bubulcus ibis, Botaurus stellaris, Sterna hirundo, Chlidonias leucopterus, Larus minutus, Larus argentatus, Larus ridibunbus, Alcedo atthis, Ciconia ciconia, Plegadis falcinellus, Circus aeruginosus, Corvus frugilegus

Keywords: Aquatic bird, Sattarkhan Lake, Identification, Iran

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Authors: Young-Seok Choi

Abstract:

We present a family of data-reusing and affine projection algorithms. For identification of a noisy linear finite impulse response channel, a partial knowledge of a channel, especially noise, can be used to improve the performance of the adaptive filter. Motivated by this fact, the proposed scheme incorporates an estimate of a knowledge of noise. A constraint, called the adaptive noise constraint, estimates an unknown information of noise. By imposing this constraint on a cost function of data-reusing and affine projection algorithms, a cost function based on the adaptive noise constraint and Lagrange multiplier is defined. Minimizing the new cost function leads to the adaptive noise constrained (ANC) data-reusing and affine projection algorithms. Experimental results comparing the proposed schemes to standard data-reusing and affine projection algorithms clearly indicate their superior performance.

Keywords: Data-reusing, affine projection algorithm, error constraint, system identification.

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Authors: Nastaran Moosavi, Mohammad Mokhtari

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Seismic inversion is a technique which has been in use for years and its main goal is to estimate and to model physical characteristics of rocks and fluids. Generally, it is a combination of seismic and well-log data. Seismic inversion can be carried out through different methods; we have conducted and compared post-stack and pre- stack seismic inversion methods on real data in one of the fields in the Persian Gulf. Pre-stack seismic inversion can transform seismic data to rock physics such as P-impedance, S-impedance and density. While post- stack seismic inversion can just estimate P-impedance. Then these parameters can be used in reservoir identification. Based on the results of inverting seismic data, a gas reservoir was detected in one of Hydrocarbon oil fields in south of Iran (Persian Gulf). By comparing post stack and pre-stack seismic inversion it can be concluded that the pre-stack seismic inversion provides a more reliable and detailed information for identification and prediction of hydrocarbon reservoirs.

Keywords: Density, P-impedance, S-impedance, post-stack seismic inversion, pre-stack seismic inversion.

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: Genetic data, Pinzgau cattle, supervised learning.

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Authors: Jafar Ahmadi, Nafiseh Noormohammadi, Sedigheh Fabriki Ourang

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GRF, Growth regulating factor, genes encode a novel class of plant-specific transcription factors. The GRF proteins play a role in the regulation of cell numbers in young and growing tissues and may act as transcription activations in growth and development of plants. Identification of GRF genes and their expression are important in plants to performance of the growth and development of various organs. In this study, to better understanding the structural and functional differences of GRFs family, 45 GRF proteins sequences in A. thaliana, Z. mays, O. sativa, B. napus, B. rapa, H. vulgare and S. bicolor, have been collected and analyzed through bioinformatics data mining. As a result, in secondary structure of GRFs, the number of alpha helices was more than beta sheets and in all of them QLQ domains were completely in the biggest alpha helix. In all GRFs, QLQ and WRC domains were completely protected except in AtGRF9. These proteins have no trans-membrane domain and due to have nuclear localization signals act in nuclear and they are component of unstable proteins in the test tube.

Keywords: Domain, Gene Family, GRF, Motif.

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Authors: Eleni Aggelogiannaki, Haralambos Sarimveis

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In this work, a radial basis function (RBF) neural network is developed for the identification of hyperbolic distributed parameter systems (DPSs). This empirical model is based only on process input-output data and used for the estimation of the controlled variables at specific locations, without the need of online solution of partial differential equations (PDEs). The nonlinear model that is obtained is suitably transformed to a nonlinear state space formulation that also takes into account the model mismatch. A stable robust control law is implemented for the attenuation of external disturbances. The proposed identification and control methodology is applied on a long duct, a common component of thermal systems, for a flow based control of temperature distribution. The closed loop performance is significantly improved in comparison to existing control methodologies.

Keywords: Hyperbolic Distributed Parameter Systems, Radial Basis Function Neural Networks, H∞ control, Thermal systems.

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Authors: Chun Hsiang Yang, Cheng Chia Lee, Chiun Hsun Chen

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In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.

Keywords: Micro Gas Turbine, Biogas; System Identification, Distributed power supply system

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Authors: Hyejin Pak, Changsoo Kim, Healahng Choi

Abstract:

The resident registration number was adopted for the purposes of enhanced services for resident convenience and effective performance of governmental administrative affairs. However, it has been used for identification purposes customarily and irrationally in line with the development and spread of the Internet. In response to the growing concern about the leakage of collected RRNs and possible abuses of stolen RRNs, e.g. identity theft, for crimes, the Korean Communications Commission began to take legal/regulatory actions in 2011 to minimize the online collection and use of resident registration numbers. As the use of the RRN was limited after the revision of the Act on Promotion of Information and Communications Network Utilization and Information Protection, etc., online business providers were required to have alternatives to the RRN for the purpose of identifying the user's identity and age, in compliance with the law, and settling disputes with customers. This paper presents means of verifying the personal identity by taking advantage of the commonly used infrastructure and simply replacing personal information entered and stored, without requiring users to enter their RRNs.

Keywords: Resident Registration Numbers(RRNs), Alternative identification for RRNs.

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