Search results for: species identification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1437

Search results for: species identification

1167 Unsupervised Classification of DNA Barcodes Species Using Multi-Library Wavelet Networks

Authors: Abdesselem Dakhli, Wajdi Bellil, Chokri Ben Amar

Abstract:

DNA Barcode provides good sources of needed information to classify living species. The classification problem has to be supported with reliable methods and algorithms. To analyze species regions or entire genomes, it becomes necessary to use the similarity sequence methods. A large set of sequences can be simultaneously compared using Multiple Sequence Alignment which is known to be NP-complete. However, all the used methods are still computationally very expensive and require significant computational infrastructure. Our goal is to build predictive models that are highly accurate and interpretable. In fact, our method permits to avoid the complex problem of form and structure in different classes of organisms. The empirical data and their classification performances are compared with other methods. Evenly, in this study, we present our system which is consisted of three phases. The first one, is called transformation, is composed of three sub steps; Electron-Ion Interaction Pseudopotential (EIIP) for the codification of DNA Barcodes, Fourier Transform and Power Spectrum Signal Processing. Moreover, the second phase step is an approximation; it is empowered by the use of Multi Library Wavelet Neural Networks (MLWNN). Finally, the third one, is called the classification of DNA Barcodes, is realized by applying the algorithm of hierarchical classification.

Keywords: DNA Barcode, Electron-Ion Interaction Pseudopotential, Multi Library Wavelet Neural Networks.

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1166 Optimization Model for Identification of Assembly Alternatives of Large-Scale, Make-to-Order Products

Authors: Henrik Prinzhorn, Peter Nyhuis, Johannes Wagner, Peter Burggräf, Torben Schmitz, Christina Reuter

Abstract:

Assembling large-scale products, such as airplanes, locomotives, or wind turbines, involves frequent process interruptions induced by e.g. delayed material deliveries or missing availability of resources. This leads to a negative impact on the logistical performance of a producer of xxl-products. In industrial practice, in case of interruptions, the identification, evaluation and eventually the selection of an alternative order of assembly activities (‘assembly alternative’) leads to an enormous challenge, especially if an optimized logistical decision should be reached. Therefore, in this paper, an innovative, optimization model for the identification of assembly alternatives that addresses the given problem is presented. It describes make-to-order, large-scale product assembly processes as a resource constrained project scheduling (RCPS) problem which follows given restrictions in practice. For the evaluation of the assembly alternative, a cost-based definition of the logistical objectives (delivery reliability, inventory, make-span and workload) is presented.

Keywords: Assembly scheduling, large-scale products, make-to-order, rescheduling, optimization.

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1165 Software Tools for System Identification and Control using Neural Networks in Process Engineering

Authors: J. Fernandez de Canete, S. Gonzalez-Perez, P. del Saz-Orozco

Abstract:

Neural networks offer an alternative approach both for identification and control of nonlinear processes in process engineering. The lack of software tools for the design of controllers based on neural network models is particularly pronounced in this field. SIMULINK is properly a widely used graphical code development environment which allows system-level developers to perform rapid prototyping and testing. Such graphical based programming environment involves block-based code development and offers a more intuitive approach to modeling and control task in a great variety of engineering disciplines. In this paper a SIMULINK based Neural Tool has been developed for analysis and design of multivariable neural based control systems. This tool has been applied to the control of a high purity distillation column including non linear hydrodynamic effects. The proposed control scheme offers an optimal response for both theoretical and practical challenges posed in process control task, in particular when both, the quality improvement of distillation products and the operation efficiency in economical terms are considered.

Keywords: Distillation, neural networks, software tools, identification, control.

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1164 Identification of States and Events for the Static and Dynamic Simulation of Single Electron Tunneling Circuits

Authors: Sharief F. Babiker, Abdelkareem Bedri, Rania Naeem

Abstract:

The implementation of single-electron tunneling (SET) simulators based on the master-equation (ME) formalism requires the efficient and accurate identification of an exhaustive list of active states and related tunnel events. Dynamic simulations also require the control of the emerging states and guarantee the safe elimination of decaying states. This paper describes algorithms for use in the stationary and dynamic control of the lists of active states and events. The paper presents results obtained using these algorithms with different SET structures.

