Search results for: like function

Authors: Hyunchul Ahn, William X. S. Wong

Abstract:

Corporate credit rating prediction is one of the most important topics, which has been studied by researchers in the last decade. Over the last decade, researchers are pushing the limit to enhance the exactness of the corporate credit rating prediction model by applying several data-driven tools including statistical and artificial intelligence methods. Among them, multiclass support vector machine (MSVM) has been widely applied due to its good predictability. However, heuristics, for example, parameters of a kernel function, appropriate feature and instance subset, has become the main reason for the critics on MSVM, as they have dictate the MSVM architectural variables. This study presents a hybrid MSVM model that is intended to optimize all the parameter such as feature selection, instance selection, and kernel parameter. Our model adopts genetic algorithm (GA) to simultaneously optimize multiple heterogeneous design factors of MSVM.

Keywords: corporate credit rating prediction, Feature selection, genetic algorithms, instance selection, multiclass support vector machines

Procedia PDF Downloads 295

Authors: Chen Zheng, Lin Zhou, Bao Xie, Xiao Du, Nianbin Shao

Abstract:

Power generated by large-scale photovoltaic plants (LSPVPs) is usually transmitted to the grid through several transformers and long distance overhead lines. Impedance of transformers and transmission lines results in complex interactions between the plant and the grid and among different inverters. In accordance with the topological structure of LSPV in reality, an equivalent model containing different inverters was built and then interactions between the plant and the grid and among different inverters were studied. Based on the vector composition principle of voltage at the point of common coupling (PCC), the mathematic function of PCC voltage in regard to the total power and grid impedance was deduced, from which the uttermost total power to guarantee the system stable is obtained. Taking the influence of different inverters numbers and the length of transmission lines to the system stability into account, the stability criterion of LSPV containing different inverters was derived. The result of simulation validated the theory analysis in the paper.

Keywords: LSPVPs, stability analysis, grid impedance, different types of inverter, PCC voltage

Procedia PDF Downloads 311

Authors: E. L. Queiroz, S. M. A. Souza, R. T. S. Santos

Abstract:

The cereal bars have emerged as a healthy alternative in the food sector, by presenting a remarkable functional appeal, being a product of high nutritional value. Cereals have an important function in feeding because they have features that particularize them as their variety, smooth flavour and aroma and easy digestion and absorption in the body. Brazil is the largest producer of cassava in the world, and the flour produced from this raw material is a source of nutrients for much of the low-income population, however it is little explored industrially. The northeast region of Brazil has great potential for honey production, which is a source of vitamins, proteins, minerals and organic acids but it is much used as a medicine. Aiming to combine the production of healthy food with the sustainable utilization and enhancement of family farming products, was created a cereal bar using regional raw materials of desirable nutritional characteristics: honey, umbu pulp and cassava flour. The cereal bar was characterized by physicochemical analyzes quantifying the content of lipids, proteins, moisture and ashes, microbiological and sensory evaluation showed that the cereal bar is a safe, and nutritious food with good sensory properties.

Keywords: cassava flour, cereal bar, honey, insoluble fibre

Procedia PDF Downloads 473

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo Ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring. SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, polarimetric SAR image, convolutional neural network, deep learnig, deep neural network

Procedia PDF Downloads 73

Authors: Felix Baumann, Aleksandar Milutinovic, Dieter Roller

Abstract:

Up to this point business process management projects in general and business process modelling projects in particular could not rely on a practical and scientifically validated method to estimate cost and effort. Especially the model development phase is not covered by a cost estimation method or model. Further phases of business process modelling starting with implementation are covered by initial solutions which are discussed in the literature. This article proposes a method of filling this gap by deriving a cost estimation method from available methods in similar domains namely software development or software engineering. Software development is regarded as closely similar to process modelling as we show. After the proposition of this method different ideas for further analysis and validation of the method are proposed. We derive this method from COCOMO II and Function Point which are established methods of effort estimation in the domain of software development. For this we lay out similarities of the software development rocess and the process of process modelling which is a phase of the Business Process Management life-cycle.

