Search results for: Weight improved particle swarm optimization method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11280

Search results for: Weight improved particle swarm optimization method

7710 Loss Function Optimization for CNN-Based Fingerprint Anti-Spoofing

Authors: Yehjune Heo

Abstract:

As biometric systems become widely deployed, the security of identification systems can be easily attacked by various spoof materials. This paper contributes to finding a reliable and practical anti-spoofing method using Convolutional Neural Networks (CNNs) based on the types of loss functions and optimizers. The types of CNNs used in this paper include AlexNet, VGGNet, and ResNet. By using various loss functions including Cross-Entropy, Center Loss, Cosine Proximity, and Hinge Loss, and various loss optimizers which include Adam, SGD, RMSProp, Adadelta, Adagrad, and Nadam, we obtained significant performance changes. We realize that choosing the correct loss function for each model is crucial since different loss functions lead to different errors on the same evaluation. By using a subset of the Livdet 2017 database, we validate our approach to compare the generalization power. It is important to note that we use a subset of LiveDet and the database is the same across all training and testing for each model. This way, we can compare the performance, in terms of generalization, for the unseen data across all different models. The best CNN (AlexNet) with the appropriate loss function and optimizers result in more than 3% of performance gain over the other CNN models with the default loss function and optimizer. In addition to the highest generalization performance, this paper also contains the models with high accuracy associated with parameters and mean average error rates to find the model that consumes the least memory and computation time for training and testing. Although AlexNet has less complexity over other CNN models, it is proven to be very efficient. For practical anti-spoofing systems, the deployed version should use a small amount of memory and should run very fast with high anti-spoofing performance. For our deployed version on smartphones, additional processing steps, such as quantization and pruning algorithms, have been applied in our final model.

Keywords: Anti-spoofing, CNN, fingerprint recognition, loss function, optimizer.

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7709 Local Curvelet Based Classification Using Linear Discriminant Analysis for Face Recognition

Authors: Mohammed Rziza, Mohamed El Aroussi, Mohammed El Hassouni, Sanaa Ghouzali, Driss Aboutajdine

Abstract:

In this paper, an efficient local appearance feature extraction method based the multi-resolution Curvelet transform is proposed in order to further enhance the performance of the well known Linear Discriminant Analysis(LDA) method when applied to face recognition. Each face is described by a subset of band filtered images containing block-based Curvelet coefficients. These coefficients characterize the face texture and a set of simple statistical measures allows us to form compact and meaningful feature vectors. The proposed method is compared with some related feature extraction methods such as Principal component analysis (PCA), as well as Linear Discriminant Analysis LDA, and independent component Analysis (ICA). Two different muti-resolution transforms, Wavelet (DWT) and Contourlet, were also compared against the Block Based Curvelet-LDA algorithm. Experimental results on ORL, YALE and FERET face databases convince us that the proposed method provides a better representation of the class information and obtains much higher recognition accuracies.

Keywords: Curvelet, Linear Discriminant Analysis (LDA) , Contourlet, Discreet Wavelet Transform, DWT, Block-based analysis, face recognition (FR).

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7708 A Monte Carlo Method to Data Stream Analysis

Authors: Kittisak Kerdprasop, Nittaya Kerdprasop, Pairote Sattayatham

Abstract:

Data stream analysis is the process of computing various summaries and derived values from large amounts of data which are continuously generated at a rapid rate. The nature of a stream does not allow a revisit on each data element. Furthermore, data processing must be fast to produce timely analysis results. These requirements impose constraints on the design of the algorithms to balance correctness against timely responses. Several techniques have been proposed over the past few years to address these challenges. These techniques can be categorized as either dataoriented or task-oriented. The data-oriented approach analyzes a subset of data or a smaller transformed representation, whereas taskoriented scheme solves the problem directly via approximation techniques. We propose a hybrid approach to tackle the data stream analysis problem. The data stream has been both statistically transformed to a smaller size and computationally approximated its characteristics. We adopt a Monte Carlo method in the approximation step. The data reduction has been performed horizontally and vertically through our EMR sampling method. The proposed method is analyzed by a series of experiments. We apply our algorithm on clustering and classification tasks to evaluate the utility of our approach.