Keywords: Active state, Coulomb blockade, Master Equation, Single electron devices

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1163 Optimization Approach to Estimate Hammerstein–Wiener Nonlinear Blocks in Presence of Noise and Disturbance

Authors: Leili Esmaeilani, Jafar Ghaisari, Mohsen Ahmadian

Abstract:

Hammerstein–Wiener model is a block-oriented model where a linear dynamic system is surrounded by two static nonlinearities at its input and output and could be used to model various processes. This paper contains an optimization approach method for analysing the problem of Hammerstein–Wiener systems identification. The method relies on reformulate the identification problem; solve it as constraint quadratic problem and analysing its solutions. During the formulation of the problem, effects of adding noise to both input and output signals of nonlinear blocks and disturbance to linear block, in the emerged equations are discussed. Additionally, the possible parametric form of matrix operations to reduce the equation size is presented. To analyse the possible solutions to the mentioned system of equations, a method to reduce the difference between the number of equations and number of unknown variables by formulate and importing existing knowledge about nonlinear functions is presented. Obtained equations are applied to an instance H–W system to validate the results and illustrate the proposed method.

Keywords: Identification, Hammerstein-Wiener, optimization, quantization.

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1162 Impulsive Noise-Resilient Subband Adaptive Filter

Authors: Young-Seok Choi

Abstract:

We present a new subband adaptive filter (R-SAF) which is robust against impulsive noise in system identification. To address the vulnerability of adaptive filters based on the L2-norm optimization criterion against impulsive noise, the R-SAF comes from the L1-norm optimization criterion with a constraint on the energy of the weight update. Minimizing L1-norm of the a posteriori error in each subband with a constraint on minimum disturbance gives rise to the robustness against the impulsive noise and the capable convergence performance. Experimental results clearly demonstrate that the proposed R-SAF outperforms the classical adaptive filtering algorithms when impulsive noise as well as background noise exist.

Keywords: Subband adaptive filter, L1-norm, system identification, robustness, impulsive interference.

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1161 Identification of Nonlinear Predictor and Simulator Models of a Cement Rotary Kiln by Locally Linear Neuro-Fuzzy Technique

Authors: Masoud Sadeghian, Alireza Fatehi

Abstract:

One of the most important parts of a cement factory is the cement rotary kiln which plays a key role in quality and quantity of produced cement. In this part, the physical exertion and bilateral movement of air and materials, together with chemical reactions take place. Thus, this system has immensely complex and nonlinear dynamic equations. These equations have not worked out yet. Only in exceptional case; however, a large number of the involved parameter were crossed out and an approximation model was presented instead. This issue caused many problems for designing a cement rotary kiln controller. In this paper, we presented nonlinear predictor and simulator models for a real cement rotary kiln by using nonlinear identification technique on the Locally Linear Neuro- Fuzzy (LLNF) model. For the first time, a simulator model as well as a predictor one with a precise fifteen minute prediction horizon for a cement rotary kiln is presented. These models are trained by LOLIMOT algorithm which is an incremental tree-structure algorithm. At the end, the characteristics of these models are expressed. Furthermore, we presented the pros and cons of these models. The data collected from White Saveh Cement Company is used for modeling.

Keywords: Cement rotary kiln, nonlinear identification, Locally Linear Neuro-Fuzzy model.

