Search results for: endpoints identification
2980 Target and Biomarker Identification Platform to Design New Drugs against Aging and Age-Related Diseases
Authors: Peter Fedichev
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We studied fundamental aspects of aging to develop a mathematical model of gene regulatory network. We show that aging manifests itself as an inherent instability of gene network leading to exponential accumulation of regulatory errors with age. To validate our approach we studied age-dependent omic data such as transcriptomes, metabolomes etc. of different model organisms and humans. We build a computational platform based on our model to identify the targets and biomarkers of aging to design new drugs against aging and age-related diseases. As biomarkers of aging, we choose the rate of aging and the biological age since they completely determine the state of the organism. Since rate of aging rapidly changes in response to an external stress, this kind of biomarker can be useful as a tool for quantitative efficacy assessment of drugs, their combinations, dose optimization, chronic toxicity estimate, personalized therapies selection, clinical endpoints achievement (within clinical research), and death risk assessments. According to our model, we propose a method for targets identification for further interventions against aging and age-related diseases. Being a biotech company, we offer a complete pipeline to develop an anti-aging drug-candidate.Keywords: aging, longevity, biomarkers, senescence
Procedia PDF Downloads 2742979 On Modeling Data Sets by Means of a Modified Saddlepoint Approximation
Authors: Serge B. Provost, Yishan Zhang
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A moment-based adjustment to the saddlepoint approximation is introduced in the context of density estimation. First applied to univariate distributions, this methodology is extended to the bivariate case. It then entails estimating the density function associated with each marginal distribution by means of the saddlepoint approximation and applying a bivariate adjustment to the product of the resulting density estimates. The connection to the distribution of empirical copulas will be pointed out. As well, a novel approach is proposed for estimating the support of distribution. As these results solely rely on sample moments and empirical cumulant-generating functions, they are particularly well suited for modeling massive data sets. Several illustrative applications will be presented.Keywords: empirical cumulant-generating function, endpoints identification, saddlepoint approximation, sample moments, density estimation
Procedia PDF Downloads 1622978 Disability, Stigma and In-Group Identification: An Exploration across Different Disability Subgroups
Authors: Sharmila Rathee
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Individuals with disability/ies often face negative attitudes, discrimination, exclusion, and inequality of treatment due to stigmatization and stigmatized treatment. While a significant number of studies in field of stigma suggest that group-identification has positive consequences for stigmatized individuals, ironically very miniscule empirical work in sight has attempted to investigate in-group identification as a coping measure against stigma, humiliation and related experiences among disability group. In view of death of empirical research on in-group identification among disability group, through present work, an attempt has been made to examine the experiences of stigma, humiliation, and in-group identification among disability group. Results of the study suggest that use of in-group identification as a coping strategy is not uniform across members of disability group and degree of in-group identification differs across different sub-groups of disability groups. Further, in-group identification among members of disability group depends on variables like degree and impact of disability, factors like onset of disability, nature, and visibility of disability, educational experiences and resources available to deal with disabling conditions.Keywords: disability, stigma, in-group identification, social identity
Procedia PDF Downloads 3242977 Forensic Challenges in Source Device Identification for Digital Videos
Authors: Mustapha Aminu Bagiwa, Ainuddin Wahid Abdul Wahab, Mohd Yamani Idna Idris, Suleman Khan
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Video source device identification has become a problem of concern in numerous domains especially in multimedia security and digital investigation. This is because videos are now used as evidence in legal proceedings. Source device identification aim at identifying the source of digital devices using the content they produced. However, due to affordable processing tools and the influx in digital content generating devices, source device identification is still a major problem within the digital forensic community. In this paper, we discuss source device identification for digital videos by identifying techniques that were proposed in the literature for model or specific device identification. This is aimed at identifying salient open challenges for future research.Keywords: video forgery, source camcorder, device identification, forgery detection
Procedia PDF Downloads 6312976 Identification of Dynamic Friction Model for High-Precision Motion Control
Authors: Martin Goubej, Tomas Popule, Alois Krejci
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This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model.Keywords: mechanical friction, LuGre model, friction identification, motion control
Procedia PDF Downloads 4132975 Identification of Nonlinear Systems Structured by Hammerstein-Wiener Model
Authors: A. Brouri, F. Giri, A. Mkhida, A. Elkarkri, M. L. Chhibat
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Standard Hammerstein-Wiener models consist of a linear subsystem sandwiched by two memoryless nonlinearities. Presently, the linear subsystem is allowed to be parametric or not, continuous- or discrete-time. The input and output nonlinearities are polynomial and may be noninvertible. A two-stage identification method is developed such the parameters of all nonlinear elements are estimated first using the Kozen-Landau polynomial decomposition algorithm. The obtained estimates are then based upon in the identification of the linear subsystem, making use of suitable pre-ad post-compensators.Keywords: nonlinear system identification, Hammerstein-Wiener systems, frequency identification, polynomial decomposition
Procedia PDF Downloads 5112974 Structural Damage Detection Using Sensors Optimally Located
Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero
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The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structuresKeywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.
