Search results for: stiff initial value problem
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10052

Search results for: stiff initial value problem

9302 Solving Single Machine Total Weighted Tardiness Problem Using Gaussian Process Regression

Authors: Wanatchapong Kongkaew

Abstract:

This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.

Keywords: Gaussian process regression, iterated local search, simulated annealing, single machine total weighted tardiness

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9301 Cars in a Neighborhood: A Case of Sustainable Living in Sector 22 Chandigarh

Authors: Maninder Singh

Abstract:

The Chandigarh city is under the strain of exponential growth of car density across various neighborhood. The consumerist nature of society today is to be blamed for this menace because everyone wants to own and ride a car. Car manufacturers are busy selling two or more cars per household. The Regional Transport Offices are busy issuing as many licenses to new vehicles as they can in order to generate revenue in the form of Road Tax. The car traffic in the neighborhoods of Chandigarh has reached a tipping point. There needs to be a more empirical and sustainable model of cars per household, which should be based on specific parameters of livable neighborhoods. Sector 22 in Chandigarh is one of the first residential sectors to be established in the city. There is scope to think, reflect, and work out a method to know how many cars we need to sell our citizens before we lose the argument to traffic problems, parking problems, and road rage. This is where the true challenge of a planner or a designer of the city lies. Currently, in Chandigarh city, there are no clear visible answers to this problem. The way forward is to look at spatial mapping, planning, and design of car parking units to address the problem, rather than suggesting extreme measures of banning cars (short-term) or promoting plans for citywide transport (very long-term). This is a chance to resolve the problem with a pragmatic approach from a citizen’s perspective, instead of an orthodox development planner’s methodology. Since citizens are at the center of how the problem is to be addressed, acceptable solutions are more likely to emerge from the car and traffic problem as defined by the citizens. Thus, the idea and its implementation would be interesting in comparison to the known academic methodologies. The novel and innovative process would lead to a more acceptable and sustainable approach to the issue of number of car parks in the neighborhood of Chandigarh city.

Keywords: cars, Chandigarh, neighborhood, sustainable living, walkability

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9300 Particle Filter State Estimation Algorithm Based on Improved Artificial Bee Colony Algorithm

Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

Abstract:

In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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9299 A Column Generation Based Algorithm for Airline Cabin Crew Rostering Problem

Authors: Nan Xu

Abstract:

In airlines, the crew scheduling problem is usually decomposed into two stages: crew pairing and crew rostering. In the crew pairing stage, pairings are generated such that each flight is covered by exactly one pairing and the overall cost is minimized. In the crew rostering stage, the pairings generated in the crew pairing stage are combined with off days, training and other breaks to create individual work schedules. The paper focuses on cabin crew rostering problem, which is challenging due to the extremely large size and the complex working rules involved. In our approach, the objective of rostering consists of two major components. The first is to minimize the number of unassigned pairings and the second is to ensure the fairness to crew members. There are two measures of fairness to crew members, the number of overnight duties and the total fly-hour over a given period. Pairings should be assigned to each crew member so that their actual overnight duties and fly hours are as close to the expected average as possible. Deviations from the expected average are penalized in the objective function. Since several small deviations are preferred than a large deviation, the penalization is quadratic. Our model of the airline crew rostering problem is based on column generation. The problem is decomposed into a master problem and subproblems. The mater problem is modeled as a set partition problem and exactly one roster for each crew is picked up such that the pairings are covered. The restricted linear master problem (RLMP) is considered. The current subproblem tries to find columns with negative reduced costs and add them to the RLMP for the next iteration. When no column with negative reduced cost can be found or a stop criteria is met, the procedure ends. The subproblem is to generate feasible crew rosters for each crew member. A separate acyclic weighted graph is constructed for each crew member and the subproblem is modeled as resource constrained shortest path problems in the graph. Labeling algorithm is used to solve it. Since the penalization is quadratic, a method to deal with non-additive shortest path problem using labeling algorithm is proposed and corresponding domination condition is defined. The major contribution of our model is: 1) We propose a method to deal with non-additive shortest path problem; 2) Operation to allow relaxing some soft rules is allowed in our algorithm, which can improve the coverage rate; 3) Multi-thread techniques are used to improve the efficiency of the algorithm when generating Line-of-Work for crew members. Here a column generation based algorithm for the airline cabin crew rostering problem is proposed. The objective is to assign a personalized roster to crew member which minimize the number of unassigned pairings and ensure the fairness to crew members. The algorithm we propose in this paper has been put into production in a major airline in China and numerical experiments show that it has a good performance.

