Search results for: root Extracts.

Authors: R. Leelaruji, V. Knazkins

Abstract:

This paper proposes a methodology for mitigating the occurrence of cascading failure in stressed power systems. The methodology is essentially based on predicting voltage instability in the power system using a voltage stability index and then devising a corrective action in order to increase the voltage stability margin. The paper starts with a brief description of the cascading failure mechanism which is probable root cause of severe blackouts. Then, the voltage instability indices are introduced in order to evaluate stability limit. The aim of the analysis is to assure that the coordination of protection, by adopting load shedding scheme, capable of enhancing performance of the system after the major location of instability is determined. Finally, the proposed method to generate instability prediction is introduced.

Keywords: Blackouts, cascading failure, voltage stability indices, singular value decomposition, load shedding.

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Authors: Vicky Min-How Lim, Siew Fan Wong, Tong Ming Lim

Abstract:

Automatic keyphrase extraction is useful in efficiently locating specific documents in online databases. While several techniques have been introduced over the years, improvement on accuracy rate is minimal. This research examines attribute scores for author-supplied keyphrases to better understand how the scores affect the accuracy rate of automatic keyphrase extraction. Five attributes are chosen for examination: Term Frequency, First Occurrence, Last Occurrence, Phrase Position in Sentences, and Term Cohesion Degree. The results show that First Occurrence is the most reliable attribute. Term Frequency, Last Occurrence and Term Cohesion Degree display a wide range of variation but are still usable with suggested tweaks. Only Phrase Position in Sentences shows a totally unpredictable pattern. The results imply that the commonly used ranking approach which directly extracts top ranked potential phrases from candidate keyphrase list as the keyphrases may not be reliable.

Keywords: Accuracy, Attribute Score, Author-supplied keyphrases, Automatic keyphrase extraction.

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Authors: Chun-Yao Lee, Yi-Xing Shen, Jung-Cheng Cheng, Yi-Yin Li, Chih-Wen Chang

Abstract:

This paper proposes the method combining artificial neural network (ANN) with particle swarm optimization (PSO) to implement the maximum power point tracking (MPPT) by controlling the rotor speed of the wind generator. First, the measurements of wind speed, rotor speed of wind power generator and output power of wind power generator are applied to train artificial neural network and to estimate the wind speed. Second, the method mentioned above is applied to estimate and control the optimal rotor speed of the wind turbine so as to output the maximum power. Finally, the result reveals that the control system discussed in this paper extracts the maximum output power of wind generator within the short duration even in the conditions of wind speed and load impedance variation.

Keywords: Maximum power point tracking, artificial neuralnetwork, particle swarm optimization.

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

Abstract:

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: Watcharin Sangma, Onsiri Chanmuang, Pitsanu Tongkhow

Abstract:

 A forecasting model for steel demand uncertainty in Thailand is proposed. It consists of trend, autocorrelation, and outliers in a hierarchical Bayesian frame work. The proposed model uses a cumulative Weibull distribution function, latent first-order autocorrelation, and binary selection, to account for trend, time-varying autocorrelation, and outliers, respectively. The Gibbs sampling Markov Chain Monte Carlo (MCMC) is used for parameter estimation. The proposed model is applied to steel demand index data in Thailand. The root mean square error (RMSE), mean absolute percentage error (MAPE), and mean absolute error (MAE) criteria are used for model comparison. The study reveals that the proposed model is more appropriate than the exponential smoothing method.

Keywords: Forecasting model, Steel demand uncertainty, Hierarchical Bayesian framework, Exponential smoothing method.

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Authors: M. F. V. Montezuma, E. P. Deus, M. C. Carvalho

Abstract:

Steel bridges are normally subjected to random loads with different traffic frequencies. They are structures with dynamic behavior and are subject to fatigue failure process, where the nucleation of a crack, growth and failure can occur. After locating and determining the size of an existing fault, it is important to predict the crack propagation and the convenient time for repair. Therefore, fracture mechanics and fatigue concepts are essential to the right approach to the problem. To study the fatigue crack growth, a computational code was developed by using the root mean square (RMS) and the cycle-by-cycle models. One observes the variable amplitude loading influence on the life structural prediction. Different loads histories and initial crack length were considered as input variables. Thus, it was evaluated the dispersion of results of the expected structural life choosing different initial parameters.

