Search results for: deep graphical model

Authors: H. C. Chinwenyi, H. D. Ibrahim, J. O. Adekunle

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The incubation period is defined as the time from infection with a microorganism to development of symptoms. In this research, two disease models: one with incubation period and another without incubation period were studied. The study involves the use of a  mathematical model with a single incubation period. The test for the existence and stability of the disease free and the endemic equilibrium states for both models were carried out. The fourth order Runge-Kutta method was used to solve both models numerically. Finally, a computer program in MATLAB was developed to run the numerical experiments. From the results, we are able to show that the endemic equilibrium state of the model with incubation period is locally asymptotically stable whereas the endemic equilibrium state of the model without incubation period is unstable under certain conditions on the given model parameters. It was also established that the disease free equilibrium states of the model with and without incubation period are locally asymptotically stable. Furthermore, results from numerical experiments using empirical data obtained from Nigeria Centre for Disease Control (NCDC) showed that the overall population of the infected people for the model with incubation period is higher than that without incubation period. We also established from the results obtained that as the transmission rate from susceptible to infected population increases, the peak values of the infected population for the model with incubation period decrease and are always less than those for the model without incubation period.

Keywords: asymptotic stability, Hartman-Grobman stability criterion, incubation period, Routh-Hurwitz criterion, Runge-Kutta method

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Authors: Abdelmalek Arrouf

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This article sets up a cognitive schema of the architectural designing activity. It begins by outlining, theoretically, an a priori model of its general cognitive mechanisms. The obtained theoretical framework represents the designing activity as a complex system composed of three interrelated subsystems of cognitive actions: a subsystem of meaning production, one of morphology production and finally a subsystem of navigation between the two formers. A protocol analysis that uses statistical and informational tools is then used to measure the validity of the built schema. The model thus achieved shows that the designer begins by conceiving abstract meanings, which he then translates into shapes. That’s why we call it a semio-morphic model of the designing activity.

Keywords: designing actions, model of the design process, morphosis, protocol analysis, semiosis

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Authors: Rainer Goetz, Zahra Ahaliabadeh, Princess S. Llanos, Aliaksandr S. Bandarenka, Tanja Kallio

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In order to understand the electrochemistry of all-solid-state batteries (ASSBs), the use of electrochemical equivalent circuits with a physical meaning is essential. A model battery is needed whose characterization is independent of the influence of the complex battery assembly. Lithium-Ion Conducting Glass-Ceramic (LICGC), a model solid electrolyte, is chosen for its stability in the air, but on the other hand, it is also well-known for its instability against metallic lithium upon direct contact. Hence, as a first step towards a model ASSB, the interface between lithium and the solid electrolyte (SE) is stabilized with thin (5 nm and 10 nm) coatings of titanium oxide (TO) and lithium titanium oxide (LTO). Impedance data shows that both materials are able to protect the SE surface from rapid degradation due to reducing lithium and, therefore, can serve as a protective interlayer on the anode side of a model ASSB.

Keywords: all-solid-state battery, lithium anode, solid electrolytes, interlayers

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Hayriye Anıl, Görkem Kar

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In addition to being rich in renewable energy resources, Turkey is one of the countries that promise potential in geothermal energy production with its high installed power, cheapness, and sustainability. Increasing imbalance penalties become an economic burden for organizations since geothermal generation plants cannot maintain the balance of supply and demand due to the inadequacy of the production forecasts given in the day-ahead market. A better production forecast reduces the imbalance penalties of market participants and provides a better imbalance in the day ahead market. In this study, using machine learning, deep learning, and, time series methods, the total generation of the power plants belonging to Zorlu Natural Electricity Generation, which has a high installed capacity in terms of geothermal, was estimated for the first one and two weeks of March, then the imbalance penalties were calculated with these estimates and compared with the real values. These modeling operations were carried out on two datasets, the basic dataset and the dataset created by extracting new features from this dataset with the feature engineering method. According to the results, Support Vector Regression from traditional machine learning models outperformed other models and exhibited the best performance. In addition, the estimation results in the feature engineering dataset showed lower error rates than the basic dataset. It has been concluded that the estimated imbalance penalty calculated for the selected organization is lower than the actual imbalance penalty, optimum and profitable accounts.