Keywords: COCOMO II, busines process modeling, cost estimation method, BPM COCOMO

Procedia PDF Downloads 444

Authors: Guillaume Craveur

Abstract:

The work presented here shows a study on several parameters identified as influencing dwell times for trains. Three kinds of rolling stocks are studied for this project and the parameters presented are the number of passengers, the allocation of passengers, their priorities, the platform station height, the door width and the train design. In order to make this study, a lot of records have been done in several stations in Paris (France). Then, in order to study these parameters, numerical simulations are completed. The goal is to quantify the impact of each parameter on the dwelling times. For example, this study highlights the impact of platform height and the presence of steps between the platform and the train. Three types of station platforms are concerned by this study : ‘optimum’ station platform which is 920 mm high, standard station platform which is 550 mm high, and high station platform which is 1150 mm high and different kinds of steps exist in order to fill these gaps. To conclude, this study shows the impact of these parameters on dwell times and their impact in function of the size of population.

Keywords: dwell times, numerical tools, rolling stock, platforms

Procedia PDF Downloads 337

Authors: Sandeep Kumar, Naveen Gupta

Abstract:

Terahertz (THz) generation has been investigated by beating two cosh-Gaussian laser beams of the same amplitude but different wavenumbers and frequencies through rippled collisionless plasma. The ponderomotive force is operative which is induced due to the intensity gradient of the laser beam over the cross-section area of the wavefront. The electrons evacuate towards a low-intensity regime, which modifies the dielectric function of the medium and results in cross focusing of cosh-Gaussian laser beams. The evolution of spot size of laser beams has been studied by solving nonlinear Schrodinger wave equation (NLSE) with variational technique. The laser beams impart oscillations to electrons which are enhanced with ripple density. The nonlinear oscillatory motion of electrons gives rise to a nonlinear current density driving THz radiation. It has been observed that the periodicity of the ripple density helps to enhance the THz radiation.

Keywords: rippled collisionless plasma, cosh-gaussian laser beam, ponderomotive force, variational technique, nonlinear current density

Procedia PDF Downloads 204

Authors: M. Najafi

Abstract:

In the present paper, a large turbo-generator shaft train including a heavy-duty gas turbine engine, a coupling, and a generator is established. The method of analysis is based on finite element simplified model for lateral and torsional vibration calculation. The basic elements of rotor are the shafts and the disks which are represented as circular cross section flexible beams and rigid body elements, respectively. For more accurate results, the gyroscopic effect and bearing dynamics coefficients and function of rotation are taken into account, and for the influence of shear effect, rotor has been modeled in the form of Timoshenko beam. Lateral critical speeds, critical speed map, damped mode shapes, Campbell diagram, zones of instability, amplitudes, phase angles response due to synchronous forces of excitation and amplification factor are calculated. Also, in the present paper, the effect of imbalanced rotor and effects of changing in internal force and temperature are studied.

Keywords: rotor dynamic analysis, finite element method, shaft train, Campbell diagram

Procedia PDF Downloads 137

Authors: Tarek M. Alguhane, Ayman H. Khalil, Nour M. Fayed, Ayman M. Ismail

Abstract:

An existing RC building in Madinah is seismically evaluated with and without infill wall. Four model systems have been considered i. e. model I (no infill), model IIA (strut infill-update from field test), model IIB (strut infill- ASCE/SEI 41) and model IIC (strut infill-Soft storey-ASCE/SEI 41). Three dimensional pushover analyses have been carried out using SAP 2000 software incorporating inelastic material behavior for concrete, steel and infill walls. Infill wall has been modeled as equivalent strut according to suggested equation matching field test measurements and to the ASCE/SEI 41 equation. The effect of building modeling on the performance point as well as capacity and demand spectra due to EQ design spectrum function in Madinah area has been investigated. The response modification factor (R) for the 5 story RC building is evaluated from capacity and demand spectra (ATC-40) for the studied models. The results are summarized and discussed.

Keywords: infill wall, pushover analysis, response modification factor, seismic assessment

Procedia PDF Downloads 394

Authors: A. Mousavi, S. Sadegzadeh

Abstract:

In this research, the effect of non-thermal micro plasma with non-Maxwellian distribution function on the one dimensional plasma photonic crystals containing alternate plasma-dielectric layers, has been studied. By using Kronig Penny model, the dispersion relation of electromagnetic modes for such a periodic structure is obtained. In this study we take two plasma photonic crystals with different dielectric layers: the first one with Silicon monoxide named PPCI, and the second one with Tellurium dioxide named PPCII. The effects of the plasma layer thickness and the material of the dielectric layer on the plasma photonic crystal band gaps have been illustrated in the dispersion relation and the group velocity figures. Results revealed that in such a system, the non-thermal plasma exerts stronger limit on the wave’s propagation. In another word, for the non-thermal plasma photonic crystals (NPPC), there are two distinct regions in the dispersion plot. The upper region consists of alternate band gaps in such a way that both width and length of the bands decrease gradually as the band gaps order increases. Whereas in the lower region where v_ph > 20 c (for PPCI), waves will not be allowed to propagate.

