Search results for: species identification

Authors: S. Chovancova, F. Illek, J. Winkler

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The effect of tillage technology of maize on intensity of weed infestation and weed species composition was observed at experimental field. Maize is grown consecutively since 2001. The experimental site is situated at an altitude of 230 m above sea level in the Czech Republic. Variants of tillage technology are CT: plowing – conventional tillage 0.22 m, MT: loosening – disc tillage on the depth of 0.1 – 0.12 m, NT: direct sowing – without tillage. The evaluation of weed infestation was carried out by numerical method in years 2012 and 2013. Within the monitoring were found 20 various species of weeds. Conventional tillage (CT) primarily supports the occurrence of perennial weeds (Cirsium arvense, Convolvulus arvensis). Late spring species (Chenopodium album, Echinochloa crus-galli) were more frequently noticed on variants of loosening (MT) and direct sowing (NT). Different tillage causes a significant change of weed species spectrum in maize.

Keywords: Weeds, maize, tillage, loosening, direct sowing.

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Authors: S. Mhamdi, O. Brendel, P. Montpied, K. Ben Yahia, N. Saouyah, B. Hasnaoui, E. Dreyer

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Leaf Life Span (LLS) is used to classify trees into two main groups: evergreen and deciduous species. It varies according to the forms of life between taxonomic groups. Co-occurrence of deciduous and evergreen oaks is common in some Mediterranean type climate areas. Nevertheless, in the Tunisian forests, there is no enough information about the functional inter-specific diversity among oak species, especially in the mixed stand marked by the simultaneous presence of Q. suber L., Q. canariensis Willd. and their hybrid (Q. afares), the latter being an endemic oak species threatened with extinction. This study has been conducted to estimate the LLS, the relative growth rate, and the count of different growth flushes of samplings in semi-controlled conditions. Our study took 17 months, with an observation's interval of 4 weeks. The aim is to characterize and compare the hybrid species to the parental ones. Differences were observed among species, both for phenology and growth. Indeed, Q. suber saplings reached higher total height and number of growth flushes then Q. canariensis, while Q. afares showed much less growth flushes than the parental species. The LLS of parental species has exceeded the duration of the experiment, but their hybrid lost all leaves on all cohorts. The short LLSs of hybrid species are in accordance with this phenology in the field, but for Q. canariensis there was a contrast with observations in the field where phenology is strictly annual. This study allowed us to differentiate the hybrid from both parental species.

Keywords: Leaf life span, growth, hybrid, evergreen, deciduous, seedlings, Q. afares Pomel, Q. suber L., Q. canariensis Willd.

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Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

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System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: Black box modeling, fixed wing aircraft, least square error, longitudinal dynamics, system identification.

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Authors: M. A. Gad, A. Z. Al-Herrawy

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Microsporidia comprises various pathogenic species can infect humans by means of water. Moreover, chlorine disinfection of drinking-water has limitations against this protozoan pathogen. A total of 48 water samples were collected from two drinking water treatment plants having two different filtration systems (slow sand filter and rapid sand filter) during one year period. Samples were collected from inlet and outlet of each plant. Samples were separately filtrated through nitrocellulose membrane (142 mm, 0.45 µm), then eluted and centrifuged. The obtained pellet from each sample was subjected to DNA extraction, then, amplification using genus-specific primer for microsporidia. Each microsporidia-PCR positive sample was performed by two species specific primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis. The results of the present study showed that the percentage of removal for microsporidia through different treatment processes reached its highest rate in the station using slow sand filters (100%), while the removal by rapid sand filter system was 81.8%. Statistically, the two different drinking water treatment plants (slow and rapid) had significant effect for removal of microsporidia. Molecular identification of microsporidia-PCR positive samples using two different primers for Enterocytozoon bieneusi and Encephalitozoon intestinalis showed the presence of the two pervious species in the inlet water of the two stations, while Encephalitozoon intestinalis was detected in the outlet water only. In conclusion, the appearance of virulent microsporidia in treated drinking water may cause potential health threat.

Keywords: Removal, efficacy, microsporidia, drinking water treatment plants, PCR.

