Search results for: Anaerobic microorganism identification

Authors: M.K. Bhuyan, Aragala Jagan.

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Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.

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Authors: Agus Harjoko, Sri Hartati, Henry Dwiyasa

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There have been numerous implementations of security system using biometric, especially for identification and verification cases. An example of pattern used in biometric is the iris pattern in human eye. The iris pattern is considered unique for each person. The use of iris pattern poses problems in encoding the human iris. In this research, an efficient iris recognition method is proposed. In the proposed method the iris segmentation is based on the observation that the pupil has lower intensity than the iris, and the iris has lower intensity than the sclera. By detecting the boundary between the pupil and the iris and the boundary between the iris and the sclera, the iris area can be separated from pupil and sclera. A step is taken to reduce the effect of eyelashes and specular reflection of pupil. Then the four levels Coiflet wavelet transform is applied to the extracted iris image. The modified Hamming distance is employed to measure the similarity between two irises. This research yields the identification success rate of 84.25% for the CASIA version 1.0 database. The method gives an accuracy of 77.78% for the left eyes of MMU 1 database and 86.67% for the right eyes. The time required for the encoding process, from the segmentation until the iris code is generated, is 0.7096 seconds. These results show that the accuracy and speed of the method is better than many other methods.

Keywords: Biometric, iris recognition, wavelet transform.

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Authors: Sandipan Chakroborty, Goutam Saha

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A state of the art Speaker Identification (SI) system requires a robust feature extraction unit followed by a speaker modeling scheme for generalized representation of these features. Over the years, Mel-Frequency Cepstral Coefficients (MFCC) modeled on the human auditory system has been used as a standard acoustic feature set for speech related applications. On a recent contribution by authors, it has been shown that the Inverted Mel- Frequency Cepstral Coefficients (IMFCC) is useful feature set for SI, which contains complementary information present in high frequency region. This paper introduces the Gaussian shaped filter (GF) while calculating MFCC and IMFCC in place of typical triangular shaped bins. The objective is to introduce a higher amount of correlation between subband outputs. The performances of both MFCC & IMFCC improve with GF over conventional triangular filter (TF) based implementation, individually as well as in combination. With GMM as speaker modeling paradigm, the performances of proposed GF based MFCC and IMFCC in individual and fused mode have been verified in two standard databases YOHO, (Microphone Speech) and POLYCOST (Telephone Speech) each of which has more than 130 speakers.

Keywords: Gaussian Filter, Triangular Filter, Subbands, Correlation, MFCC, IMFCC, GMM.

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Authors: A. I. Alajtal, H. G. M. Edwards, M. A. Elbagermi

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Raman spectroscopy is currently a part of the instrumentation suite of the ESA ExoMars mission for the remote detection of life signatures in the Martian surface and subsurface. Terrestrial analogues of Martian sites have been identified and the biogeological modifications incurred as a result of extremophilic activity have been studied. Analytical instrumentation protocols for the unequivocal detection of biomarkers in suitable geological matrices are critical for future unmanned explorations, including the forthcoming ESA ExoMars mission to search for life on Mars scheduled for 2018 and Raman spectroscopy is currently a part of the Pasteur instrumentation suite of this mission. Here, Raman spectroscopy using 785nm excitation was evaluated for determining various concentrations of beta-carotene in admixture with polyaromatic hydrocarbons and usnic acid have been investigated by Raman microspectrometry to determine the lowest levels detectable in simulation of their potential identification remotely in geobiological conditions in Martian scenarios. Information from this study will be important for the development of a miniaturized Raman instrument for targetting Martian sites where the biosignatures of relict or extant life could remain in the geological record.

Keywords: Raman spectroscopy, Mars-analog, Beta-carotene, PAHs.

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Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: Asymptotic stability, incubation period, Routh-Hurwitz criterion, Runge Kutta method.

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Authors: T. Thompson, E. F. Zegeye

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Bacterial Cellulose (BC) is a structural organic compound produced in the anaerobic process. This material can be a useful eco-friendly substitute for commercial textiles that are used in industries today. BC is easily and sustainably produced and has the capabilities to be used as a replacement in textiles. However, BC is extremely fragile when it completely dries. This research was conducted to improve the mechanical properties of the BC by reinforcing with an organic polymer and exfoliated graphite (EG). The BC films were grown over a period of weeks in a green tea and kombucha solution at 30 °C, then cleaned and added to an enhancing solution. The enhancing solutions were a mixture of 2.5 wt% polymer and 2.5 wt% latex solution, a 5 wt% polymer solution, a 0.20 wt% graphite solution and were each allowed to sit in a furnace for 48 h at 50 °C. Tensile test samples were prepared and tested until fracture at a strain rate of 8 mm/min. From the research with the addition of a 5 wt% polymer solution, the flexibility of the BC has significantly improved with the maximum strain significantly larger than that of the base sample. The addition of EG has also increased the modulus of elasticity of the BC by about 25%.

