Search results for: structural equation models

Authors: Zhouhong Li

Abstract:

In this paper, by applying Mawhin-s continuation theorem of coincidence degree theory, we study the existence of almost periodic solutions for neural multi-delay logarithmic population model and obtain one sufficient condition for the existence of positive almost periodic solution for the above equation. An example is employed to illustrate our result.

Keywords: Almost periodic solution, Multi-delay, Logarithmic population model, Coincidence degree.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1416

Authors: Yu Zhang, Pedro Desouza

Abstract:

Since big data has become substantially more accessible and manageable due to the development of powerful tools for dealing with unstructured data, people are eager to mine information from social media resources that could not be handled in the past. Sentiment analysis, as a novel branch of text mining, has in the last decade become increasingly important in marketing analysis, customer risk prediction and other fields. Scientists and researchers have undertaken significant work in creating and improving their sentiment models. In this paper, we present a concept of selecting appropriate classifiers based on the features and qualities of data sources by comparing the performances of five classifiers with three popular social media data sources: Twitter, Amazon Customer Reviews, and Movie Reviews. We introduced a couple of innovative models that outperform traditional sentiment classifiers for these data sources, and provide insights on how to further improve the predictive power of sentiment analysis. The modeling and testing work was done in R and Greenplum in-database analytic tools.

Keywords: Sentiment Analysis, Social Media, Twitter, Amazon, Data Mining, Machine Learning, Text Mining.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3491

Authors: Manash Pratim Sarma, Kandarpa Kumar Sarma

Abstract:

A set of Artificial Neural Network (ANN) based methods for the design of an effective system of speech recognition of numerals of Assamese language captured under varied recording conditions and moods is presented here. The work is related to the formulation of several ANN models configured to use Linear Predictive Code (LPC), Principal Component Analysis (PCA) and other features to tackle mood and gender variations uttering numbers as part of an Automatic Speech Recognition (ASR) system in Assamese. The ANN models are designed using a combination of Self Organizing Map (SOM) and Multi Layer Perceptron (MLP) constituting a Learning Vector Quantization (LVQ) block trained in a cooperative environment to handle male and female speech samples of numerals of Assamese- a language spoken by a sizable population in the North-Eastern part of India. The work provides a comparative evaluation of several such combinations while subjected to handle speech samples with gender based differences captured by a microphone in four different conditions viz. noiseless, noise mixed, stressed and stress-free.

Keywords: Assamese, Recognition, LPC, Spectral, ANN.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1966

Authors: Hitoshi Takata, Tomohiro Hachino, Masaki Horai, Kazuo Komatsu

Abstract:

In this paper, we are concerned with the design and its simulation studies of a modified extremum seeking control for nonlinear systems. A standard extremum seeking control has a simple structure, but it takes a long time to reach an optimal operating point. We consider a modification of the standard extremum seeking control which is aimed to reach the optimal operating point more speedily than the standard one. In the modification, PD acceleration term is added before an integrator making a principal control, so that it enables the objects to be regulated to the optimal point smoothly. This proposed method is applied to Monod and Williams-Otto models to investigate its effectiveness. Numerical simulation results show that this modified method can improve the time response to the optimal operating point more speedily than the standard one.

Keywords: Extremum seeking control, Monod model, Williams- Otto model, PD acceleration term, Optimal operating point.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1489

Authors: Mark Schudeleit, Christian Sieg, Ferit Küçükay

Abstract:

This paper describes how to dimension the electric components of a 48V hybrid system considering real customer use. Furthermore, it provides information about savings in energy and CO2 emissions by a customer-tailored 48V hybrid. Based on measured customer profiles, the electric units such as the electric motor and the energy storage are dimensioned. Furthermore, the CO2 reduction potential in real customer use is determined compared to conventional vehicles. Finally, investigations are carried out to specify the topology design and preliminary considerations in order to hybridize a conventional vehicle with a 48V hybrid system. The emission model results from an empiric approach also taking into account the effects of engine dynamics on emissions. We analyzed transient engine emissions during representative customer driving profiles and created emission meta models. The investigation showed a significant difference in emissions when simulating realistic customer driving profiles using the created verified meta models compared to static approaches which are commonly used for vehicle simulation.