Keywords: band gap, dispersion relation, non-thermal plasma, plasma photonic crystal

Procedia PDF Downloads 541

Authors: Abdelaziz Fellah, Allaoua Maamir

Abstract:

We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

Procedia PDF Downloads 389

Authors: M. S. Ahmed, F. A. Mohammad

Abstract:

The aim of this paper is to perform experimental modal analysis (EMA) of reinforced concrete (RC) square slabs. EMA is the process of determining the modal parameters (Natural Frequencies, damping factors, modal vectors) of a structure from a set of frequency response functions FRFs (curve fitting). Although experimental modal analysis (or modal testing) has grown steadily in popularity since the advent of the digital FFT spectrum analyzer in the early 1970’s, studying all members and materials using such method have not yet been well documented. Therefore, in this work, experimental tests were conducted on RC square specimens (0.6m x 0.6m with 40 mm). Experimental analysis is based on freely supported boundary condition. Moreover, impact testing as a fast and economical means of finding the modes of vibration of a structure was used during the experiments. In addition, Pico Scope 6 device and MATLAB software were used to acquire data, analyze and plot Frequency Response Function (FRF). The experimental natural frequencies which were extracted from measurements exhibit good agreement with analytical predictions. It is showed that EMA method can be usefully employed to perform the dynamic behavior of RC slabs.

Keywords: natural frequencies, mode shapes, modal analysis, RC slabs

Procedia PDF Downloads 409

Authors: Aisulu Tileukulova, Zhexebay Dauren

Abstract:

Radar plays an important role because it is widely used in civil and military fields. Target detection is one of the most important radar applications. The accuracy of detecting inconspicuous aerial objects in radar facilities is lower against the background of noise. Convolutional neural networks can be used to improve the recognition of this type of aerial object. The purpose of this work is to develop an algorithm for recognizing aerial objects using convolutional neural networks, as well as training a neural network. In this paper, the structure of a convolutional neural network (CNN) consists of different types of layers: 8 convolutional layers and 3 layers of a fully connected perceptron. ReLU is used as an activation function in convolutional layers, while the last layer uses softmax. It is necessary to form a data set for training a neural network in order to detect a target. We built a Confusion Matrix of the CNN model to measure the effectiveness of our model. The results showed that the accuracy when testing the model was 95.7%. Classification of echo signals using CNN shows high accuracy and significantly speeds up the process of predicting the target.

Keywords: radar, neural network, convolutional neural network, echo signals

Procedia PDF Downloads 356

Authors: Elif Kalkanli, Constantinos Soutis

Abstract:

The use of textile preform in the advanced fields including aerospace, automotive and marine has exponentially grown in recent years. These preforms offer excellent advantages such as being lightweight and low-cost, and also, their suitability for creating different fiber architectures with different materials whilst improved mechanical properties in certain aspects. In this study, a novel honeycomb core is developed by a 3Dweaving process. The assembly of the layers is achieved thanks to innovative weaving design. Polyester yarn is selected for the 3D woven honeycomb core (3DWHC). The core is used to manufacture a sandwich panel with 2x2 twill glass fiber composite face sheets. These 3DWHC sandwich panels will be tested in three-point bending. The in-plane and out-of-plane (through-the-thickness) mechanical response of the core will be examined as a function of cell size in addition to the flexural response of the sandwich panel. The failure mechanisms of the core and the sandwich skins will be reported in addition to flexural strength and stiffness. Possible engineering applications will be identified.