Keywords: aircrew rostering, aircrew scheduling, column generation, SPPRC

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9298 Numerical Solution of Portfolio Selecting Semi-Infinite Problem

Authors: Alina Fedossova, Jose Jorge Sierra Molina

Abstract:

SIP problems are part of non-classical optimization. There are problems in which the number of variables is finite, and the number of constraints is infinite. These are semi-infinite programming problems. Most algorithms for semi-infinite programming problems reduce the semi-infinite problem to a finite one and solve it by classical methods of linear or nonlinear programming. Typically, any of the constraints or the objective function is nonlinear, so the problem often involves nonlinear programming. An investment portfolio is a set of instruments used to reach the specific purposes of investors. The risk of the entire portfolio may be less than the risks of individual investment of portfolio. For example, we could make an investment of M euros in N shares for a specified period. Let yi> 0, the return on money invested in stock i for each dollar since the end of the period (i = 1, ..., N). The logical goal here is to determine the amount xi to be invested in stock i, i = 1, ..., N, such that we maximize the period at the end of ytx value, where x = (x1, ..., xn) and y = (y1, ..., yn). For us the optimal portfolio means the best portfolio in the ratio "risk-return" to the investor portfolio that meets your goals and risk ways. Therefore, investment goals and risk appetite are the factors that influence the choice of appropriate portfolio of assets. The investment returns are uncertain. Thus we have a semi-infinite programming problem. We solve a semi-infinite optimization problem of portfolio selection using the outer approximations methods. This approach can be considered as a developed Eaves-Zangwill method applying the multi-start technique in all of the iterations for the search of relevant constraints' parameters. The stochastic outer approximations method, successfully applied previously for robotics problems, Chebyshev approximation problems, air pollution and others, is based on the optimal criteria of quasi-optimal functions. As a result we obtain mathematical model and the optimal investment portfolio when yields are not clear from the beginning. Finally, we apply this algorithm to a specific case of a Colombian bank.

Keywords: outer approximation methods, portfolio problem, semi-infinite programming, numerial solution

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9297 Kirchoff Type Equation Involving the p-Laplacian on the Sierpinski Gasket Using Nehari Manifold Technique

Authors: Abhilash Sahu, Amit Priyadarshi

Abstract:

In this paper, we will discuss the existence of weak solutions of the Kirchhoff type boundary value problem on the Sierpinski gasket. Where S denotes the Sierpinski gasket in R² and S₀ is the intrinsic boundary of the Sierpinski gasket. M: R → R is a positive function and h: S × R → R is a suitable function which is a part of our main equation. ∆p denotes the p-Laplacian, where p > 1. First of all, we will define a weak solution for our problem and then we will show the existence of at least two solutions for the above problem under suitable conditions. There is no well-known concept of a generalized derivative of a function on a fractal domain. Recently, the notion of differential operators such as the Laplacian and the p-Laplacian on fractal domains has been defined. We recall the result first then we will address the above problem. In view of literature, Laplacian and p-Laplacian equations are studied extensively on regular domains (open connected domains) in contrast to fractal domains. In fractal domains, people have studied Laplacian equations more than p-Laplacian probably because in that case, the corresponding function space is reflexive and many minimax theorems which work for regular domains is applicable there which is not the case for the p-Laplacian. This motivates us to study equations involving p-Laplacian on the Sierpinski gasket. Problems on fractal domains lead to nonlinear models such as reaction-diffusion equations on fractals, problems on elastic fractal media and fluid flow through fractal regions etc. We have studied the above p-Laplacian equations on the Sierpinski gasket using fibering map technique on the Nehari manifold. Many authors have studied the Laplacian and p-Laplacian equations on regular domains using this Nehari manifold technique. In general Euler functional associated with such a problem is Frechet or Gateaux differentiable. So, a critical point becomes a solution to the problem. Also, the function space they consider is reflexive and hence we can extract a weakly convergent subsequence from a bounded sequence. But in our case neither the Euler functional is differentiable nor the function space is known to be reflexive. Overcoming these issues we are still able to prove the existence of at least two solutions of the given equation.

