Search results for: modified simplex algorithm

Authors: Qiang Zhang, Xiaojian Hu

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In multi-vehicle tracking, based on feature selection, the tracking system efficiently tracks vehicles in a video with minimal error in combination with color attribution, which focuses on presenting a simple and fast, yet accurate and robust solution to the problem such as inaccurately and untimely responses of statistics-based adaptive traffic control system in the intersection scenario. In this study, a real-time tracking system is proposed for multi-vehicle tracking in the intersection scene. Considering the complexity and application feasibility of the algorithm, in the object detection step, the detection result provided by virtual loops were post-processed and then used as the input for the tracker. For the tracker, lightweight methods were designed to extract and select features and incorporate them into the adaptive color tracking (ACT) framework. And the approbatory online feature selection algorithms are integrated on the mature ACT system with good compatibility. The proposed feature selection methods and multi-vehicle tracking method are evaluated on KITTI datasets and show efficient vehicle tracking performance when compared to the other state-of-the-art approaches in the same category. And the system performs excellently on the video sequences recorded at the intersection. Furthermore, the presented vehicle tracking system is suitable for surveillance applications.

Keywords: real-time, multi-vehicle tracking, feature selection, color attribution

Procedia PDF Downloads 163

Authors: J. K. Adedeji, S. T. Ijatuyi

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The application of neural network using pattern recognition to study the fluid dynamics and predict the groundwater reservoirs properties has been used in this research. The essential of geophysical survey using the manual methods has failed in basement environment, hence the need for an intelligent computing such as predicted from neural network is inevitable. A non-linear neural network with an XOR (exclusive OR) output of 8-bits configuration has been used in this research to predict the nature of groundwater reservoirs and fluid dynamics of a typical basement crystalline rock. The control variables are the apparent resistivity of weathered layer (p₁), fractured layer (p₂), and the depth (h), while the dependent variable is the flow parameter (F=λ). The algorithm that was used in training the neural network is the back-propagation coded in C++ language with 300 epoch runs. The neural network was very intelligent to map out the flow channels and detect how they behave to form viable storage within the strata. The neural network model showed that an important variable g_r (gravitational resistance) can be deduced from the elevation and apparent resistivity p_a. The model results from SPSS showed that the coefficients, a, b and c are statistically significant with reduced standard error at 5%.

Keywords: gravitational resistance, neural network, non-linear, pattern recognition

Procedia PDF Downloads 213

Authors: Lubabatu Sada Sodangi

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The rapid growth in exchange and accessibility of information via the internet makes many organisations acquire data on their own operation. The aim of data mining is to analyse the different behaviour of a dataset using observation. Although, the subset of the dataset being analysed may not display all the behaviours and relationships of the entire data and, therefore, may not represent other parts that exist in the dataset. There is a range of techniques used in data mining to determine the hidden or unknown information in datasets. In this paper, the performance of two algorithms Chi-Square Automatic Interaction Detection (CHAID) and multilayer perceptron (MLP) would be matched using an Adult dataset to find out the percentage of an/the adults that earn > 50k and those that earn <= 50k per year. The two algorithms were studied and compared using IBM SPSS statistics software. The result for CHAID shows that the most important predictors are relationship and education. The algorithm shows that those are married (husband) and have qualification: Bachelor, Masters, Doctorate or Prof-school whose their age is > 41<57 earn > 50k. Also, multilayer perceptron displays marital status and capital gain as the most important predictors of the income. It also shows that individuals that their capital gain is less than 6,849 and are single, separated or widow, earn <= 50K, whereas individuals with their capital gain is > 6,849, work > 35 hrs/wk, and > 27yrs their income will be > 50k. By comparing the two algorithms, it is observed that both algorithms are reliable but there is strong reliability in CHAID which clearly shows that relation and education contribute to the prediction as displayed in the data visualisation.

Keywords: data mining, CHAID, multi-layer perceptron, SPSS, Adult dataset

Procedia PDF Downloads 378

Authors: Peter Akayuure

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One key determinant of the quality of mathematics learning is the teacher’s ability to assess students adequately and effectively and make assessment an integral part of the instructional practices. If the mathematics teacher lacks the required literacy to perform classroom assessment roles, the true trajectory of learning success and attainment of curriculum expectations might be indeterminate. It is therefore important that educators and policymakers understand and seek ways to improve the literacy level of mathematics teachers to implement classroom assessments that would meet curriculum demands. This study employed a descriptive survey design to explore perceived levels of assessment literacy of mathematics teachers to implement classroom assessment with the school based assessment framework in Ghana. A 25-item classroom assessment inventory on teachers’ assessment scenarios was adopted, modified, and administered to a purposive sample of 48 mathematics teachers from eleven Senior High Schools. Seven other items were included to further collect data on their self-efficacy towards assessment literacy. Data were analyzed using descriptive and bivariate correlation statistics. The result shows that, on average, 48.6% of the mathematics teachers attained standard levels of assessment literacy. Specifically, 50.0% met standard one in choosing appropriate assessment methods, 68.3% reached standard two in developing appropriate assessment tasks, 36.6% reached standard three in administering, scoring, and interpreting assessment results, 58.3% reached standard four in making appropriate assessment decisions, 41.7% reached standard five in developing valid grading procedures, 45.8% reached standard six in communicating assessment results, and 36.2 % reached standard seven by identifying unethical, illegal and inappropriate use of assessment results. Participants rated their self-efficacy belief in performing assessments high, making the relationships between participants’ assessment literacy scores and self-efficacy scores weak and statistically insignificant. The study recommends that institutions training mathematics teachers or providing professional developments should accentuate assessment literacy development to ensure standard assessment practices and quality instruction in mathematics education at senior high schools.