Keywords: Bacterial cellulose, exfoliated graphite, kombucha scoby, tensile test.

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Authors: Isam A. Mohamed Ahmed, Jiro Arima, Tsuyoshi Ichiyanagi, Emi Sakuno, Nobuhiro Mori

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The aim of this study was to screen for microorganism that able to utilize 3-N-trimethylamino-1-propanol (homocholine) as a sole source of carbon and nitrogen. The aerobic degradation of homocholine has been found by a gram-positive Rhodococcus sp. bacterium isolated from soil. The isolate was identified as Rhodococcus sp. strain A4 based on the phenotypic features, physiologic and biochemical characteristics, and phylogenetic analysis. The cells of the isolated strain grown on both basal-TMAP and nutrient agar medium displayed elementary branching mycelia fragmented into irregular rod and coccoid elements. Comparative 16S rDNA sequencing studies indicated that the strain A4 falls into the Rhodococcus erythropolis subclade and forms a monophyletic group with the type-strains of R. opacus, and R. wratislaviensis. Metabolites analysis by capillary electrophoresis, fast atom bombardment-mass spectrometry, and gas chromatography- mass spectrometry, showed trimethylamine (TMA) as the major metabolite beside β-alanine betaine and trimethylaminopropionaldehyde. Therefore, the possible degradation pathway of trimethylamino propanol in the isolated strain is through consequence oxidation of alcohol group (-OH) to aldehyde (-CHO) and acid (-COOH), and thereafter the cleavage of β-alanine betaine C-N bonds yielded trimethylamine and alkyl chain.

Keywords: Homocholine, 3-N-trimethylamino-1-propanol, Quaternary ammonium compounds, 16S rDNA gene sequence.

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Authors: J. Bernasovská, R. Lohajová Behulová, E. Petrejčiková, I. Boroňová, I. Bernasovský

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Y chromosome microdeletions are the most common genetic cause of male infertility and screening for these microdeletions in azoospermic or severely oligospermic men is now standard practice. Analysis of the Y chromosome in men with azoospermia or severe oligozoospermia has resulted in the identification of three regions in the euchromatic part of the long arm of the human Y chromosome (Yq11) that are frequently deleted in men with otherwise unexplained spermatogenic failure. PCR analysis of microdeletions in the AZFa, AZFb and AZFc regions of the human Y chromosome is an important screening tool. The aim of this study was to analyse the type of microdeletions in men with fertility disorders in Slovakia. We evaluated 227 patients with azoospermia and with normal karyotype. All patient samples were analyzed cytogenetically. For PCR amplification of sequence-tagged sites (STS) of the AZFa, AZFb and AZFc regions of the Y chromosome was used Devyser AZF set. Fluorescently labeled primers for all markers in one multiplex PCR reaction were used and for automated visualization and identification of the STS markers we used genetic analyzer ABi 3500xl (Life Technologies). We reported 13 cases of deletions in the AZF region 5,73%. Particular types of deletions were recorded in each region AZFa,b,c .The presence of microdeletions in the AZFc region was the most frequent. The study confirmed that percentage of microdeletions in the AZF region is low in Slovak azoospermic patients, but important from a prognostic view.

Keywords: AZF, male infertility, microdeletions, Y chromosome.

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Authors: R.Sangeetha, T.Karunanithi

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A combination of photosynthetic bacteria along with anaerobic acidogenic bacteria is an ideal option for efficient hydrogen production. In the present study, the optimum concentration of substrates for the growth of Rhodobacter sphaeroides was found by response surface methodology. The optimum combination of three individual fatty acids was determined by Box Behnken design. Increase of volatile fatty acid concentration decreased the growth. Combination of sodium acetate and sodium propionate was most significant for the growth of the organism. The results showed that a maximum biomass concentration of 0.916 g/l was obtained when the concentrations of acetate, propionate and butyrate were 0.73g/l,0.99g/l and 0.799g/l, respectively. The growth was studied under an optimum concentration of volatile fatty acids and at a light intensity of 3000 lux, initial pH of 7 and a temperature of 35°C.The maximum biomass concentration of 0.92g/l was obtained which verified the practicability of this optimization.