Keywords: Customer use, dimensioning, hybrid electric vehicles, vehicle simulation, 48V hybrid system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3541

Authors: Vickneswaran Jeyabalan, Andrews Samraj, Loo Chu Kiong

Abstract:

The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.

Keywords: Adaptive autoregressive, adaptive bandpass filter, brain machine Interface, EEG, motor imaginary.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2869

Authors: Kasthurirangan Gopalakrishnan, Marshall R. Thompson, Anshu Manik

Abstract:

This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data. The HWD test is one of the most widely used tests for routinely assessing the structural integrity of airport pavements in a non-destructive manner. The elastic moduli of the individual pavement layers backcalculated from the HWD deflection profiles are effective indicators of layer condition and are used for estimating the pavement remaining life. HWD tests were periodically conducted at the Federal Aviation Administration-s (FAA-s) National Airport Pavement Test Facility (NAPTF) to monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test gear trafficking on the structural condition of flexible pavement sections. In this study, a multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD backcalculation function. The synthetic database generated using an advanced non-linear pavement finite-element program was used to train the ANN to overcome the limitations associated with conventional pavement moduli backcalculation. The changes in ANN-based backcalculated pavement moduli with trafficking were used to compare the relative severity effects of the aircraft landing gears on the NAPTF test pavements.

Keywords: Airfield pavements, ANN, backcalculation, newgeneration aircraft

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2163

Authors: Sima Ziaee, Khosro Jafarpur

Abstract:

Among all mechanical joining processes, welding has been employed for its advantage in design flexibility, cost saving, reduced overall weight and enhanced structural performance. However, for structures made of relatively thin components, welding can introduce significant buckling distortion which causes loss of dimensional control, structural integrity and increased fabrication costs. Different parameters can affect buckling behavior of welded thin structures such as, heat input, welding sequence, dimension of structure. In this work, a 3-D thermo elastic-viscoplastic finite element analysis technique is applied to evaluate the effect of shell dimensions on buckling behavior and entropy generation of welded thin shells. Also, in the present work, the approximated longitudinal transient stresses which produced in each time step, is applied to the 3D-eigenvalue analysis to ratify predicted buckling time and corresponding eigenmode. Besides, the possibility of buckling prediction by entropy generation at each time is investigated and it is found that one can predict time of buckling with drawing entropy generation versus out of plane deformation. The results of finite element analysis show that the length, span and thickness of welded thin shells affect the number of local buckling, mode shape of global buckling and post-buckling behavior of welded thin shells.

Keywords: Buckling behavior, Elastic viscoplastic model, Entropy generation, Finite element method, Shell dimensions.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1613

Authors: Kaustubh Chakradeo, Michael Delves, Sofya Titarenko

Abstract:

Malaria is a serious disease which affects hundreds of millions of people around the world, each year. If not treated in time, it can be fatal. Despite recent developments in malaria diagnostics, the microscopy method to detect malaria remains the most common. Unfortunately, the accuracy of microscopic diagnostics is dependent on the skill of the microscopist and limits the throughput of malaria diagnosis. With the development of Artificial Intelligence tools and Deep Learning techniques in particular, it is possible to lower the cost, while achieving an overall higher accuracy. In this paper, we present a VGG-based model and compare it with previously developed models for identifying infected cells. Our model surpasses most previously developed models in a range of the accuracy metrics. The model has an advantage of being constructed from a relatively small number of layers. This reduces the computer resources and computational time. Moreover, we test our model on two types of datasets and argue that the currently developed deep-learning-based methods cannot efficiently distinguish between infected and contaminated cells. A more precise study of suspicious regions is required.