Keywords: assessment literacy, mathematics teacher, senior high schools, Ghana

Procedia PDF Downloads 133

Authors: T. Sattarpour, D. Nazarpour

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This paper investigates the effect of simultaneous placement of DGs and smart meters (SMs), on voltage profile improvement in active distribution networks (ADNs). A substantial center of attention has recently been on responsive loads initiated in power system problem studies such as distributed generations (DGs). Existence of responsive loads in active distribution networks (ADNs) would have undeniable effect on sizing and siting of DGs. For this reason, an optimal framework is proposed for sizing and siting of DGs and SMs in ADNs. SMs are taken into consideration for the sake of successful implementing of demand response programs (DRPs) such as direct load control (DLC) with end-side consumers. Looking for voltage profile improvement, the optimization procedure is solved by genetic algorithm (GA) and tested on IEEE 33-bus distribution test system. Different scenarios with variations in the number of DG units, individual or simultaneous placing of DGs and SMs, and adaptive power factor (APF) mode for DGs to support reactive power have been established. The obtained results confirm the significant effect of DRPs and APF mode in determining the optimal size and site of DGs to be connected in ADN resulting to the improvement of voltage profile as well.

Keywords: active distribution network (ADN), distributed generations (DGs), smart meters (SMs), demand response programs (DRPs), adaptive power factor (APF)

Procedia PDF Downloads 303

Authors: Qais M. Yousef, Yasmeen A. Alshaer

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Over the last few years, the amount of data available on the globe has been increased rapidly. This came up with the emergence of recent concepts, such as the big data and the Internet of Things, which have furnished a suitable solution for the availability of data all over the world. However, managing this massive amount of data remains a challenge due to their large verity of types and distribution. Therefore, locating the required file particularly from the first trial turned to be a not easy task, due to the large similarities of names for different files distributed on the web. Consequently, the accuracy and speed of search have been negatively affected. This work presents a method using Electroencephalography signals to locate the files based on their contents. Giving the concept of natural mind waves processing, this work analyses the mind wave signals of different people, analyzing them and extracting their most appropriate features using multi-objective metaheuristic algorithm, and then classifying them using artificial neural network to distinguish among files with similar names. The aim of this work is to provide the ability to find the files based on their contents using human thoughts only. Implementing this approach and testing it on real people proved its ability to find the desired files accurately within noticeably shorter time and retrieve them as a first choice for the user.

Keywords: artificial intelligence, data contents search, human active memory, mind wave, multi-objective optimization

Procedia PDF Downloads 179

Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

Procedia PDF Downloads 139

Authors: Shidrokh Goudarzi, Wan Haslina Hassan

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Heterogeneous wireless networks are converging towards an all-IP network as part of the so-called next-generation network. In this paradigm, different access technologies need to be interconnected; thus, vertical handovers or vertical handoffs are necessary for seamless mobility. In this paper, we conduct a review of existing vertical handover decision-making mechanisms that aim to provide ubiquitous connectivity to mobile users. To offer a systematic comparison, we categorize these vertical handover measurement and decision structures based on their respective methodology and parameters. Subsequently, we analyze several vertical handover approaches in the literature and compare them according to their advantages and weaknesses. The paper compares the algorithms based on the network selection methods, complexity of the technologies used and efficiency in order to introduce our vertical handover decision framework. We find that vertical handovers on heterogeneous wireless networks suffer from the lack of a standard and efficient method to satisfy both user and network quality of service requirements at different levels including architectural, decision-making and protocols. Also, the consolidation of network terminal, cross-layer information, multi packet casting and intelligent network selection algorithm appears to be an optimum solution for achieving seamless service continuity in order to facilitate seamless connectivity.

Keywords: heterogeneous wireless networks, vertical handovers, vertical handover metric, decision-making algorithms

Procedia PDF Downloads 395

Authors: Isabel Moscol, Carlos J. Díaz, Ciro Rodríguez

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Hip replacement becomes necessary when a person suffers severe pain or considerable functional limitations and the best option to enhance their quality of life is through the replacement of the damaged joint. One of the main components in femoral prostheses is the stem which distributes the loads from the joint to the proximal femur. To preserve more bone stock and avoid weakening of the diaphysis, a short starting stem was selected, generated from the intramedullary morphology of the patient's femur. It ensures the implantability of the design and leads to geometric delimitation for personalized optimization with machine learning (ML) and metaheuristic algorithms. The present study attempts to design a cementless short stem to make the strain deviation before and after implantation close to zero, promoting its fixation and durability. Regression models developed to estimate the percentage change of maximum principal stresses were used as objective optimization functions by the metaheuristic algorithm. The latter evaluated different geometries of the short stem with the modification of certain parameters in oblique sections from the osteotomy plane. The optimized geometry reached a global stress shielding (SS) of 18.37% with a determination factor (R²) of 0.667. The predicted results favour implantability integration in the short stem optimization to effectively reduce SS in the proximal femur.