Keywords: Euler functional, p-Laplacian, p-energy, Sierpinski gasket, weak solution

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9296 Prediction of Fracture Aperture in Fragmented Rocks

Authors: Hossein Agheshlui, Stephan Matthai

Abstract:

In fractured rock masses open fractures tend to act as the main pathways of fluid flow. The permeability of a rock fracture depends on its aperture. The change of aperture with stress can cause a many-orders-of-magnitude change in the hydraulic conductivity at moderate compressive stress levels. In this study, the change of aperture in fragmented rocks is investigated using finite element analysis. A full 3D mechanical model of a simplified version of an outcrop analog is created and studied. A constant initial aperture value is applied to all fractures. Different far field stresses are applied and the change of aperture is monitored considering the block to block interaction. The fragmented rock layer is assumed to be sandwiched between softer layers. Frictional contact forces are defined at the layer boundaries as well as among contacting rock blocks. For a given in situ stress, the blocks slide and contact each other, resulting in new aperture distributions. A map of changed aperture is produced after applying the in situ stress and compared to the initial apertures. Subsequently, the permeability of the system before and after the stress application is compared.

Keywords: fractured rocks, mechanical model, aperture change due to stress, frictional interface

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9295 Model Updating-Based Approach for Damage Prognosis in Frames via Modal Residual Force

Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

Abstract:

This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: frame, grey wolf optimization algorithm, modal residual force, structural damage detection

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9294 The Examination of Withdrawn Behavior in Chinese Adolescents

Authors: Zhidong Zhang, Zhi-Chao Zhang, Georgiana Duarte

Abstract:

This study examined withdrawn syndromes of Chinese school children in northeast China in Northeast China. Specifically, the study examined withdrawn behaviors and the relationship to anxious syndromes and education environments. The purpose is to examine how the elements of educational environments and the early adolescents’ behaviors as independent variables influence and possibly predict the school children’s withdrawn problems. Achenbach System of Empirically Based Assessment (ASEBA), was the instrument, used in collection of data. A stratified sampling method was utilized to collect data from 2532 participants in seven schools. The results indicated that several background variables influenced withdrawn problem. Specifically, age, grade, sports activities and hobbies had a relationship with the anxious/depressed variable. Further withdrawn syndromes and anxious problem indicate a significant correlation.

Keywords: anxious/depressed problem, ASEBA, CBCL, withdrawn syndromes

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9293 A Modified NSGA-II Algorithm for Solving Multi-Objective Flexible Job Shop Scheduling Problem

Authors: Aydin Teymourifar, Gurkan Ozturk, Ozan Bahadir

Abstract:

NSGA-II is one of the most well-known and most widely used evolutionary algorithms. In addition to its new versions, such as NSGA-III, there are several modified types of this algorithm in the literature. In this paper, a hybrid NSGA-II algorithm has been suggested for solving the multi-objective flexible job shop scheduling problem. For a better search, new neighborhood-based crossover and mutation operators are defined. To create new generations, the neighbors of the selected individuals by the tournament selection are constructed. Also, at the end of each iteration, before sorting, neighbors of a certain number of good solutions are derived, except for solutions protected by elitism. The neighbors are generated using a constraint-based neural network that uses various constructs. The non-dominated sorting and crowding distance operators are same as the classic NSGA-II. A comparison based on some multi-objective benchmarks from the literature shows the efficiency of the algorithm.

Keywords: flexible job shop scheduling problem, multi-objective optimization, NSGA-II algorithm, neighborhood structures

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9292 Nursing Experience for a Lung Cancer Patient Undergoing First Time Concurrent Chemotherapy and Radiation Therapy

Authors: Hui Ling Chen

Abstract:

This article describes the experience of caring for a 68-year-old lung cancer patient undergoing the initial stage of concurrent chemotherapy and radiation therapy during the period of October 21 to November 16. In this study, the author collected data through observation, interviews, medical examination, and the use of Roy’s adaptation model as a guide for data collection and assessment. This study confirmed that chemotherapy induced nausea and vomiting, and radiation therapy impaired skin integrity. At the same time, the patient experienced an anxious reaction to the initial cancer diagnosis and the insertion of subcutaneous infusion ports at the start of medical treatment. Similarly, the patient’s wife shares his anxiety, not to mention the feeling of inadequacy from the lack of training in cancer care. In response, the nursing intervention strategy has included keeping the patient and his family informed of his treatment progress, transfer of cancer care knowledge, and providing them with spiritual support. For example, the nursing staff has helped them draw up a mutually agreeable dietary plan that best suits the wife’s cooking skills, provided them with knowledge in pre- and post-radiation skin care, as well as means to cope with nausea and vomiting reactions. The nursing staff has also worked on building rapport with the patient and his spouse, providing them with encouragement, caring attention and companionship. After the patient was discharged from the hospital, the nursing staff followed up with caring phone calls to help the patient and his family make life-style adjustments to normalcy. The author hopes that his distinctive nursing experience can be useful as a reference for the clinical care of lung cancer patients undergoing the initial stage of concurrent chemotherapy and radiation therapy treatment.