Keywords: Malaria, deep learning, DL, convolution neural network, CNN, thin blood smears.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 623

Authors: S. A. Moeini, M. T.Ahmadian

Abstract:

Structural behavior of ring stiffened thick walled cylinders made of functionally graded materials (FGMs) is investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture of metal and ceramic. The gradient compositional variation of the constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction. A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and modal behavior of stiffened FGM thick walled cylinders. By using this super-element the number of elements, which are needed for modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by comparison to finite element formulation with conventional elements. Comparison indicates a good conformity between results.

Keywords: FGMs, Modal analysis, Static analysis, Stiffened cylinders.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2291

Authors: Yingguo Li

Abstract:

In this paper, we consider a discrete Gompertz model with time delay. Firstly, the stability of the equilibrium of the system is investigated by analyzing the characteristic equation. By choosing the time delay as a bifurcation parameter, we prove that Neimark- Sacker bifurcations occur when the delay passes a sequence of critical values. The direction and stability of the Neimark-Sacker are determined by using normal forms and centre manifold theory. Finally, some numerical simulations are given to verify the theoretical analysis.

Keywords: Gompertz system, Neimark-Sacker bifurcation, stability, time delay.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1909

Authors: Tomio Iwasaki, Yosuke Kawahito

Abstract:

The adhesion strength and wettability at the interfaces between a polyetheretherketone (PEEK) resin and titanium dioxide (TiO2) have become more important because direct joining of PEEK resin and titanium (Ti), whose surface has usually the oxide (TiO2), is needed not only in vehicles such as airplanes, automobiles, and space vehicles, but also in medical devices such as implants. To realize strong joint between the PEEK resin and TiO2, the dependence of the adhesion strength and wettability on crystal orientations of rutile TiO2 were investigated by using molecular simulations. Molecular dynamics simulations were conducted by combining quantum-mechanics equation of electrons with Newton’s equation of motion of nuclear coordinates (atomic coordinates). By putting a PEEK-resin sphere on a rutile TiO2 surface and by heating the system to 650 K, the contact angles at the interfaces were calculated to evaluate the wettability. After the system is cooled to 300 K from 650 K, to evaluate the adhesin strength, the adhesive fracture energy is calculated as the difference between the energy of the PEEK-TiO2 attached state and that of the PEEK-TiO2 detached state. The results of the contact angles showed that PEEK resin on the TiO2(100) and that on the TiO2(001) surface has low wettability with large contact angles. On the other hand, PEEK resin on the TiO2(110) surface has high wettability with a small contact angle. The results of the adhesive fracture energies showed that the adhesion at the PEEK-resin/TiO2(100) and PEEK-resin/TiO2(001) interfaces are weak. On the other hand, the adhesion at the PEEK-resin/TiO2(110) interface is strong. To clarify the reason that the higher wettability and stronger adhesion are obtained at the PEEK/TiO2(110) interface than at the at the PEEK/TiO2(100) and PEEK/TiO2(001) interfaces, atomic configurations at the interfaces were visualized. The atomic configuration at the PEEK/TiO2(110) interface showed that the lattice-matched coherent interface is realized, and the atomic density is high. On the other hand, the atomic configuration at the PEEK/TiO2(001) interface showed the lattice-unmatched incoherent interface. The atomic configuration at the PEEK/TiO2(100) interface showed that the atomic density is very low although the lattice-matched interface is realized. Therefore, the lattice matching and the high atomic density at the PEEK/TiO2(001) interface are considered to be dominant factors in the high wettability and strong adhesion.

Keywords: Adhesion, direct joining, PEEK, TiO2, wettability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 400

Authors: Ali Faal Ghayoumi, Mahmoud Dehghan Nayeri, Manouchehre Ansari, Taha Raeesi

Abstract:

This study aims to investigate empirically the valuerelevance of accounting information to domestic investors in Tehran stock exchange from 1999 to 2006. During the present research impacts of two factors, including positive vs. negative earnings and the firm size are considered as well. The authors used earnings per share and annual change of earnings per share as the income statement indices, and book value of equity per share as the balance sheet index. Return and Price models through regression analysis are deployed in order to test the research hypothesis. Results depicted that accounting information is value-relevance to domestic investors in Tehran Stock Exchange according to both studied models. However, income statement information has more value-relevance than the balance sheet information. Furthermore, positive vs. negative earnings and firm size seems to have significant impact on valuerelevance of accounting information.