Keywords: Data Stream, Monte Carlo, Sampling, DensityEstimation.

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7707 Multiscale Blind Image Restoration with a New Method

Authors: Alireza Mallahzadeh, Hamid Dehghani, Iman Elyasi

Abstract:

A new method, based on the normal shrink and modified version of Katssagelous and Lay, is proposed for multiscale blind image restoration. The method deals with the noise and blur in the images. It is shown that the normal shrink gives the highest S/N (signal to noise ratio) for image denoising process. The multiscale blind image restoration is divided in two sections. The first part of this paper proposes normal shrink for image denoising and the second part of paper proposes modified version of katssagelous and Lay for blur estimation and the combination of both methods to reach a multiscale blind image restoration.

Keywords: Multiscale blind image restoration, image denoising, blur estimation.

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7706 On Identity Disclosure Risk Measurement for Shared Microdata

Authors: M. N. Huda, S. Yamada, N. Sonehara

Abstract:

Probability-based identity disclosure risk measurement may give the same overall risk for different anonymization strategy of the same dataset. Some entities in the anonymous dataset may have higher identification risks than the others. Individuals are more concerned about higher risks than the average and are more interested to know if they have a possibility of being under higher risk. A notation of overall risk in the above measurement method doesn-t indicate whether some of the involved entities have higher identity disclosure risk than the others. In this paper, we have introduced an identity disclosure risk measurement method that not only implies overall risk, but also indicates whether some of the members have higher risk than the others. The proposed method quantifies the overall risk based on the individual risk values, the percentage of the records that have a risk value higher than the average and how larger the higher risk values are compared to the average. We have analyzed the disclosure risks for different disclosure control techniques applied to original microdata and present the results.

Keywords: Anonymization, microdata, disclosure risk, privacy.

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7705 Positive Solutions for Three-Point Boundary Value Problems of Third-Order Nonlinear Singular Differential Equations in Banach Space

Authors: Li Xiguang

Abstract:

In this paper, by constructing a special set and utilizing fixed point index theory, we study the existence of solution for singular differential equation in Banach space, which improved and generalize the result of related paper.

Keywords: Banach space, cone, fixed point index, singular differential equation.

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7704 Effects of Roughness Elements on Heat Transfer during Natural Convection

Authors: M. Yousaf, S. Usman

Abstract:

The present study focused on the investigation of the effects of roughness elements on heat transfer during natural convection in a rectangular cavity using numerical technique. Roughness elements were introduced on the bottom hot wall with a normalized amplitude (A*/H) of 0.1. Thermal and hydrodynamic behaviors were studied using computational method based on Lattice Boltzmann method (LBM). Numerical studies were performed for a laminar flow in the range of Rayleigh number (Ra) from 103 to 106 for a rectangular cavity of aspect ratio (L/H) 2.0 with a fluid of Prandtl number (Pr) 1.0. The presence of the sinusoidal roughness elements caused a minimum to maximum decrease in the heat transfer as 7% to 17% respectively compared to smooth enclosure. The results are presented for mean Nusselt number (Nu), isotherms and streamlines.

Keywords: Natural convection, Rayleigh number, surface roughness, Nusselt number, Lattice Boltzmann Method.

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7703 The Effect of Geometry Dimensions on the Earthquake Response of the Finite Element Method

Authors: Morteza Jiryaei Sharahi

Abstract:

In this paper, the effect of width and height of the model on the earthquake response in the finite element method is discussed. For this purpose an earth dam as a soil structure under earthquake has been considered. Various dam-foundation models are analyzed by Plaxis, a finite element package for solving geotechnical problems. The results indicate considerable differences in the seismic responses.