Procedia PDF Downloads 4312973 Self-Tuning Robot Control Based on Subspace Identification
Authors: Mathias Marquardt, Peter Dünow, Sandra Baßler
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The paper describes the use of subspace based identification methods for auto tuning of a state space control system. The plant is an unstable but self balancing transport robot. Because of the unstable character of the process it has to be identified from closed loop input-output data. Based on the identified model a state space controller combined with an observer is calculated. The subspace identification algorithm and the controller design procedure is combined to a auto tuning method. The capability of the approach was verified in a simulation experiments under different process conditions.Keywords: auto tuning, balanced robot, closed loop identification, subspace identification
Procedia PDF Downloads 3802972 Distributed Perceptually Important Point Identification for Time Series Data Mining
Authors: Tak-Chung Fu, Ying-Kit Hung, Fu-Lai Chung
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In the field of time series data mining, the concept of the Perceptually Important Point (PIP) identification process is first introduced in 2001. This process originally works for financial time series pattern matching and it is then found suitable for time series dimensionality reduction and representation. Its strength is on preserving the overall shape of the time series by identifying the salient points in it. With the rise of Big Data, time series data contributes a major proportion, especially on the data which generates by sensors in the Internet of Things (IoT) environment. According to the nature of PIP identification and the successful cases, it is worth to further explore the opportunity to apply PIP in time series ‘Big Data’. However, the performance of PIP identification is always considered as the limitation when dealing with ‘Big’ time series data. In this paper, two distributed versions of PIP identification based on the Specialized Binary (SB) Tree are proposed. The proposed approaches solve the bottleneck when running the PIP identification process in a standalone computer. Improvement in term of speed is obtained by the distributed versions.Keywords: distributed computing, performance analysis, Perceptually Important Point identification, time series data mining
Procedia PDF Downloads 4332971 Genetic Algorithms for Parameter Identification of DC Motor ARMAX Model and Optimal Control
Authors: A. Mansouri, F. Krim
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This paper presents two techniques for DC motor parameters identification. We propose a numerical method using the adaptive extensive recursive least squares (AERLS) algorithm for real time parameters estimation. This algorithm, based on minimization of quadratic criterion, is realized in simulation for parameters identification of DC motor autoregressive moving average with extra inputs (ARMAX). As advanced technique, we use genetic algorithms (GA) identification with biased estimation for high dynamic performance speed regulation. DC motors are extensively used in variable speed drives, for robot and solar panel trajectory control. GA effectiveness is derived through comparison of the two approaches.Keywords: ARMAX model, DC motor, AERLS, GA, optimization, parameter identification, PID speed regulation
Procedia PDF Downloads 3792970 Machine Learning Based Gender Identification of Authors of Entry Programs
Authors: Go Woon Kwak, Siyoung Jun, Soyun Maeng, Haeyoung Lee
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Entry is an education platform used in South Korea, created to help students learn to program, in which they can learn to code while playing. Using the online version of the entry, teachers can easily assign programming homework to the student and the students can make programs simply by linking programming blocks. However, the programs may be made by others, so that the authors of the programs should be identified. In this paper, as the first step toward author identification of entry programs, we present an artificial neural network based classification approach to identify genders of authors of a program written in an entry. A neural network has been trained from labeled training data that we have collected. Our result in progress, although preliminary, shows that the proposed approach could be feasible to be applied to the online version of entry for gender identification of authors. As future work, we will first use a machine learning technique for age identification of entry programs, which would be the second step toward the author identification.Keywords: artificial intelligence, author identification, deep neural network, gender identification, machine learning
Procedia PDF Downloads 3232969 Methodology for the Integration of Object Identification Processes in Handling and Logistic Systems
Authors: L. Kiefer, C. Richter, G. Reinhart