Keywords: machine learning, deep learning, time series models, feature engineering, geothermal energy production forecasting

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Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic

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Authors: W. I. Mazyan, A. Ahmadi, M. Hoorfar

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Objectives/Scope: This paper proposes a mathematical model for calculating the solid-gas separation efficiency in cyclones. This model provides better agreement with experimental results compared to existing mathematical models. Methods: The separation ratio efficiency, ϵsp, is evaluated by calculating the outlet to inlet count ratio. Similar to mathematical derivations in the literature, the inlet and outlet particle count were evaluated based on Eulerian approach. The model also includes the external forces acting on the particle (i.e., centrifugal and drag forces). In addition, the proposed model evaluates the exact length that the particle travels inside the cyclone for the evaluation of number of turns inside the cyclone. The separation efficiency model derivation using Stoke’s law considers the effect of the inlet tangential velocity on the separation performance. In cyclones, the inlet velocity is a very important factor in determining the performance of the cyclone separation. Therefore, the proposed model provides accurate estimation of actual cyclone separation efficiency. Results/Observations/Conclusion: The separation ratio efficiency, ϵsp, is studied to evaluate the performance of the cyclone for particles ranging from 1 microns to 10 microns. The proposed model is compared with the results in the literature. It is shown that the proposed mathematical model indicates an error of 7% between its efficiency and the efficiency obtained from the experimental results for 1 micron particles. At the same time, the proposed model gives the user the flexibility to analyze the separation efficiency at different inlet velocities. Additive Information: The proposed model determines the separation efficiency accurately and could also be used to optimize the separation efficiency of cyclones at low cost through trial and error testing, through dimensional changes to enhance separation and through increasing the particle centrifugal forces. Ultimately, the proposed model provides a powerful tool to optimize and enhance existing cyclones at low cost.

Keywords: cyclone efficiency, solid-gas separation, mathematical model, models error comparison

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Authors: Adisorn Bansong, Walai Isarankura Na Ayudhaya, Aumporn Makanong

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A Development of an Instructional Model for Health Education was the aim to develop and study the effectiveness of an instructional model for health education to enhance self-regulation and learning achievement of lower secondary school students. It was the Quasi-Experimental Designs, used a Single-group Interrupted Time-series Designs, conducted by 2 phases: 1. To develop an instructional model based on Social Cognitive Theory and Strategic Life Planning. 2. To trial and evaluate effectiveness of an instructional model. The results as the following: i. An Instructional Model for Health Education consists of five main components: a) Attention b) Forethought c) Tactic Planning d) Execution and e) Reflection. ii. After an Instructional Model for Health Education has used for a semester trial, found the 4.07 percent of sample’s Self-Regulation higher and learning achievement on post-test were significantly higher than pre-test at .05 levels (p = .033, .000).

Keywords: social cognitive theory, strategic life planning, self-regulation, learning achievement

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Authors: Satpreet Singh

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This paper introduces the new LACGC model to sustain the academic and non-academic business to future educational and organizational generations. The consumption of knowledge and the creation of new knowledge is a strength and focal interest of all academics and Non-academic organizations. Implementing newly created knowledge sustains the businesses to the next generation with growth without detriment. Existing models like the Scholar-practitioner model and Organization knowledge creation models focus specifically on academic or non-academic, not both. LACGC model can be used for both Academic and Non-academic at the domestic or international level. Researchers and scholars play a substantial role in finding literature and practice gaps in academic and non-academic disciplines. LACGC model has unrestricted the number of recurrences because the Consumption, Creation, and implementation of new ideas, disciplines, systems, and knowledge is a never-ending process and must continue from one generation to the next.

Keywords: academics, consumption, creation, generations, non-academics, research, sustainability

Procedia PDF Downloads 181

Authors: Cinna Soltanpur, Mohammad Ghamari, Behzad Momahed Heravi, Fatemeh Zare

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Low-density parity-check (LDPC) codes have been shown to deliver capacity approaching performance; however, problematic graphical structures (e.g. trapping sets) in the Tanner graph of some LDPC codes can cause high error floors in bit-error-ratio (BER) performance under conventional sum-product algorithm (SPA). This paper presents a serial concatenation scheme to avoid the trapping sets and to lower the error floors of LDPC code. The outer code in the proposed concatenation is the LDPC, and the inner code is a high rate array code. This approach applies an interactive hybrid process between the BCJR decoding for the array code and the SPA for the LDPC code together with bit-pinning and bit-flipping techniques. Margulis code of size (2640, 1320) has been used for the simulation and it has been shown that the proposed concatenation and decoding scheme can considerably improve the error floor performance with minimal rate loss.