Keywords: lung cancer, initiate diagnosis, concurrent chemotherapy and radiation therapy, nursing care

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9291 Three-Dimensional Optimal Path Planning of a Flying Robot for Terrain Following/Terrain Avoidance

Authors: Amirreza Kosari, Hossein Maghsoudi, Malahat Givar

Abstract:

In this study, the three-dimensional optimal path planning of a flying robot for Terrain Following / Terrain Avoidance (TF/TA) purposes using Direct Collocation has been investigated. To this purpose, firstly, the appropriate equations of motion representing the flying robot translational movement have been described. The three-dimensional optimal path planning of the flying vehicle in terrain following/terrain avoidance maneuver is formulated as an optimal control problem. The terrain profile, as the main allowable height constraint has been modeled using Fractal Generation Method. The resulting optimal control problem is discretized by applying Direct Collocation numerical technique, and then transformed into a Nonlinear Programming Problem (NLP). The efficacy of the proposed method is demonstrated by extensive simulations, and in particular, it is verified that this approach could produce a solution satisfying almost all performance and environmental constraints encountering a low-level flying maneuver

Keywords: path planning, terrain following, optimal control, nonlinear programming

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9290 Influence of Shear Parameter on Liquefaction Susceptibility of Ramsar Sand

Authors: Siavash Salamatpoor, Hossein Motaghedi, Jr., Mehrdad Nategh

Abstract:

In this study, undrained triaxial tests under anisotropic consolidation were conducted on the reconstituted samples of Ramsar sand, which underlies a densely populated, seismic region of the southern coast of Caspian Sea in Mazandaran province, Iran. Ramsar costal city is regularly visited by many tourists. Accordingly, many tall building and heavy structures are going to be constructed over this coastal area. This region is overlaid by poorly graded clean sand and because of high water level, is susceptible to liquefaction. The specimens were consolidated anisotropically to simulate initial shear stress which is mobilized due to surface constructions. Different states of soil behavior were obtained by applying different levels of initial relative density, shear stress, and effective stress. It is shown that Ramsar clean sand can experience the whole possible states of liquefiable soils i.e. fully liquefaction, limited liquefaction, and dilation behaviors. It would be shown that by increasing the shear parameter in high confine pressure, the liquefaction susceptibility has increased while for low confine pressure it would be vice versa.

Keywords: anisotropic, triaxial test, shear parameter, static liquefaction

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9289 Evidence Theory Based Emergency Multi-Attribute Group Decision-Making: Application in Facility Location Problem

Authors: Bidzina Matsaberidze

Abstract:

It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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9288 Formulation of Extended-Release Gliclazide Tablet Using a Mathematical Model for Estimation of Hypromellose

Authors: Farzad Khajavi, Farzaneh Jalilfar, Faranak Jafari, Leila Shokrani

Abstract:

Formulation of gliclazide in the form of extended-release tablet in 30 and 60 mg dosage forms was performed using hypromellose (HPMC K4M) as a retarding agent. Drug-release profiles were investigated in comparison with references Diamicron MR 30 and 60 mg tablets. The effect of size of powder particles, the amount of hypromellose in formulation, hardness of tablets, and also the effect of halving the tablets were investigated on drug release profile. A mathematical model which describes hypromellose behavior in initial times of drug release was proposed for the estimation of hypromellose content in modified-release gliclazide 60 mg tablet. This model is based on erosion of hypromellose in dissolution media. The model is applicable to describe release profiles of insoluble drugs. Therefore, by using dissolved amount of drug in initial times of dissolution and the model, the amount of hypromellose in formulation can be predictable. The model was used to predict the HPMC K4M content in modified-release gliclazide 30 mg and extended-release quetiapine 200 mg tablets.