Keywords: Geometry dimensions, finite element, earthquake

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7702 Copy-Move Image Forgery Detection in Virtual Electrostatic Field

Authors: Michael Zimba, Darlison Nyirenda

Abstract:

A novel copy-move image forgery, CMIF, detection method is proposed. The proposed method presents a new approach which relies on electrostatic field theory, EFT. Solely for the purpose of reducing the dimension of a suspicious image, the proposed algorithm firstly performs discrete wavelet transform, DWT, of the suspicious image and extracts only the approximation subband. The extracted subband is then bijectively mapped onto a virtual electrostatic field where concepts of EFT are utilized to extract robust features. The extracted features are invariant to additive noise, JPEG compression, and affine transformation. Finally, same affine transformation selection, SATS, a duplication verification method, is applied to detect duplicated regions. SATS is a better option than the common shift vector method because SATS is insensitive to affine transformation. Consequently, the proposed CMIF algorithm is not only fast but also more robust to attacks compared to the existing related CMIF algorithms. The experimental results show high detection rates, as high as 100% in some cases.

Keywords: Affine transformation, Radix sort, SATS, Virtual electrostatic field.

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7701 Rough Set Based Intelligent Welding Quality Classification

Authors: L. Tao, T. J. Sun, Z. H. Li

Abstract:

The knowledge base of welding defect recognition is essentially incomplete. This characteristic determines that the recognition results do not reflect the actual situation. It also has a further influence on the classification of welding quality. This paper is concerned with the study of a rough set based method to reduce the influence and improve the classification accuracy. At first, a rough set model of welding quality intelligent classification has been built. Both condition and decision attributes have been specified. Later on, groups of the representative multiple compound defects have been chosen from the defect library and then classified correctly to form the decision table. Finally, the redundant information of the decision table has been reducted and the optimal decision rules have been reached. By this method, we are able to reclassify the misclassified defects to the right quality level. Compared with the ordinary ones, this method has higher accuracy and better robustness.

Keywords: intelligent decision, rough set, welding defects, welding quality level

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7700 Semi-Automatic Artifact Rejection Procedure Based on Kurtosis, Renyi's Entropy and Independent Component Scalp Maps

Authors: Antonino Greco, Nadia Mammone, Francesco Carlo Morabito, Mario Versaci

Abstract:

Artifact rejection plays a key role in many signal processing applications. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Our aim is to automatically remove the artifacts, in particular from the Electroencephalographic (EEG) recordings. A technique for the automatic artifact rejection, based on the Independent Component Analysis (ICA) for the artifact extraction and on some high order statistics such as kurtosis and Shannon-s entropy, was proposed some years ago in literature. In this paper we try to enhance this technique proposing a new method based on the Renyi-s entropy. The performance of our method was tested and compared to the performance of the method in literature and the former proved to outperform the latter.

Keywords: Artifact, EEG, Renyi's entropy, kurtosis, independent component analysis.

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7699 A Numerical Algorithm for Positive Solutions of Concave and Convex Elliptic Equation on R2

Authors: Hailong Zhu, Zhaoxiang Li

Abstract:

In this paper we investigate numerically positive solutions of the equation -Δu = λuq+up with Dirichlet boundary condition in a boundary domain ╬® for λ > 0 and 0 < q < 1 < p < 2*, we will compute and visualize the range of λ, this problem achieves a numerical solution.

Keywords: positive solutions, concave-convex, sub-super solution method, pseudo arclength method.