Keywords: concatenated coding, low–density parity–check codes, array code, error floors

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Authors: Farid Gaci, Zoubir Nemouchi

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A numerical study of laminar and turbulent fluid flows in 90° bend of square section was carried out. Three-dimensional meshes, based on hexahedral cells, were generated. The QUICK scheme was employed to discretize the convective term in the transport equations. The SIMPLE algorithm was adopted to treat the velocity-pressure coupling. The flow structure obtained showed interesting features such as recirculation zones and counter-rotating pairs of vortices. The performance of three different turbulence models was evaluated: the standard k- ω model, the SST k-ω model and the Reynolds Stress Model (RSM). Overall, it was found that, the multi-equation model performed better than the two equation models. In fact, the existence of four pairs of counter rotating cells, in the straight duct upstream of the bend, were predicted by the RSM closure but not by the standard eddy viscosity model nor the SST k-ω model. The analysis of the results led to a better understanding of the induced three dimensional secondary flows and the behavior of the local pressure coefficient and the friction coefficient.

Keywords: curved duct, counter-rotating cells, secondary flow, laminar, turbulent

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Authors: Carl van Walraven, Meltem Tuna

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Background: Network meta-analysis (NMA) quantifies the relative efficacy of 3 or more interventions from studies containing a subgroup of interventions. This study applied the analytical approach of NMA to quantify the relative accuracy of prediction models with distinct inclusion criteria that are evaluated on a common population (‘concurrent external validation’). Methods: We simulated binary events in 5000 patients using a known risk function. We biased the risk function and modified its precision by pre-specified amounts to create 15 prediction models with varying accuracy and distinct patient applicability. Prediction model accuracy was measured using the Scaled Brier Score (SBS). Overall prediction model accuracy was measured using fixed-effects methods that accounted for model applicability patterns. Prediction model accuracy was summarized as the Network Relative Model Accuracy (NeRMA) Score which ranges from -∞ through 0 (accuracy of random guessing) to 1 (accuracy of most accurate model in concurrent external validation). Results: The unbiased prediction model had the highest SBS. The NeRMA score correctly ranked all simulated prediction models by the extent of bias from the known risk function. A SAS macro and R-function was created to implement the NeRMA Score. Conclusions: The NeRMA Score makes it possible to quantify the accuracy of binomial prediction models having distinct inclusion criteria in a concurrent external validation.

Keywords: prediction model accuracy, scaled brier score, fixed effects methods, concurrent external validation

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Authors: Lisandy A. Suryana, Lidia Mayangsari, Santi Novani

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Creative industry in Indonesia become an important aspect of the economy. One of the sectors of creative industry which give the highest contribution toward Indonesia’s GDP is fashion sector. In line with the target of Indonesia in 2020 to be the qibla’ of moeslem fashion of the world, all of the stakeholders of the business ecosystem should collaborate. Rather than focus on the internal aspects of producer, external aspects such as customers, government, community, etc. become important to be involved in the ecosystem to support the development and sustainability of those fashion sector. Unfortunately, although Indonesia has the biggest moeslem population, the number of hijab business penetration only 10%. Therefore, this research aims to analyze and develop the virtual co-creation platform for hijab creative industry as the strategy to achieve sustainability and increase the market share. This preliminary research describes the main stakeholders in the hijab creative industry based on business model approach. This business model is adapted by considering the service science context, and the data is collected by using the qualitative approach especially in-depth interview. This business model shows the relationship between resource integration, value co-creation, the value proposition of the company, and also the financial aspect of the business.