Keywords: Fatigue crack propagation, life prediction, variable loadings, steel bridges.

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Authors: H.K. Abd El-Maksoud, H.H. Keyser

Abstract:

Competitive relationships among Bradyrhizobium japonicum USDA serogroup 123, 122 and 138 were screened versus the standard commercial soybean variety Williams and two introductions P1 377578 "671" in a field trial. Displacement of strain 123 by an effective strain should improved N2 fixation. Root nodules were collected and strain occupancy percentage was determined using strain specific fluorescent antibodies technique. As anticipated the strain USDA 123 dominated 92% of nodules due to the high affinity between the host and the symbiont. This dominance was consistent and not changed materially either by inoculation practice or by introducing new strainan. The interrelationship between the genotype Williams and serogroup 122 & 138 was found very weak although the cell density of the strain in the rhizosphere area was equal. On the other hand, the nodule occupancy of genotypes 671 and 166 with rhizobia serogroup 123 was almost diminished to zero. . The data further exhibited that the genotypes P1 671 and P1 166 have high affinity to colonize with strains 122 and 138 whereas Williams was highly promiscuous to strain 123.

Keywords: B. japonicum serogroups, Competition, Host restriction, Soybean genotype.

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Authors: S. M. Biondi, V. Catania, R. Di Natale, A. R. Intilisano, D. Panno

Abstract:

One of the major goals of Spoken Dialog Systems (SDS) is to understand what the user utters. In the SDS domain, the Spoken Language Understanding (SLU) Module classifies user utterances by means of a pre-definite conceptual knowledge. The SLU module is able to recognize only the meaning previously included in its knowledge base. Due the vastity of that knowledge, the information storing is a very expensive process. Updating and managing the knowledge base are time-consuming and error-prone processes because of the rapidly growing number of entities like proper nouns and domain-specific nouns. This paper proposes a solution to the problem of Name Entity Recognition (NER) applied to a SDS domain. The proposed solution attempts to automatically recognize the meaning associated with an utterance by using the PANKOW (Pattern based Annotation through Knowledge On the Web) method at runtime. The method being proposed extracts information from the Web to increase the SLU knowledge module and reduces the development effort. In particular, the Google Search Engine is used to extract information from the Facebook social network.

Keywords: Spoken Dialog System, Spoken Language Understanding, Web Semantic, Name Entity Recognition.

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Authors: Chia-Yu Yao

Abstract:

This paper presents experimental results on testing the symbol-error-rate (SER) performance of quadrature amplitude modulation (QAM) systems employing symmetric pulse-shaping square-root (SR) filters designed by minimizing the roughness function and by minimizing the peak-to-average power ratio (PAR). The device used in the experiments is the 'bladeRF' software-defined-radio platform. PAR is a well-known measurement, whereas the roughness function is a concept for measuring the jitter-induced interference. The experimental results show that the system employing minimum-roughness pulse-shaping SR filters outperforms the system employing minimum-PAR pulse-shaping SR filters in the sense of SER performance.

Keywords: Pulse-shaping filters, jitter, inter-symbol interference, symmetric FIR filters, QAM

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Authors: E. Ardil, Erdem Uçar, Parvinder S. Sandhu

Abstract:

As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, SoftwareFaults, Accuracy, MAE, RMSE.

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Authors: Yongsuk Jang Kim, Sun-Tae Chung, Boogyun Kim, Seongwon Cho

Abstract:

Realistic 3D face model is more precise in representing pose, illumination, and expression of face than 2D face model so that it can be utilized usefully in various applications such as face recognition, games, avatars, animations, and etc. In this paper, we propose a 3D face modeling method based on 3D dense morphable shape model. The proposed 3D modeling method first constructs a 3D dense morphable shape model from 3D face scan data obtained using a 3D scanner. Next, the proposed method extracts and matches facial landmarks from 2D image sequence containing a face to be modeled, and then reconstructs 3D vertices coordinates of the landmarks using a factorization-based SfM technique. Then, the proposed method obtains a 3D dense shape model of the face to be modeled by fitting the constructed 3D dense morphable shape model into the reconstructed 3D vertices. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method generates a 3D face model by rendering the 3D dense face shape model using the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise.