Keywords: machine learning techniques, metaheuristic algorithms, short-stem design, stress shielding, hip replacement

Procedia PDF Downloads 196

Authors: Fereshteh Pourmohammad, Mehdi Zare

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The city of Karaj, having a population of 2.2 millions (est. 2022) is located in the South West of Alborz Mountain Belt in Northern Iran. The region is known to be a highly active seismic zone. This study is focused on the geological and seismological analyses within a radius of 200 km from the center of Karaj. There are identified five seismic zones and seven linear seismic sources. The maximum magnitude was calculated for the seismic zones. Scine tghe seismicity catalog is incomplete, we have used a parametric-historic algorithm and the Kijko and Sellevoll (1992) method was used to calculate seismicity parameters, and the return periods and the probability frequency of recurrence of the earthquake magnitude in each zone obtained for 475-years return period. According to the calculations, the highest and lowest earthquake magnitudes of 7.6 and 6.2 were respectively obtained in Zones 1 and 4. This result is a new and extremely important in view point of earthquake risk in a densely population city. The maximum strong horizontal ground motion for the 475-years return period 0.42g and for 2475-year return period 0.70g also the maximum strong vertical ground motion for 475-years return period 0.25g and 2475-years return period 0.44g was calculated using attenuation relationships. These acceleration levels are new, and are obtained to be about 25% higher than presented values in the Iranian building code.

Keywords: seismic zones, ground motion, return period, hazard analysis

Procedia PDF Downloads 98

Authors: Patricia Jiménez, Rafael Corchuelo

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Nowadays the World Wide Web is the most popular source of information that relies on billions of on-line documents. Web mining is used to crawl through these documents, collect the information of interest and process it by applying data mining tools in order to use the gathered information in the best interest of a business, what enables companies to promote theirs. Unfortunately, it is not easy to extract the information a web site provides automatically when it lacks an API that allows to transform the user-friendly data provided in web documents into a structured format that is machine-readable. Rule-based information extractors are the tools intended to extract the information of interest automatically and offer it in a structured format that allow mining tools to process it. However, the performance of an information extractor strongly depends on the search heuristic employed since bad choices regarding how to learn a rule may easily result in loss of effectiveness and/or efficiency. Improving search heuristics regarding efficiency is of uttermost importance in the field of Web Information Extraction since typical datasets are very large. In this paper, we employ an information extractor based on a classical top-down algorithm that uses the so-called Information Gain heuristic introduced by Quinlan and Cameron-Jones. Unfortunately, the Information Gain relies on some well-known problems so we analyse an intuitive alternative, Termini, that is clearly more efficient; we also analyse other proposals in the literature and conclude that none of them outperforms the previous alternative.

Keywords: information extraction, search heuristics, semi-structured documents, web mining.

Procedia PDF Downloads 338

Authors: Wendy Carolina Gomez Ramirez, Rodulfo Ospina Torres

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Thygater aethiops is a species of solitary bee with a neotropical distribution that has been adapted to live in urban environments. This species of bee presents a marked sexual dimorphism since the males have antenna almost as long as their body different from the females that present antenna with smaller size. In this work, placoid sensilla were studied, which are structures that appear in the antenna and are involved in the detection of substances both, for reproduction and for the search of food. The aim of this study was to evaluate the differences between these sensory structures in the different sexes, for which males and females were captured. Later some body measures were taken such as fresh weight with abdomen and without it, since the weight could be modified by the stomach content; other measures were taken as the total antenna length and length of the flagellum and flagelomere. After negative imprints of the antenna were made using nail polish, the imprint was cut with a microblade and mounted onto a microscope slide. The placoid sensilla were visible on the imprint, so they were counted manually on the 100x objective lens of the optical microscope. Initially, the males presented a specific distribution pattern in two types of sensilla: trichoid and placoid, the trichoid were found aligned in the dorsal face of the antenna and the placoid were distributed along the entire antenna; that was different to the females since they did not present a distribution pattern the sensilla were randomly organized. It was obtained that the males, because they have a longer antenna, have a greater number of sensilla in relation to the females. Additionally, it was found that there was no relationship between the weight and the number of sensilla, but there was a positive relationship between the length of the antenna, the length of the flagellum and the number of sensilla. The relationship between the number of sensilla per unit area in each of the sexes was also calculated, which showed that, on average, males have 4.2 ± 0.38 sensilla per unit area and females present 2.2 ± 0.20 and likewise a significant difference between sexes. This dimorphism found may be related to the sexual behavior of the species, since it has been demonstrated that males are more adapted to the perception of substances related to reproduction than to the search of food.