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Authors: Yanto Santosa, Rozza Tri Kwatrina

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High Conservation Value (HCV) is an area with conservation function within oil palm plantation. Despite the important role of HCV area in biodiversity conservation and various studies on HCV, there was a lack of research studying the factors determining its success. A preliminary study was conducted to identify the determinant factor of HCV that affected the diversity. Line transect method was used to calculate the species diversity of butterfly, birds, mammals, and herpetofauna species as well as their richness. Specifically for mammals, camera traps were also used. The research sites comprised of 12 HCV areas in 3 provinces of Indonesia (Central Kalimantan, Riau, and Palembang). The relationship between the HCV biophysical factor with the species number and species diversity for each wildlife class was identified using Chi-Square analysis with Cross tab (contingency table). Results of the study revealed that species diversity varied by research locations. Four factors determining the success of HCV area in relations to the number and diversity of wildlife species are land cover types for mammals, the width of area and distance to rivers for birds, and distance to settlements for butterflies.

Keywords: Ecological factors, high conservation value area, oil palm plantation, wildlife diversity.

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Authors: Tamara Nestorović, Jean Lefèvre, Stefan Ringwelski, Ulrich Gabbert

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Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.

Keywords: Acoustic box, experimental verification, finite element model, subspace identification.

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Authors: Alexander Efremov

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A system for market identification (SMI) is presented. The resulting representations are multivariable dynamic demand models. The market specifics are analyzed. Appropriate models and identification techniques are chosen. Multivariate static and dynamic models are used to represent the market behavior. The steps of the first stage of SMI, named data preprocessing, are mentioned. Next, the second stage, which is the model estimation, is considered in more details. Stepwise linear regression (SWR) is used to determine the significant cross-effects and the orders of the model polynomials. The estimates of the model parameters are obtained by a numerically stable estimator. Real market data is used to analyze SMI performance. The main conclusion is related to the applicability of multivariate dynamic models for representation of market systems.

Keywords: market identification, dynamic models, stepwise regression.

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Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

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The multimodal biometric identification is the combination of several biometric systems; the challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: Biometric databases, Multimodal biometrics, security authentication, Digital watermarking.

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Authors: M. Hashemi, R. Madani, N. Razmi

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M. paratuberculosis is a slow growing mycobactin dependent mycobacterial species known to be the causative agent of Johne’s disease in all species of domestic ruminants worldwide. JD is characterized by gradual weight loss; decreased milk production. Excretion of the organism may occur for prolonged periods (1 to 2.5 years) before the onset of clinical disease. In recent years researchers focus on identification a specific antigen of MAP to use in diagnosis test and preparation of effective vaccine. In this paper, for production of polyclonal antibody against proteins of Mycobacterium avium paratuberculosis cell well a rabbit immunization at a certain time period with antigen. After immunization of the animal, rabbit was bleeded for producing enriched serum. Antibodies were purification with ion exchange chromatography. For exact measurement of interaction, western blotting test was used that this study demonstrated sharp bands appears in nitrocellulose paper and specific bands were 50 and 150 KD molecular weight. These were indicating immunodominant proteins.

Keywords: Paratuberculosis, Immunodominant, Western blotting, Ion exchange choromatography.

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Authors: Z. Masoumi, B. Moaveni

Abstract:

This article is about first step of structural health monitoring by identifying structural system in the presence of unknown input. In the structural system identification, identification of structural parameters such as stiffness and damping are considered. In this study, the Kalman filter (KF) design for structural systems with unknown excitation is expressed. External excitations, such as earthquakes, wind or any other forces are not measured or not available. The purpose of this filter is its strengths to estimate the state variables of the system in the presence of unknown input. Also least squares estimation (LSE) method with unknown input is studied. Estimates of parameters have been adopted. Finally, using two examples advantages and drawbacks of both methods are studied.

Keywords: Structural health monitoring, Kalman filter, Least square estimation, structural system identification.

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Authors: L. V. Ignatova, Y. V. Brazhnikova, T. D. Mukasheva, A. A. Omirbekova, R. Zh. Berzhanova, R. K. Sydykbekova, T. A. Karpenyuk, A. V. Goncharova

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The comparative analysis of different taxonomic groups of microorganisms isolated from dark chernozem soils under different agricultures (alfalfa, melilot, sainfoin, soybean, rapeseed) at Almaty region of Kazakhstan was conducted. It was shown that the greatest number of micromycetes was typical to the soil planted with alfalfa and canola. Species diversity of micromycetes markedly decreases as it approaches the surface of the root, so that the species composition in the rhizosphere is much more uniform than in the virgin soil. Promising strains of microscopic fungi and yeast with plant growth-promoting activity to agricultures were selected. Among the selected fungi there are representatives of Penicillium bilaiae, Trichoderma koningii, Fusarium equiseti, Aspergillus ustus. The highest rates of growth and development of seedlings of plants observed under the influence of yeasts Aureobasidium pullulans, Rhodotorula mucilaginosa, Metschnikovia pulcherrima. Using molecular - genetic techniques confirmation of the identification results of selected micromycetes was conducted.

