Search results for: Alternative identification for RRNs.

Authors: F. Caliskan

Abstract:

This paper presents a Neural Network (NN) identification of icing parameters in an A340 aircraft and a reconfiguration technique to keep the A/C performance close to the performance prior to icing. Five aircraft parameters are assumed to be considerably affected by icing. The off-line training for identifying the clear and iced dynamics is based on the Levenberg-Marquard Backpropagation algorithm. The icing parameters are located in the system matrix. The physical locations of the icing are assumed at the right and left wings. The reconfiguration is based on the technique known as the control mixer approach or pseudo inverse technique. This technique generates the new control input vector such that the A/C dynamics is not much affected by icing. In the simulations, the longitudinal and lateral dynamics of an Airbus A340 aircraft model are considered, and the stability derivatives affected by icing are identified. The simulation results show the successful NN identification of the icing parameters and the reconfigured flight dynamics having the similar performance before the icing. In other words, the destabilizing icing affect is compensated.

Keywords: Aircraft Icing, Stability Derivatives, Neural NetworkIdentification, Reconfiguration.

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Authors: Pang-Chieh Wang, Ting-Wei Hou, Jung-Hsuan Wu, Bo-Chiuan Chen

Abstract:

In this paper we discuss on the security module for the car appliances to prevent stealing and illegal use on other cars. We proposed an open structure including authentication and encryption by embed a security module in each to protect car appliances. Illegal moving and use a car appliance with the security module without permission will lead the appliance to useless. This paper also presents the component identification and deal with relevant procedures. It is at low cost to recover from destroys by the burglar. Expect this paper to offer the new business opportunity to the automotive and technology industry.

Keywords: Automotive, component identification, electronic immobilizer, key management.

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Authors: Sudipta Majumdar, Harish Parthasarathy

Abstract:

In this paper, a wavelet based method is proposed to identify the constant coefficients of a second order linear system and is compared with the least squares method. The proposed method shows improved accuracy of parameter estimation as compared to the least squares method. Additionally, it has the advantage of smaller data requirement and storage requirement as compared to the least squares method.

Keywords: Least squares method, linear system, system identification, wavelet transform.

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Authors: P. Ninduangdee, V. I. Kuprianov

Abstract:

Palm kernel shell is an important bioenergy resource in Thailand. However, due to elevated alkali content in biomass ash, this oil palm residue shows high tendency to bed agglomeration in a fluidized-bed combustion system using conventional bed material (silica sand). In this study, palm kernel shell was burned in the conical fluidized-bed combustor (FBC) using alumina and dolomite as alternative bed materials to prevent bed agglomeration. For each bed material, the combustion tests were performed at 45kg/h fuel feed rate with excess air within 20–80%. Experimental results revealed rather weak effects of the bed material type but substantial influence of excess air on the behavior of temperature, O2, CO, CxHy, and NO inside the reactor, as well as on the combustion efficiency and major gaseous emissions of the conical FBC. The optimal level of excess air ensuring high combustion efficiency (about 98.5%) and acceptable level of the emissions was found to be about 40% when using alumina and 60% with dolomite. By using these alternative bed materials, bed agglomeration can be prevented when burning the shell in the proposed conical FBC. However, both bed materials exhibited significant changes in their morphological, physical and chemical properties in the course of the time.

Keywords: Palm kernel shell, fluidized-bed combustion, alternative bed materials, combustion and emission performance, bed agglomeration prevention.

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Authors: Paulo Gomes, Adelaide Figueiredo

Abstract:

We consider n individuals described by p standardized variables, represented by points of the surface of the unit hypersphere S_n-1. For a previous choice of n individuals we suppose that the set of observables variables comes from a mixture of bipolar Watson distribution defined on the hypersphere. EM and Dynamic Clusters algorithms are used for identification of such mixture. We obtain estimates of parameters for each Watson component and then a partition of the set of variables into homogeneous groups of variables. Additionally we will present a factor analysis model where unobservable factors are just the maximum likelihood estimators of Watson directional parameters, exactly the first principal component of data matrix associated to each group previously identified. Such alternative model it will yield us to directly interpretable solutions (simple structure), avoiding factors rotations.