Keywords: 3D woven, assembly, failure modes, honeycomb sandwich panel

Procedia PDF Downloads 207

Authors: Sadegh Abedi, Ali Yaghoubi, Hamidreza Mashatzadegan

Abstract:

This paper proposes an approach to identify key processes required by an organization in the field of knowledge management and aligning them with organizational objectives. For this purpose, first, organization’s most important non-financial objectives which are impacted by knowledge management processes are identified and then, using a quality house, are linked with knowledge management processes which are regarded as technical elements. Using this method, processes that are in need of improvement and more attention are prioritized based on their significance. This means that if a process has more influence on organization’s objectives and is in a dire situation comparing to others, is prioritized for choice and improvement. In this research process dominance is considered to be an influential element in process ranking (in addition to communication matrix). This is the reason for utilizing DEA techniques for prioritizing processes in quality house. Results of implementing the method in Khuzestan steel company represents this method’s capability of identifying key processes that require improvements in organization’s knowledge management system.

Keywords: knowledge management, organizational performance, fuzzy data, envelopment analysis

Procedia PDF Downloads 420

Authors: Amir Hajian, Sepehr Damavandinejadmonfared

Abstract:

In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

Procedia PDF Downloads 367

Authors: Linda A. O’Higgins, Astrid Wingler, Jorge Oliveira

Abstract:

The growth of Chlorella vulgaris was characterized as a function of irradiance in a laboratory turbidostat (1 L) and compared to batch growth in sunlit modules (5–25 L) of the commercial Phytobag photobioreactor. The effects of variable sunlight and culture density were deconvoluted by a mathematical model. The analysis showed that algal growth was light-limited due to shading by external construction elements and due to light attenuation within the algal bags. The model was also used to predict maximum biomass productivity. The manipulative experiments and the model predictions were confronted with data from a production season of a 10m2 pilot-scale photobioreactor, Phytobag (10,000 L). The analysis confirmed light limitation in all three photobioreactors. An additional limitation of biomass productivity was caused by the nitrogen starvation that was used to induce lipid accumulation. Reduction of shading and separation of biomass and lipid production are proposed for future optimization.

Keywords: microalgae, batch cultivation, Chlorella vulgaris, Mathematical model, photobioreactor, scale-up

Procedia PDF Downloads 119

Authors: Abdorreza Rabiee, Shahla Mohammad Hoseini Mirzaei

Abstract:

The advantages of distributed generations (DGs) based on renewable energy sources (RESs) leads to high penetration level of DGs in distribution network. With incorporation of DGs in distribution systems, the system reliability and security, as well as voltage profile, is improved. However, the protection of such systems is still challenging. In this paper, at first, the related papers are reviewed and then a practical scheme is proposed for coordination of OCRs in distribution system with DGs. The coordination problem is formulated as a nonlinear programming (NLP) optimization problem with the object function of minimizing total operating time of OCRs. The proposed method is studied based on a simple test system. The optimization problem is solved by General Algebraic Modeling System (GAMS) to calculate the optimal time dial setting (TDS) and also pickup current setting of OCRs. The results show the effectiveness of the proposed method and its applicability.

Keywords: distributed generation, DG, distribution network, over current relay, OCR, protection coordination, pickup current, time dial setting, TDS

Procedia PDF Downloads 140

Authors: Hossein Aghababaei, Sergio Vitale, Giampaolo ferraioli

Abstract:

In the context of Synthetic Aperture Radar (SAR) data, polarization is an important source of information for Earth's surface monitoring . SAR Systems are often considered to transmit only one polarization. This constraint leads to either single or dual polarimetric SAR imaging modalities. Single polarimetric systems operate with a fixed single polarization of both transmitted and received electromagnetic (EM) waves, resulting in a single acquisition channel. Dual polarimetric systems, on the other hand, transmit in one fixed polarization and receive in two orthogonal polarizations, resulting in two acquisition channels. Dual polarimetric systems are obviously more informative than single polarimetric systems and are increasingly being used for a variety of remote sensing applications. In dual polarimetric systems, the choice of polarizations for the transmitter and the receiver is open. The choice of circular transmit polarization and coherent dual linear receive polarizations forms a special dual polarimetric system called hybrid polarimetry, which brings the properties of rotational invariance to geometrical orientations of features in the scene and optimizes the design of the radar in terms of reliability, mass, and power constraints. The complete characterization of target scattering, however, requires fully polarimetric data, which can be acquired with systems that transmit two orthogonal polarizations. This adds further complexity to data acquisition and shortens the coverage area or swath of fully polarimetric images compared to the swath of dual or hybrid polarimetric images. The search for solutions to augment dual polarimetric data to full polarimetric data will therefore take advantage of full characterization and exploitation of the backscattered field over a wider coverage with less system complexity. Several methods for reconstructing fully polarimetric images using hybrid polarimetric data can be found in the literature. Although the improvements achieved by the newly investigated and experimented reconstruction techniques are undeniable, the existing methods are, however, mostly based upon model assumptions (especially the assumption of reflectance symmetry), which may limit their reliability and applicability to vegetation and forest scenarios. To overcome the problems of these techniques, this paper proposes a new framework for reconstructing fully polarimetric information from hybrid polarimetric data. The framework uses Deep Learning solutions to augment hybrid polarimetric data without relying on model assumptions. A convolutional neural network (CNN) with a specific architecture and loss function is defined for this augmentation problem by focusing on different scattering properties of the polarimetric data. In particular, the method controls the CNN training process with respect to several characteristic features of polarimetric images defined by the combination of different terms in the cost or loss function. The proposed method is experimentally validated with real data sets and compared with a well-known and standard approach from the literature. From the experiments, the reconstruction performance of the proposed framework is superior to conventional reconstruction methods. The pseudo fully polarimetric data reconstructed by the proposed method also agree well with the actual fully polarimetric images acquired by radar systems, confirming the reliability and efficiency of the proposed method.