Keywords: Agricultures, biodiversity, micromycetes, plant growth-promoting microorganisms.

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Authors: Mohamed Hafez, Georg Hausner

Abstract:

The full length mitochondrial small subunit ribosomal (mt-rns) gene has been characterized for Ophiostoma novo-ulmi subspecies americana. The gene was also characterized for Ophiostoma ulmi and a group II intron was noted in the mt-rns gene of O. ulmi. The insertion in the mt-rns gene is at position S952 and it is a group IIB1 intron that encodes a double motif LAGLIDADG homing endonuclease from an open reading frame located within a loop of domain III. Secondary structure models for the mt-rns RNA of O. novo-ulmi subsp. americana and O. ulmi were generated to place the intron within the context of the ribosomal RNA. The in vivo splicing of the O.ul-mS952 group II intron was confirmed with reverse transcription-PCR. A survey of 182 strains of Dutch Elm Diseases causing agents showed that the mS952 intron was absent in what is considered to be the more aggressive species O. novo-ulmi but present in strains of the less aggressive O. ulmi. This observation suggests that the O.ul-mS952 intron can be used as a PCR-based molecular marker to discriminate between O. ulmi and O. novo-ulmi subsp. americana.

Keywords: Dutch Elm Disease, group II introns, mtDNA, species identification

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Authors: Ahmad Gholami, Saeed Sharafi, Hamid Abbasdokht

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The heterotrophic seedling growth can be defined as a product of two components: (1) the weight of mobilized seed reserve, and (2) conversion efficiency of utilized seed reserve to seedling tissue. The first component can be further divided into (1) initial seed weight, and (2) the fraction of seed reserve, which is mobilized. The objective of this study was the identification of the sensitive seedling growth component(s) in response to drought and salinity stresses. Two experiments were separately conducted using various salinity levels (osmotic pressure) of 0, 0.25, 0.50, 0.75, 1, 1.25 and 1.5 MPa created using NaCl as first experiment and by polyethylene glycol (drought stress) of 0, 0.2, 0.4, 0.6, 0.8, 1, 1.2 and 1.4 MPa in second experiment. Seeds of five crops species (Hordeum vulgare, Brassica napus, Zea mays, Medicago sativa and Medicago scutellata) were used in each experiment. In both experiments, seedling growth, fraction of seed reserve utilization and weight of mobilized seed reserve decreased with increasing drought and salt intensity. However, drought and salinity stresses had no effect on the conversion efficiency. It was concluded that the sensitive component of seedling growth is the weight of mobilized seed reserve.

Keywords: Salinity, Drought, Seed reserve, Seedling, Cropsspecies

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Authors: Jutta Hämmerle-Uhl, Georg Penn, Gerhard Pötzelsberger, Andreas Uhl

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Iris codes contain bits with different entropy. This work investigates different strategies to reduce the size of iris code templates with the aim of reducing storage requirements and computational demand in the matching process. Besides simple subsampling schemes, also a binary multi-resolution representation as used in the JBIG hierarchical coding mode is assessed. We find that iris code template size can be reduced significantly while maintaining recognition accuracy. Besides, we propose a two-stage identification approach, using small-sized iris code templates in a pre-selection stage, and full resolution templates for final identification, which shows promising recognition behaviour.

Keywords: Iris recognition, compact iris code, fast matching, best bits, pre-selection identification, two-stage identification.

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Authors: Abdul H, Jamil A, Imran U

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Conflicts identification among non-functional requirements is often identified intuitively which impairs conflict analysis practices. This paper proposes a new model to identify conflicts among non-functional requirements. The proposed model uses the matrix mechanism to identify the quality based conflicts among non-functional requirements. The potential conflicts are identified through the mapping of low level conflicting quality attributes to low level functionalities using the matrices. The proposed model achieves the identification of conflicts among product and process requirements, identifies false conflicts, decreases the documentation overhead, and maintains transparency of identified conflicts. The attributes are not concomitantly taken into account by current models in practice.