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The uprising complexity in production systems due to an increasing amount of variants up to customer innovated products leads to requirements that hierarchical control systems are not able to fulfil. Therefore, factory planners can install autonomous manufacturing systems. The fundamental requirement for an autonomous control is the identification of objects within production systems. In this approach an attribute-based identification is focused for avoiding dose-dependent identification costs. Instead of using an identification mark (ID) like a radio frequency identification (RFID)-Tag, an object type is directly identified by its attributes. To facilitate that it’s recommended to include the identification and the corresponding sensors within handling processes, which connect all manufacturing processes and therefore ensure a high identification rate and reduce blind spots. The presented methodology reduces the individual effort to integrate identification processes in handling systems. First, suitable object attributes and sensor systems for object identification in a production environment are defined. By categorising these sensor systems as well as handling systems, it is possible to match them universal within a compatibility matrix. Based on that compatibility further requirements like identification time are analysed, which decide whether the combination of handling and sensor system is well suited for parallel handling and identification within an autonomous control. By analysing a list of more than thousand possible attributes, first investigations have shown, that five main characteristics (weight, form, colour, amount, and position of subattributes as drillings) are sufficient for an integrable identification. This knowledge limits the variety of identification systems and leads to a manageable complexity within the selection process. Besides the procedure, several tools, as an example a sensor pool are presented. These tools include the generated specific expert knowledge and simplify the selection. The primary tool is a pool of preconfigured identification processes depending on the chosen combination of sensor and handling device. By following the defined procedure and using the created tools, even laypeople out of other scientific fields can choose an appropriate combination of handling devices and sensors which enable parallel handling and identification.Keywords: agent systems, autonomous control, handling systems, identification
Procedia PDF Downloads 1772968 Frequency Identification of Wiener-Hammerstein Systems
Authors: Brouri Adil, Giri Fouad
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The problem of identifying Wiener-Hammerstein systems is addressed in the presence of two linear subsystems of structure totally unknown. Presently, the nonlinear element is allowed to be noninvertible. The system identification problem is dealt by developing a two-stage frequency identification method such a set of points of the nonlinearity are estimated first. Then, the frequency gains of the two linear subsystems are determined at a number of frequencies. The method involves Fourier series decomposition and only requires periodic excitation signals. All involved estimators are shown to be consistent.Keywords: Wiener-Hammerstein systems, Fourier series expansions, frequency identification, automation science
Procedia PDF Downloads 5352967 The Effect of Measurement Distribution on System Identification and Detection of Behavior of Nonlinearities of Data
Authors: Mohammad Javad Mollakazemi, Farhad Asadi, Aref Ghafouri
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In this paper, we considered and applied parametric modeling for some experimental data of dynamical system. In this study, we investigated the different distribution of output measurement from some dynamical systems. Also, with variance processing in experimental data we obtained the region of nonlinearity in experimental data and then identification of output section is applied in different situation and data distribution. Finally, the effect of the spanning the measurement such as variance to identification and limitation of this approach is explained.Keywords: Gaussian process, nonlinearity distribution, particle filter, system identification
Procedia PDF Downloads 5152966 Evaluation of the Patient Identification Process in Healthcare Facilities in a Brazilian City Area
Authors: Carmen Silvia Gabriel, Maria de Fátima Paiva Brito, Mariane de Paula Candido, Vanessa Barato Oliveira
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Patient identification is a necessary practice to ensure patient safety in any healthcare environment, including emergency care units, test laboratories, home care and clinics. The present study aimed to provide evidence that can effectively contribute to practices concerning patient identification. Its objective was to investigate patient identification in basic healthcare units through patient safety standards. To do so, a descriptive and non-experimental research outline study was carried out to inquire how patient identification takes place in a particular situation. All technical manager nurses from the chosen healthcare facilities were included in the sample for the study. Data was collected in September of 2014 after approval from the Committee of Ethics. All researched institutions fit the same profile: they’re public facilities for general care with observation beds. None of them has a wristband identification protocol or policy. Only one institution mentioned using some kind of visual identification; namely, body tags separated by colors according to the type of care, but it still does not apply the recommended tags by the Brazilian Ministry of Health. This study allowed the authors to acknowledge how important the commitment from the whole healthcare team in the patient identification process is and also acknowledge how necessary it is to implement institutional policies that may aid the healthcare units in this area to promote a quality and safe patient care.Keywords: patient safety, identification, nursing, emergency care units