Keywords: Dynamic Clusters algorithm, EM algorithm, Factor analysis model, Hierarchical Clustering, Watson distribution.

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Authors: M.V Rajesh, Archana R, A Unnikrishnan, R Gopikakumari, Jeevamma Jacob

Abstract:

The System Identification problem looks for a suitably parameterized model, representing a given process. The parameters of the model are adjusted to optimize a performance function based on error between the given process output and identified process output. The linear system identification field is well established with many classical approaches whereas most of those methods cannot be applied for nonlinear systems. The problem becomes tougher if the system is completely unknown with only the output time series is available. It has been reported that the capability of Artificial Neural Network to approximate all linear and nonlinear input-output maps makes it predominantly suitable for the identification of nonlinear systems, where only the output time series is available. [1][2][4][5]. The work reported here is an attempt to implement few of the well known algorithms in the context of modeling of nonlinear systems, and to make a performance comparison to establish the relative merits and demerits.

Keywords: Multilayer neural networks, Radial Basis Functions, Clustering algorithm, Back Propagation training, Extended Kalmanfiltering, Mean Square Error, Nonlinear Modeling, Cramer RaoLower Bound.

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Authors: A. Bumbová, M. Čáslavský, F. Božek, J. Dvořák

Abstract:

The paper deals with the analysis of hazards and sensitivity of potential resource of emergency water supply of population in a selected region of the Czech Republic. The procedure of identification and analysis of hazards and sensitivity is carried out on the basis of a unique methodology of classifying the drinking water resources earmarked for emergency supply of population. The hazard identification is based on a general register of hazards for individual parts of hydrological structure and the elements of technological equipment. It is followed by a semi-quantitative point indexation for the activation of each identified hazard, i.e. fires of anthropogenic origin, flood and the increased radioactive background accompanied by the leak of radon. Point indexation of sensitivity has been carried out at the same time. The analysis is the basis for a risk assessment of potential resource of emergency supply of population and the subsequent classification of such resource within the system of crisis planning.

Keywords: Hazard identification, sensitivity, semi-quantitative assessment, emergency water supply, crisis situation, ground water.

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Authors: Weifeng Wang, Guoqing Huang, Xianwei Zeng

Abstract:

The nearly 21-year-old Jiujiang Bridge, which is suffering from uneven line shape, constant great downwarping of the main beam and cracking of the box girder, needs reinforcement and cable adjustment. It has undergone cable adjustment for twice with incomplete data. Therefore, the initial internal force state of the Jiujiang Bridge is identified as the key for the cable adjustment project. Based on parameter identification by means of static force test data, this paper suggests determining the initial internal force state of the cable-stayed bridge according to the cable force-displacement relationship parameter identification method. That is, upon measuring the displacement and the change in cable forces for twice, one can identify the parameters concerned by means of optimization. This method is applied to the cable adjustment, replacement and reinforcement project for the Jiujiang Bridge as a guidance for the cable adjustment and reinforcement project of the bridge.

Keywords: Cable-stayed bridge, cable force-displacement, parameter identification, internal force state

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Authors: Atilla Akpinar, Basri Celik

Abstract:

In this paper we are interested in Moufang-Klingenberg planesM(A) defined over a local alternative ring A of dual numbers. We show that a collineation of M(A) preserve cross-ratio. Also, we obtain some results about harmonic points.