Keywords: Conflict Identification, Matrix Maps, Non-functional Requirements, Requirements Analysis, Software Engineering

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Authors: Clio G. Vossou, Ioannis N. Koukoulis, Christopher G. Provatidis

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The present work encounters the solution of the defect identification problem with the use of an evolutionary algorithm combined with a simplex method. In more details, a Matlab implementation of Genetic Algorithms is combined with a Simplex method in order to lead to the successful identification of the defect. The influence of the location and the orientation of the depressed ellipsoidal flaw was investigated as well as the use of different amount of static data in the cost function. The results were evaluated according to the ability of the simplex method to locate the global optimum in each test case. In this way, a clear impression regarding the performance of the novel combination of the optimization algorithms, and the influence of the geometrical parameters of the flaw in defect identification problems was obtained.

Keywords: Defect identification, genetic algorithms, optimization.

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Authors: B. Chandra, P. Paul Varghese

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Crypto System Identification is one of the challenging tasks in Crypt analysis. The paper discusses the possibility of employing Neural Networks for identification of Cipher Systems from cipher texts. Cascade Correlation Neural Network and Back Propagation Network have been employed for identification of Cipher Systems. Very large collection of cipher texts were generated using a Block Cipher (Enhanced RC6) and a Stream Cipher (SEAL). Promising results were obtained in terms of accuracy using both the Neural Network models but it was observed that the Cascade Correlation Neural Network Model performed better compared to Back Propagation Network.

Keywords: Back Propagation Neural Networks, CascadeCorrelation Neural Network, Crypto systems, Block Cipher, StreamCipher.

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Authors: Ozan Mut, Mehmet Göktürk

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Matching algorithms have significant importance in speaker recognition. Feature vectors of the unknown utterance are compared to feature vectors of the modeled speakers as a last step in speaker recognition. A similarity score is found for every model in the speaker database. Depending on the type of speaker recognition, these scores are used to determine the author of unknown speech samples. For speaker verification, similarity score is tested against a predefined threshold and either acceptance or rejection result is obtained. In the case of speaker identification, the result depends on whether the identification is open set or closed set. In closed set identification, the model that yields the best similarity score is accepted. In open set identification, the best score is tested against a threshold, so there is one more possible output satisfying the condition that the speaker is not one of the registered speakers in existing database. This paper focuses on closed set speaker identification using a modified version of a well known matching algorithm. The results of new matching algorithm indicated better performance on YOHO international speaker recognition database.

Keywords: Automatic Speaker Recognition, Voice Recognition, Pattern Recognition, Digital Audio Signal Processing.

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Authors: Ekta Singh, M. P. Singh

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The habitat where the present study has been carried out is productive in relation to nutrient quality and they may perform several useful functions, but are also threatened for their existence. Hence, the proposed work, will add much new information about biodiversity of macrophytes in drains and their embankment. All the species were identified with their different stages of growth which encountered on the three selected sites (I, II and III). The number of species occurring at each site is grouped seasonally, i.e. summer, rainy and winter season and the species were further recorded for the study of phytosociology. Phytosociological characters such as frequency, density and abundance were influenced by the climatic, anthropogenic and biotic stresses prevailing at the three study sites. All the species present at the study sites have shown maximum values of frequency, density and abundance in rainy season in comparison to that of summer and winter seasons.

Keywords: Abundance, Biodiversity, Density, Frequency, Macrophytes, Phytosociology.

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Authors: Cemil Turan, Mohammad Shukri Salman

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The convergence rate of the least-mean-square (LMS) algorithm deteriorates if the input signal to the filter is correlated. In a system identification problem, this convergence rate can be improved if the signal is white and/or if the system is sparse. We recently proposed a sparse transform domain LMS-type algorithm that uses a variable step-size for a sparse system identification. The proposed algorithm provided high performance even if the input signal is highly correlated. In this work, we investigate the performance of the proposed TD-LMS algorithm for a large number of filter tap which is also a critical issue for standard LMS algorithm. Additionally, the optimum value of the most important parameter is calculated for all experiments. Moreover, the convergence analysis of the proposed algorithm is provided. The performance of the proposed algorithm has been compared to different algorithms in a sparse system identification setting of different sparsity levels and different number of filter taps. Simulations have shown that the proposed algorithm has prominent performance compared to the other algorithms.

Keywords: Adaptive filtering, sparse system identification, VSSLMS algorithm, TD-LMS algorithm.