Procedia PDF Downloads 4062965 Use of Digital Forensics for Sex Determination by Nasal Index
Authors: Ashwini Kumar, Vinod Nayak, Shankar M. Bakkannavar
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The identification of humans is important in forensic investigations not only in living but also in dead, especially in cases of mass disorders. The procedure followed in dead known as post-mortem identification is a challenging task for the forensic pathologist. However, it is mandatory in terms of the law to fulfill the social norms. Many times, due to mutilation of body parts, the normal methods of identification using skeletal remains cannot be used in the process of identification. In such cases, the intact components of the skeletal remains or bony parts play an important role in identification. In these situations, digital forensics can come to our rescue. The authors hereby made a study for determination of sex based on nasal index by using (Big Bore 16 Slice) Multidetector Computed Tomography 2D Scans. The results are represented as a poster.Keywords: sex determination, multidetector computed tomography, nasal index, digital forensic
Procedia PDF Downloads 3982964 System Identification and Quantitative Feedback Theory Design of a Lathe Spindle
Authors: M. Khairudin
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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.Keywords: lathe spindle, QFT, robust control, system identification
Procedia PDF Downloads 5432963 Identification of Shocks from Unconventional Monetary Policy Measures
Authors: Margarita Grushanina
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After several prominent central banks including European Central Bank (ECB), Federal Reserve System (Fed), Bank of Japan and Bank of England employed unconventional monetary policies in the aftermath of the financial crisis of 2008-2009 the problem of identification of the effects from such policies became of great interest. One of the main difficulties in identification of shocks from unconventional monetary policy measures in structural VAR analysis is that they often are anticipated, which leads to a non-fundamental MA representation of the VAR model. Moreover, the unconventional monetary policy actions may indirectly transmit to markets information about the future stance of the interest rate, which raises a question of the plausibility of the assumption of orthogonality between shocks from unconventional and conventional policy measures. This paper offers a method of identification that takes into account the abovementioned issues. The author uses factor-augmented VARs to increase the information set and identification through heteroskedasticity of error terms and rank restrictions on the errors’ second moments’ matrix to deal with the cross-correlation of the structural shocks.Keywords: factor-augmented VARs, identification through heteroskedasticity, monetary policy, structural VARs
Procedia PDF Downloads 3482962 Effective Tandem Mesh Nebulisation of Pulmonary Vasodilator and Bronchodilators in Critical Respiratory Failure
Authors: Nathalie Bolding, Marta Montero, Joaquim Cevallos, Juan F. Martin-Lazaro
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Background: Inhaled epoprostenol (iEPO) have been shown to improve PaO2:FiO2 (PF) in combination with bronchodilators (BD). However, there is not an available device to deliver these two therapies concomitantly. We describe a new method to provide this therapy successfully. Objective: To evaluate the response to continuous nebulization of iEPO and intermittent nebulization of Salbutamol/Ipratropium bromide in adults with severe respiratory failure through a double mesh nebulisation in tandem. Methods: This observational study included two mechanical ventilated adults under hourly ventilatory, gasometrical and clinical measurements during 48h. Both had severe respiratory failure treated with continuous iEPO (50 – 200 micrograms/h) and BD (Salbutamol 2.5 mg and Ipratropium bromide 500 mcg every 6 hours) through double mesh nebulisation (Aerogen solo®) placed in tandem in the dry side of the humidificator. The primary endpoints were the variables associated with a positive response to this tandem nebulised therapy (PaFiO2 index, ROX index). Secondary endpoints were laboratory (ABG) clinical and ventilatory variables. Statistical analysis (SPSS v29) included linear regression and ANOVA. Results: The patients included (n=2) survived, both extubated, one after ECMO therapy. Severe acute respiratory failure had a positive response rate to continuous iEPO and intermittent BD: PaFiO2 increased (7.40 to 30.91; P75: 27%) as well as ROX index (2.91 to 11.43; P75: 33%). There was a linear correlation of improvement between iEPO with PaFiO2 (ANOVA, r=0.393, p<0.002) and ROX (r=0.419, p<0.001). iEPO+BD therapy did not show any complications. Conclusion: Continuous and intermittent mesh tandem nebulisation can be effectively delivered with this method with a positive effect in ventilatory parameters without observed complications. Randomised studies will be able to provide reassurance in this new therapy.Keywords: tandem, mesh, nebulisers, pulmonary, vasoldilators, bronchodilators, respiratory, failure