Keywords: Biohydrogen, Response Surface Methodology, Rhodobacter sphaeroides, Volatile fatty acid

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Authors: A. M. Pashayev, C. Ardil, D. D. Askerov, R. A. Sadiqov, P. S. Abdullayev

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In this paper is shown that the probability-statistic methods application, especially at the early stage of the aviation gas turbine engine (GTE) technical condition diagnosing, when the flight information has property of the fuzzy, limitation and uncertainty is unfounded. Hence is considered the efficiency of application of new technology Soft Computing at these diagnosing stages with the using of the Fuzzy Logic and Neural Networks methods. Training with high accuracy of fuzzy multiple linear and non-linear models (fuzzy regression equations) which received on the statistical fuzzy data basis is made. Thus for GTE technical condition more adequate model making are analysed dynamics of skewness and kurtosis coefficients' changes. Researches of skewness and kurtosis coefficients values- changes show that, distributions of GTE work parameters have fuzzy character. Hence consideration of fuzzy skewness and kurtosis coefficients is expedient. Investigation of the basic characteristics changes- dynamics of GTE work parameters allows to draw conclusion on necessity of the Fuzzy Statistical Analysis at preliminary identification of the engines' technical condition. Researches of correlation coefficients values- changes shows also on their fuzzy character. Therefore for models choice the application of the Fuzzy Correlation Analysis results is offered. For checking of models adequacy is considered the Fuzzy Multiple Correlation Coefficient of Fuzzy Multiple Regression. At the information sufficiency is offered to use recurrent algorithm of aviation GTE technical condition identification (Hard Computing technology is used) on measurements of input and output parameters of the multiple linear and non-linear generalised models at presence of noise measured (the new recursive Least Squares Method (LSM)). The developed GTE condition monitoring system provides stage-bystage estimation of engine technical conditions. As application of the given technique the estimation of the new operating aviation engine temperature condition was made.

Keywords: Gas turbine engines, neural networks, fuzzy logic, fuzzy statistics.

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Authors: Saeed Safari Dolatabad, Rajab Choukan

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Selection of maize (Zea mays) hybrids with wide adaptability across diverse farming environments is important, prior to recommending them to achieve a high rate of hybrid adoption. Grain yield of 14 maize hybrids, tested in a randomized completeblock design with four replicates across 22 environments in Iran, was analyzed using site regression (SREG) stability model. The biplot technique facilitates a visual evaluation of superior genotypes, which is useful for cultivar recommendation and mega-environment identification. The objectives of this study were (i) identification of suitable hybrids with both high mean performance and high stability (ii) to determine mega-environments for maize production in Iran. Biplot analysis identifies two mega-environments in this study. The first mega-environments included KRM, KSH, MGN, DZF A, KRJ, DRB, DZF B, SHZ B, and KHM, where G10 hybrid was the best performing hybrid. The second mega-environment included ESF B, ESF A, and SHZ A, where G4 hybrid was the best hybrid. According to the ideal-hybrid biplot, G10 hybrid was better than all other hybrids, followed by the G1 and G3 hybrids. These hybrids were identified as best hybrids that have high grain yield and high yield stability. GGE biplot analysis provided a framework for identifying the target testing locations that discriminates genotypes that are high yielding and stable.

Keywords: Zea mays L, GGE biplot, Multi-environment trials, Yield stability.

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

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e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of nearly 3000 winnings-announcing UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the winnings-announcing UBE documents. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexisset in the given UBE and the probability that the given UBE will be the one announcing fake winnings. To the best of our knowledge and survey of related literature, this is the first formal attempt for identification of most frequently occurring lexis in winningsannouncing UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.

Keywords: Lexis, Unsolicited Bulk e-mail (UBE), Vector SpaceDocument Model, Winnings, Lottery

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Authors: C. Cole, M. Osmani, A. Wheatley, M. Quddus

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EU and UK Government targets for minimising and recycling household waste has led the responsible authorities to research the alternatives to landfill. In the work reported here the local waste collection authority (Charnwood Borough Council) has adopted the aspirational strategy of becoming a “Zero Waste Borough” to lead the drive for public participation. The work concludes that the separate collection of food waste would be needed to meet the two regulatory standards on recycling and biologically active wastes.

An analysis of a neighbouring Authority (Newcastle-Under-Lyne Borough Council (NBC), a similar sized local authority that has a successful weekly food waste collection service was undertaken. Results indicate that the main challenges for Charnwood Borough Council would be gaining householder co-operation, the extra costs of collection and organising alternative treatment. The analysis also demonstrated that there was potential offset value via anaerobic digestion for CBC to overcome these difficulties and improve its recycling performance.