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1160 Improved Closed Set Text-Independent Speaker Identification by Combining MFCC with Evidence from Flipped Filter Banks

Authors: Sandipan Chakroborty, Anindya Roy, Goutam Saha

Abstract:

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 SI applications. However, due to the structure of its filter bank, it captures vocal tract characteristics more effectively in the lower frequency regions. This paper proposes a new set of features using a complementary filter bank structure which improves distinguishability of speaker specific cues present in the higher frequency zone. Unlike high level features that are difficult to extract, the proposed feature set involves little computational burden during the extraction process. When combined with MFCC via a parallel implementation of speaker models, the proposed feature set outperforms baseline MFCC significantly. This proposition is validated by experiments conducted on two different kinds of public databases namely YOHO (microphone speech) and POLYCOST (telephone speech) with Gaussian Mixture Models (GMM) as a Classifier for various model orders.

Keywords: Complementary Information, Filter Bank, GMM, IMFCC, MFCC, Speaker Identification, Speaker Recognition.

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1159 Robust Face Recognition Using Eigen Faces and Karhunen-Loeve Algorithm

Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Prateek Gupta

Abstract:

The current research paper is an implementation of Eigen Faces and Karhunen-Loeve Algorithm for face recognition. The designed program works in a manner where a unique identification number is given to each face under trial. These faces are kept in a database from where any particular face can be matched and found out of the available test faces. The Karhunen –Loeve Algorithm has been implemented to find out the appropriate right face (with same features) with respect to given input image as test data image having unique identification number. The procedure involves usage of Eigen faces for the recognition of faces.

Keywords: Eigen Faces, Karhunen-Loeve Algorithm, FaceRecognition.

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1158 Application of a Generalized Additive Model to Reveal the Relations between the Density of Zooplankton with Other Variables in the West Daya Bay, China

Authors: Weiwen Li, Hao Huang, Chengmao You, Jianji Liao, Lei Wang, Lina An

Abstract:

Zooplankton are a central issue in the ecology which makes a great contribution to maintaining the balance of an ecosystem. It is critical in promoting the material cycle and energy flow within the ecosystems. A generalized additive model (GAM) was applied to analyze the relationships between the density (individuals per m³) of zooplankton and other variables in West Daya Bay. All data used in this analysis (the survey month, survey station (longitude and latitude), the depth of the water column, the superficial concentration of chlorophyll a, the benthonic concentration of chlorophyll a, the number of zooplankton species and the number of zooplankton species) were collected through monthly scientific surveys during January to December 2016. GLM model (generalized linear model) was used to choose the significant variables’ impact on the density of zooplankton, and the GAM was employed to analyze the relationship between the density of zooplankton and the significant variables. The results showed that the density of zooplankton increased with an increase of the benthonic concentration of chlorophyll a, but decreased with a decrease in the depth of the water column. Both high numbers of zooplankton species and the overall total number of zooplankton individuals led to a higher density of zooplankton.

Keywords: Density, generalized linear model, generalized additive model, the West Daya Bay, zooplankton.

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1157 An Information Theoretic Approach to Rescoring Peptides Produced by De Novo Peptide Sequencing

Authors: John R. Rose, James P. Cleveland, Alvin Fox

Abstract:

Tandem mass spectrometry (MS/MS) is the engine driving high-throughput protein identification. Protein mixtures possibly representing thousands of proteins from multiple species are treated with proteolytic enzymes, cutting the proteins into smaller peptides that are then analyzed generating MS/MS spectra. The task of determining the identity of the peptide from its spectrum is currently the weak point in the process. Current approaches to de novo sequencing are able to compute candidate peptides efficiently. The problem lies in the limitations of current scoring functions. In this paper we introduce the concept of proteome signature. By examining proteins and compiling proteome signatures (amino acid usage) it is possible to characterize likely combinations of amino acids and better distinguish between candidate peptides. Our results strongly support the hypothesis that a scoring function that considers amino acid usage patterns is better able to distinguish between candidate peptides. This in turn leads to higher accuracy in peptide prediction.

Keywords: Tandem mass spectrometry, proteomics, scoring, peptide, de novo, mutual information

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1156 Radio Frequency Identification Encryption via Modified Two Dimensional Logistic Map

Authors: Hongmin Deng, Qionghua Wang

Abstract:

A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M0 development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: Chaos encryption, logistic map, pseudo-random sequence, RFID.