Keywords: value co-creation, Hijab Fashion Industry, creative industry, service business model, business model canvas

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Authors: Chuan Yang, Jing Bie, Panagiotis Psimoulis, Zhong Wang

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Modelling and understanding vehicle volume distribution over the urban network are essential for urban design and transport planning. The space syntax approach was widely applied as the main conceptual and methodological framework for contemporary vehicle volume models with the help of the statistical method of multiple regression analysis (MRA). However, the MRA model with space syntax variables shows a limitation in vehicle volume predicting in accounting for the crossed effect of the urban configurational characters and socio-economic factors. The aim of this paper is to construct models by interacting with the combined impact of the street network structure and socio-economic factors. In this paper, we present a multilevel linear (ML) and an agent-based (AB) vehicle volume model at an urban scale interacting with space syntax theoretical framework. The ML model allowed random effects of urban configurational characteristics in different urban contexts. And the AB model was developed with the incorporation of transformed space syntax components of the MRA models into the agents’ spatial behaviour. Three models were implemented in the same urban environment. The ML model exhibit superiority over the original MRA model in identifying the relative impacts of the configurational characters and macro-scale socio-economic factors that shape vehicle movement distribution over the city. Compared with the ML model, the suggested AB model represented the ability to estimate vehicle volume in the urban network considering the combined effects of configurational characters and land-use patterns at the street segment level.

Keywords: space syntax, vehicle volume modeling, multilevel model, agent-based model

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Authors: Babak H. Tabrizi, Seyed Farid Ghaderi

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Concurrent planning of project scheduling and material ordering can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance.

Keywords: material ordering, project scheduling, quantity discount, space availability

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Authors: Ahmad K. Samaila, Basant K. Jha

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This study is devoted to investigate the effect of transpiration on transient as well as steady-state natural convection flow of a reactive viscous fluid in a vertical channel formed by two infinite vertical parallel porous plates. The Boussinesq assumption is applied and the nonlinear governing equations of energy and momentum are developed. The problem is solved numerically using implicit finite difference method and analytically for steady-state case using perturbation method. Solutions are presented in graphical form for fluid temperature, velocity, and skin-friction and wall heat transfer rate for various parametric values. It is found that velocity, temperature, rate of heat transfer as well as skin-friction are strongly affected by mass leakage through the porous plates.

Keywords: transpiration, reactive viscous fluid, porous plates, natural convection, suction/injection

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Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

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The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

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Authors: Murat Gunduz, Mustafa Ozdemir

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In this research, a framework is to be proposed to model the safety performance in construction sites. Determinants of safety performance are to be defined through extensive literature review and a multidimensional safety performance model is to be developed. In this context, a questionnaire is to be administered to construction companies with sites. The collected data through questionnaires including linguistic terms are then to be defuzzified to get concrete numbers by using fuzzy set theory which provides strong and significant instruments for the measurement of ambiguities and provides the opportunity to meaningfully represent concepts expressed in the natural language. The validity of the proposed safety performance model, relationships between determinants of safety performance are to be analyzed using the structural equation modeling (SEM) which is a highly strong multi variable analysis technique that makes possible the evaluation of latent structures. After validation of the model, a safety performance index assessment tool is to be proposed by the help of software. The proposed safety performance assessment tool will be based on the empirically validated theoretical model.

Keywords: Fuzzy set theory, safety performance assessment, safety index, structural equation modeling (SEM), construction sites

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Authors: Min Kyung An

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In this paper, we study the data collection problem in Wireless Sensor Networks (WSNs) adopting the two interference models: The graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR). The main issue of the problem is to compute schedules with the minimum number of timeslots, that is, to compute the minimum latency schedules, such that data from every node can be collected without any collision or interference to a sink node. While existing works studied the problem with unit-sized and unbounded-sized message models, we investigate the problem with the bounded-sized message model, and introduce a constant factor approximation algorithm. To the best known of our knowledge, our result is the first result of the data collection problem with bounded-sized model in both interference models.

Keywords: data collection, collision-free, interference-free, physical interference model, SINR, approximation, bounded-sized message model, wireless sensor networks

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Authors: Jaroslav Krutil, František Pochylý, Simona Fialová, Vladimír Habán

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A mathematical model of the additional effects of the liquid in the hydrodynamic gap is presented in the paper. An in-compressible viscous fluid is considered. Based on computational modeling are determined the matrices of mass, stiffness and damping. The mathematical model is experimentally verified.