Keywords: Moufang-Klingenberg planes, local alternative ring, projective collineation, cross-ratio, harmonic points.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

Abstract:

Email has become a fast and cheap means of online communication. The main threat to email is Unsolicited Bulk Email (UBE), commonly called spam email. The current work aims at identification of unigrams in more than 2700 UBE that advertise body-enhancement drugs. The identification is based on the requirement that the unigram is neither present in dictionary, nor is a slang term. The motives of the paper are many fold. This is an attempt to analyze spamming behaviour and employment of wordmutation technique. On the side-lines of the paper, we have attempted to better understand the spam, the slang and their interplay. The problem has been addressed by employing Tokenization technique and Unigram BOW model. We found that the non-lexicon words constitute nearly 66% of total number of lexis of corpus whereas non-slang words constitute nearly 2.4% of non-lexicon words. Further, non-lexicon non-slang unigrams composed of 2 lexicon words, form more than 71% of the total number of such unigrams. To the best of our knowledge, this is the first attempt to analyze usage of non-lexicon non-slang unigrams in any kind of UBE.

Keywords: Body Enhancement, Lexicon, Medicinal, Slang, Unigram, Unsolicited Bulk e-mail (UBE)

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Authors: Salvatore Pinna

Abstract:

The growth of organic farming practices in the last few decades is continuing to stimulate the international debate about this alternative food market. As a part of a PhD project research about embeddedness in Alternative Food Networks (AFNs), this paper focuses on the promotional aspects of organic farms websites from the Madrid region. As a theoretical tool, some knowledge categories drawn on the geographic studies literature are used to classify the many ideas expressed in the web pages. By analysing texts and pictures of 30 websites, the study aims to question how and to what extent actors from organic world communicate to the potential customers their personal beliefs about farming practices, products qualities, and ecological and social benefits. Moreover, the paper raises the question of whether organic farming laws and regulations lack of completeness about the social and cultural aspects of food.

Keywords: Alternative food networks, de-commoditisation, organic farming, Madrid, reconnection of food.

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Authors: Emmanuel U. Ohaegbulem, Felix N. Nwobi

Abstract:

Alternative and simple computational arrangements in carrying out multivariate profile analysis when more than two groups (populations) are involved are presented. These arrangements have been demonstrated to not only yield equivalent results for the test statistics (the Wilks lambdas), but they have less computational efforts relative to other arrangements so far presented in the literature; in addition to being quite simple and easy to apply.

Keywords: Coincident profiles, g-group profile analysis, level profiles, parallel profiles, repeated measures MANOVA.

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Authors: Rebecca Angeles

Abstract:

This case study features the Kuehne + Nagel PharmaChain solution for ‘cold chain’ pharmaceutical and biologic product shipments with IOT-enabled features for shipment temperature and location tracking. Using the case study method and content analysis, this research project investigates the application of the structurational model of technology theory introduced by Orlikowski in order to interpret the firm’s entry and participation in the IOT-impelled marketplace.

Keywords: Internet of things, IoT, radio frequency identification, supply chain management, business intelligence.

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Authors: Young-Seok Choi

Abstract:

This work presents a new type of the affine projection (AP) algorithms which incorporate the sparsity condition of a system. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weighting for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results exhibit that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.

Keywords: System identification, adaptive filter, affine projection, sparsity, sparse system.

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Authors: Guoyuan Qi , Yskandar Hamam, Barend Jacobus van Wyk, Shengzhi Du

Abstract:

The majority of existing predictors for time series are model-dependent and therefore require some prior knowledge for the identification of complex systems, usually involving system identification, extensive training, or online adaptation in the case of time-varying systems. Additionally, since a time series is usually generated by complex processes such as the stock market or other chaotic systems, identification, modeling or the online updating of parameters can be problematic. In this paper a model-free predictor (MFP) for a time series produced by an unknown nonlinear system or process is derived using tracking theory. An identical derivation of the MFP using the property of the Newton form of the interpolating polynomial is also presented. The MFP is able to accurately predict future values of a time series, is stable, has few tuning parameters and is desirable for engineering applications due to its simplicity, fast prediction speed and extremely low computational load. The performance of the proposed MFP is demonstrated using the prediction of the Dow Jones Industrial Average stock index.