Keywords: England, Food Waste Collections, Household Waste, Local Authority.

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Authors: Masamitsu Chikaraishi, Mutsuto Kawahara

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This paper focuses on a technique for identifying the geological boundary of the ground strata in front of a tunnel excavation site using the first order adjoint method based on the optimal control theory. The geological boundary is defined as the boundary which is different layers of elastic modulus. At tunnel excavations, it is important to presume the ground situation ahead of the cutting face beforehand. Excavating into weak strata or fault fracture zones may cause extension of the construction work and human suffering. A theory for determining the geological boundary of the ground in a numerical manner is investigated, employing excavating blasts and its vibration waves as the observation references. According to the optimal control theory, the performance function described by the square sum of the residuals between computed and observed velocities is minimized. The boundary layer is determined by minimizing the performance function. The elastic analysis governed by the Navier equation is carried out, assuming the ground as an elastic body with linear viscous damping. To identify the boundary, the gradient of the performance function with respect to the geological boundary can be calculated using the adjoint equation. The weighed gradient method is effectively applied to the minimization algorithm. To solve the governing and adjoint equations, the Galerkin finite element method and the average acceleration method are employed for the spatial and temporal discretizations, respectively. Based on the method presented in this paper, the different boundary of three strata can be identified. For the numerical studies, the Suemune tunnel excavation site is employed. At first, the blasting force is identified in order to perform the accuracy improvement of analysis. We identify the geological boundary after the estimation of blasting force. With this identification procedure, the numerical analysis results which almost correspond with the observation data were provided.

Keywords: Parameter identification, finite element method, average acceleration method, first order adjoint equation method, weighted gradient method, geological boundary, navier equation, optimal control theory.

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

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Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R²).

Keywords: Time series modelling, stochastic processes, ARIMA model, Karkheh River.

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Authors: Antonio Vitale, Nicola Genito, Giovanni Cuciniello, Ferdinando Montemari

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The introduction of tilt-rotor aircraft into the existing civilian air transportation system will provide beneficial effects due to tilt-rotor capability to combine the characteristics of a helicopter and a fixed-wing aircraft into one vehicle. The disposability of reliable tilt-rotor simulation models supports the development of such vehicle. Indeed, simulation models are required to design automatic control systems that increase safety, reduce pilot's workload and stress, and ensure the optimal aircraft configuration with respect to flight envelope limits, especially during the most critical flight phases such as conversion from helicopter to aircraft mode and vice versa. This article presents a process to build a simplified tilt-rotor simulation model, derived from the analysis of flight data. The model aims to reproduce the complex dynamics of tilt-rotor during the in-flight conversion phase. It uses a set of scheduled linear transfer functions to relate the autopilot reference inputs to the most relevant rigid body state variables. The model also computes information about the rotor flapping dynamics, which are useful to evaluate the aircraft control margin in terms of rotor collective and cyclic commands. The rotor flapping model is derived through a mixed theoretical-empirical approach, which includes physical analytical equations (applicable to helicopter configuration) and parametric corrective functions. The latter are introduced to best fit the actual rotor behavior and balance the differences existing between helicopter and tilt-rotor during flight. Time-domain system identification from flight data is exploited to optimize the model structure and to estimate the model parameters. The presented model-building process was applied to simulated flight data of the ERICA Tilt-Rotor, generated by using a high fidelity simulation model implemented in FlightLab environment. The validation of the obtained model was very satisfying, confirming the validity of the proposed approach.

Keywords: Flapping Dynamics, Flight Dynamics, System Identification, Tilt-Rotor Modeling and Simulation.

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Authors: Alexandru Epureanu, Virgil Teodor

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One of the main research directions in CAD/CAM machining area is the reducing of machining time. The feedrate scheduling is one of the advanced techniques that allows keeping constant the uncut chip area and as sequel to keep constant the main cutting force. They are two main ways for feedrate optimization. The first consists in the cutting force monitoring, which presumes to use complex equipment for the force measurement and after this, to set the feedrate regarding the cutting force variation. The second way is to optimize the feedrate by keeping constant the material removal rate regarding the cutting conditions. In this paper there is proposed a new approach using an extended database that replaces the system model. The feedrate scheduling is determined based on the identification of the reconfigurable machine tool, and the feed value determination regarding the uncut chip section area, the contact length between tool and blank and also regarding the geometrical roughness. The first stage consists in the blank and tool monitoring for the determination of actual profiles. The next stage is the determination of programmed tool path that allows obtaining the piece target profile. The graphic representation environment models the tool and blank regions and, after this, the tool model is positioned regarding the blank model according to the programmed tool path. For each of these positions the geometrical roughness value, the uncut chip area and the contact length between tool and blank are calculated. Each of these parameters are compared with the admissible values and according to the result the feed value is established. We can consider that this approach has the following advantages: in case of complex cutting processes the prediction of cutting force is possible; there is considered the real cutting profile which has deviations from the theoretical profile; the blank-tool contact length limitation is possible; it is possible to correct the programmed tool path so that the target profile can be obtained. Applying this method, there are obtained data sets which allow the feedrate scheduling so that the uncut chip area is constant and, as a result, the cutting force is constant, which allows to use more efficiently the machine tool and to obtain the reduction of machining time.