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7698 Evidence Theory Enabled Quickest Change Detection Using Big Time-Series Data from Internet of Things

Authors: Hossein Jafari, Xiangfang Li, Lijun Qian, Alexander Aved, Timothy Kroecker

Abstract:

Traditionally in sensor networks and recently in the Internet of Things, numerous heterogeneous sensors are deployed in distributed manner to monitor a phenomenon that often can be model by an underlying stochastic process. The big time-series data collected by the sensors must be analyzed to detect change in the stochastic process as quickly as possible with tolerable false alarm rate. However, sensors may have different accuracy and sensitivity range, and they decay along time. As a result, the big time-series data collected by the sensors will contain uncertainties and sometimes they are conflicting. In this study, we present a framework to take advantage of Evidence Theory (a.k.a. Dempster-Shafer and Dezert-Smarandache Theories) capabilities of representing and managing uncertainty and conflict to fast change detection and effectively deal with complementary hypotheses. Specifically, Kullback-Leibler divergence is used as the similarity metric to calculate the distances between the estimated current distribution with the pre- and post-change distributions. Then mass functions are calculated and related combination rules are applied to combine the mass values among all sensors. Furthermore, we applied the method to estimate the minimum number of sensors needed to combine, so computational efficiency could be improved. Cumulative sum test is then applied on the ratio of pignistic probability to detect and declare the change for decision making purpose. Simulation results using both synthetic data and real data from experimental setup demonstrate the effectiveness of the presented schemes.

Keywords: CUSUM, evidence theory, KL divergence, quickest change detection, time series data.

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7697 A TFETI Domain Decompositon Solver for Von Mises Elastoplasticity Model with Combination of Linear Isotropic-Kinematic Hardening

Authors: Martin Cermak, Stanislav Sysala

Abstract:

In this paper we present the efficient parallel implementation of elastoplastic problems based on the TFETI (Total Finite Element Tearing and Interconnecting) domain decomposition method. This approach allow us to use parallel solution and compute this nonlinear problem on the supercomputers and decrease the solution time and compute problems with millions of DOFs. In our approach we consider an associated elastoplastic model with the von Mises plastic criterion and the combination of linear isotropic-kinematic hardening law. This model is discretized by the implicit Euler method in time and by the finite element method in space. We consider the system of nonlinear equations with a strongly semismooth and strongly monotone operator. The semismooth Newton method is applied to solve this nonlinear system. Corresponding linearized problems arising in the Newton iterations are solved in parallel by the above mentioned TFETI. The implementation of this problem is realized in our in-house MatSol packages developed in MatLab.

Keywords: Isotropic-kinematic hardening, TFETI, domain decomposition, parallel solution.

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7696 The Solution of the Direct Problem of Electrical Prospecting with Direct Current under Conditions of Ground Surface Relief

Authors: Balgaisha Mukanova, Tolkyn Mirgalikyzy

Abstract:

Theory of interpretation of electromagnetic fields studied in the electrical prospecting with direct current is mainly developed for the case of a horizontal surface observation. However in practice we often have to work in difficult terrain surface. Conducting interpretation without the influence of topography can cause non-existent anomalies on sections. This raises the problem of studying the impact of different shapes of ground surface relief on the results of electrical prospecting's research. This research examines the numerical solutions of the direct problem of electrical prospecting for two-dimensional and three-dimensional media, taking into account the terrain. The problem is solved using the method of integral equations. The density of secondary currents on the relief surface is obtained.

Keywords: Ground surface relief, method of integral equations, numerical method.

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7695 The Use of Process-Oriented Methods of Calculation to Determine the Costs of Logistics Processes

Authors: Tomas Cechura, Michal Simon

Abstract:

The aim of this paper is to create a proposal for determining the costs of logistics processes by using process-oriented calculation methods. The traditional approach is that logistics costs are part of manufacturing overhead which is usually calculated as a percentage surcharge. Therefore in the traditional approach it is not obvious where and in which activities costs were incurred. So it is impossible to trace logistics costs to products. Our point of view is trying to fix or at least improve this issue. Another benefit of applying the process approach is identification of logistics processes which are otherwise part of manufacturing overhead. In the first part this paper describes the development of process-oriented methods over time. The next part shows the possibility of implementing the process-oriented method called Prozesskostenrechnung to logistics processes. The conclusion summarizes advantages and disadvantages of using this method in logistics.

Keywords: Cost, logistics, calculation, process-oriented method.