Keywords: Gliclazide, hypromellose, drug release, modified-release tablet, mathematical model

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9287 Numerical Simulation of the Kurtosis Effect on the EHL Problem

Authors: S. Gao, S. Srirattayawong

Abstract:

In this study, a computational fluid dynamics (CFD) model has been developed for studying the effect of surface roughness profile on the EHL problem. The cylinders contact geometry, meshing and calculation of the conservation of mass and momentum equations are carried out by using the commercial software packages ICEMCFD and ANSYS Fluent. The user defined functions (UDFs) for density, viscosity and elastic deformation of the cylinders as the functions of pressure and temperature have been defined for the CFD model. Three different surface roughness profiles are created and incorporated into the CFD model. It is found that the developed CFD model can predict the characteristics of fluid flow and heat transfer in the EHL problem, including the leading parameters such as the pressure distribution, minimal film thickness, viscosity, and density changes. The obtained results show that the pressure profile at the center of the contact area directly relates to the roughness amplitude. The rough surface with kurtosis value over 3 influences the fluctuated shape of pressure distribution higher than other cases.

Keywords: CFD, EHL, kurtosis, surface roughness

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9286 Non-Parametric Changepoint Approximation for Road Devices

Authors: Loïc Warscotte, Jehan Boreux

Abstract:

The scientific literature of changepoint detection is vast. Today, a lot of methods are available to detect abrupt changes or slight drift in a signal, based on CUSUM or EWMA charts, for example. However, these methods rely on strong assumptions, such as the stationarity of the stochastic underlying process, or even the independence and Gaussian distributed noise at each time. Recently, the breakthrough research on locally stationary processes widens the class of studied stochastic processes with almost no assumptions on the signals and the nature of the changepoint. Despite the accurate description of the mathematical aspects, this methodology quickly suffers from impractical time and space complexity concerning the signals with high-rate data collection, if the characteristics of the process are completely unknown. In this paper, we then addressed the problem of making this theory usable to our purpose, which is monitoring a high-speed weigh-in-motion system (HS-WIM) towards direct enforcement without supervision. To this end, we first compute bounded approximations of the initial detection theory. Secondly, these approximating bounds are empirically validated by generating many independent long-run stochastic processes. The abrupt changes and the drift are both tested. Finally, this relaxed methodology is tested on real signals coming from a HS-WIM device in Belgium, collected over several months.

Keywords: changepoint, weigh-in-motion, process, non-parametric

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9285 Optimum Design of Piled-Raft Systems

Authors: Alaa Chasib Ghaleb, Muntadher M. Abbood

Abstract:

This paper presents a study of the problem of the optimum design of piled-raft foundation systems. The study has been carried out using a hypothetic problem and soil investigations of six sites locations in Basrah city to evaluate the adequacy of using the piled-raft foundation concept. Three dimensional finite element analysis method has been used, to perform the structural analysis. The problem is optimized using Hooke and Jeeves method with the total weight of the foundation as objective function and each of raft thickness, piles length, number of piles and piles diameter as design variables. It is found that the total and differential settlement decreases with increasing the raft thickness, the number of piles, the piles length, and the piles diameter. Finally parametric study for load values, load type and raft dimensions have been studied and the results have been discussed.

Keywords: Hooke and Jeeves, optimum design, piled-raft, foundations

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9284 Numerical Analysis and Influence of the Parameters on Slope Stability

Authors: Fahim Kahlouche, Alaoua Bouaicha, Sihem Chaîbeddra, Sid-Ali Rafa, Abdelhamid Benouali

Abstract:

A designing of a structure requires its realization on rough or sloping ground. Besides the problem of the stability of the landslide, the behavior of the foundations that are bearing the structure is influenced by the destabilizing effect of the ground’s slope. This article focuses on the analysis of the slope stability exposed to loading by introducing the different factors influencing the slope’s behavior on the one hand, and on the influence of this slope on the foundation’s behavior on the other hand. This study is about the elastoplastic modelization using FLAC 2D. This software is based on the finite difference method, which is one of the older methods of numeric resolution of differential equations system with initial and boundary conditions. It was developed for the geotechnical simulation calculation. The aim of this simulation is to demonstrate the notable effect of shear modulus « G », cohesion « C », inclination angle (edge) « β », and distance between the foundation and the head of the slope on the stability of the slope as well as the stability of the foundation. In our simulation, the slope is constituted by homogenous ground. The foundation is considered as rigid/hard; therefore, the loading is made by the application of the vertical strengths on the nodes which represent the contact between the foundation and the ground. 