Keywords: 3D Face Modeling, 3D Morphable Shape Model, 3DReconstruction, 3D Correspondence.

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Authors: Amelia B. Hizon-Fradejas, Yoichi Nakano, Satoshi Nakai, Wataru Nishijima, Mitsumasa Okada

Abstract:

Dredged sediment (DS) was utilized as source of silt-clay and organic matter in artificially prepared eelgrass substrates with mountain sand (MS) as the sand media. Addition of DS showed improved growth of eelgrass in the mixed substrates. Increase in added DS up to 15% silt-clay showed increased shoot growth but additional DS in 20% silt-clay mixture didn-t result to further increase in eelgrass growth. Improved root establishment were also found for plants in pots with added DS as shown by the increased resistance to uprooting, increased number of rhizome nodes and longer roots. Results demonstrated that addition of DS may be beneficial to eelgrass up to a certain extent only and too much of it might be harmful to eelgrass plants.

Keywords: Dredged sediment, eelgrass, eelgrass bed restoration, mountain sand, Zostera marina.

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Authors: Sonia Manhas, Parvinder S. Sandhu, Vinay Chopra, Nirvair Neeru

Abstract:

The cost of developing the software from scratch can be saved by identifying and extracting the reusable components from already developed and existing software systems or legacy systems [6]. But the issue of how to identify reusable components from existing systems has remained relatively unexplored. We have used metric based approach for characterizing a software module. In this present work, the metrics McCabe-s Cyclometric Complexity Measure for Complexity measurement, Regularity Metric, Halstead Software Science Indicator for Volume indication, Reuse Frequency metric and Coupling Metric values of the software component are used as input attributes to the different types of Neural Network system and reusability of the software component is calculated. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE).

Keywords: Software reusability, Neural Networks, MAE, RMSE, Accuracy.

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Authors: A. H. Elkholy, A. H. Falah

Abstract:

A new approach has been developed to estimate the load share and distribution of worm gear drives, and to calculate the instantaneous tooth meshing stiffness. In the approach, the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well-established formulae of spur gear loading and stresses. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. Based on the slicing method introduced in this study, the instantaneous meshing stiffness and load share are obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.

Keywords: Gear, load/stress distribution, worm, wheel, tooth stiffness, contact line.

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Authors: Nerijus Remeikis, Ignas Skucas, Vida Melninkaite

Abstract:

Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.

Keywords: Text categorization, decision trees, neural networks, machine learning.

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Authors: Saijal K. K., K. Prabhakaran Nair

Abstract:

This study aims to determine change in optimal locations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multiobjective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization result shows that the inboard flap location at low Ct /σ ratio move farther from the baseline value and at high Ct /σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: Helicopter rotor, Trailing-edge flap, Thrust coefficient to solidity (Ct /σ) ratio, Optimization.

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Authors: M. Hosseinnezhad, K. Gharanjig

Abstract:

Natural dyes, extracted from black carrot and bramble, were utilized as photosensitizers to prepare dye-sensitized solar cells (DSSCs). Spectrophotometric studies of the natural dyes in solution and on a titanium dioxide substrate were carried out in order to assess changes in the status of the dyes. The results show that the bathochromic shift is seen on the photo-electrode substrate. The chemical binding of the natural dyes at the surface photo-electrode were increased by the chelating effect of the Ti(IV) ions. The cyclic voltammetry results showed that all extracts are suitable to be performed in DSSCs. Finally, photochemical performance and stability of DSSCs based on natural dyes were studied. The DSSCs sensitized by black carrot extract have been reported to achieve up to Jsc=1.17 mAcm^-2, Voc= 0.55 V, FF= 0.52, η=0.34%, whereas Bramble extract can obtain up to Jsc=2.24 mAcm^-2, Voc= 0.54 V, FF= 0.57, η=0.71%. The power conversion efficiency was obtained from the mixed dyes in DSSCs. The power conversion efficiency of dye-sensitized solar cells using mixed Black carrot and Bramble dye is the average of the their efficiency in single DSSCs.

Keywords: Anthocyanin, dye-sensitized solar cells, green energy, optical materials.