Keywords: Value-Relevance of Accounting Information, Iranianstock exchange, Return Model, Price Model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2542

Authors: Pradeep Kumar, Abdul Wahid

Abstract:

Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.

Keywords: Classification, Cascade Correlation Neural Network, Random Forest, Software reliability, TreeNet.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1812

Authors: Hiram I. Beltrán, Arturo Rojo-Domínguez, Máximo Eduardo Sánchez Gutiérrez, Pedro Pablo González Pérez

Abstract:

A computational platform is presented in this contribution. It has been designed as a virtual laboratory to be used for exploring optimization algorithms in biological problems. This platform is built on a blackboard-based agent architecture. As a test case, the version of the platform presented here is devoted to the study of protein folding, initially with a bead-like description of the chain and with the widely used model of hydrophobic and polar residues (HP model). Some details of the platform design are presented along with its capabilities and also are revised some explorations of the protein folding problems with different types of discrete space. It is also shown the capability of the platform to incorporate specific tools for the structural analysis of the runs in order to understand and improve the optimization process. Accordingly, the results obtained demonstrate that the ensemble of computational tools into a single platform is worthwhile by itself, since experiments developed on it can be designed to fulfill different levels of information in a self-consistent fashion. By now, it is being explored how an experiment design can be useful to create a computational agent to be included within the platform. These inclusions of designed agents –or software pieces– are useful for the better accomplishment of the tasks to be developed by the platform. Clearly, while the number of agents increases the new version of the virtual laboratory thus enhances in robustness and functionality.

Keywords: genetic algorithms, multi-agent systems, bioinformatics, optimization, protein folding, structural biology.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1864

Authors: Hassan E. A. Ibrahim, Mohamed F. Serag

Abstract:

In this paper, Novel method, Particle Swarm Optimization (PSO) algorithm, based technique is proposed to estimate and analyze the steady state performance of self-excited induction generator (SEIG). In this novel method the tedious job of deriving the complex coefficients of a polynomial equation and solving it, as in previous methods, is not required. By comparing the simulation results obtained by the proposed method with those obtained by the well known mathematical methods, a good agreement between these results is obtained. The comparison validates the effectiveness of the proposed technique.

Keywords: Evolution theory, MATLAB, optimization, PSO, SEIG.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2440

Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: Over-parameterization, Rectified Linear Units (ReLU), convergence, gradient descent, neural networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 850

Authors: Safyeh Soufian, Hoosein Naderi-Manesh, Abdoali Alizadeh, Mohammad Nabi Sarbolouki

Abstract:

Aurein 1.2 is a 13-residue amphipathic peptide with antibacterial and anticancer activity. Aurein1.2 and its retro analog were synthesized to study the activity of the peptides in relation to their structure. The antibacterial test result showed the retro-analog is inactive. The secondary structural analysis by CD spectra indicated that both of the peptides at TFE/Water adopt alpha-helical conformation. MD simulation was performed on aurein 1.2 and retro-analog in water and TFE in order to analyse the factors that are involved in the activity difference between retro and the native peptide. The simulation results are discussed and validated in the light of experimental data from the CD experiment. Both of the peptides showed a relatively similar pattern for their hydrophobicity, hydrophilicity, solvent accessible surfaces, and solvent accessible hydrophobic surfaces. However, they showed different in directions of dipole moment of peptides. Also, Our results further indicate that the reversion of the amino acid sequence affects flexibility .The data also showed that factors causing structural rigidity may decrease the activity. Consequently, our finding suggests that in the case of sequence-reversed peptide strategy, one has to pay attention to the role of amino acid sequence order in making flexibility and role of dipole moment direction in peptide activity. KeywordsAntimicrobial peptides, retro, molecular dynamic, circular dichroism.