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Authors: Marzuki Khalid, RubiyahYusof, AnisSalwaMohdKhairuddin

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An automated wood recognition system is designed to classify tropical wood species.The wood features are extracted based on two feature extractors: Basic Grey Level Aura Matrix (BGLAM) technique and statistical properties of pores distribution (SPPD) technique. Due to the nonlinearity of the tropical wood species separation boundaries, a pre classification stage is proposed which consists ofKmeans clusteringand kernel discriminant analysis (KDA). Finally, Linear Discriminant Analysis (LDA) classifier and KNearest Neighbour (KNN) are implemented for comparison purposes. The study involves comparison of the system with and without pre classification using KNN classifier and LDA classifier.The results show that the inclusion of the pre classification stage has improved the accuracy of both the LDA and KNN classifiers by more than 12%.

Keywords: Tropical wood species, nonlinear data, featureextractors, classification

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Authors: Saktioto, F.D Ismail, P.P. Yupapin, J. Ali

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The equilibrium process of plasma nitrogen species by chemical kinetic reactions along various pressures is successfully investigated. The equilibrium process is required in industrial application to obtain the stable condition when heating up the material for having homogenous reaction. Nitrogen species densities is modeled by a continuity equation and extended Arrhenius form. These equations are used to integrate the change of density over the time. The integration is to acquire density and the reaction rate of each reaction where temperature and time dependence are imposed. A comparison is made with global model within pressure range of 1- 100mTorr and the temperature of electron is set to be higher than other nitrogen species. The results shows that the chemical kinetic model only agrees for high pressure because of no power imposed; while the global model considers the external power along the pressure range then the electron and nitrogen species give highly quantity densities by factor of 3 to 5.

Keywords: chemical kinetic model, Arrhenius equation, nitrogen plasma, low pressure discharge

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Authors: Rafik Djemili, Mouldi Bedda, Hocine Bourouba

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This paper proposes a novel approach that combines statistical models and support vector machines. A hybrid scheme which appropriately incorporates the advantages of both the generative and discriminant model paradigms is described and evaluated. Support vector machines (SVMs) are trained to divide the whole speakers' space into small subsets of speakers within a hierarchical tree structure. During testing a speech token is assigned to its corresponding group and evaluation using gaussian mixture models (GMMs) is then processed. Experimental results show that the proposed method can significantly improve the performance of text independent speaker identification task. We report improvements of up to 50% reduction in identification error rate compared to the baseline statistical model.

Keywords: Speaker identification, Gaussian mixture model (GMM), support vector machine (SVM), hybrid GMM/SVM.

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Authors: Kholoud A. Al-Shammery , Badr El-Sabah A. Fetoh, Ahmed M. Alshammari

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Protein and Esterase electrophoresis were used to genetically identify two Saudi tick species. Engorged females of the camel tick Hyalomma dromedarii (Koch) (Acari: Ixodidae) and the cattle tick Boophilus annulatus (Say) (Acari: Ixodidae) ticks collected from infested camels and cattle in the animals resting house at Hail region in KSA were used. The results showed that there are a variation in both of protein and esterase activity levels and a high polymorphism within and between the genera and species of Hyalomma and Boophilus . In conclusion, the protein and esterase electrophoretic analysis used in the present study could successfully distinguish among tick species, commonly found in Saudi Arabia.

Keywords: Molecular biology, The camel tick Hyalomma dromedarii, The cattle tick Boophilus annulatus , Ticks.

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Authors: Tyng-Rong Roan, Fuji Foo, Wenwey Hseush

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Recent development of AI and edge computing plays a critical role to capture meaningful events such as detection of an unattended bag. One of the core problems is re-identification across multiple CCTVs. Immediately following the detection of a meaningful event is to track and trace the objects related to the event. In an extensive environment, the challenge becomes severe when the number of CCTVs increases substantially, imposing difficulties in achieving high accuracy while maintaining real-time performance. The algorithm that re-identifies cross-boundary objects for extensive tracking is referred to Extensive Re-Identification, which emphasizes the issues related to the complexity behind a great number of CCTVs. The Spatial-Temporal Awareness approach challenges the conventional thinking and concept of operations which is labor intensive and time consuming. The ability to perform Extensive Re-Identification through a multi-sensory network provides the next-level insights – creating value beyond traditional risk management.

Keywords: Long-short-term memory, re-identification, security critical application, spatial-temporal awareness.