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1155 Applications of Prediction and Identification Using Adaptive DCMAC Neural Networks

Authors: Yu-Lin Liao, Ya-Fu Peng

Abstract:

An adaptive dynamic cerebellar model articulation controller (DCMAC) neural network used for solving the prediction and identification problem is proposed in this paper. The proposed DCMAC has superior capability to the conventional cerebellar model articulation controller (CMAC) neural network in efficient learning mechanism, guaranteed system stability and dynamic response. The recurrent network is embedded in the DCMAC by adding feedback connections in the association memory space so that the DCMAC captures the dynamic response, where the feedback units act as memory elements. The dynamic gradient descent method is adopted to adjust DCMAC parameters on-line. Moreover, the analytical method based on a Lyapunov function is proposed to determine the learning-rates of DCMAC so that the variable optimal learning-rates are derived to achieve most rapid convergence of identifying error. Finally, the adaptive DCMAC is applied in two computer simulations. Simulation results show that accurate identifying response and superior dynamic performance can be obtained because of the powerful on-line learning capability of the proposed DCMAC.

Keywords: adaptive, cerebellar model articulation controller, CMAC, prediction, identification

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1154 Bioconcentration Analysis of Iodine Species in Seaweed (Eucheuma cottonii) from Maluku Marine as Alternative Food Source

Authors: Yeanchon H. Dulanlebit, Nikmans Hattu, Gloria Bora

Abstract:

Seaweed is a type of macro algae which are good source of iodine and have been widely used as food and nutrition supplement. One of iodine species that found in ocean plant is iodate. Analysis of iodate in seaweed (Eucheuma cottonii) from coastal area of Maluku has been done. The determination is done by using spectrophotometric method. Iodate in sample is reduced in excess of potassium iodide in the presence of acid solution, and then is reacted with starch to form blue complex. The study found out that the highest wavelength on determination of iodate species using spectrophotometer analysis method is 570 nm. Optimum value to yield maximum absorption is used in this research. Contents of iodate in seawater from coastal area of Ambon Island, Western Seram and Southeast Maluku are 0.2655, 0.2719 and 0.1760 mg/L, respectively. While in seaweeds from Ambon Island, Western Seram, Southeast Maluku-Taar, Ohoidertawun and Wab are 6.3122, 6.3293, 6.2333, 3.7406 and 4.4207 mg/kg in dry weight. Bioconcentration (enrichment) factor of iodate in seaweed (Eucheuma cottonii) from the three samples (cluster) is different; in Coastal area of Ambon Island, Western Seram and Southeast Maluku respectively are 23.78, 23.28 and 27.26.

Keywords: Bioconcentration, Eucheuma cottonii, iodate, iodine, seaweed.

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1153 Development of a Vegetation Searching System

Authors: Rattanathip Rattanachai, Kunyanuth Kularbphettong

Abstract:

 

This paper describes the development of a Vegetation Searching System based on Web Application in case of Suan Sunandha Rajabhat University. The model was developed by PHP, JavaScript and MySQL database system and it was designed to support searching for endemic and rare species of trees on Web site. We describe the design methods and functional components of this prototype. To evaluate the system performance, questionnaires for the system usability and Black Box Testing were used to measure expert and user satisfaction. The results were satisfactory as followed: Means for experts and users were 4.30 and 4.50, and standard deviation for experts and users were 0.61and 0.73 respectively. Further analysis showed that the quality of the plant searching Website was also at a good level as well.

Keywords: Endemic species, Vegetation, Web based System, and Black Box Testing.

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1152 Plants as Alternative Covers at Contaminated Sites

Authors: M. Grifoni, G. Petruzzelli, M. Barbafieri, I. Rosellini, B. Pezzarossa, F. Pedron

Abstract:

Evapotranspiration (ET) covers are an alternative cover system that utilizes water balance approach to maximize the ET process to reduce the contaminants leaching through the soil profile. Microcosm tests allow to identify in a short time the most suitable plant species to be used as alternative covers, their survival capacity, and simultaneously the transpiration and evaporation rate of the cover in a specific contaminated soil. This work shows the soil characterization and ET results of microcosm tests carried out on two contaminated soils by using Triticum durum and Helianthus annuus species. The data indicated that transpiration was higher than evaporation, supporting the use of plants as alternative cover at this contaminated site.