Keywords: Antimicrobial peptides, retro, molecular dynamic, circular dichroism.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1829

Authors: S. Khamtree, T. Ratanawilai, C. Nuntadusit

Abstract:

Rubberwood is a crucial commercial timber in Southern Thailand. All processes in a rubberwood production depend on the knowledge and expertise of the technicians, especially the drying process. This research aims to develop an empirical model for drying kinetics in rubberwood. During the experiment, the temperature of the hot air and the average air flow velocity were kept at 80-100 °C and 1.75 m/s, respectively. The moisture content in the samples was determined less than 12% in the achievement of drying basis. The drying kinetic was simulated using an empirical solver. The experimental results illustrated that the moisture content was reduced whereas the drying temperature and time were increased. The coefficient of the moisture ratio between the empirical and the experimental model was tested with three statistical parameters, R-square (R²), Root Mean Square Error (RMSE) and Chi-square (χ²) to predict the accuracy of the parameters. The experimental moisture ratio had a good fit with the empirical model. Additionally, the results indicated that the drying of rubberwood using the Henderson and Pabis model revealed the suitable level of agreement. The result presented an excellent estimation (R² = 0.9963) for the moisture movement compared to the other models. Therefore, the empirical results were valid and can be implemented in the future experiments.

Keywords: Empirical models, hot air, moisture ratio, rubberwood.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 749

Authors: Chin-Yu Lee, Iau-Teh Wang

Abstract:

The mountain road slope failures triggered by earthquake activities and torrential rain namely to create the disaster. Province Road No. 24 is a main route to the Wutai Township. The area of the study is located at the mileages between 46K and 47K along the road. However, the road has been suffered frequent damages as a result of landslide and slope failures during typhoon seasons. An understanding of the sliding behaviors in the area appears to be necessary. Slope failures triggered by earthquake activities and heavy rainfalls occur frequently. The study is to understand the mechanism of slope failures and to look for the way to deal with the situation. In order to achieve these objectives, this paper is based on theoretical and structural geology data interpretation program to assess the potential slope sliding behavior. The study showed an intimate relationship between the landslide behavior of the slopes and the stratum materials, based on structural geology analysis method to analysis slope stability and finds the slope safety coefficient to predict the sites of destroyed layer. According to the case study and parameter analyses results, the slope mainly slips direction compared to the site located in the southeast area. Find rainfall to result in the rise of groundwater level is main reason of the landslide mechanism. Future need to set up effective horizontal drain at corrective location, that can effective restrain mountain road slope failures and increase stability of slope.

Keywords: slope stability analysis, Stereographic Projection, wedge Failure.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4660

Authors: A. M. Tahsini

Abstract:

Supersonic hydrogen-air cylindrical mixing layer is numerically analyzed to investigate the effect of inlet swirl on ignition time delay in scramjets. Combustion is treated using detail chemical kinetics. One-equation turbulence model of Spalart and Allmaras is chosen to study the problem and advection upstream splitting method is used as computational scheme. The results show that swirling both fuel and oxidizer streams may drastically decrease the ignition distance in supersonic combustion, unlike using the swirl just in fuel stream which has no helpful effect.

Keywords: Ignition delay, Supersonic combustion, Swirl, Numerical simulation, Turbulence.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2174

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

Abstract:

As we enter the new era of Artificial Intelligence (AI) and cloud computing, we mostly rely on the machine and natural language processing capabilities of AI, and energy efficient hardware and software devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and to sustain the depletion of natural resources. The core pillars of sustainability are Economic, Environmental, and Social, which are also informally referred to as 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core sustainability model in the enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand there is also a growing concern in many industries on how to reduce carbon emission and conserve natural resources while adopting sustainability in the corporate business models and policies. In our paper, we would like to discuss the driving forces such as climate changes, natural disasters, pandemic, disruptive technologies, corporate policies, scaled business models and emerging social media and AI platforms that influence the 3 main pillars of sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increase recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (shared IT services, cloud computing and application modernization) with the vision for a sustainable environment.