Procedia PDF Downloads 832961 UEMSD Risk Identification: Case Study
Authors: K. Sekulová, M. Šimon
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The article demonstrates on a case study how it is possible to identify MSD risk. It is based on a dissertation risk identification model of occupational diseases formation in relation to the work activity that determines what risk can endanger workers who are exposed to the specific risk factors. It is evaluated based on statistical calculations. These risk factors are main cause of upper-extremities musculoskeletal disorders.Keywords: case study, upper-extremity musculoskeletal disorders, ergonomics, risk identification
Procedia PDF Downloads 4992960 An Improved Parameter Identification Method for Three Phase Induction Motor
Authors: Liang Zhao, Chong-quan Zhong
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In order to improve the control performance of vector inverter, an improved parameter identification solution for induction motor is proposed in this paper. Dc or AC voltage is applied to the induction motor using the SVPWM through the inverter. Then stator resistance, stator leakage inductance, rotor resistance, rotor leakage inductance and mutual inductance are obtained according to the signal response. The discrete Fourier transform (DFT) is used to deal with the noise and harmonic. The impact on parameter identification caused by delays in the inverter switch tube, tube voltage drop and dead-time is avoided by effective compensation measures. Finally, the parameter identification experiment is conducted based on the vector inverter which using TMS320F2808 DSP as the core processor and results show that the strategy is verified.Keywords: vector inverter, parameter identification, SVPWM; DFT, dead-time compensation
Procedia PDF Downloads 4612959 Modeling of a UAV Longitudinal Dynamics through System Identification Technique
Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad
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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc. This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.Keywords: fixed wing UAV, system identification, black box modeling, longitudinal dynamics, least square error
Procedia PDF Downloads 3252958 Morphological and Biological Identification of Fusarium Species Associated with Ear Rot Disease of Maize in Indonesia and Malaysia
Authors: Darnetty Baharuddin Salleh
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Fusarium ear rot disease is one of the most important diseases of maize and not only causes significant losses but also produced harmful mycotoxins to animals and humans. A total of 141 strains of Fusarium species were isolated from maize plants showing typical ear rot symptoms in Indonesia, and Malaysia by using the semi-selective medium (peptone pentachloronitrobenzene agar, PPA). These strains were identified morphologically. For strains in Gibberella fujikuroi species complex (Gfsc), the identification was continued by using biological identification. Three species of Fusarium were morphologically identified as Fusarium in Gibberella species complex (105 strains, 74.5%), F. verticillioides (78 strains), F. proliferatum (24 strains) and F. subglutinans (3 strains) and five species from other section (36 strains, 25.5%), F. graminearum (14 strains), F. oxysporum (8 strains), F. solani ( 1 strain), and F. semitectum (13 strains). Out of 105 Fusarium species in Gfsc, 63 strains were identified as MAT-1, 25 strains as MAT-2 and 17 strains could not be identified and in crosses with nine standard testers, three mating populations of Fusarium were identified as MP-A, G. moniliformis (68 strains, 64.76%), MP-D, G. intermedia (21 strains, 20%) and MP-E, G. subglutinans (3 strains, 2.9%), and 13 strains (12.38%) could not be identified. All trains biologically identified as MP-A, MP-D, and MP-E, were identified morphologically as F. verticillioides, F. proliferatum, and F. subglutinans, respectively. Thus, the results of this study indicated that identification based on biological identification were consistent with those of morphological identification. This is the first report on the presence of MP-A, MP-D, and MP-E on ear rot-infected maize in Indonesia; MP-A and MP-E in Malaysia.Keywords: Fusarium, MAT-1, MAT-2, MP-A, MP-D, MP-E
Procedia PDF Downloads 3102957 The Impact of the Cross Race Effect on Eyewitness Identification
Authors: Leah Wilck
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Eyewitness identification is arguably one of the most utilized practices within our legal system; however, exoneration cases indicate that this practice may lead to accuracy and conviction errors. The purpose of this study was to examine the effects of the cross-race effect, the phenomena in which people are able to more easily and accurately identify faces from within their racial category, on the accuracy of eyewitness identification. Participants watched three separate videos of a perpetrator trying to steal a bicycle. In each video, the perpetrator was of a different race and gender. Participants watched a video where the perpetrator was a Black male, a White male, and a White female. Following the completion of watching each video, participants were asked to recall everything they could about the perpetrator they witnessed. The initial results of the study did not find the expected cross-race effect impacted the eyewitness identification accuracy. These surprising results are discussed in terms of cross-race bias and recognition theory as well as applied implications.Keywords: cross race effect, eyewitness identification, own-race bias, racial profiling