Keywords: SAR image, deep learning, convolutional neural network, deep neural network, SAR polarimetry

Procedia PDF Downloads 96

Authors: Lina Wu, Ye Li

Abstract:

An equivalent relation between a harmonic form and a closed co-closed form is established on a complete non-compact manifold. This equivalence has been generalized for a differential k-form ω from Lq spaces to non-Lq spaces when q=2 in the context of p-balanced growth where p=2. Especially for a simple differential k-form on a complete non-compact manifold, the equivalent relation has been verified with the extended scope of q for from finite q-energy in Lq spaces to infinite q-energy in non-Lq spaces when with 2-balanced growth. Generalized Hadamard Theorem, Cauchy-Schwarz Inequality, and Calculus skills including Integration by Parts as well as Convergent Series have been applied as estimation techniques to evaluate growth rates for a differential form. In particular, energy growth rates as indicated by an appropriate power range in a selected test function lead to a balance between a harmonic differential form and a closed co-closed differential form. Research ideas and computational methods in this paper could provide an innovative way in the study of broadening Lq spaces to non-Lq spaces with a wide variety of infinite energy growth for a differential form.

Keywords: closed forms, co-closed forms, harmonic forms, L^q spaces, p-balanced growth, simple differential k-forms

Procedia PDF Downloads 453

Authors: Ogechi Nzeagwu, Assumpta Osuagwu, Charlse Nkwoala

Abstract:

Malnutrition in infants due to poverty, poor feeding practices, and high cost of commercial complementary foods among others is a concern in developing countries. The study evaluated the proximate, vitamin and mineral compositions, antinutrients and functional properties, biochemical, haematological and sensory evaluation of complementary food made from sorghum, groundnut, crayfish and paw-paw flour blends using standard procedures. The blends were formulated on protein requirement of infants (18 g/day) using Nutrisurvey linear programming software in ratio of sorghum(S), groundnut(G), crayfish(C) and pawpaw(P) flours as 50:25:10:15(SGCP1), 60:20:10:10 (SGCP2), 60:15:15:10 (SGCP3) and 60:10:20:10 (SGCP4). Plain-pap (fermented maize flour)(TCF) and cerelac (commercial complementary food) served as basal and control diets. Thirty weanling male albino rats aged 28-35 days weighing 33-60 g were purchased and used for the study. The rats after acclimatization were fed with gruel produced with the experimental diets and the control with water ad libitum daily for 35days. Effect of the blends on lipid profile, blood glucose, haematological (RBC, HB, PCV, MCV), liver and kidney function and weight gain of the rats were assessed. Acceptability of the gruel was conducted at the end of rat feeding on forty mothers of infants’ ≥ 6 months who gave their informed consent to participate using a 9 point hedonic scale. Data was analyzed for means and standard deviation, analysis of variance and means were separated using Duncan multiple range test and significance judged at 0.05, all using SPSS version 22.0. The results indicated that crude protein, fibre, ash and carbohydrate of the formulated diets were either comparable or higher than values in cerelac. The formulated diets (SGCP1- SGCP4) were significantly (P>0.05) higher in vitamin A and thiamin compared to cerelac. The iron content of the formulated diets SGCP1- SGCP4 (4.23-6.36 mg/100) were within the recommended iron intake of infants (0.55 mg/day). Phytate (1.56-2.55 mg/100g) and oxalate (0.23-0.35 mg/100g) contents of the formulated diets were within the permissible limits of 0-5%. In functional properties, bulk density, swelling index, % dispersibility and water absorption capacity significantly (P<0.05) increased and compared favourably with cerelac. The essential amino acids of the formulated blends were within the amino acid profile of the FAO/WHO/UNU reference protein for children 0.5 -2 years of age. Urea concentration of rats fed with SGCP1-SGCP4 (19.48 mmol/L),(23.76 mmol/L),(24.07 mmol/L),(23.65 mmol/L) respectively was significantly higher than that of rat fed cerelac (16.98 mmol/L); however, plain pap had the least value (9.15 mmol/L). Rats fed with SGCP1-SGCP4 (116 mg/dl), (119 mg/dl), (115 mg/dl), (117 mg/dl) respectively had significantly higher glucose levels those fed with cerelac (108 mg/dl). Liver function parameters (AST, ALP and ALT), lipid profile (triglyceride, HDL, LDL, VLDL) and hematological parameters of rats fed with formulated diets were within normal range. Rats fed SGCP1 gained more weight (90.45 g) than other rats fed with SGCP2-SGCP4 (71.65 g, 79.76 g, 75.68 g), TCF (20.13 g) and cerelac (59.06 g). In all the sensory attributes, the control was preferred with respect to the formulated diets. The formulated diets were generally adequate and may likely have potentials to meet nutrient requirements of infants as complementary food.