Keywords: antenna, olfactory organ, sensilla, sexual dimorphism, solitary bees

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Authors: Xinhuang Wu, Yousef Sardahi

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A hybrid and optimal multi-loop control structure combining linear and nonlinear control algorithms are introduced in this paper to regulate the position of a quadcopter unmanned aerial vehicle (UAV) driven by four brushless DC motors. To this end, a nonlinear mathematical model of the UAV is derived and then linearized around one of its operating points. Using the nonlinear version of the model, a sliding mode control is used to derive the control laws of the motor thrust forces required to drive the UAV to a certain position. The linear model is used to design two controllers, XG-controller and YG-controller, responsible for calculating the required roll and pitch to maneuver the vehicle to the desired X and Y position. Three attitude controllers are designed to calculate the desired angular rates of rotors, assuming that the Euler angles are minimal. After that, a many-objective optimization problem involving 20 design parameters and ten objective functions is formulated and solved by HypE (Hypervolume estimation algorithm), one of the widely used many-objective optimization algorithms approaches. Both stability and performance constraints are imposed on the optimization problem. The optimization results in terms of Pareto sets and fronts are obtained and show that some of the design objectives are competing. That is, when one objective goes down, the other goes up. Also, Numerical simulations conducted on the nonlinear UAV model show that the proposed optimization method is quite effective.

Keywords: optimal control, many-objective optimization, sliding mode control, linear control, cascade controllers, UAV, drones

Procedia PDF Downloads 73

Authors: Shiri Elisheva Decktor, Sharon Hornstein

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Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

Procedia PDF Downloads 107

Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

Procedia PDF Downloads 500

Authors: Gabriel Sitler, Yousef Sardahi, Asad Salem

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This paper presents an optimal and robust sliding mode controller (SMC) to regulate the position of the knee joint angle for patients suffering from knee injuries. The controller imitates the role of active orthoses that produce the joint torques required to overcome gravity and loading forces and regain natural human movements. To this end, a mathematical model of the shank, the lower part of the leg, is derived first and then used for the control system design and computer simulations. The design of the controller is carried out in optimal and multi-objective settings. Four objectives are considered: minimization of the control effort and tracking error; and maximization of the control signal smoothness and closed-loop system’s speed of response. Optimal solutions in terms of the Pareto set and its image, the Pareto front, are obtained. The results show that there are trade-offs among the design objectives and many optimal solutions from which the decision-maker can choose to implement. Also, computer simulations conducted at different points from the Pareto set and assuming knee squat movement demonstrate competing relationships among the design goals. In addition, the proposed control algorithm shows robustness in tracking a standard gait signal when accounting for uncertainty in the shank’s parameters.

Keywords: optimal control, multi-objective optimization, sliding mode control, wearable knee exoskeletons

Procedia PDF Downloads 82

Authors: Dewi Juliah Ratnaningsih, Imas Sukaesih Sitanggang

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Classification is one of data mining techniques that aims to discover a model from training data that distinguishes records into the appropriate category or class. Data mining classification methods can be applied in education, for example, to determine the classification of non-active students in Indonesia Open University. This paper presents a comparison of three methods of classification: Naïve Bayes, Bagging, and C.45. The criteria used to evaluate the performance of three methods of classification are stratified cross-validation, confusion matrix, the value of the area under the ROC Curve (AUC), Recall, Precision, and F-measure. The data used for this paper are from the non-active Indonesia Open University students in registration period of 2004.1 to 2012.2. Target analysis requires that non-active students were divided into 3 groups: C1, C2, and C3. Data analyzed are as many as 4173 students. Results of the study show: (1) Bagging method gave a high degree of classification accuracy than Naïve Bayes and C.45, (2) the Bagging classification accuracy rate is 82.99 %, while the Naïve Bayes and C.45 are 80.04 % and 82.74 % respectively, (3) the result of Bagging classification tree method has a large number of nodes, so it is quite difficult in decision making, (4) classification of non-active Indonesia Open University student characteristics uses algorithms C.45, (5) based on the algorithm C.45, there are 5 interesting rules which can describe the characteristics of non-active Indonesia Open University students.

Keywords: comparative analysis, data mining, clasiffication, Bagging, Naïve Bayes, C.45, non-active students, Indonesia Open University

Procedia PDF Downloads 316

Authors: Om Prakash Bharti, Aanchal Verma, R. K. Saket

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The Doubly-Fed Induction Generator (DFIG) is suggested for Wind Energy Conversion System (WECS) to extract wind power. DFIG is preferably employed due to its robustness towards variable wind and rotor speed. DFIG has the adaptable property because the system parameters are smoothly dealt with, including real power, reactive power, DC-link voltage, and the transient and dynamic responses, which are needed to analyze constantly. The analysis becomes more prominent during any unusual condition in the electrical power system. Hence, the study and improvement in the system parameters and transient response performance of DFIG are required to be accomplished using some controlling techniques. For fulfilling the task, the present work implements and compares the optimization methods for the design of the DFIG controller for WECS. The bio-inspired optimization techniques are applied to get the optimal controller design parameters for DFIG-based WECS. The optimized DFIG controllers are then used to retrieve the transient response performance of the six-order DFIG model with a step input. The results using MATLAB/Simulink show the betterment of the Firefly algorithm (FFA) over other control techniques when compared with the other controller design methods.