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7694 Nonlinear Estimation Model for Rail Track Deterioration

Authors: M. Karimpour, L. Hitihamillage, N. Elkhoury, S. Moridpour, R. Hesami

Abstract:

Rail transport authorities around the world have been facing a significant challenge when predicting rail infrastructure maintenance work for a long period of time. Generally, maintenance monitoring and prediction is conducted manually. With the restrictions in economy, the rail transport authorities are in pursuit of improved modern methods, which can provide precise prediction of rail maintenance time and location. The expectation from such a method is to develop models to minimize the human error that is strongly related to manual prediction. Such models will help them in understanding how the track degradation occurs overtime under the change in different conditions (e.g. rail load, rail type, rail profile). They need a well-structured technique to identify the precise time that rail tracks fail in order to minimize the maintenance cost/time and secure the vehicles. The rail track characteristics that have been collected over the years will be used in developing rail track degradation prediction models. Since these data have been collected in large volumes and the data collection is done both electronically and manually, it is possible to have some errors. Sometimes these errors make it impossible to use them in prediction model development. This is one of the major drawbacks in rail track degradation prediction. An accurate model can play a key role in the estimation of the long-term behavior of rail tracks. Accurate models increase the track safety and decrease the cost of maintenance in long term. In this research, a short review of rail track degradation prediction models has been discussed before estimating rail track degradation for the curve sections of Melbourne tram track system using Adaptive Network-based Fuzzy Inference System (ANFIS) model.

Keywords: ANFIS, MGT, Prediction modeling, rail track degradation.

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7693 A Stereo Vision System for Top View Book Scanners

Authors: Erik Lilienblum, Robert Niese, Bernd Michaelis

Abstract:

This paper proposes a novel stereo vision technique for top view book scanners which provide us with dense 3d point clouds of page surfaces. This is a precondition to dewarp bound volumes independent of 2d information on the page. Our method is based on algorithms, which normally require the projection of pattern sequences with structured light. We use image sequences of the moving stripe lighting of the top view scanner instead of an additional light projection. Thus the stereo vision setup is simplified without losing measurement accuracy. Furthermore we improve a surface model dewarping method through introducing a difference vector based on real measurements. Although our proposed method is hardly expensive neither in calculation time nor in hardware requirements we present good dewarping results even for difficult examples.

Keywords: stereo vision, 3d surface reconstruction, dewarpingdocuments, book scanner

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7692 Unequal Error Protection for Region of Interest with Embedded Zerotree Wavelet

Authors: T. Hirner, J. Polec

Abstract:

This paper describes a new method of unequal error protection (UEP) for region of interest (ROI) with embedded zerotree wavelet algorithm (EZW). ROI technique is important in applications with different parts of importance. In ROI coding, a chosen ROI is encoded with higher quality than the background (BG). Unequal error protection of image is provided by different coding techniques. In our proposed method, image is divided into two parts (ROI, BG) that consist of more important bytes (MIB) and less important bytes (LIB). The experimental results verify effectiveness of the design. The results of our method demonstrate the comparison of the unequal error protection (UEP) of image transmission with defined ROI and the equal error protection (EEP) over multiple noisy channels.

Keywords: embedded zerotree wavelet (EZW), equal error protection (EEP), region of interest (ROI), RS code, unequal error protection (UEP)

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7691 A Novel and Green Approach to Produce Nano- Porous Materials Zeolite A and MCM-41 from Coal Fly Ash and their Applications in Environmental Protection

Authors: K. S. Hui, K. N. Hui, Seong Kon Lee

Abstract:

Zeolite A and MCM-41 have extensive applications in basic science, petrochemical science, energy conservation/storage, medicine, chemical sensor, air purification, environmentally benign composite structure and waste remediation. However, the use of zeolite A and MCM-41 in these areas, especially environmental remediation, are restricted due to prohibitive production cost. Efficient recycling of and resource recovery from coal fly ash has been a major topic of current international research interest, aimed at achieving sustainable development of human society from the viewpoints of energy, economy, and environmental strategy. This project reported an original, novel, green and fast methods to produce nano-porous zeolite A and MCM-41 materials from coal fly ash. For zeolite A, this novel production method allows a reduction by half of the total production time while maintaining a high degree of crystallinity of zeolite A which exists in a narrower particle size distribution. For MCM-41, this remarkably green approach, being an environmentally friendly process and reducing generation of toxic waste, can produce pure and long-range ordered MCM-41 materials from coal fly ash. This approach took 24 h at 25 oC to produce 9 g of MCM-41 materials from 30 g of the coal fly ash, which is the shortest time and lowest reaction temperature required to produce pure and ordered MCM-41 materials (having the largest internal surface area) compared to the values reported in the literature. Performance evaluation of the produced zeolite A and MCM-41 materials in wastewater treatment and air pollution control were reported. The residual fly ash was also converted to zeolite Na-P1 which showed good performance in removal of multi-metal ions in wastewater. In wastewater treatment, compared to commercial-grade zeolite A, adsorbents produced from coal fly ash were effective in removing multi heavy metal ions in water and could be an alternative material for treatment of wastewater. In methane emission abatement, the zeolite A (produced from coal fly ash) achieved similar methane removal efficiency compared to the zeolite A prepared from pure chemicals. This report provides the guidance for production of zeolite A and MCM-41 from coal fly ash by a cost-effective approach which opens potential applications of these materials in environmental industry. Finally, environmental and economic aspects of production of zeolite A and MCM-41 from coal fly ash were discussed.

Keywords: Metal ions, waste water, methane, volatile organic compounds

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7690 A New Method to Enhance Contrast of Electron Micrograph of Rat Tissues Sections

Authors: Lise P. Labéjof, Raiza S. P. Bizerra, Galileu B. Costa, Thaísa B. dos Santos

Abstract:

This report presents an alternative technique of application of contrast agent in vivo, i.e. before sampling. By this new method the electron micrograph of tissue sections have an acceptable contrast compared to other methods and present no artifact of precipitation on sections. Another advantage is that a small amount of contrast is needed to get a good result given that most of them are expensive and extremely toxic.

Keywords: Image quality, Microscopy research, Staining technique, Ultrathin section.

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7689 Usability in E-Commerce Websites: Results of Eye Tracking Evaluations

Authors: Beste Kaysı, Yasemin Topaloğlu

Abstract:

Usability is one of the most important quality attributes for web-based information systems. Specifically, for e-commerce applications, usability becomes more prominent. In this study, we aimed to explore the features that experienced users seek in e-commerce applications. We used eye tracking method in evaluations. Eye movement data are obtained from the eye-tracking method and analyzed based on task completion time, number of fixations, as well as heat map and gaze plot measures. The results of the analysis show that the eye movements of participants' are too static in certain areas and their areas of interest are scattered in many different places. It has been determined that this causes users to fail to complete their transactions. According to the findings, we outlined the issues to improve the usability of e-commerce websites. Then we propose solutions to identify the issues. In this way, it is expected that e-commerce sites will be developed which will make experienced users more satisfied.

Keywords: E-commerce websites, eye tracking method, usability, website evaluations.

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7688 Detection of Clipped Fragments in Speech Signals

Authors: Sergei Aleinik, Yuri Matveev

Abstract:

In this paper a novel method for the detection of  clipping in speech signals is described. It is shown that the new  method has better performance than known clipping detection  methods, is easy to implement, and is robust to changes in signal  amplitude, size of data, etc. Statistical simulation results are  presented.

 

Keywords: Clipping, clipped signal, speech signal processing.

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7687 Production of Cellulases by Aspergillus Heteromorphus from Wheat Straw under Submerged Fermentation

Authors: Anita Singh, Namita Singh, Narsi R. Bishnoi

Abstract:

To investigate the production of cellulases from Aspergillus heteromorphus, submerged fermentation was performed using wheat straw as substrate. Optimization of saccharification conditions like pH, temperature and time were studied. Highest reducing sugar was released on 5th day at 5 pH, 30° C temperature. When A. heteromorphous was grown on wheat straw in submerged fermentation after 5 days incubation at 30 ° C, 3.2 IU/ml and 83 IU/ml, filter paper activity and CMCase activity respectively.