Keywords: AI, cloud computing, machine learning, social media platform.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 156

Authors: V. Keim, J. Spachtholz, J. Hammer

Abstract:

The importance of fibre reinforced plastics continually increases due to the excellent mechanical properties, low material and manufacturing costs combined with significant weight reduction. Today, components are usually designed and calculated numerically by using finite element methods (FEM) to avoid expensive laboratory tests. These programs are based on material models including material specific deformation characteristics. In this research project, material models for short glass fibre reinforced plastics are presented to simulate the visco-elasto-plastic deformation behaviour. Prior to modelling specimens of the material EMS Grivory HTV-5H1, consisting of a Polyphthalamide matrix reinforced by 50wt.-% of short glass fibres, are characterized experimentally in terms of the highly time dependent deformation behaviour of the matrix material. To minimize the experimental effort, the cyclic deformation behaviour under tensile and compressive loading (R = −1) is characterized by isothermal complex low cycle fatigue (CLCF) tests. Combining cycles under two strain amplitudes and strain rates within three orders of magnitude and relaxation intervals into one experiment the visco-elastic deformation is characterized. To identify visco-plastic deformation monotonous tensile tests either displacement controlled or strain controlled (CERT) are compared. All relevant modelling parameters for this complex superposition of simultaneously varying mechanical loadings are quantified by these experiments. Subsequently, two different material models are compared with respect to their accuracy describing the visco-elasto-plastic deformation behaviour. First, based on Chaboche an extended 12 parameter model (EVP-KV2) is used to model cyclic visco-elasto-plasticity at two time scales. The parameters of the model including a total separation of elastic and plastic deformation are obtained by computational optimization using an evolutionary algorithm based on a fitness function called genetic algorithm. Second, the 12 parameter visco-elasto-plastic material model by Launay is used. In detail, the model contains a different type of a flow function based on the definition of the visco-plastic deformation as a part of the overall deformation. The accuracy of the models is verified by corresponding experimental LCF testing.

Keywords: Complex low cycle fatigue, material modelling, short glass fibre reinforced polyphthalamides, visco-elasto-plastic deformation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1345

Authors: Dinesh Acharya U., N. V. Subba Reddy, Krishnamoorthi Makkithaya

Abstract:

The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Keywords: Fuzzy k Nearest Neighbor, Multiple Classifiers, Numeral Recognition, Structural features.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1727

Authors: A. Hol

Abstract:

21^st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.

Keywords: Education sector, business transformation, eTransformation model, cognitive model, cognitive systems, eTransformation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 638

Authors: Migbar Assefa

Abstract:

The performance of a machine tool is eventually assessed by its ability to produce a component of the required geometry in minimum time and at small operating cost. It is customary to base the structural design of any machine tool primarily upon the requirements of static rigidity and minimum natural frequency of vibration. The operating properties of machines like cutting speed, feed and depth of cut as well as the size of the work piece also have to be kept in mind by a machine tool structural designer. This paper presents a novel approach to the design of machine tool column for static and dynamic rigidity requirement. Model evaluation is done effectively through use of General Finite Element Analysis software ANSYS. Studies on machine tool column are used to illustrate finite element based concept evaluation technique. This paper also presents results obtained from the computations of thin walled box type columns that are subjected to torsional and bending loads in case of static analysis and also results from modal analysis. The columns analyzed are square and rectangle based tapered open column, column with cover plate, horizontal partitions and with apertures. For the analysis purpose a total of 70 columns were analyzed for bending, torsional and modal analysis. In this study it is observed that the orientation and aspect ratio of apertures have no significant effect on the static and dynamic rigidity of the machine tool structure.