Keywords: doubly-fed induction generator, wind turbine, wind energy conversion system, induction generator, transfer function, proportional, integral, derivatives

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Authors: Pradeep G. Siddheshwar, K. M. Lakshmi

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The present study deals with weakly non-linear stability analysis of Rayleigh-Benard-Brinkman convection in nanoliquid-saturated porous enclosures. The modified-Buongiorno-Brinkman model (MBBM) is used for the conservation of linear momentum in a nanoliquid-saturated-porous medium under the assumption of Boussinesq approximation. Thermal equilibrium is imposed between the base liquid and the nanoparticles. The thermophysical properties of nanoliquid are modeled using phenomenological laws and mixture theory. The fifth-order Lorenz model is derived for the problem and is then reduced to the first-order Ginzburg-Landau equation (GLE) using the multi-scale method. The analytical solution of the GLE for the amplitude is then used to quantify the heat transport in closed form, in terms of the Nusselt number. It is found that addition of dilute concentration of nanoparticles significantly enhances the heat transport and the dominant reason for the same is the high thermal conductivity of the nanoliquid in comparison to that of the base liquid. This aspect of nanoliquids helps in speedy removal of heat. The porous medium serves the purpose of retainment of energy in the system due to its low thermal conductivity. The present model helps in making a unified study for obtaining the results for base liquid, nanoliquid, base liquid-saturated porous medium and nanoliquid-saturated porous medium. Three different types of enclosures are considered for the study by taking different values of aspect ratio, and it is observed that heat transport in tall porous enclosure is maximum while that of shallow is the least. Detailed discussion is also made on estimating heat transport for different volume fractions of nanoparticles. Results of single-phase model are shown to be a limiting case of the present study. The study is made for three boundary combinations, viz., free-free, rigid-rigid and rigid-free.

Keywords: Boungiorno model, Ginzburg-Landau equation, Lorenz equations, porous medium

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Authors: Shubhita Mathur, Ritika Kar Bahal, Priyanka Chauhan, Anil K. Tyagi

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Mycobacterium tuberculosis, the causative agent of human tuberculosis, is a major cause of mortality. Bacillus Calmette-Guérin (BCG), the only licensed vaccine available for protection against tuberculosis confers highly variable protection ranging from 0%-80%. Thus, novel vaccine strains need to be evaluated for their potential as a vaccine against tuberculosis. We had previously constructed a triple gene mutant of M. tuberculosis (MtbΔmms), having deletions in genes encoding for phosphatases mptpA, mptpB, and sapM that are involved in host-pathogen interaction. Though vaccination with Mtb∆mms strain induced protection in the lungs of guinea pigs, the mutant strain was not able to control the hematogenous spread of the challenge strain to the spleens. Additionally, inoculation with Mtb∆mms resulted in some pathological damage to the spleens in the early phase of infection. In order to overcome the pathology caused by MtbΔmms in the spleens of guinea pigs and also to control the dissemination of the challenge strain, MtbΔmms was genetically modified by disrupting bioA gene to generate MtbΔmmsb strain. Further, in vivo attenuation of MtbΔmmsb was evaluated, and its protective efficacy was assessed against virulent M. tuberculosis challenge in guinea pigs. Our study demonstrates that Mtb∆mmsb mutant was highly attenuated for growth and virulence in guinea pigs. Vaccination with Mtb∆mmsb mutant generated significant protection in comparison to sham-immunized animals at 4 and 12 weeks post-infection in lungs and spleens of the infected animals. Our findings provide evidence that deletion of genes involved in signal transduction and biotin biosynthesis severely attenuates the pathogen and the single immunization with the auxotroph was able to provide significant protection as compared to sham-immunized animals. The protection imparted by Mtb∆mmsb fell short in comparison to the protection observed in BCG-immunized animals. This study nevertheless indicates the importance of attenuated multiple gene deletion mutants of M. tuberculosis in generating protection against tuberculosis.