Keywords: Aspergillus heteromorphus, Wheat Straw, Submerged Fermentation, Production of Cellulases

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7686 Structure-Activity Relationship of Gold Catalysts on Alumina Supported Cu-Ce Oxides for CO and Volatile Organic Compound Oxidation

Authors: Tatyana T. Tabakova, Elitsa N. Kolentsova, Dimitar Y. Dimitrov, Krasimir I. Ivanov, Yordanka G. Karakirova, Petya Cv. Petrova, Georgi V. Avdeev

Abstract:

The catalytic oxidation of CO and volatile organic compounds (VOCs) is considered as one of the most efficient ways to reduce harmful emissions from various chemical industries. The effectiveness of gold-based catalysts for many reactions of environmental significance was proven during the past three decades. The aim of this work was to combine the favorable features of Au and Cu-Ce mixed oxides in the design of new catalytic materials of improved efficiency and economic viability for removal of air pollutants in waste gases from formaldehyde production. Supported oxides of copper and cerium with Cu: Ce molar ratio 2:1 and 1:5 were prepared by wet impregnation of g-alumina. Gold (2 wt.%) catalysts were synthesized by a deposition-precipitation method. Catalysts characterization was carried out by texture measurements, powder X-ray diffraction, temperature programmed reduction and electron paramagnetic resonance spectroscopy. The catalytic activity in the oxidation of CO, CH3OH and (CH3)2O was measured using continuous flow equipment with fixed bed reactor. Both Cu-Ce/alumina samples demonstrated similar catalytic behavior. The addition of gold caused significant enhancement of CO and methanol oxidation activity (100 % degree of CO and CH3OH conversion at about 60 and 140 oC, respectively). The composition of Cu-Ce mixed oxides affected the performance of gold-based samples considerably. Gold catalyst on Cu-Ce/γ-Al2O3 1:5 exhibited higher activity for CO and CH3OH oxidation in comparison with Au on Cu-Ce/γ-Al2O3 2:1. The better performance of Au/Cu-Ce 1:5 was related to the availability of highly dispersed gold particles and copper oxide clusters in close contact with ceria.

Keywords: CO and VOCs oxidation, copper oxide, ceria, gold catalysts.

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7685 A Hybrid Feature Selection by Resampling, Chi squared and Consistency Evaluation Techniques

Authors: Amir-Massoud Bidgoli, Mehdi Naseri Parsa

Abstract:

In this paper a combined feature selection method is proposed which takes advantages of sample domain filtering, resampling and feature subset evaluation methods to reduce dimensions of huge datasets and select reliable features. This method utilizes both feature space and sample domain to improve the process of feature selection and uses a combination of Chi squared with Consistency attribute evaluation methods to seek reliable features. This method consists of two phases. The first phase filters and resamples the sample domain and the second phase adopts a hybrid procedure to find the optimal feature space by applying Chi squared, Consistency subset evaluation methods and genetic search. Experiments on various sized datasets from UCI Repository of Machine Learning databases show that the performance of five classifiers (Naïve Bayes, Logistic, Multilayer Perceptron, Best First Decision Tree and JRIP) improves simultaneously and the classification error for these classifiers decreases considerably. The experiments also show that this method outperforms other feature selection methods.

Keywords: feature selection, resampling, reliable features, Consistency Subset Evaluation.