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Authors: Yasmeen A. S. Essawy, Khaled Nassar

Abstract:

With the rapid increase of complexity in the building industry, professionals in the A/E/C industry were forced to adopt Building Information Modeling (BIM) in order to enhance the communication between the different project stakeholders throughout the project life cycle and create a semantic object-oriented building model that can support geometric-topological analysis of building elements during design and construction. This paper presents a model that extracts topological relationships and geometrical properties of building elements from an existing fully designed BIM, and maps this information into a directed acyclic Elemental Graph Data Model (EGDM). The model incorporates BIM-based search algorithms for automatic deduction of geometrical data and topological relationships for each building element type. Using graph search algorithms, such as Depth First Search (DFS) and topological sortings, all possible construction sequences can be generated and compared against production and construction rules to generate an optimized construction sequence and its associated schedule. The model is implemented in a C# platform.

Keywords: Building information modeling, elemental graph data model, geometric and topological data models, and graph theory.

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Authors: Shuenn-Yih Chang, Chiu-Li Huang

Abstract:

Three structure-dependent integration methods have been developed for solving equations of motion, which are second-order ordinary differential equations, for structural dynamics and earthquake engineering applications. Although they generally have the same numerical properties, such as explicit formulation, unconditional stability and second-order accuracy, a different performance is found in solving the free vibration response to either linear elastic or nonlinear systems with high frequency modes. The root cause of this different performance in the free vibration responses is analytically explored herein. As a result, it is verified that a weak instability is responsible for the different performance of the integration methods. In general, a weak instability will result in an inaccurate solution or even numerical instability in the free vibration responses of high frequency modes. As a result, a weak instability must be prohibited for time integration methods.

Keywords: Dynamic analysis, high frequency, integration method, overshoot, weak instability.

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Authors: Karina Ruse, Martins Sabovics, Tatjana Rakcejeva, Lija Dukalska, Ruta Galoburda, Laima Berzina

Abstract:

the research was accomplished on fresh in Latvia wild growing cranberries and cranberry cultivars. The aim of the study was to evaluate effect of pretreatment method and drying conditions on the volatile compounds composition in cranberries. Berries pre-treatment methods were: perforation, halving and steam-blanching. The berries before drying in a cabinet drier were pre-treated using all three methods, in microwave vacuum drier – using a steam-blanching and halving. Volatile compounds in cranberries were analysed using GC-MS of extracts obtained by SPME. During present research 21 various volatile compounds were detected in fresh cranberries: the cultivar 'Steven' - 15, 'Bergman' and 'Early black' – 13, 'Ben Lear' and 'Pilgrim' – 11 and wild cranberries – 14 volatile compounds. In dried cranberries 20 volatile compounds were detected. Mathematical data processing allows drawing a conclusion that there exists the significant influence of cranberry cultivar, pre-treatment method and drying condition on volatile compounds in berries and new volatile compound formation.

Keywords: volatile compounds, cranberries, convective drier, microwave-vacuum drier

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Authors: Omer Nebil Yaveroglu, Tolga Can

Abstract:

In this study, a high accuracy protein-protein interaction prediction method is developed. The importance of the proposed method is that it only uses sequence information of proteins while predicting interaction. The method extracts phylogenetic profiles of proteins by using their sequence information. Combining the phylogenetic profiles of two proteins by checking existence of homologs in different species and fitting this combined profile into a statistical model, it is possible to make predictions about the interaction status of two proteins. For this purpose, we apply a collection of pattern recognition techniques on the dataset of combined phylogenetic profiles of protein pairs. Support Vector Machines, Feature Extraction using ReliefF, Naive Bayes Classification, K-Nearest Neighborhood Classification, Decision Trees, and Random Forest Classification are the methods we applied for finding the classification method that best predicts the interaction status of protein pairs. Random Forest Classification outperformed all other methods with a prediction accuracy of 76.93%

Keywords: Protein Interaction Prediction, Phylogenetic Profile, SVM , ReliefF, Decision Trees, Random Forest Classification

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Authors: Shang-Han Tsai, Yong-Hong Lin, Chung-Ruey Yen

Abstract:

Waxapple (Syzygium samarngense Merr.et Perry) is an important tropical fruit in Taiwan. The famous producing area is located on the coast in Pingtung County. Land subsidence and climate change will tend to soil alkalization more seriously. This study was to evaluate the effects of NaCl in waxapple seedlings. NaCl salinity reduced waxapple shoot growth; it may due to reducing relative water content in leaf and new shoot. Leaf Cl and Na concentration were increased but K, Ca, and Mg content had no significant difference after irrigated with NaCl for six weeks. In roots, Na and Cl content increase significantly with 90 mM NaCl treatment, but K, Ca, and Mg content was reduced. 30-90mM Nacl treatment do not effect K/Na, Ca/Na and Mg/Na ratio, but decrease significantly in 90mM treatment in roots. The leaf and root electrolyte leakage were significantly affected by 90 mM NaCl treatment. Suggesting 90mM was optimum concentration for sieve out other tolerance waxapples verities.