Keywords: Mycobacterium tuberculosis, BCG, MtbΔmmsb, bioA, guinea pigs

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Authors: Richa Soni, Vibha Bhatnagar, N. K. Jain

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This study was conducted to develop a computer mediated programme for weight management and physical fitness and examining its efficacy in reducing weight and improving physical fitness in obese adults. A user friendly, computer based programme was developed to provide a simple, quick, easy and user-friendly method of assessing energy balance at individual level. The programme had four main sections viz. personal Profile, know about your weight, fitness and food exchange list. The computer programme was developed to provide facilities of creating individual profile, tracking meal and physical activities, suggesting nutritional and exercise requirements, planning calorie specific menus, keeping food diaries and revising the diet and exercise plans if needed. The programme was also providing information on obesity, underweight, physical fitness. An exhaustive food exchange list was also given in the programme to assist user to make right food choice decisions. The developed programme was evaluated by a panel of 15 experts comprising endocrinologists, nutritionists and diet counselors. Suggestions given by the experts were paned down and the entire programme was modified in light of suggestions given by the panel members and was reevaluated by the same panel of experts. For assessing the impact of the programme 22 obese subjects were selected purposively and randomly assigned to intervention group (n=12) and no information control group. (n=10). The programme group was asked to strictly follow the programme for one month. Significant reduction in the intake of energy, fat and carbohydrates was observed while intake of fruits, green leafy vegetables was increased. The programme was also found to be effective in reducing body weight, body fat percent and body fat mass whereas total body water and physical fitness scores improved significantly. There was no significant alteration observed in any parameters in the control group.

Keywords: body composition, body weight, computer programme, physical fitness

Procedia PDF Downloads 287

Authors: Omar Bouhassoun, Cristian Garrido, César Hueso

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The radiation shielding design is an optimization problem with multiple -constrained- objective functions (radiation dose, weight, price, etc.) that depend on several parameters (material, thickness, position, etc.). The classical approach for shielding design consists of a brute force trial-and-error process subject to previous designer experience. Therefore, the result is an empirical solution but not optimal, which can degrade the overall performance of the shielding. In order to automate the shielding design procedure, the IDOM Shielding Optimization Tool (ISOT) has been developed. This software combines optimization algorithms with the capabilities to read/write input files, run calculations, as well as parse output files for different radiation transport codes. In the first stage, the software was established to adjust the input files for two well-known Monte Carlo codes (MCNP and Serpent) and optimize the result (weight, volume, price, dose rate) using multi-objective genetic algorithms. Nevertheless, its modular implementation easily allows the inclusion of more radiation transport codes and optimization algorithms. The work related to the development of ISOT and its verification on a simple 3D multi-layer shielding problem using both MCNP and Serpent will be presented. ISOT looks very promising for achieving an optimal solution to complex shielding problems.

Keywords: optimization, shielding, nuclear, genetic algorithm

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Authors: Rachel Fanelwa Ajayi, Anovuyo Jonnas, Emmanuel I. Iwuoha

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Tuberculosis (TB) is an infectious disease caused by the bacterium (Mycobacterium tuberculosis) which has a predilection for lung tissue due to its rich oxygen supply. The mycobacterial cell has a unique innate characteristic which allows it to resist human immune systems and drug treatments; hence, it is one of the most difficult of all bacterial infections to treat, let alone to cure. At the same time, multi-drug resistance TB (MDR-TB) caused by poorly managed TB treatment, is a growing problem and requires the administration of expensive and less effective second line drugs which take much longer treatment duration than fist line drugs. Therefore, to acknowledge the issues of patients falling ill as a result of inappropriate dosing of treatment and inadequate treatment administration, a device with a fast response time coupled with enhanced performance and increased sensitivity is essential. This study involved the synthesis of electroactive platforms for application in the development of nano-biosensors suitable for the appropriate dosing of clinically diagnosed patients by promptly quantifying the levels of the TB drug; Isonaizid. These nano-biosensors systems were developed on gold surfaces using the enzyme N-acetyletransferase 2 coupled to the cysteamine modified poly(8-anilino-1-napthalene sulphonic acid)/zinc oxide nanocomposites. The morphology of ZnO nanoparticles, PANSA/ZnO nano-composite and nano-biosensors platforms were characterized using High-Resolution Transmission Electron Microscopy (HRTEM) and High-Resolution Scanning Electron Microscopy (HRSEM). On the other hand, the elemental composition of the developed nanocomposites and nano-biosensors were studied using Fourier Transform Infra-Red Spectroscopy (FTIR) and Energy Dispersive X-Ray (EDX). The electrochemical studies showed an increase in electron conductivity for the PANSA/ZnO nanocomposite which was an indication that it was suitable as a platform towards biosensor development.

Keywords: N-acetyletransferase 2, isonaizid, tuberculosis, zinc oxide

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Authors: Hyojin Lim, Cuong Nguyen Khac, Yeongyu Choi, Ho-Youl Jung

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In this paper, we propose a simple moving object detection, which is based on motion vectors obtained from pyramidal Lucas-Kanade optical flow. The proposed method detects moving objects such as pedestrians, the other vehicles and some obstacles at the front-side of the host vehicle, and it can provide the warning to the driver. Motion vectors are obtained by using pyramidal Lucas-Kanade optical flow, and some outliers are eliminated by comparing the amplitude of each vector with the pre-defined threshold value. The background model is obtained by calculating the mean and the variance of the amplitude of recent motion vectors in the rectangular shaped local region called the cell. The model is applied as the reference to classify motion vectors of moving objects and those of background. Motion vectors are clustered to rectangular regions by using the unsupervised clustering K-means algorithm. Labeling method is applied to label groups which is close to each other, using by distance between each center points of rectangular. Through the simulations tested on four kinds of scenarios such as approaching motorbike, vehicle, and pedestrians to host vehicle, we prove that the proposed is simple but efficient for moving object detection in parking lots.