Keywords: Forecast, model-free predictor, prediction, time series

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Authors: A. Doosti, S. Moshkelani

Abstract:

Brucellosis is a zoonotic disease; its symptoms and appearances are not exclusive in human and its traditional diagnosis is based on culture, serological methods and conventional PCR. For more sensitive, specific detection and differentiation of Brucella spp., the real time PCR method is recommended. This research has performed to determine the presence and prevalence of Brucella spp. and differentiation of Brucella abortus and Brucella melitensis in house mouse (Mus musculus) in west of Iran. A TaqMan analysis and single-step PCR was carried out in total 326 DNA of Mouse's spleen samples. From the total number of 326 samples, 128 (39.27%) gave positive results for Brucella spp. by conventional PCR, also 65 and 32 out of the 128 specimens were positive for B. melitensis, B. abortus, respectively. These results indicate a high presence of this pathogen in this area and that real time PCR is considerably faster than current standard methods for identification and differentiation of Brucella species. To our knowledge, this study is the first prevalence report of direct identification and differentiation of B. abortus and B. melitensis by real time PCR in mouse tissue samples in Iran.

Keywords: Differentiation, B. abortus, B. melitensis, TaqManprobe, Iran.

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Authors: Niina M. Nissinen

Abstract:

This paper introduces an approach to construct a set of criteria for evaluating alternative options. Content analysis was used to collet criterion elements. Then the elements were classified and organized yielding to hierarchic structure. The reliability of the constructed criteria was evaluated in an experiment. Finally the criteria were used to evaluate alternative options indecision-making.

Keywords: Conceptual analysis, Content Analysis, Criteria, Decision-Making, Evaluation of Candidates

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Authors: Satya P. Dubey, Hrushikesh A. Abhyankar, Veronica Marchante, James L. Brighton, Björn Bergmann

Abstract:

PLA emerged as a promising polymer because of its property as a compostable, biodegradable thermoplastic made from renewable sources. PLA can be polymerized from monomers (Lactide or Lactic acid) obtained by fermentation processes from renewable sources such as corn starch or sugarcane. For PLA synthesis, ring opening polymerization (ROP) of Lactide monomer is one of the preferred methods. In the literature, the technique mainly developed for ROP of PLA is based on metal/bimetallic catalyst (Sn, Zn and Al) or other organic catalysts in suitable solvent. However, the PLA synthesized using such catalysts may contain trace elements of the catalyst which may cause toxicity. This work estimated the usefulness and drawbacks of using different catalysts as well as effect of alternative energies and future aspects for PLA production.

Keywords: Alternative energy, bio-degradable, metal catalyst, poly lactic acid (PLA), ring opening polymerization (ROP).

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Authors: R. Biondi, G. Dys, G. Ferone, T. Renard, M. Zysman

Abstract:

This paper describes an automated implementable system for impulsive signals detection and recognition. The system uses a Digital Signal Processing device for the detection and identification process. Here the system analyses the signals in real time in order to produce a particular response if needed. The system analyses the signals in real time in order to produce a specific output if needed. Detection is achieved through normalizing the inputs and comparing the read signals to a dynamic threshold and thus avoiding detections linked to loud or fluctuating environing noise. Identification is done through neuronal network algorithms. As a setup our system can receive signals to “learn” certain patterns. Through “learning” the system can recognize signals faster, inducing flexibility to new patterns similar to those known. Sound is captured through a simple jack input, and could be changed for an enhanced recording surface such as a wide-area recorder. Furthermore a communication module can be added to the apparatus to send alerts to another interface if needed.

Keywords: Sound Detection, Impulsive Signal, Background Noise, Neural Network.