Keywords: Reconfigurable machine tool, system identification, uncut chip area, cutting conditions scheduling.

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Authors: Guenther Schuh, Christina Koenig, Nico Schoen, Markus Wellensiek

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Identification and selection of appropriate product and manufacturing technologies are key factors for competitiveness and market success of technology-based companies. Therefore, many companies perform technology intelligence (TI) activities to ensure the identification of evolving technologies at the right time. Technology monitoring is one of the three base activities of TI, besides scanning and scouting. As the technological progress is accelerating, more and more technologies are being developed. Against the background of limited resources it is therefore necessary to focus TI activities. In this paper we propose a concept for defining appropriate search fields for technology monitoring. This limitation of search space leads to more concentrated monitoring activities. The concept will be introduced and demonstrated through an anonymized case study conducted within an industry project at the Fraunhofer Institute for Production Technology IPT. The described concept provides a customized monitoring approach, which is suitable for use in technology-oriented companies. It is shown in this paper that the definition of search fields and search tasks are suitable methods to define topics of interest and thus to align monitoring activities. Current as well as planned product, production and material technologies and existing skills, capabilities and resources form the basis for derivation of relevant search areas. To further improve the concept of technology monitoring the proposed concept should be extended during future research e.g. by the definition of relevant monitoring parameters.

Keywords: Monitoring radar, search field, technology intelligence, technology monitoring.

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Authors: A. Baith Mohamed, Ayman Abdel-Hamid, Kareem Youssri Mohamed

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Current proposals for E-passport or ID-Card is similar to a regular passport with the addition of tiny contactless integrated circuit (computer chip) inserted in the back cover, which will act as a secure storage device of the same data visually displayed on the photo page of the passport. In addition, it will include a digital photograph that will enable biometric comparison, through the use of facial recognition technology at international borders. Moreover, the e-passport will have a new interface, incorporating additional antifraud and security features. However, its problems are reliability, security and privacy. Privacy is a serious issue since there is no encryption between the readers and the E-passport. However, security issues such as authentication, data protection and control techniques cannot be embedded in one process. In this paper, design and prototype implementation of an improved E-passport reader is presented. The passport holder is authenticated online by using GSM network. The GSM network is the main interface between identification center and the e-passport reader. The communication data is protected between server and e-passport reader by using AES to encrypt data for protection will transferring through GSM network. Performance measurements indicate a 19% improvement in encryption cycles versus previously reported results.

Keywords: RFID "Radio Frequency Identification", EPC"Electronic Product Code", ICAO "International Civil Aviation Organization", IFF "Identify Friend or Foe"

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Authors: Hariton N. Costin, Iulian Ciocoiu, Tudor Barbu, Cristian Rotariu

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In this paper three different approaches for person verification and identification, i.e. by means of fingerprints, face and voice recognition, are studied. Face recognition uses parts-based representation methods and a manifold learning approach. The assessment criterion is recognition accuracy. The techniques under investigation are: a) Local Non-negative Matrix Factorization (LNMF); b) Independent Components Analysis (ICA); c) NMF with sparse constraints (NMFsc); d) Locality Preserving Projections (Laplacianfaces). Fingerprint detection was approached by classical minutiae (small graphical patterns) matching through image segmentation by using a structural approach and a neural network as decision block. As to voice / speaker recognition, melodic cepstral and delta delta mel cepstral analysis were used as main methods, in order to construct a supervised speaker-dependent voice recognition system. The final decision (e.g. “accept-reject" for a verification task) is taken by using a majority voting technique applied to the three biometrics. The preliminary results, obtained for medium databases of fingerprints, faces and voice recordings, indicate the feasibility of our study and an overall recognition precision (about 92%) permitting the utilization of our system for a future complex biometric card.

Keywords: Biometry, image processing, pattern recognition, speech analysis.