Procedia PDF Downloads 1642956 Discontinuous Galerkin Method for Higher-Order Ordinary Differential Equations
Authors: Helmi Temimi
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In this paper, we study the super-convergence properties of the discontinuous Galerkin (DG) method applied to one-dimensional mth-order ordinary differential equations without introducing auxiliary variables. We found that nth−derivative of the DG solution exhibits an optimal O (hp+1−n) convergence rates in the L2-norm when p-degree piecewise polynomials with p≥1 are used. We further found that the odd-derivatives and the even derivatives are super convergent, respectively, at the upwind and downwind endpoints.Keywords: discontinuous, galerkin, superconvergence, higherorder, error, estimates
Procedia PDF Downloads 4782955 New Approach for Constructing a Secure Biometric Database
Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir
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The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking
Procedia PDF Downloads 3902954 Early Talent Identification and Its Impact on Children’s Growth and Development: An Examination of “The Social Learning Theory, by Albert Bandura"
Authors: Michael Subbey, Kwame Takyi Danquah
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Finding a child's exceptional skills and abilities at a young age and nurturing them is a challenging process. The Social Learning Theory (SLT) of Albert Bandura is used to analyze the effects of early talent identification on children's growth and development. The study examines both the advantages and disadvantages of early talent identification and stresses the significance of a moral strategy that puts the welfare of the child first. The paper emphasizes the value of a balanced approach to early talent identification that takes into account individual differences, cultural considerations, and the child's social environment.Keywords: early talent development, social learning theory, child development, child welfare
Procedia PDF Downloads 1082953 Urban and Rural Children’s Knowledge on Biodiversity in Bizkaia: Tree Identification Skills and Animal and Plant Listing
Authors: Joserra Díez, Ainhoa Meñika, Iñaki Sanz-Azkue, Arritokieta Ortuzar
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Biodiversity provides humans with a great range of ecosystemic services; it is therefore an indispensable resource and a legacy to coming generations. However, in the last decades, the increasing exploitation of the Planet has caused a great loss of biodiversity and its acquaintance has decreased remarkably; especially in urbanized areas, due to the decreasing attachment of humans to nature. Yet, the Primary Education curriculum primes the identification of flora and fauna to guarantee the knowledge of children on their surroundings, so that they care for the environment as well as for themselves. In order to produce effective didactic material that meets the needs of both teachers and pupils, it is fundamental to diagnose the current situation. In the present work, the knowledge on biodiversity of 3rd cycle Primary Education students in Biscay (n=98) and its relation to the size of the town/city of their school is discussed. Two tests have been used with such aim: one for tree identification and the other one so that the students enumerated the species of trees and animals they knew. Results reveal that knowledge of students on tree identification is scarce regardless the size of the city/town and of their school. On the other hand, animal species are better known than tree species.Keywords: biodiversity, population, tree identification, animal identification
Procedia PDF Downloads 1972952 Ultracapacitor State-of-Energy Monitoring System with On-Line Parameter Identification
Authors: N. Reichbach, A. Kuperman
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The paper describes a design of a monitoring system for super capacitor packs in propulsion systems, allowing determining the instantaneous energy capacity under power loading. The system contains real-time recursive-least-squares identification mechanism, estimating the values of pack capacitance and equivalent series resistance. These values are required for accurate calculation of the state-of-energy.Keywords: real-time monitoring, RLS identification algorithm, state-of-energy, super capacitor
Procedia PDF Downloads 5352951 Kalman Filter Design in Structural Identification with Unknown Excitation
Authors: Z. Masoumi, B. Moaveni
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This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.Keywords: Kalman filter (KF), least square estimation (LSE), structural health monitoring (SHM), structural system identification
Procedia PDF Downloads 317