Keywords: computational modeling, mathematical model, hydrodynamic gap, matrices of mass, stiffness and damping

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Authors: Md. Jahoor Alam

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Recent studies suggest that Glucose controls several lifesaving pathways. Glucose molecule is reported to be responsible for the production of ROS (reactive oxygen species). In the present work, a p53-MDM2-Glucose model is developed in order to study spatiotemporal properties of the p53 pathway. The systematic model is mathematically described. The model is numerically simulated using high computational facility. It is observed that the variation in glucose concentration level triggers the system at different states, namely, oscillation death (stabilized), sustain and damped oscillations which correspond to various cellular states. The transition of these states induced by glucose is phase transition-like behaviour. Further, the amplitude of p53 dynamics with the variation of glucose concentration level follows power law behaviour, As(k) ~ kϒ, where, ϒ is a constant. Further Stochastic approach is needed for understanding of realistic behaviour of the model. The present model predicts the variation of p53 states under the influence of glucose molecule which is also supported by experimental facts reported by various research articles.

Keywords: oscillation, temporal behavior, p53, glucose

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Authors: Emiliano Lustrissimi, Bonifacio Bianco, Sebastiano Caravaggi, Antonio Rosato

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A mathematical framework has been designed to enhance the configuration of an end-of-production-line (EOL) test bench. This system can be used to assess the performance of electric motors or axles intended for electric vehicles. The model has been developed to predict the behaviour of EOL test benches and electric motors/axles under various boundary conditions, eliminating the need for extensive physical testing and reducing the corresponding power consumption. The suggested model is versatile, capable of being utilized across various types of electric motors or axles, and adaptable to accommodate varying power ratings of electric motors or axles. The maximum performance to be guaranteed by the EMs according to the car maker's specifications are taken as inputs in the model. Then, the required performance of each main EOL test bench component is calculated, and the corresponding systems available on the market are selected based on manufacturers’ catalogues. In this study, an EOL test bench has been designed according to the proposed model outputs for testing a low-power (about 22 kW) electric axle. The performance of the designed EOL test bench has been measured and used to validate the proposed model and assess both the consistency of the constraints as well as the accuracy of predictions in terms of electric demands. The comparison between experimental and predicted data exhibited a reasonable agreement, allowing to demonstrate that, despite some discrepancies, the model gives an accurate representation of the EOL test benches' performance.

Keywords: electric motors, electric vehicles, end-of-production-line test bench, mathematical model, field tests

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Authors: Bing Li, Zhi Li, Yilong Yang

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Web classification can promote the quality of service discovery and management in the service repository. It is widely used to locate developers desired services. Although traditional classification methods based on supervised learning models can achieve classification tasks, developers need to manually mark web services, and the quality of these tags may not be enough to establish an accurate classifier for service classification. With the doubling of the number of web services, the manual tagging method has become unrealistic. In recent years, the attention mechanism has made remarkable progress in the field of deep learning, and its huge potential has been fully demonstrated in various fields. This paper designs a multi-head attention graph convolutional network (MHAGCN) service classification method, which can assign different weights to the neighborhood nodes without complicated matrix operations or relying on understanding the entire graph structure. The framework combines the advantages of the attention mechanism and graph convolutional neural network. It can classify web services through automatic feature extraction. The comprehensive experimental results on a real dataset not only show the superior performance of the proposed model over the existing models but also demonstrate its potentially good interpretability for graph analysis.

Keywords: attention mechanism, graph convolutional network, interpretability, service classification, service discovery

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Authors: Yuan Zheng

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3D model-based vehicle matching provides a new way for vehicle recognition, localization and tracking. Its key is to construct an evaluation function, also called fitness function, to measure the degree of vehicle matching. The existing fitness functions often poorly perform when the clutter and occlusion exist in traffic scenarios. In this paper, we present a practical and efficient fitness function. Unlike the existing evaluation functions, the proposed fitness function is to study the vehicle matching problem from both local and global perspectives, which exploits the pixel gradient information as well as the silhouette information. In view of the discrepancy between 3D vehicle model and real vehicle, a weighting strategy is introduced to differently treat the fitting of the model’s wireframes. Additionally, a normalization operation for the model’s projection is performed to improve the accuracy of the matching. Experimental results on real traffic videos reveal that the proposed fitness function is efficient and robust to the cluttered background and partial occlusion.

Keywords: 3D-2D matching, fitness function, 3D vehicle model, local image gradient, silhouette information

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Authors: M. Kamal M. Shah, Noorhifiantylaily Ahmad, O. Irma Wani, J. Sahari

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This paper presents the computationally mechanics analysis of energy absorption for cylindrical and square thin wall tubed structure by using ABAQUS/explicit. The crashworthiness behavior of AISI 1020 mild steel thin-walled tube under axial loading has been studied. The influence effects of different model’s cross-section, as well as model length on the crashworthiness behavior of thin-walled tube, are investigated. The model was placed on loading platform under axial loading with impact velocity of 5 m/s to obtain the deformation results of each model under quasi-static loading. The results showed that model undergoes different deformation mode exhibits different energy absorption performance.