Keywords: biochemical, chemical evaluation, complementary food, quadrimix

Procedia PDF Downloads 174

Authors: Yanpei Zhen

Abstract:

The nonlinear Schrödinger (NLS) equation models wave dynamics in many physical problems related to fluids, plasmas, and optics. The standing periodic waves are known to be modulationally unstable, and rogue waves (localized perturbations in space and time) have been observed on their backgrounds in numerical experiments. The exact solutions for rogue waves arising on the periodic standing waves have been obtained analytically. It is natural to ask if the rogue waves persist on the standing periodic waves in the integrable discretizations of the integrable NLS equation. We study the standing periodic waves in the semidiscrete integrable system modeled by the high-order Ablowitz-Ladik (AL) equation. The standing periodic wave of the high-order AL equation is expressed by the Jacobi cnoidal elliptic function. The exact solutions are obtained by using the separation of variables and one-fold Darboux transformation. Since the cnoidal wave is modulationally unstable, the rogue waves are generated on the periodic background.

Keywords: Darboux transformation, periodic wave, Rogue wave, separating the variables

Procedia PDF Downloads 185

Authors: Jamal Hussain Al-Smail

Abstract:

Hydrogen fuel cells (HFCs) are environmentally friendly, energy converter devices that convert the chemical energy of the reactants (oxygen and hydrogen) to electricity through electrochemical reactions. The level of the electricity production of HFCs mainly increases depending on the oxygen distribution in the HFC’s cathode gas diffusion layer (GDL). With a constant porosity of the GDL, the electrochemical reaction can have a great variation that reduces the cell’s productivity and stability. Our findings bring a methodology in finding porosity designs of the diffusion layer to improve the oxygen distribution such that it results in a stable oxygen-hydrogen reaction. We first introduce a mathematical model involving the mass and momentum transport equations, in which a porosity function of the GDL is incorporated as a control for the fluid flow. We then derive numerical methods for solving the mathematical model. In conclusion, we present our numerical results to show how to design the GDL porosity to result in a uniform oxygen distribution.