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7684 Comparative Usability Study of the Websites of Top Universities in Three Continents: A Case Study of the University of Cape Town, Oxford University, and Harvard University

Authors: Stephen Akuma, Racheal Aluma, Abraham Undu

Abstract:

Academic websites play an important role in promoting education for all. They allow universities to provide users with digital academic services to save time and resources. A university website is not only a cost-effective and timely way to communicate with a variety of stakeholders, such as students, faculty, and visitors, but it is also a vehicle for the university to shape its image. The quality of a website is a major factor that universities consider in cyberspace. Potential students can easily apply to universities where the website provides useful and clear information. This has made the usability of websites an important area in meeting the needs and expectations of website users. In this paper, a comparative usability study of the University of Cape Town, Oxford University, and Harvard University academic websites (http://www.uct.ac.za/, https://www.ox.ac.uk/, and https://www.harvard.edu/) was carried out. The proactive user feedback technique was adopted for the comparative usability assessment of the aforementioned universities. The method was used by the researchers to collect and log records from the participants in real time. The result shows that the average dwell time on the websites of Harvard University, Oxford University, and Cape Town University in seconds for the three tasks are 51.58, 33.28, and 54.82 respectively. The System Usability Scale (SUS) scores for Harvard, Oxford, and the University of Cape Town are 49.81, 69.43, and 54.14 respectively. The result of the Analysis of Variance on the dwell time data shows a significant difference (p = .009) on the three websites. Our findings show that Oxford University has the most suitable website in terms of usability factors and other metrics than the other websites investigated. Practical implications are highlighted, and recommendations for improved website usability are suggested.

Keywords: Usability factors, user feedback, university websites, University of Cape Town, Harvard University, Oxford University.

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7683 Circuit Models for Conducted Susceptibility Analyses of Multiconductor Shielded Cables

Authors: Saih Mohamed, Rouijaa Hicham, Ghammaz Abdelilah

Abstract:

This paper presents circuit models to analyze the conducted susceptibility of multiconductor shielded cables in frequency domains using Branin’s method, which is referred to as the method of characteristics. These models, which can be used directly in the time and frequency domains, take into account the presence of both the transfer impedance and admittance. The conducted susceptibility is studied by using an injection current on the cable shield as the source. Two examples are studied; a coaxial shielded cable and shielded cables with two parallel wires (i.e., twinax cables). This shield has an asymmetry (one slot on the side). Results obtained by these models are in good agreement with those obtained by other methods.

Keywords: Circuit models, multiconductor shielded cables, Branin’s method, coaxial shielded cable, twinax cables.

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7682 Making Businesses Work Smarter with Mobile Business Intelligence

Authors: Zeljko Panian

Abstract:

Through the course of this paper we outline how mobile Business Intelligence (m-BI) can help businesses to work smarter and to improve their agility. When we analyze the industry from the usage perspective or how interaction with the enterprise BI system happens via mobile devices, we may easily understand that there are two major types of mobile BI: passive and active. Active mobile BI gives provisions for users to interact with the BI systems on-the-fly. Active mobile business intelligence often works as a combination of both “push and pull" techniques. Some mistakes were done in the up-to-day progress of mobile technologies and mobile BI, as well as some problems that still have to be resolved. We discussed in the paper rather broadly.

Keywords: Business intelligence, mobile business intelligence, business agility, mobile technologies, optimization

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7681 Effect of Concrete Nonlinear Parameters on the Seismic Response of Concrete Gravity Dams

Authors: Z. Heirany, M. Ghaemian

Abstract:

Behavior of dams against the seismic loads has been studied by many researchers. Most of them proposed new numerical methods to investigate the dam safety. In this paper, to study the effect of nonlinear parameters of concrete in gravity dams, a twodimensional approach was used including the finite element method, staggered method and smeared crack approach. Effective parameters in the models are physical properties of concrete such as modulus of elasticity, tensile strength and specific fracture energy. Two different models were used in foundation (mass-less and massed) in order to determine the seismic response of concrete gravity dams. Results show that when the nonlinear analysis includes the dam- foundation interaction, the foundation-s mass, flexibility and radiation damping are important in gravity dam-s response.

Keywords: Numerical methods; concrete gravity dams; finiteelement method; boundary condition

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