Keywords: slope, shallow foundation, numeric method, FLAC 2D

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9283 Recovery of Copper from Edge Trims of Printed Circuit Boards Using Acidithiobacillus Ferrooxidans: Bioleaching

Authors: Shashi Arya, Nand L. Singh, Samiksha Singh, Pradeep K. Mishra, Siddh N. Upadhyay

Abstract:

The enormous generation of E- waste and its recycling have greater environmental concern especially in developing countries like India. A major part of this waste comprises printed circuit boards (PCBs). Edge trims of PCBs have high copper content ranging between 25-60%. The extraction of various metals out of these PCBs is more or less a proven technology, wherein various hazardous chemicals are being used in the resource recovery, resulting into secondary pollution. The current trend of extracting of valuable metals is the utilization of microbial strains to eliminate the problem of a secondary pollutant. Keeping the above context in mind, this work aims at the enhanced recovery of copper from edge trims, through bioleaching using bacterial strain Acidithiobacillus ferrooxidans. The raw material such as motherboards, hard drives, floppy drives and DVD drives were obtained from the warehouse of the University. More than 90% copper could be extracted through bioleaching using Acidithiobacillus ferrooxidans. Inoculate concentration has merely insignificant effect over copper recovery above 20% inoculate concentration. Higher concentration of inoculation has the only initial advantage up to 2-4 days. The complete recovery has been obtained between 14- 24 days.

Keywords: acidithiobacillus ferrooxidans, bioleaching, e-waste, printed circuit boards

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9282 Reflective Thinking and Experiential Learning – A Quasi-Experimental Quanti-Quali Response to Greater Diversification of Activities, Greater Integration of Student Profiles

Authors: Paulo Sérgio Ribeiro de Araújo Bogas

Abstract:

Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

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9281 Improving Coverage in Wireless Sensor Networks Using Particle Swarm Optimization Algorithm

Authors: Ehsan Abdolzadeh, Sanaz Nouri, Siamak Khalaj

Abstract:

Today WSNs have many applications in different fields like the environment, military operations, discoveries, monitoring operations, and so on. Coverage size and energy consumption are the important challenges that these networks need to face. This paper tries to solve the problem of coverage with a requirement of k-coverage and minimum energy consumption. In order to minimize energy consumption, visual sensor networks have been used that observe and process just those targets that are located in their view direction. As a result, sensor rotations have decreased, and subsequently, energy consumption has been minimized. To solve the problem of coverage particle swarm optimization, coverage optimization has been able to ensure coverage requirement together with minimizing sensor rotations while meeting the problem requirement of k≤14. So energy consumption has decreased, and this could extend the sensors’ lifetime subsequently.

Keywords: K coverage, particle union optimization algorithm, wireless sensor networks, visual sensor networks

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9280 Determination of the Shear Strength of Wastes Using Back-Analyses from Observed Failures

Authors: Sadek Salah

Abstract:

The determination of the strength characteristics of waste materials is essential when evaluating the stability of waste fills during initial placement and at the time of closure and rehabilitation of the landfill. Significant efforts, mostly experimental, have been deployed to date in attempts to quantify the mechanical properties of municipal wastes various stages of decomposition. Even though the studies and work done so far have helped in setting baseline parameters and characteristics for waste materials, inherent concerns remain as to the scalability of the findings between the laboratory and the field along with questions as to the suitability of the actual test conditions. These concerns are compounded by the complexity of the problem itself with significant variability in composition, placement conditions, and levels of decay of the various constituents of the waste fills. A complimentary, if not necessarily an alternative approach is to rely on field observations of behavior and instability of such materials. This paper describes an effort at obtaining relevant shear strength parameters from back-analyses of failures which have been observed at a major un-engineered waste fill along the Mediterranean shoreline. Results from the limit-equilibrium failure back-analyses are presented and compared to results from laboratory-scale testing on comparable waste materials.