Keywords: moving object detection, dynamic scene, optical flow, pyramidal optical flow

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Authors: Zair Firdaous, Fourka Mohamed, Elfelsoufi Zoubir

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The arrival of e-commerce has changed the supply chain management on the operational level as well as on the organization and strategic and even tactical decisions of the companies. The optimization of resources is an issue that is needed on the tactical and operational strategic plan. This work considers the allocation of resources in the case of pure players that have launched online sales. The aim is to improve the level of customer satisfaction and maintaining the benefits of e-retailer and of its cooperators and reducing costs and risks. We first modeled the B2C chain with all operations that integrates and possible scenarios since online retailers offer a wide selection of personalized service. The personalized services that online shopping companies offer to the clients can be embodied in many aspects, such as the customizations of payment, the distribution methods, and after-sales service choices. Every aspect of customized service has several modes. At that time, we analyzed the optimization problems of supply chain resource in customized online shopping service mode. Then, we realized an optimization model and algorithm for the development based on the analysis of the of the B2C supply chain resources. It is a multi-objective optimization that considers the collaboration of resources in operations, time and costs but also the risks and the quality of services as well as dynamic and uncertain characters related to the request.

Keywords: supply chain resource, e-commerce, pure-players, optimization

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Authors: Ronal Muresano, Andrea Pagano

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Nowadays, the mathematical/statistical applications are developed with more complexity and accuracy. However, these precisions and complexities have brought as result that applications need more computational power in order to be executed faster. In this sense, the multicore environments are playing an important role to improve and to optimize the execution time of these applications. These environments allow us the inclusion of more parallelism inside the node. However, to take advantage of this parallelism is not an easy task, because we have to deal with some problems such as: cores communications, data locality, memory sizes (cache and RAM), synchronizations, data dependencies on the model, etc. These issues are becoming more important when we wish to improve the application’s performance and scalability. Hence, this paper describes an optimization method developed for Systemic Model of Banking Originated Losses (SYMBOL) tool developed by the European Commission, which is based on analyzing the application's weakness in order to exploit the advantages of the multicore. All these improvements are done in an automatic and transparent manner with the aim of improving the performance metrics of our tool. Finally, experimental evaluations show the effectiveness of our new optimized version, in which we have achieved a considerable improvement on the execution time. The time has been reduced around 96% for the best case tested, between the original serial version and the automatic parallel version.

Keywords: algorithm optimization, bank failures, OpenMP, parallel techniques, statistical tool

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Authors: Nivatha Elangovan, Lakshman Neelakantan, Murugaiyan Amirthalingam

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Magnesium and its alloys are widely used for various lightweight engineering and biomedical applications as they render high strength to low weight ratio and excellent corrosion resistance. These alloys possess good bio-compatibility and similar mechanical properties to natural bone. However, manufacturing magnesium alloy components by conventional formative and subtractive methods is challenging due to their poor castability, oxidation potential, and machinability. Therefore, efforts are made to produce complex-design containing magnesium alloy components by additive manufacturing (AM). Arc-wire directed energy deposition (AW-DED), also known as wire arc additive manufacturing (WAAM), is more attractive to produce large volume components with increased productivity than any other AM technique. In this research work, efforts were made to optimise the deposition parameters to build thick-walled (about 10 mm) AZ31 magnesium alloy components by a gas metal arc (GMA) based AW-DED process. By using controlled dip short-circuiting metal transfer in a GMA process, depositions were carried out without defects and spatter formation. Current and voltage waveforms were suitably modified to achieve stable metal transfer. Moreover, the droplet transfer behaviour was analysed using high-speed image analysis and correlated with arc energy. Optical and scanning electron microscopy analyses were carried out to correlate the influence of deposition parameters with the microstructural evolution during deposition. The investigation reveals that by carefully controlling the current-voltage waveform and droplet transfer behaviour, it is possible to stabilise equiaxed grain microstructures in the deposited AZ31 components. The printed component exhibited an improved mechanical property as equiaxed grains improve the ductility and enhance the toughness. The equiaxed grains in the component improved the corrosion-resistant behaviour of other conventionally manufactured components.