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Authors: Dima Stopel, Zvi Boger, Robert Moskovitch, Yuval Shahar, Yuval Elovici

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Computer worm detection is commonly performed by antivirus software tools that rely on prior explicit knowledge of the worm-s code (detection based on code signatures). We present an approach for detection of the presence of computer worms based on Artificial Neural Networks (ANN) using the computer's behavioral measures. Identification of significant features, which describe the activity of a worm within a host, is commonly acquired from security experts. We suggest acquiring these features by applying feature selection methods. We compare three different feature selection techniques for the dimensionality reduction and identification of the most prominent features to capture efficiently the computer behavior in the context of worm activity. Additionally, we explore three different temporal representation techniques for the most prominent features. In order to evaluate the different techniques, several computers were infected with five different worms and 323 different features of the infected computers were measured. We evaluated each technique by preprocessing the dataset according to each one and training the ANN model with the preprocessed data. We then evaluated the ability of the model to detect the presence of a new computer worm, in particular, during heavy user activity on the infected computers.

Keywords: Artificial Neural Networks, Feature Selection, Temporal Analysis, Worm Detection.

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Authors: Shin-Jer Yang, Kai-Tai Yang

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In response to a changing world and the fast growth of the Internet, more and more enterprises are replacing web-based services with cloud-based ones. Multi-tenancy technology is becoming more important especially with Software as a Service (SaaS). This in turn leads to a greater focus on the application of Identity and Access Management (IAM). Conventional Near-Field Communication (NFC) based verification relies on a computer browser and a card reader to access an NFC tag. This type of verification does not support mobile device login and user-based access management functions. This study designs an NFC-based third-party cloud identity and access management scheme (NFC-IAM) addressing this shortcoming. Data from simulation tests analyzed with Key Performance Indicators (KPIs) suggest that the NFC-IAM not only takes less time in identity identification but also cuts time by 80% in terms of two-factor authentication and improves verification accuracy to 99.9% or better. In functional performance analyses, NFC-IAM performed better in salability and portability. The NFC-IAM App (Application Software) and back-end system to be developed and deployed in mobile device are to support IAM features and also offers users a more user-friendly experience and stronger security protection. In the future, our NFC-IAM can be employed to different environments including identification for mobile payment systems, permission management for remote equipment monitoring, among other applications.

Keywords: Cloud service, multi-tenancy, NFC, IAM, mobile device.

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Authors: M. Hamad Hassan, S.A.M. Gilani

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In this paper, a novel scheme is proposed for Ownership Identification and Color Image Authentication by deploying Cryptography & Digital Watermarking. The color image is first transformed from RGB to YST color space exclusively designed for watermarking. Followed by color space transformation, each channel is divided into 4×4 non-overlapping blocks with selection of central 2×2 sub-blocks. Depending upon the channel selected two to three LSBs of each central 2×2 sub-block are set to zero to hold the ownership, authentication and recovery information. The size & position of sub-block is important for correct localization, enhanced security & fast computation. As YS ÔèÑ T so it is suitable to embed the recovery information apart from the ownership and authentication information, therefore 4×4 block of T channel along with ownership information is then deployed by SHA160 to compute the content based hash that is unique and invulnerable to birthday attack or hash collision instead of using MD5 that may raise the condition i.e. H(m)=H(m'). For recovery, intensity mean of 4x4 block of each channel is computed and encoded upto eight bits. For watermark embedding, key based mapping of blocks is performed using 2DTorus Automorphism. Our scheme is oblivious, generates highly imperceptible images with correct localization of tampering within reasonable time and has the ability to recover the original work with probability of near one.

Keywords: Hash Collision, LSB, MD5, PSNR, SHA160

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Authors: Jatinderkumar R. Saini, Apurva A. Desai

Abstract:

e-mail has become an important means of electronic communication but the viability of its usage is marred by Unsolicited Bulk e-mail (UBE) messages. UBE consists of many types like pornographic, virus infected and 'cry-for-help' messages as well as fake and fraudulent offers for jobs, winnings and medicines. UBE poses technical and socio-economic challenges to usage of e-mails. To meet this challenge and combat this menace, we need to understand UBE. Towards this end, the current paper presents a content-based textual analysis of more than 2700 body enhancement medicinal UBE. Technically, this is an application of Text Parsing and Tokenization for an un-structured textual document and we approach it using Bag Of Words (BOW) and Vector Space Document Model techniques. We have attempted to identify the most frequently occurring lexis in the UBE documents that advertise various products for body enhancement. The analysis of such top 100 lexis is also presented. We exhibit the relationship between occurrence of a word from the identified lexis-set in the given UBE and the probability that the given UBE will be the one advertising for fake medicinal product. To the best of our knowledge and survey of related literature, this is the first formal attempt for identification of most frequently occurring lexis in such UBE by its textual analysis. Finally, this is a sincere attempt to bring about alertness against and mitigate the threat of such luring but fake UBE.