Keywords: Finite Element Modeling, Modal Analysis, Machine tool structure, Static Analysis.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5010

Authors: Chanin Park, Sundarapandian Thangapandian, Yuno Lee, Minky Son, Shalini John, Young-sik Sohn, Keun Woo Lee

Abstract:

Hypertension is characterized with stress on the heart and blood vessels thus increasing the risk of heart attack and renal diseases. The Renin angiotensin system (RAS) plays a major role in blood pressure control. Renin is the enzyme that controls the RAS at the rate-limiting step. Our aim is to develop new drug-like leads which can inhibit renin and thereby emerge as therapeutics for hypertension. To achieve this, molecular dynamics (MD) simulation and receptor-based pharmacophore modeling were implemented, and three rennin-inhibitor complex structures were selected based on IC50 value and scaffolds of inhibitors. Three pharmacophore models were generated considering conformations induced by inhibitor. The compounds mapped to these models were selected and subjected to drug-like screening. The identified hits were docked into the active site of renin. Finally, hit1 satisfying the binding mode and interaction energy was selected as possible lead candidate to be used in novel renin inhibitors.

Keywords: Renin inhibitor, Molecular dynamics simulation, Structure-based pharmacophore modeling

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1948

Authors: Seok Hong Min, Woo Young Jung, Tae Kwon Ha

Abstract:

Superplastic deformation and high temperature load relaxation behavior of coarse-grained iron aluminides with the composition of Fe-28 at.% Al have been investigated. A series of load relaxation and tensile tests were conducted at temperatures ranging from 600 to 850oC. The flow curves obtained from load relaxation tests were found to have a sigmoidal shape and to exhibit stress vs. strain rate data in a very wide strain rate range from 10-7/s to 10-2/s. Tensile tests have been conducted at various initial strain rates ranging from 3×10-5/s to 1×10-2/s. Maximum elongation of ~500 % was obtained at the initial strain rate of 3×10-5/s and the maximum strain rate sensitivity was found to be 0.68 at 850oC in binary Fe-28Al alloy. Microstructure observation through the optical microscopy (OM) and the electron back-scattered diffraction (EBSD) technique has been carried out on the deformed specimens and it has revealed the evidences for grain boundary migration and grain refinement to occur during superplastic deformation, suggesting the dynamic recrystallization mechanism. The addition of Cr by the amount of 5 at.% appeared to deteriorate the superplasticity of the binary iron aluminide. By applying the internal variable theory of structural superplasticity, the addition of Cr has been revealed to lower the contribution of the frictional resistance to dislocation glide during high temperature deformation of the Fe3Al alloy.

Keywords: Iron aluminide (Fe3Al), large grain size, structural superplasticity, dynamic recrystallization, chromium (Cr).

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1765

Authors: Sanja Pfeifer, Nataša Šarlija, Marina Jeger, Ana Bilandžić

Abstract:

The purpose of this study is to explore the different facets of growth among micro, small and medium-sized firms in Croatia and to analyze the differences between models designed for all micro, small and medium-sized firms and those in creative industries. Three growth prediction models were designed and tested using the growth of sales, employment and assets of the company as dependent variables. The key drivers of sales growth are: prudent use of cash, industry affiliation and higher share of intangible assets. Growth of assets depends on retained profits, internal and external sources of financing, as well as industry affiliation. Growth in employment is closely related to sources of financing, in particular, debt and it occurs less frequently than growth in sales and assets. The findings confirm the assumption that growth strategies of small and medium-sized enterprises (SMEs) in creative industries have specific differences in comparison to SMEs in general. Interestingly, only 2.2% of growing enterprises achieve growth in employment, assets and sales simultaneously.

Keywords: Creative industries, growth prediction model, growth determinants, growth measures.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1555

Authors: A. R. Nezamabadi, M. Karami Khorramabadi

Abstract:

This paper presents the elastic buckling of homogeneous beams with a pair of piezoelectric layers surface bonded on both sides of the beams. The displacement field of beam is assumed based on the Engesser-Timoshenko beam theory. Applying the Hamilton's principle, the equilibrium equation is established. The influences of applied voltage, dimensionless geometrical parameter and piezoelectric thickness on the critical buckling load of beam are presented. To investigate the accuracy of the present analysis, a compression study is carried out with a known data.

Keywords: Mechanical Buckling, Engesser-Timoshenko beam theory - Piezoelectric layer.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2220