Keywords: Contaminated sites, ET cover, evapotranspiration, microcosm experiments.

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1151 Web Service Security Method To SOA Development

Authors: Nafise Fareghzadeh

Abstract:

Web services provide significant new benefits for SOAbased applications, but they also expose significant new security risks. There are huge number of WS security standards and processes. At present, there is still a lack of a comprehensive approach which offers a methodical development in the construction of secure WS-based SOA. Thus, the main objective of this paper is to address this needs, presenting a comprehensive method for Web Services Security guaranty in SOA. The proposed method defines three stages, Initial Security Analysis, Architectural Security Guaranty and WS Security Standards Identification. These facilitate, respectively, the definition and analysis of WS-specific security requirements, the development of a WS-based security architecture and the identification of the related WS security standards that the security architecture must articulate in order to implement the security services.

Keywords: Kernel, Repository, Security Standards, WS Security Policy, WS specification.

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1150 Fuzzy Inference System for Determining Collision Risk of Ship in Madura Strait Using Automatic Identification System

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: Automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA.

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1149 Online Battery Equivalent Circuit Model Estimation on Continuous-Time Domain Using Linear Integral Filter Method

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: Equivalent circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square.

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1148 Decision Support System “Crop-9-DSS“ for Identified Crops

Authors: Ganesan V.

Abstract:

Application of Expert System in the area of agriculture would take the form of Integrated Crop Management decision aids and would encompass water management, fertilizer management, crop protection systems and identification of implements. In order to remain competitive, the modern farmer often relies on agricultural specialists and advisors to provide information for decision-making. An expert system normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes knowledge base), and end user interface (accepting inputs, generating outputs). Software named 'CROP-9-DSS' incorporating all modern features like, graphics, photos, video clippings etc. has been developed. This package will aid as a decision support system for identification of pest and diseases with control measures, fertilizer recommendation system, water management system and identification of farm implements for leading crops of Kerala (India) namely Coconut, Rice, Cashew, Pepper, Banana, four vegetables like Amaranthus, Bhindi, Brinjal and Cucurbits. 'CROP-9-DSS' will act as an expert system to agricultural officers, scientists in the field of agriculture and extension workers for decision-making and help them in suggesting suitable recommendations.

Keywords: Diagnostic, inference engine, knowledge base and user interface.

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1147 Empowering Communications Challenged users using Development Kits

Authors: Winsy P.S. Dissanayake, Chandana P. W. Prasad, Ashutosh K. Singh

Abstract:

The rapid pace of technological advancement and its consequential widening digital divide has resulted in the marginalization of the disabled especially the communication challenged. The dearth of suitable technologies for the development of assistive technologies has served to further marginalize the communications challenged user population and widen this chasm even further. Given the varying levels of disability there and its associated requirement for customized solution based. This paper explains the use of a Software Development Kits (SDK) for the bridging of this communications divide through the use of industry poplar communications SDKs towards identification of requirements for communications challenged users as well as identification of appropriate frameworks for future development initiatives.

Keywords: Assistive Technology, Communication, Disability, Marginalization, Software Development Kit, Waveform and Wideband

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1146 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants

Authors: S. Safi, A. Zeroual

Abstract:

In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.

Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.