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Authors: Mohammed Zidane, Said Safi, Mohamed Sabri, Ahmed Boumezzough

Abstract:

This paper describes a blind algorithm, which is compared with two another algorithms proposed in the literature, for estimating of the minimum phase channel parameters. In order to identify blindly the impulse response of these channels, we have used Higher Order Statistics (HOS) to build our algorithm. The simulation results in noisy environment, demonstrate that the proposed method could estimate the phase and magnitude with high accuracy of these channels blindly and without any information about the input, except that the input excitation is identically and independent distribute (i.i.d) and non-Gaussian.

Keywords: System Identification, Higher Order Statistics, Communication Channels.

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Authors: Yu. I. Pigolkin, M. A. Garcia Corro

Abstract:

Age determination of unknown dead bodies in forensic personal identification is a complicated process which involves the application of numerous methods and techniques. Skeletal remains are less exposed to influences of environmental factors. In order to enhance the accuracy of forensic age estimation additional properties of bones correlating with age are required to be revealed. Material and Methods: Dimensional examination of the sella turcica was carried out on cadavers with the cranium opened by a circular vibrating saw. The sample consisted of a total of 90 Russian subjects, ranging in age from two months and 87 years. Results: The tendency of dimensional variations throughout life was detected. There were no observed gender differences in the morphometry of the sella turcica. The shared use of the sella turcica depth and length values revealed the possibility to categorize an examined sample in a certain age period. Conclusions: Based on the results of existing methods of age determination, the morphometry of the sella turcica can be an additional characteristic, amplifying the received values, and accordingly, increasing the accuracy of forensic biological age diagnosis.

Keywords: Age–related changes in bone structures, forensic personal identification, Sella turcica morphometry, body identification.

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Authors: Morteza Talebi, Jianan Wang, Zhihua Qu

Abstract:

The security of power systems against malicious cyberphysical data attacks becomes an important issue. The adversary always attempts to manipulate the information structure of the power system and inject malicious data to deviate state variables while evading the existing detection techniques based on residual test. The solutions proposed in the literature are capable of immunizing the power system against false data injection but they might be too costly and physically not practical in the expansive distribution network. To this end, we define an algebraic condition for trustworthy power system to evade malicious data injection. The proposed protection scheme secures the power system by deterministically reconfiguring the information structure and corresponding residual test. More importantly, it does not require any physical effort in either microgrid or network level. The identification scheme of finding meters being attacked is proposed as well. Eventually, a well-known IEEE 30-bus system is adopted to demonstrate the effectiveness of the proposed schemes.

Keywords: Algebraic Criterion, Malicious Cyber-Physical Data Injection, Protection and Identification, Trustworthy Power System.

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Authors: J. G. Batista, K. N. Sousa, J. L. Nunes, R. L. S. Sousa, G. A. P. Thé

Abstract:

This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measured and/or expected values.

Keywords: Modeling, AC servomotor, Permanent Magnet Synchronous Motor-PMSM, Genetic Algorithm, Vector Control, Robotic Manipulator, Control.

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Authors: Isari Pairoa, Proud Arunrangsiwed

Abstract:

Celebrity and brand mascot endorsement have been explored for more than three decades. Both endorsers can effectively transfer their reputation to corporate image and can influence the customers to purchase the product. However, there was little known about the mediators between the level of endorsement and its effect on buying behavior. The objective of the current study is to identify the gab of the previous studies and to seek possible mediators. It was found that consumer’s memory and identification are the mediators, of source credibility and endorsement effect. A future study should confirm the model of endorsement, which was established in the current study.

Keywords: Product endorsement, memory, identification theory, source credibility, unintentional effect.

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Authors: Dejan Stantic, Jun Jo

Abstract:

There have been significant improvements in automatic voice recognition technology. However, existing systems still face difficulties, particularly when used by non-native speakers with accents. In this paper we address a problem of identifying the English accented speech of speakers from different backgrounds. Once an accent is identified the speech recognition software can utilise training set from appropriate accent and therefore improve the efficiency and accuracy of the speech recognition system. We introduced the Q factor, which is defined by the sum of relationships between frequencies of the formants. Four different accents were considered and experimented for this research. A scoring method was introduced in order to effectively analyse accents. The proposed concept indicates that the accent could be identified by analysing their formants.