Keywords: axial loading, computational mechanics, energy absorption performance, crashworthiness behavior, deformation mode

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Authors: R. V. Dahibhate, A. B. Deoghare, P. M. Padole

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Maintaining natural integrity of biosystem is paramount significant for orthopedic surgeon while performing surgery. Restoration is challenging task to rehabilitate trauma patient. Drilling is an inevitable procedure to fix implants. The task leads to rise in temperature at the contact site which intends to thermal necrosis. A precise monitoring can avoid thermal necrosis. To accomplish it, data acquiring instrument is integrated with the drill bit. To contemplate it, electronic feedback system is developed. It not only measures temperature without any physical contact in between measuring device and target but also visualizes the site and monitors correct movement of tool path. In the current research work an infrared thermometer data acquisition system is used which monitors variation in temperature at the drilling site and a camera captured movement of drill bit advancement. The result is presented in graphical form which represents variations in temperature, drill rotation and time. A feedback system helps in keeping drill speed in threshold limit.

Keywords: thermal necrosis, infrared thermometer, drilling tool, feedback system

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Authors: Kaouther Selmi, Alaeddine Sridi, Mohamed Bouallegue, Kais Bouallegue

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Neurons are the fundamental units of the brain and the nervous system. The variable structure model of neurons consists of a system of differential equations with various parameters. By optimizing these parameters, we can create a unique model that describes the dynamic behavior of a single neuron. We introduce a neural network based on neurons with multiple dendrites employing an activation function with a variable structure. In this paper, we present a model for heart behavior. Finally, we showcase our successful simulation of the heart's ECG diagram using our Variable Structure Neuron Model (VSMN). This result could provide valuable insights into cardiology.

Keywords: neural networks, neuron, dendrites, heart behavior, ECG

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Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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Authors: Loreine Makki, Marc Anthony Mannah, Christophe Batard, Nicolas Ginot, Julien Weckbrodt

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Planar transformers are extensively utilized in high-frequency, high power density power electronic converters. The breakthrough of wide-bandgap technology compelled power electronic system miniaturization while inducing pivotal effects on system modeling and manufacturing within the power electronics industry. A significant consideration to simulate and model the unanticipated parasitic parameters emerges with the requirement to mitigate electromagnetic disturbances. This paper will present an equivalent circuit model of a shielded pulse planar transformer quantifying leakage inductance and resistance in addition to the interwinding capacitance of the primary and secondary windings. ANSYS Q3D Extractor was utilized to model and simulate the transformer, intending to study the immunity of the simulated equivalent model to high dv/dt occurrences. A convenient correlation between simulation and experimental results is presented.

Keywords: Planar transformers, wide-band gap, equivalent circuit model, shielded, ANSYS Q3D Extractor, dv/dt

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Authors: Kanica Goel, Nilam

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Infectious diseases are a leading cause of death worldwide and hence a great challenge for every nation. Thus, it becomes utmost essential to prevent and reduce the spread of infectious disease among humans. Mathematical models help to better understand the transmission dynamics and spread of infections. For this purpose, in the present article, we have proposed a nonlinear time-delayed SVIRS (Susceptible-Vaccinated-Infected-Recovered-Susceptible) mathematical model with nonlinear type incidence rate and nonlinear type treatment rate. Analytical study of the model shows that model exhibits two types of equilibrium points, namely, disease-free equilibrium and endemic equilibrium. Further, for the long-term behavior of the model, stability of the model is discussed with the help of basic reproduction number R₀ and we showed that disease-free equilibrium is locally asymptotically stable if the basic reproduction number R₀ is less than one and unstable if the basic reproduction number R₀ is greater than one for the time lag τ≥0. Furthermore, when basic reproduction number R₀ is one, using center manifold theory and Casillo-Chavez and Song theorem, we showed that the model undergoes transcritical bifurcation. Moreover, numerical simulations are being carried out using MATLAB 2012b to illustrate the theoretical results.

Keywords: nonlinear incidence rate, nonlinear treatment rate, stability, time delayed SVIRS epidemic model

Procedia PDF Downloads 140