Keywords: solid waste, shear strength, landfills, slope stability

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9279 Sundarban as a Buffer against Storm Surge Flooding

Authors: Mohiuddin Sakib, Fatin Nihal, Anisul Haque, Munsur Rahman, Mansur Ali

Abstract:

Sundarban, the largest mangrove forest in the world, is known to act as a buffer against the cyclone and storm surge. Theoretically, Sundarban absorbs the initial thrust of the wind and acts to ‘resist’ the storm surge flooding. The role of Sundarban was evident during the cyclone Sidr when the Sundarban solely defended the initial thrust of the cyclonic wind and the resulting storm surge inundation. In doing this, Sundarban sacrificed 30% of its plant habitats. Although no scientific study has yet been conducted, it is generally believed that Sundarban will continuously play its role as a buffer against the cyclone when landfall of the cyclone is at or close to the Sundarban. Considering these facts, the present study mainly focused on a scientific insight into the role of Sundarban as a buffer against the present-day cyclone and storm surge and also its probable role on the impacts of future storms of similar nature but with different landfall locations. The Delft 3D dashboard and flow model are applied to compute the resulting inundation due to cyclone induced storm surge. The results show that Sundarban indeed acts as a buffer against the storm surge inundation when cyclone landfall is at or close to Sundarban.

Keywords: buffer, Mangrove forest, Sidr, landfall, roughness

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9278 Equilibrium, Kinetics, and Thermodynamic Studies on Heavy Metal Biosorption by Trichoderma Species

Authors: Sobia Mushtaq, Firdaus E. Bareen, Asma Tayyeb

Abstract:

This study conducted to investigate the metal biosorption potential of indigenous Trichoderma species (T. harzianum KS05T01, T. longibrachiatum KS09T03, Trichoderma sp KS17T09., T. viridi KS17T011, T. atrobruneo KS21T014, and T. citrinoviride) that have been isolated from contaminated soil of Kasur Tannery Waste Management Agency. The effect of different biosorption parameters as initial metal ion concentration, pH, contact time , and temperature of incubation was investigated on the biosorption potential of these species. The metal removal efficiency and (E%) and metal uptake capacity (mg/g) increased along with the increase of initial metal concentration in media. The Trichoderma species can tolerate and survive under heavy metal stress up to 800mg/L. Among the two isotherm models were applied on the biosorption data, Langmuir isotherm model and Freundlich isotherm model, maximum correlation coefficients values (R 2 ) of 1was found for Langmuir model, which showed the better fitted model for the Trichoderma biosorption. The metal biosorption was increased with the increase of temperature and pH of the media. The maximum biosorption was observed between 25-30 o C and at pH 6.-7.5, while the biosorption rate was increased from 3-6 days of incubation, and then the rate of biosorption was slowed down. The biosorption data was better fitted for Pseudo kinetic first order during the initial days of biosorption. Thermodynamic parameters as standard Gibbs free energy (G), standard enthalpy change (H), and standard entropy (S) were calculated. The results confirmed the heavy metal biosorption by Trichoderma species was endothermic and spontaneous reaction in nature. The FTIR spectral analysis and SEM-EDX analysis of the treated and controlled mycelium revealed the changes in the active functional sites and morphological variations of the outer surface. The data analysis envisaged that high metal tolerance exhibited by Trichoderma species indicates its potential as efficacious and successful mediator for bioremediation of the heavy metal polluted environments.

Keywords: heavy metal, fungal biomass, biosorption, kinetics

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9277 Seismic Hazard Prediction Using Seismic Bumps: Artificial Neural Network Technique

Authors: Belkacem Selma, Boumediene Selma, Tourkia Guerzou, Abbes Labdelli

Abstract:

Natural disasters have occurred and will continue to cause human and material damage. Therefore, the idea of "preventing" natural disasters will never be possible. However, their prediction is possible with the advancement of technology. Even if natural disasters are effectively inevitable, their consequences may be partly controlled. The rapid growth and progress of artificial intelligence (AI) had a major impact on the prediction of natural disasters and risk assessment which are necessary for effective disaster reduction. The Earthquakes prediction to prevent the loss of human lives and even property damage is an important factor; that is why it is crucial to develop techniques for predicting this natural disaster. This present study aims to analyze the ability of artificial neural networks (ANNs) to predict earthquakes that occur in a given area. The used data describe the problem of high energy (higher than 10^4J) seismic bumps forecasting in a coal mine using two long walls as an example. For this purpose, seismic bumps data obtained from mines has been analyzed. The results obtained show that the ANN with high accuracy was able to predict earthquake parameters; the classification accuracy through neural networks is more than 94%, and that the models developed are efficient and robust and depend only weakly on the initial database.