Keywords: fuel cells, material porosity design, mathematical modeling, porous media

Procedia PDF Downloads 155

Authors: Hiroshi Kinoshita, Yasuto Nakanishi, Ryuhei Okuno, Toshio Higashi

Abstract:

Various kinds of pegboards have been developed and used widely in research and clinics of rehabilitation for evaluation and training of patient’s hand function. A common measure in these peg boards is a total time of performance execution assessed by a tester’s stopwatch. Introduction of electrical and automatic measurement technology to the apparatus, on the other hand, has been delayed. The present work introduces the development of a pegboard with an electric sensor to detect moments of individual peg’s insertion and removal. The work also gives fundamental data obtained from a group of healthy young individuals who performed peg transfer tasks using the pegboard developed. Through trails and errors in pilot tests, two 10-hole peg-board boxes installed with a small photo-reflector and a DC amplifier at the bottom of each hole were designed and built by the present authors. The amplified electric analogue signals from the 20 reflectors were automatically digitized at 500 Hz per channel, and stored in a PC. The boxes were set on a test table at different distances (25, 50, 75, and 125 mm) in parallel to examine the effect of hole-to-hole distance. Fifty healthy young volunteers (25 in each gender) as subjects of the study performed successive fast 80 time peg transfers at each distance using their dominant and non-dominant hands. The data gathered showed a clear-cut light interruption/continuation moment by the pegs, allowing accurately (no tester’s error involved) and precisely (an order of milliseconds) to determine the pull out and insertion times of each peg. This further permitted computation of individual peg movement duration (PMD: from peg-lift-off to insertion) apart from hand reaching duration (HRD: from peg insertion to lift-off). An accidental drop of a peg led to an exceptionally long ( < mean + 3 SD) PMD, which was readily detected from an examination of data distribution. The PMD data were commonly right-skewed, suggesting that the median can be a better estimate of individual PMD than the mean. Repeated measures ANOVA using the median values revealed significant hole-to-hole distance, and hand dominance effects, suggesting that these need to be fixed in the accurate evaluation of PMD. The gender effect was non-significant. Performance consistency was also evaluated by the use of quartile variation coefficient values, which revealed no gender, hole-to-hole, and hand dominance effects. The measurement reliability was further examined using interclass correlation obtained from 14 subjects who performed the 25 and 125 mm hole distance tasks at two 7-10 days separate test sessions. Inter-class correlation values between the two tests showed fair reliability for PMD (0.65-0.75), and for HRD (0.77-0.94). We concluded that a sensor peg board developed in the present study could provide accurate (excluding tester’s errors), and precise (at a millisecond rate) time information of peg movement separated from that used for hand movement. It could also easily detect and automatically exclude erroneous execution data from his/her standard data. These would lead to a better evaluation of hand dexterity function compared to the widely used conventional used peg boards.

Keywords: hand, dexterity test, peg movement time, performance consistency

Procedia PDF Downloads 136

Authors: O. P. Rahi, Manoj Kumar

Abstract:

Power transformers are essential and expensive equipments in electrical power system. Dissolved gas analysis (DGA) is one of the most useful techniques to detect incipient faults in power transformers. However, the identification of the faulted location by conventional method is not always an easy task due to variability of gas data and operational variables. In this paper, an extension theory based power transformer fault diagnosis method is presented. Extension theory tries to solve contradictions and incompatibility problems. This paper first briefly introduces the basic concept of matter element theory, establishes the matter element models for three-ratio method, and then briefly discusses extension set theory. Detailed analysis is carried out on the extended relation function (ERF) adopted in this paper for transformer fault diagnosis. The detailed diagnosing steps are offered. Simulation proves that the proposed method can overcome the drawbacks of the conventional three-ratio method, such as no matching and failure to diagnose multi-fault. It enhances diagnosing accuracy.

Keywords: DGA, extension theory, ERF, fault diagnosis power transformers, fault diagnosis, fuzzy logic

Procedia PDF Downloads 415

Authors: Pantip Kayee

Abstract:

17α-ethinylestradiol (EE2) is a recalcitrant micropollutant which is found in small amounts in municipal wastewater. But these small amounts still adversely affect for the reproductive function of aquatic organisms. Evidence in the past suggested that full-scale WWTPs equipped with nitrification process enhanced the removal of EE2 in the municipal wastewater. EE2 has been proven to be able to be transformed by ammonia oxidizing bacteria (AOB) via co-metabolism. This research aims to clarify the EE2 degradation pattern by different consortium of ammonia oxidizing microorganism (AOM) including AOA (ammonia oxidizing archaea) and investigate contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM. The result showed that AOA or AOB of N. oligotropha cluster in enriched nitrifying activated sludge (NAS) from 2mM and 5mM, commonly found in municipal WWTPs, could degrade EE2 in wastewater via co-metabolism. Moreover, the investigation of the contribution between the existing ammonia monooxygenase (AMO) and new synthesized AOM demonstrated that the new synthesized AMO enzyme may perform ammonia oxidation rather than the existing AMO enzyme or the existing AMO enzyme may has a small amount to oxidize ammonia.