Keywords: Growth, NaCl stress, Nutrient, Waxapple.

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Authors: David Wiese

Abstract:

In order to maximize efficiency of an information management platform and to assist in decision making, the collection, storage and analysis of performance-relevant data has become of fundamental importance. This paper addresses the merits and drawbacks provided by the OLAP paradigm for efficiently navigating large volumes of performance measurement data hierarchically. The system managers or database administrators navigate through adequately (re)structured measurement data aiming to detect performance bottlenecks, identify causes for performance problems or assessing the impact of configuration changes on the system and its representative metrics. Of particular importance is finding the root cause of an imminent problem, threatening availability and performance of an information system. Leveraging OLAP techniques, in contrast to traditional static reporting, this is supposed to be accomplished within moderate amount of time and little processing complexity. It is shown how OLAP techniques can help improve understandability and manageability of measurement data and, hence, improve the whole Performance Analysis process.

Keywords: Data Warehousing, OLAP, Multidimensional Navigation, Performance Diagnosis, Performance Management, Performance Tuning.

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Authors: Vipin Kumar Jain, Praveen Kumar, Y.K. Vijay

Abstract:

ZnO-SnO2 i.e. Zinc-Tin-Oxide (ZTO) thin films were deposited on glass substrate with varying concentrations (ZnO:SnO2 - 100:0, 90:10, 70:30 and 50:50 wt.%) at room temperature by flash evaporation technique. These deposited ZTO film were annealed at 450 0C in vacuum. These films were characterized to study the effect of annealing on the structural, electrical, and optical properties. Atomic force microscopy (AFM) and Scanning electron microscopy (SEM) images manifest the surface morphology of these ZTO thin films. The apparent growth of surface features revealed the formation of nanostructure ZTO thin films. The small value of surface roughness (root mean square RRMS) ensures the usefulness in optical coatings. The sheet resistance was also found to be decreased for both types of films with increasing concentration of SnO2. The optical transmittance found to be decreased however blue shift has been observed after annealing.

Keywords: ZTO thin film, AFM, SEM, Optical transmittance, Sheet resistance.

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Authors: Md. Zahangir Alom, Mei-Lan Piao, Md. Ashraful Alam, Nam Kim, Jae-Hyeung Park

Abstract:

A new approach for facial expressions recognition based on face context and adaptively weighted sub-pattern PCA (Aw-SpPCA) has been presented in this paper. The facial region and others part of the body have been segmented from the complex environment based on skin color model. An algorithm has been proposed to accurate detection of face region from the segmented image based on constant ratio of height and width of face (δ= 1.618). The paper also discusses on new concept to detect the eye and mouth position. The desired part of the face has been cropped to analysis the expression of a person. Unlike PCA based on a whole image pattern, Aw-SpPCA operates directly on its sub patterns partitioned from an original whole pattern and separately extracts features from them. Aw-SpPCA can adaptively compute the contributions of each part and a classification task in order to enhance the robustness to both expression and illumination variations. Experiments on single standard face with five types of facial expression database shows that the proposed method is competitive.

Keywords: Aw-SpPC, Expressoin Recognition, Face context, Face Detection, PCA

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Authors: J. K. Adedeji, M. O. Oyekanmi

Abstract:

This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: Biometric characters, facial recognition, neural network, OpenCV.