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1145 Prevalence and Associated Risk Factors of Eimeria in Sheep of Punjab, Pakistan

Authors: M.N. Khan, T. Rehman, Z Iqbal, M.S Sajid, M Ahmad, M Riaz

Abstract:

A cross-sectional study was carried out to determine the prevalence, species characterization and associated risk factors with Eimeria (E.) in sheep of district Toba Tek Singh from April, 2009 to March, 2010. Of the total 486 faecal samples examined for Eimeria, 209 (43%) were found infected with five species of Eimeria. Amongst the identified species of Eimeria, E. ovinoidalis was the commonest one (48.32%), followed in order by E. ahsata, E. intricata, E. parva and E. faurei with prevalence of 45.45, 28.71, 24.40 and 19.14 percent respectively. Peak prevalence was observed in August. Wet season (rainy and post-rainy) was found to be favourable for Eimeria infection. Lambs had significantly higher prevalence (P < 0.05) of Eimeria than adults. Similarly higher prevalence of Eimeria was observed in female as compared to male. Among management and husbandry practices; watering system, housing system, floor type and herd size strongly influenced the prevalence of Eimeria. Coccidiosis was more prevalent in closed housing system, non-cemented floor type, pond watered animals and larger herds (P < 0.05) as compared to open housing system, partially cemented floor type, tap watered animals and smaller herds respectively. Feeding system, breed and body condition of animals were not found as risk factors (P>0.05) influencing prevalence of Eimeria.

Keywords: Eimeria, Pakistan prevalence, sheep.

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1144 A 25-year Monitoring of the Air Pollution Depicted by Plane Tree Species in Tehran

Authors: S. A. A. Korori, H. Valipour K., S. Shabestani, A. shirvany, M. Matinizadeh

Abstract:

Tehran, one of the heavily-populated capitals, is severely suffering from increasing air pollution. To show a documented trend of such pollutants during last years, plane tree species (Platanus orientalis) were suited to be studied as indicators, for the species have been planted throughout the city many years ago. Two areas (Saadatabad and Narmak districts) allotting different contents of crowed and highly-traffic routs but the same ecological characteristics were selected. Twelve sample individuals were cored twice perpendicularly in each area. Tree-rings of each core were measured by a binocular microscope and separated annually for the last 25 years. Two heavy metals including Cd and Pb accompanied by a mineral element (Ca) were analyzed using Hatch method. Treerings analysis of the two areas showed different groups in term of physiologically ability as the growths were plunged during the last 10 years in Saadatabad district and showed a slight decrease in the same period for another studying area. In direct contrast to decreasing growth trend in Saadatabad, all three mentioned elements increased sharply during last 25 years in the same area. When it came to Narmak district, the trend was completely different with Saadatabad. There were some fluctuations in absorbing trace elements like tree-rings widths were, yet calcium showed an upward trend all the last 25 years. The results of the study proved the possibility of using tree species of each region to monitor its air pollution trends of the past, hence to depict a pollution assessment of a populated city for last years and then to make appropriate decisions for the future as it is well-known what the trend is. On the other hand, risen values of calcium (as the stress-indicator element) accompanied by increased trace elements suggests non-sustainable state of the trees.

Keywords: Air pollution, Platanus orientalis, Tehran, Traceelements, Tree rings.

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1143 Investigation of the Synthesis of Alcohols Byproducts in Fischer-Tropsch Synthesis on Modified Fe-Cu Catalyst: Reactivity and Mechanism

Authors: Wanyu Mao, Qiwen Sun, Weiyong Ying, Dingye Fang

Abstract:

The influence of copper promoters and reaction conditions on the formation of alcohols byproducts of a common Fischer-Tropsch synthesis used iron-based catalysts were investigated. A good compromise of 28%Cu/FeKLaSiO2 can lead to the optimization of an improved Fischer-Tropsch catalyst. The product distribution shifts towards hydrocarbons with increasing the reaction temperature, while pressure promotes the formation of alcohols. It was found that the production of either alcohols or hydrocarbons followed A-S-F distributions, and their α parameters were essentially different which indicated a competition in the growing chain between the two species. TPD after acetaldehyde adsorption gave strong evidence of the insertion of a C1 oxygen-containing species into an alkyl chain.