Keywords: 17α-ethinylestradiol, nitrification, ammonia oxidizing bacteria, ammonia oxidizing archaea

Procedia PDF Downloads 295

Authors: Makara Rith, Young Kyu Kim, Seung Woo Lee

Abstract:

In heavy duty areas, asphalt pavement constructed as entrance roadway may expose distresses such as cracking and rutting during service life. To mitigate these problems, composite pavement with a roller-compacted concrete base may be a good alternative; however, it should be initially investigated. Structural performances such as fatigue cracking and rut depth may be changed due to variation of some design factors. Therefore, this study focuses on the variation effect of material modulus, layer thickness and loading on composite pavement performances. Stress and strain at the critical location are determined and used as the input of transfer function for corresponding distresses to evaluate the pavement performance. Also, composite pavement satisfying the design criteria may be selected as a design section for heavy duty areas. Consequently, this investigation indicates that composite pavement has the ability to eliminate fatigue cracking in asphalt surfaces and significantly reduce rut depth. In addition, a thick or strong rigid base can significantly reduce rut depth and prolong fatigue life of this layer.

Keywords: composite pavement, ports, cracking, rutting

Procedia PDF Downloads 212

Authors: Fethi Soltani, Adel Almarashi, Idir Mechai

Abstract:

Tikhonov regularization and reproducing kernels are the most popular approaches to solve ill-posed problems in computational mathematics and applications. And the Fourier multiplier operators are an essential tool to extend some known linear transforms in Euclidean Fourier analysis, as: Weierstrass transform, Poisson integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean operators, partial Fourier integral, Riesz potential, Bessel potential, etc. Using the theory of reproducing kernels, we construct a simple and efficient representations for some class of Fourier multiplier operators Tm on the Paley-Wiener space Hh. In addition, we give an error estimate formula for the approximation and obtain some convergence results as the parameters and the independent variables approaches zero. Furthermore, using numerical quadrature integration rules to compute single and multiple integrals, we give numerical examples and we write explicitly the extremal function and the corresponding Fourier multiplier operators.

Keywords: fourier multiplier operators, Gauss-Kronrod method of integration, Paley-Wiener space, Tikhonov regularization

Procedia PDF Downloads 320

Authors: Francesco Buccafurri, Celeste Romolo

Abstract:

Nowadays phishing is the most frequent starting point of cyber-attack vectors. Phishing is implemented both via email and social network messages. While a wide scientific literature exists which addresses the problem of contrasting email spam-phishing, no specific countermeasure has been so far proposed for phishing included into private messages of social network platforms. Unfortunately, the problem is severe. This paper proposes an approach against social network phishing, based on a non invasive collaborative information-sharing approach which leverages blockchain. The detection method works by filtering candidate messages, by distilling them by means of a distance-preserving hash function, and by publishing hashes over a public blockchain through a trusted smart contract (thus avoiding denial of service attacks). Phishing detection exploits social information embedded into social network profiles to identify similar messages belonging to disjoint contexts. The main contribution of the paper is to introduce a new approach to contrasting the problem of social network phishing, which, despite its severity, received little attention by both research and industry.

Keywords: phishing, social networks, information sharing, blockchain

Procedia PDF Downloads 331

Authors: Bailey Hall, Athena Hoppe, Tevyn Kagele, Anna Nichols, Breeanna Messner

Abstract:

The Spokane Street Medicine (SSM) Program aims to deliver medical care to people experiencing homelessness in Spokane, Washington. Street medicine is designed to function in a non-traditional setting to help deliver healthcare to a largely underserved population. In this analysis, the SSM Program’s medical charts from street and shelter encounters in early 2021 were reviewed in order to identify illness and diseases in people experiencing homelessness in Spokane. More than half of the prescriptions written during these encounters were for either an antibacterial, an antibiotic, or an antifungal. Estimates of the cost to the local healthcare system are included. Initiating treatment for communicable diseases in people experiencing homelessness via street medicine efforts greatly reduces economic costs while improving health outcomes.

Keywords: ethical issues in public health, equity issues in public health, health economics, health disparities, healthcare costs, medical public health, public health ethics, street medicine

Procedia PDF Downloads 192