Keywords: Body Enhancement, Lexis, Medicinal, Unsolicited Bulk e-mail (UBE), Vector Space Document Model, Viagra

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Authors: Jaruwan Chutrtong

Abstract:

Yoghurt is a fermented milk product. The process of making yogurt involves fermenting milk with live and active bacterial cultures by adding bacteria directly to the dairy product. It is usually made with a culture of Lactobacillus sp. (L. acidophilus or L. bulgaricus) and Streptococcus thermophilus. Many people like to eat it plain or flavored and it's also use as ingredient in many dishes. Yogurt is rich in nutrients including the microorganism which have important role in balancing the digestion and absorption of the boy.Consumers will benefit from lactic acid bacteria more or less depending on the amount of bacteria that lives in yogurt while eating. When purchasing yogurt, consumers should always check the label for live cultures. Yoghurt must keep in refrigerator at 4°C for up to ten days. After this amount of time, the cultures often become weak. This research studied freezing dry yogurt storage by monitoring on the survival of microorganisms when stored at different temperatures. At 30⁰C, representative room temperature of country in equator zone, number of lactic acid bacteria reduced 4 log cycles in 10 week. At 40⁰C, representative temperature in summer of country in equator zone, number of lactic acid bacteria also dropped 4 log cycle in 10 week, similar as storage at 30⁰C. But drying yogurt storage at 40⁰C couldn’t reformed to be good character yogurt as good as storage at 40⁰C only 4 week storage too. After 1 month, it couldn’t bring back the yogurt form. So if it is inevitable to keep yogurt powder at a temperature of 40°C, yoghurt is maintained only up to 4 weeks.

Keywords: Dynamic, dry yoghurt, storage, temperature.

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Authors: J. Prakash, K. Rajesh

Abstract:

In this paper we present a new method for coin identification. The proposed method adopts a hybrid scheme using Eigenvalues of covariance matrix, Circular Hough Transform (CHT) and Bresenham-s circle algorithm. The statistical and geometrical properties of the small and large Eigenvalues of the covariance matrix of a set of edge pixels over a connected region of support are explored for the purpose of circular object detection. Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain only a small number of non-zero elements, they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of the circumference pixels is identified using Raster scan algorithm which uses geometrical symmetry property. After finding circular objects, the proposed method uses the texture on the surface of the coins called texton, which are unique properties of coins, refers to the fundamental micro structure in generic natural images. This method has been tested on several real world images including coin and non-coin images. The performance is also evaluated based on the noise withstanding capability.

Keywords: Circular Hough Transform, Coin detection, Covariance matrix, Eigenvalues, Raster scan Algorithm, Texton.

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Authors: P. S. Hiremath, Siddu P. Algur

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With the explosive growth of information sources available on the World Wide Web, it has become increasingly difficult to identify the relevant pieces of information, since web pages are often cluttered with irrelevant content like advertisements, navigation-panels, copyright notices etc., surrounding the main content of the web page. Hence, tools for the mining of data regions, data records and data items need to be developed in order to provide value-added services. Currently available automatic techniques to mine data regions from web pages are still unsatisfactory because of their poor performance and tag-dependence. In this paper a novel method to extract data items from the web pages automatically is proposed. It comprises of two steps: (1) Identification and Extraction of the data regions based on visual clues information. (2) Identification of data records and extraction of data items from a data region. For step1, a novel and more effective method is proposed based on visual clues, which finds the data regions formed by all types of tags using visual clues. For step2 a more effective method namely, Extraction of Data Items from web Pages (EDIP), is adopted to mine data items. The EDIP technique is a list-based approach in which the list is a linear data structure. The proposed technique is able to mine the non-contiguous data records and can correctly identify data regions, irrespective of the type of tag in which it is bound. Our experimental results show that the proposed technique performs better than the existing techniques.

Keywords: Web data records, web data regions, web mining.