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Authors: Yetti Marlida , Rina Delfita , Neni Gusmanizar, Gita Ciptaan

Abstract:

Phytases are acid phosphatase enzymes, which efficiently cleave phosphate moieties from phytic acid, thereby generating myo-inositol and inorganic phosphate. Thirty four isolates of endophytic fungi to produce of phytases were isolated from leaf, stem and root fragments of soybean. Screening of 34 isolates of endophytic fungi identified the phytases produced by Rhizoctonia sp. and Fusarium verticillioides . The phytase production were the best induced by phytic acid and rice bran compared the others inducer in submerged fermentation medium used. The phytase produced by both Rhizoctonia sp. and F. verticillioides have pH optimum at 4.0 and 5.0 respectively. The characterization of phytase from Fusarium verticillioides showed that temperature optimum was 500C and stability until 600C, the pH optimum 5.0 and pH stability was 2.5 – 6.0, and substrate specificity were rice bran>soybean meal>corn> coconut cake, respectively.

Keywords: endophytic fungus, phytase, soybean, Rhizoctoniasp., Fusarium verticillioides,

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Authors: M.V.R.K Sarma, Krishna Saharan, Lalit Kumar, Ashwani Gautam, Avhijeet Kapoor, Nishant Srivastava, Vikram Sahai, V.S Bisaria

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The fluorescent pseudomonad strain R81 is a root colonizing rhizobacteria which promotes the growth of many plants by various mechanisms. Its broth containing siderophore (ironchelating compound) and 2,4- diacetyl phloroglucinol (DAPG) is used for preparing bioinoculant formulations for agronomical applications. Glycerol was found to be the best carbon source for improved biomass production. Splitting of nitrogen source to NH4Cl and urea had a stabilizing effect on pH during batch cultivation. Ltryptophan at 0.5 % in the medium increased the siderophore production to 850 mg/l. During batch cultivation of the strain in a bioreactor, a maximum of 4 g/l of dry cell mass, 1.8 g/l of siderophore and 20 mg/l of DAPG was achieved when glycerol was 15 g/l and C/N ratio was maintained at 12.5. In case of intermittent feeding of fresh medium during fed-batch cultivation, the dry cell mass was increased to 25 g/l with improved production of DAPG to 70 mg/l.

Keywords: Batch cultivation, Fed-batch cultivation, fluorescent pseudomonad, Metabolites

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Authors: Zohreh Sheikh Khozani, Wan Hanna Melini Wan Mohtar, Mojtaba Porhemmat

Abstract:

Prediction of wall shear stress in a rectangular channel, with non-homogeneous roughness distribution, was studied. Estimation of shear stress is an important subject in hydraulic engineering, since it affects the flow structure directly. In this study, the Genetic Algorithm Artificial (GAA) neural network is introduced as a hybrid methodology of the Artificial Neural Network (ANN) and modified Genetic Algorithm (GA) combination. This GAA method was employed to predict the wall shear stress. Various input combinations and transfer functions were considered to find the most appropriate GAA model. The results show that the proposed GAA method could predict the wall shear stress of open channels with high accuracy, by Root Mean Square Error (RMSE) of 0.064 in the test dataset. Thus, using GAA provides an accurate and practical simple-to-use equation.

Keywords: Artificial neural network, genetic algorithm, genetic programming, rectangular channel, shear stress.

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Authors: Gopalu Karunakaran, Matheswaran Jagathambal, Nguyen Van Minh, Evgeny Kolesnikov, Denis Kuznetsov

Abstract:

This work investigated the use of Beijerinckia indica extracellular extract for the synthesis of silver nanoparticles using AgNO₃. The formation of nanoparticles was confirmed by different methods, such as UV-Vis absorption spectroscopy, XRD, FTIR, EDX, and TEM analysis. The formation of silver nanoparticles (AgNPs) was confirmed by the change in color from light yellow to dark brown. The absorbance peak obtained at 430 nm confirmed the presence of silver nanoparticles. The XRD analysis showed the cubic crystalline phase of the synthesized nanoparticles. FTIR revealed the presence of groups that acts as stabilizing and reducing agents for silver nanoparticles formation. The synthesized silver nanoparticles were generally found to be spherical in shape with size ranging from 5 to 20 nm, as evident by TEM analysis. These nanoparticles were found to inhibit pathogenic bacterial strains. This work proved that the bacterial extract is a potential eco-friendly candidate for the synthesis of silver nanoparticles with promising antibacterial and antioxidant properties. 

Keywords: Antioxidant activity, antimicrobial activity, Beijerinckia indica, characterisation, extracellular extracts, silver nanoparticles.

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