Keywords: Fischer-Tropsch synthesis, Fe-Cu catalyst, alcohols byproducts, reaction pathways

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1142 DNA Methylation Changes Caused by Lawsone

Authors: Zuzana Poborilova, Anna B. Ohlsson, Torkel Berglund, Anna Vildova, Petr Babula

Abstract:

Lawsone is a pigment that occurs naturally in plants. It has been used as a skin and hair dye for a long time. Moreover, its different biological activities have been reported. The present study focused on the effect of lawsone on a plant cell model represented by tobacco BY-2 cell suspension culture, which is used as a model comparable with the HeLa cells. It has been shown that lawsone inhibits the cell growth in the concentration-dependent manner. In addition, changes in DNA methylation level have been determined. We observed decreasing level of DNA methylation in the presence of increasing concentrations of lawsone. These results were accompanied with overproduction of reactive oxygen species (ROS). Since epigenetic modifications can be caused by different stress factors, there could be a connection between the changes in the level of DNA methylation and ROS production caused by lawsone.

Keywords: DNA methylation, Lawsone, Naphthoquinone, Reactive Oxygen Species.

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1141 Providing a Secure, Reliable and Decentralized Document Management Solution Using Blockchain by a Virtual Identity Card

Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

Abstract:

In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: Blockchain, decentralized system, fingerprint impression, identity management, iris scan.

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1140 Developing Research Involving Different Species: Opportunities and Empirical Foundations

Authors: A. V. Varfolomeeva, N. S. Tkachenko, A. G. Tishchenko

Abstract:

In this study, we addressed the problem of weak validity, implausible results, and inaccurate reporting in psychological research on different species. The theoretical basis of the study was the systems-evolutionary approach (SEA). We assumed that the root of the problem is the values and attitudes of the researchers (in particular anthropomorphism and anthropocentrism). The first aim of the study was the formulation of a research design that avoids this problem. Based on a literature review, we concluded that such design, amongst other things, should include methodics with playful components. The second aim was to conduct a series of studies on the differences in the formation of instrumental skill in rats raised and housed in different environments. As a result, we revealed that there are contradictions between some of the statements of SEA, so that it is not possible to choose one of the alternative hypotheses. We suggested that in order to get out of this problem, it is necessary to modify these provisions by aligning them with the attitude of multicentrism.

Keywords: epistemological attitudes, experimental design, validity, psychological structure, learning

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1139 Ontology for Semantic Enrichment of Radio Frequency Identification Systems

Authors: Haitham S. Hamza, Mohamed Maher, Shourok Alaa, Aya Khattab, Hadeal Ismail, Kamilia Hosny

Abstract:

Radio Frequency Identification (RFID) has become a key technology in the emerging concept of Internet of Things (IoT). Naturally, business applications would require the deployment of various RFID systems developed by different vendors that use different data formats and structures. This heterogeneity poses a challenge in developing real-life IoT systems with RFID, as integration is becoming very complex and challenging. Semantic integration is a key approach to deal with this challenge. To do so, ontology for RFID systems need to be developed in order to annotated semantically RFID systems, and hence, facilitate their integration. Accordingly, in this paper, we propose ontology for RFID systems. The proposed ontology can be used to semantically enrich RFID systems, and hence, improve their usage and reasoning.

Keywords: IoT, RFID, Semantic, sparql, Ontology.

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1138 A Comparison of Shunt Active Power Filter Control Methods under Non-Sinusoidal and Unbalanced Voltage Conditions

Authors: H. Abaali, M. T. Lamchich, M. Raoufi

Abstract:

There are a variety of reference current identification methods, for the shunt active power filter (SAPF), such as the instantaneous active and reactive power, the instantaneous active and reactive current and the synchronous detection method are evaluated and compared under ideal, non sinusoidal and unbalanced voltage conditions. The SAPF performances, for the investigated identification methods, are tested for a non linear load. The simulation results, using Matlab Power System Blockset Toolbox from a complete structure, are presented and discussed.

Keywords: Shunt active power filter, Current perturbation, Non sinusoidal and unbalanced voltage conditions.

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