Keywords: arc wire directed energy deposition, AZ31 magnesium alloy, equiaxed grain, corrosion

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Authors: Hsin-Chieh Lee, Fen-Ling Kuo, Jui-Chi Lin

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Background: Upper extremity functional impairment that occurs after stroke includes hemiplegia, synergy movement, muscle hypertonicity, and somatosensory impairment, which result in inefficient and inaccurate movement. Robot-assisted rehabilitation is an intensive training approach that is effective in sensorimotor and hand function recovery. However, these systems mostly focused on the proximal part of the upper limb rather than the distal part. The device used in our study was Gloreha Sinfonia, which focuses on the distal part of the upper limb and uses a dynamic support system to facilitate the whole limb function. The objective of this study was to investigate the effects of robot-assisted therapy (RT) with Gloreha device on sensorimotor, and ADLs in patients with stroke. Method: Patients with stroke (N=25) participated AB or BA (A = 12 RT sessions and B = 12 conventional therapy (CT) sessions) for 6 weeks (60 min at each session, twice a week), with 1-month break for washout period. The performance of the patients was assessed by a blinded assessor at 4 time points (pretest 1, posttest 1, pretest 2, posttest 2) which including the Fugl–Meyer Assessment-upper extremity (FMA-UE), box and block test, electromyography of the extensor digitorum communis (EDC) and brachioradialis, a grip dynamometer for motor evaluation; Semmes–Weinstein hand monofilament and Revision of the Nottingham Sensory Assessment for sensory evaluation; and the Modified Barthel Index (MBI) for assessing the ADL ability. Result: RT group significantly improved FMA-UE proximal scores (p = 0.038), FMA-UE total scores (p = 0.046), and MBI (p = 0.030). The EDC exhibited higher efficiency during the small block grasping task in the RT group than in the CT group (p = 0.050). Conclusions: RT with the Gloreha device might lead to beneficial effects on arm motor function, ADL ability, and EDC muscle recruitment efficacy in patients with subacute to chronic stroke.

Keywords: activities of daily living, hand function, robotic rehabilitation, stroke

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Authors: Rekha M. Y., Punith Kumar, Anshul Kamboj, Chandan Srivastava

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Coatings plays an important role in providing protection for a substrate and in improving the surface quality. Graphene/graphene oxide (GO) using in coating systems provides an environmental friendly solution towards protection against corrosion. Issues such as, lack of scale, high cost, low quality limits the practical application of graphene/GO as corrosion resistant coating material. One other way to employ these materials for corrosion protection is to incorporate them into coatings that are conventionally used for corrosion protection. Due to the extraordinary properties of graphene/GO, it has been demonstrated that the coatings containing graphene/GO are more corrosion resistant than pure metal/alloy coatings. In the present work, Cr-graphene and SnZn-GO composite coatings were investigated in enhancing the corrosion resistant property when compared to pure Cr coating and pure SnZn coating respectively. All the coatings were electrodeposited over mild-steel substrate. Graphene and GO were synthesized by electrochemical exfoliation method and modified Hummers’ method respectively. In Cr coatings, the microstructural study revealed that the addition of formic acid in the coatings reduced the number of cracks in the coatings. Further addition of graphene in Cr coating enhanced the Cr coating’s morphology. Chemically synthesized ZnO nanoparticles were also embedded in the as-deposited Cr and Cr-graphene coatings to enhance the adhesion of the coating, to improve the surface finish and to increase the corrosion resistant property of the coatings. Diffraction analysis revealed that the addition of graphene also altered the texture of the Cr coatings. In SnZn alloy coatings, the morphological and topographical characterization revealed that the relative smoothness and compactness of the coatings increased with increase in the addition of GO in the coatings. The microstructural investigation revealed large-scale segregation of Zn-rich and Sn-rich phases in the pure SnZn coating. However, in SnZn-GO composite coating the uniform distribution of Zn phase in the Sn-rich matrix was observed. This distribution caused the early and uniform formation of ZnO, which is the corrosion product, yielding better corrosion resistance for the SnZn-GO composite coatings as compared to pure SnZn coating. A significant improvement in corrosion resistance in terms of reduction in corrosion current and corrosion rate and increase in the polarization resistance was observed in Cr coating containing graphene and in SnZn coatings containing GO.

Keywords: coatings, corrosion, electrodeposition, graphene, graphene-oxide

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Authors: Wen Li, Zhengyu Bai, Qi Zhang

Abstract:

The demand for smart scheduling platform in agriculture, particularly in the scheduling process of machinery equipment, is high. With the continuous development of agricultural machinery equipment technology, a large number of agricultural machinery equipment and agricultural machinery cooperative service organizations continue to appear in China. The large area of cultivated land and a large number of agricultural activities in the central and western regions of China have made the demand for smart and efficient agricultural machinery equipment scheduling platforms more intense. In this study, we design and implement a platform for agricultural machinery equipment scheduling to allocate agricultural machinery equipment resources reasonably. With agricultural machinery equipment scheduling platform taken as the research object, we discuss its research significance and value, use the service blueprint technology to analyze and characterize the agricultural machinery equipment schedule workflow, the network analytic method to obtain the demand platform function requirements, and divide the platform functions through the platform function division diagram. Simultaneously, based on the case-based reasoning (CBR) algorithm, the equipment scheduling module of the agricultural machinery equipment scheduling platform is realized; finally, a design scheme of the agricultural machinery equipment scheduling platform architecture is provided, and the visualization interface of the platform is established via VB programming language. It provides design ideas and theoretical support for the construction of a modern agricultural equipment information scheduling platform.

Keywords: case-based reasoning, service blueprint, system design, ANP, VB programming language

Procedia PDF Downloads 176