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Authors: K. Tunde Olagunju, C. Scott Allen, F.D. (Freek) van der Meer

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Identification of hydrocarbon oil in remote sensing images is often the first step in monitoring oil during spill events. Most remote sensing methods adopt techniques for hydrocarbon identification to achieve detection in order to model an appropriate cleanup program. Identification on optical sensors does not only allow for detection but also for characterization and quantification. Until recently, in optical remote sensing, quantification and characterization were only potentially possible using high-resolution laboratory and airborne imaging spectrometers (hyperspectral data). Unlike multispectral, hyperspectral data are not freely available, as this data category is mainly obtained via airborne survey at present. In this research, two operational high-resolution multispectral satellites (WorldView-3 and Sentinel-2) are theoretically assessed for their suitability for hydrocarbon characterization, using the Hydrocarbon Spectra Slope model (HYSS). This method utilized the two most persistent hydrocarbon diagnostic/absorption features at 1.73 µm and 2.30 µm for hydrocarbon mapping on multispectral data. In this research, spectra measurement of seven different hydrocarbon oils (crude and refined oil) taken on 10 different substrates with the use of laboratory ASD Fieldspec were convolved to Sentinel-2 and WorldView-3 resolution, using their full width half maximum (FWHM) parameter. The resulting hydrocarbon slope values obtained from the studied samples enable clear qualitative discrimination of most hydrocarbons, despite the presence of different background substrates, particularly on WorldView-3. Due to close conformity of central wavelengths and narrow bandwidths to key hydrocarbon bands used in HYSS, the statistical significance for qualitative analysis on WorldView-3 sensors for all studied hydrocarbon oil returned with 95% confidence level (P-value ˂ 0.01), except for Diesel. Using multifactor analysis of variance (MANOVA), the discriminating power of HYSS is statistically significant for most hydrocarbon-substrate combinations on Sentinel-2 and WorldView-3 FWHM, revealing the potential of these two operational multispectral sensors as rapid response tools for hydrocarbon mapping. One notable exception is highly transmissive hydrocarbons on Sentinel-2 data due to the non-conformity of spectral bands with key hydrocarbon absorptions and the relatively coarse bandwidth (> 100 nm).

Keywords: hydrocarbon, oil spill, remote sensing, hyperspectral, multispectral, hydrocarbon – substrate combination, Sentinel-2, WorldView-3

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Authors: Gaetano Zazzaro, Angelo Martone, Roberto V. Montaquila, Luigi Pavone

Abstract:

Seizure is the main factor that affects the quality of life of epileptic patients. The diagnosis of epilepsy, and hence the identification of epileptogenic zone, is commonly made by using continuous Electroencephalogram (EEG) signal monitoring. Seizure identification on EEG signals is made manually by epileptologists and this process is usually very long and error prone. The aim of this paper is to describe an automated method able to detect seizures in EEG signals, using knowledge discovery in database process and data mining methods and algorithms, which can support physicians during the seizure detection process. Our detection method is based on Artificial Neural Network classifier, trained by applying the multilayer perceptron algorithm, and by using a software application, called Training Builder that has been developed for the massive extraction of features from EEG signals. This tool is able to cover all the data preparation steps ranging from signal processing to data analysis techniques, including the sliding window paradigm, the dimensionality reduction algorithms, information theory, and feature selection measures. The final model shows excellent performances, reaching an accuracy of over 99% during tests on data of a single patient retrieved from a publicly available EEG dataset.

Keywords: Artificial Neural Network, Data Mining, Electroencephalogram, Epilepsy, Feature Extraction, Seizure Detection, Signal Processing.

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Authors: Ali Alotaibi, Francis Edum-Fotwe, Andrew Price /

Abstract:

Mega construction projects create buildings and major infrastructure to respond to work and life requirements while playing a vital role in promoting any nation’s economy. However, the industry is often criticised for not balancing economic, environmental and social dimensions of their projects, with emphasis typically on one aspect to the detriment of the others. This has resulted in many negative impacts including environmental pollution, waste throughout the project lifecycle, low productivity, and avoidable accidents. The identification of comprehensive Social Responsibility (SR) indicators, which combine social, environmental and economic aspects, is urgently needed. This is particularly the case in the context of the Kingdom of Saudi Arabia (KSA), which often has mega public construction projects. The aim of this paper is to develop a set of wide-ranging SR indicators which encompass social, economic and environmental aspects unique to the KSA. A qualitative approach was applied to explore relevant indicators through a review of the existing literature, international standards and reports. A list of appropriate indicators was developed, and its comprehensiveness was corroborated by interviews with experts on mega construction projects working with SR concepts in the KSA. The findings present 39 indicators and their metrics, covering 10 economic, 12 environmental and 17 social aspects of SR mapped against their references. These indicators are a valuable reference for decision-makers and academics in the KSA to understand factors related to SR in mega construction projects. The indicators are related to mega construction projects within the KSA and require validation in a real case scenario or within a different industry to demonstrate their generalisability.

Keywords: Social responsibility, construction projects, economic, social, environmental, indicators.

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