Keywords: Accent Identification, Formants, Q Factor.

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Authors: Ventura Assuncao

Abstract:

In automotive systems almost all steps concerning the calibration of several control systems, e.g., low idle governor or boost pressure governor, are made with the vehicle because the timeto- production and cost requirements on the projects do not allow for the vehicle analysis necessary to build reliable models. Here is presented a procedure using parametric and NN (neural network) models that enables the generation of vehicle system models based on normal ECU engine control unit) vehicle measurements. These models are locally valid and permit pre and follow-up calibrations so that, only the final calibrations have to be done with the vehicle.

Keywords: Automotive systems, neuro-hybrid models, demodulator, nonlinear systems, identification, and neural networks.

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Authors: Farhad Asadi, S. Hossein Sadati

Abstract:

Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, adaptive Kalman filter with Bayesian approach for identification of variances in measurement parameter noise is developed. Next, it is applied for estimation of the dynamical state and measurement data in discrete linear dynamical system. This algorithm at each step time estimates noise variance in measurement noise and state of system with Kalman filter. Next, approximation is designed at each step separately and consequently sufficient statistics of the state and noise variances are computed with a fixed-point iteration of an adaptive Kalman filter. Different simulations are applied for showing the influence of noise variance in measurement data on algorithm. Firstly, the effect of noise variance and its distribution on detection and identification performance is simulated in Kalman filter without Bayesian formulation. Then, simulation is applied to adaptive Kalman filter with the ability of noise variance tracking in measurement data. In these simulations, the influence of noise distribution of measurement data in each step is estimated, and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained. 

Keywords: adaptive filtering, Bayesian approach Kalman filtering approach, variance tracking

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Authors: Sheng-Hong Pong, Herng-Yu Huang, Yi-Ju Lee, Shih-Hsuan Chiu

Abstract:

In this paper, a neural network technique is applied to real-time classifying media while a projectile is penetrating through them. A laboratory-scaled penetrating setup was built for the experiment. Features used as the network inputs were extracted from the acceleration of penetrator. 6000 set of features from a single penetration with known media and status were used to train the neural network. The trained system was tested on 30 different penetration experiments. The system produced an accuracy of 100% on the training data set. And, their precision could be 99% for the test data from 30 tests.

Keywords: back-propagation, identification, neural network, penetration.

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Authors: Girija Chetty, Monica Singh

Abstract:

In this paper we propose a novel approach for ascertaining human identity based on fusion of profile face and gait biometric cues The identification approach based on feature learning in PCA-LDA subspace, and classification using multivariate Bayesian classifiers allows significant improvement in recognition accuracy for low resolution surveillance video scenarios. The experimental evaluation of the proposed identification scheme on a publicly available database [2] showed that the fusion of face and gait cues in joint PCA-LDA space turns out to be a powerful method for capturing the inherent multimodality in walking gait patterns, and at the same time discriminating the person identity..

Keywords: Biometrics, gait recognition, PCA, LDA, Eigenface, Fisherface, Multivariate Gaussian Classifier

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Authors: Mira Trebar

Abstract:

Logistics processes of perishable food in the supply chain include the distribution activities and the real time temperature monitoring to fulfil the cold chain requirements. The paper presents the use of RFID (Radio Frequency Identification) technology as an identification tool of receiving and shipping activities in the cold store. At the same time, the use of RFID data loggers with temperature sensors is presented to observe and store the temperatures for the purpose of analyzing the processes and having the history data available for traceability purposes and efficient recall management.

Keywords: Logistics, warehouse, RFID device, cold chain.

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