Keywords: earthquake prediction, ANN, seismic bumps

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9276 Developmental Relationships between Alcohol Problems and Internalising Symptoms in a Longitudinal Sample of College Students

Authors: Lina E. Homman, Alexis C. Edwards, Seung Bin Cho, Danielle M. Dick, Kenneth S. Kendler

Abstract:

Research supports an association between alcohol problems and internalising symptoms, but the understanding of how the two phenotypes relate to each other is poor. It has been hypothesized that the relationship between the phenotypes is causal; however investigations in regards to direction are inconsistent. Clarity of the relationship between the two phenotypes may be provided by investigating the phenotypes developmental inter-relationships longitudinally. The objective of the study was to investigate a) changes in alcohol problems and internalising symptoms in college students across time and b) the direction of effect of growth between alcohol problems and internalising symptoms from late adolescent to emerging adulthood c) possible gender differences. The present study adds to the knowledge of comorbidity of alcohol problems and internalising symptoms by examining a longitudinal sample of college students and by examining the simultaneous development of the symptoms. A sample of college students is of particular interest as symptoms of both phenotypes often have their onset around this age. A longitudinal sample of college students from a large, urban, public university in the United States was used. Data was collected over a time period of 2 years at 3 time points. Latent growth models were applied to examine growth trajectories. Parallel process growth models were used to assess whether initial level and rate of change of one symptom affected the initial level and rate of change of the second symptom. Possible effects of gender and ethnicity were investigated. Alcohol problems significantly increased over time, whereas internalizing symptoms remained relatively stable. The two phenotypes were significantly correlated in each wave, correlations were stronger among males. Initial level of alcohol problems was significantly positively correlated with initial level of internalising symptoms. Rate of change of alcohol problems positively predicted rate of change of internalising symptoms for females but not for males. Rate of change of internalising symptoms did not predict rate of change of alcohol problems for either gender. Participants of Black and Asian ethnicities indicated significantly lower levels of alcohol problems and a lower increase of internalising symptoms across time, compared to White participants. Participants of Black ethnicity also reported significantly lower levels of internalising symptoms compared to White participants. The present findings provide additional support for a positive relationship between alcohol problems and internalising symptoms in youth. Our findings indicated that both internalising symptoms and alcohol problems increased throughout the sample and that the phenotypes were correlated. The findings mainly implied a bi-directional relationship between the phenotypes in terms of significant associations between initial levels as well as rate of change. No direction of causality was indicated in males but significant results were found in females where alcohol problems acted as the main driver for the comorbidity of alcohol problems and internalising symptoms; alcohol may have more detrimental effects in females than in males. Importantly, our study examined a population-based longitudinal sample of college students, revealing that the observed relationships are not limited to individuals with clinically diagnosed mental health or substance use problems.

Keywords: alcohol, comorbidity, internalising symptoms, longitudinal modelling

Procedia PDF Downloads 344
9275 Investigating Software Engineering Challenges in Game Development

Authors: Fawad Zaidi

Abstract:

This paper discusses a variety of challenges and solutions involved with creating computer games and the issues faced by the software engineers working in this field. This review further investigates the articles coverage of project scope and the problem of feature creep that appears to be inherent with game development. The paper tries to answer the following question: Is this a problem caused by a shortage, or bad software engineering practices, or is this outside the control of the software engineering component of the game production process?

Keywords: software engineering, computer games, software applications, development

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9274 A Memetic Algorithm for an Energy-Costs-Aware Flexible Job-Shop Scheduling Problem

Authors: Christian Böning, Henrik Prinzhorn, Eric C. Hund, Malte Stonis

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In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.

Keywords: energy costs, flexible job-shop scheduling, memetic algorithm, power peak

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9273 A Survey on Constraint Solving Approaches Using Parallel Architectures

Authors: Nebras Gharbi, Itebeddine Ghorbel

Abstract:

In the latest years and with the advancements of the multicore computing world, the constraint programming community tried to benefit from the capacity of new machines and make the best use of them through several parallel schemes for constraint solving. In this paper, we propose a survey of the different proposed approaches to solve Constraint Satisfaction Problems using parallel architectures. These approaches use in a different way a parallel architecture: the problem itself could be solved differently by several solvers or could be split over solvers.

Keywords: constraint programming, parallel programming, constraint satisfaction problem, speed-up

Procedia PDF Downloads 315