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Authors: S. J. Mitchual, K. Frimpong-Mensah, N. A. Darkwa

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The fuel potential of six tropical hardwood species namely: Triplochiton scleroxylon, Ceiba pentandra, Aningeria robusta, Terminalia superba, Celtis mildbreadii and Piptadenia africana were studied. Properties studied included species density, gross calorific value, volatile matter, ash content, organic carbon and elemental composition. Fuel properties were determined using standard laboratory methods. The result indicates that the gross calorific value (GCV) of the species ranged from 20.16 to 22.22 MJ/kg and they slightly varied from each other. Additionally, the GCV of the biomass materials were higher than that of other biomass materials like; wheat straw, rice straw, maize straw and sugar cane. The ash and volatile matter content varied from 0.6075 to 5.0407%, and 75.23% to 83.70% respectively. The overall rating of the properties of the six biomass materials suggested that Piptadenia africana has the best fuel property to be used as briquettes and Aningeria robusta the worse. This study therefore suggests that a holistic assessment of a biomass material needs to be done before selecting it for fuel purpose.

Keywords: Ash content, Briquette, Calorific value, Elemental composition, Species, Volatile matter.

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Authors: Aliakbar Akbari, Majid Hashemipour, Shiva Mirshahi

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Radio-frequency identification has entered as a beneficial means with conforming GS1 standards to provide the best solutions in the manufacturing area. It competes with other automated identification technologies e.g. barcodes and smart cards with regard to high speed scanning, reliability and accuracy as well. The purpose of this study is to improve production line-s performance by implementing RFID system in the manufacturing area on the basis of radio-frequency identification (RFID) system by 3D modeling in the program Cinema 4D R13 which provides obvious graphical scenes for users to portray their applications. Finally, with regard to improving system performance, it shows how RFID appears as a well-suited technology in a comparison of the barcode scanner to handle different kinds of raw materials in the production line base on logical process.

Keywords: Radio Frequency Identification, Manufacturing and Production Lines, 3D modeling

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Authors: Christian Endisch, Christoph Hackl, Dierk Schröder

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This paper presents an exact pruning algorithm with adaptive pruning interval for general dynamic neural networks (GDNN). GDNNs are artificial neural networks with internal dynamics. All layers have feedback connections with time delays to the same and to all other layers. The structure of the plant is unknown, so the identification process is started with a larger network architecture than necessary. During parameter optimization with the Levenberg- Marquardt (LM) algorithm irrelevant weights of the dynamic neural network are deleted in order to find a model for the plant as simple as possible. The weights to be pruned are found by direct evaluation of the training data within a sliding time window. The influence of pruning on the identification system depends on the network architecture at pruning time and the selected weight to be deleted. As the architecture of the model is changed drastically during the identification and pruning process, it is suggested to adapt the pruning interval online. Two system identification examples show the architecture selection ability of the proposed pruning approach.

Keywords: System identification, dynamic neural network, recurrentneural network, GDNN, optimization, Levenberg Marquardt, realtime recurrent learning, network pruning, quasi-online learning.

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Authors: Shaoying Guo, Yanyun Xu, Meng Zhang, Weiqing Huang

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The wireless communication network is developing rapidly, thus the wireless security becomes more and more important. Specific emitter identification (SEI) is an vital part of wireless communication security as a technique to identify the unique transmitters. In this paper, a SEI method based on multiscale dispersion entropy (MDE) and refined composite multiscale dispersion entropy (RCMDE) is proposed. The algorithms of MDE and RCMDE are used to extract features for identification of five wireless devices and cross-validation support vector machine (CV-SVM) is used as the classifier. The experimental results show that the total identification accuracy is 99.3%, even at low signal-to-noise ratio(SNR) of 5dB, which proves that MDE and RCMDE can describe the communication signal series well. In addition, compared with other methods, the proposed method is effective and provides better accuracy and stability for SEI.

Keywords: Cross-validation support vector machine, refined composite multiscale dispersion entropy, specific emitter identification, transient signal, wireless communication device.

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Authors: Bhaskar Thakker, Anoop Lal Vyas

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Wrist pulse analysis for identification of health status is found in Ancient Indian as well as Chinese literature. The preprocessing of wrist pulse is necessary to remove outlier pulses and fluctuations prior to the analysis of pulse pressure signal. This paper discusses the identification of irregular pulses present in the pulse series and intricacies associated with the extraction of time domain pulse features. An approach of Dynamic Time Warping (DTW) has been utilized for the identification of outlier pulses in the wrist pulse series. The ambiguity present in the identification of pulse features is resolved with the help of first derivative of Ensemble Average of wrist pulse series. An algorithm for detecting tidal and dicrotic notch in individual wrist pulse segment is proposed.

Keywords: Wrist Pulse Segment, Ensemble Average, Dynamic Time Warping (DTW), Pulse Similarity Vector.

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