Search results for: stiff initial value problem

Authors: Yassir AbdelRazig

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Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model.

Keywords: ant colony, construction site layout, optimization, genetic algorithms

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Authors: Nese Ozturk Korpe, Muhammed H. Karas

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Reaction synthesis, or combustion synthesis, is a processing technique in which the thermal activation energy of formation of a compound is sustained by its exothermic heat of reaction. The aim of the present study was to investigate the effect of high initial pressing pressures (420 MPa, 630 MPa, and 850 MPa) on porosity of Ti3Al which produced by volume combustion synthesis. Microstructure examinations were performed by optical microscope (OM) and scanning electron microscope (SEM). Phase analyses were performed with X-ray diffraction device (XRD). A significant decrease in porosity was obtained due to an increase in the initial pressing pressure.

Keywords: Titanium Aluminide, Volume Combustion Synthesis, Intermetallic, Porosity

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Authors: Roza Afarin, Saeed Mozaffari

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The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: B. Marasović, S. Pivac, S. V. Vukasović

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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Markowitz model, fractional quadratic programming, portfolio optimization, transaction costs

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Authors: Malika Yaici, Assia Arab, Betitra Yakouben, Samia Zermani

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Ubiquitous computing is nowadays a reality through the networking of a growing number of computing devices. It allows providing users with context aware information and services in a heterogeneous environment, anywhere and anytime. Selection of the best context-aware service, between many available services and providers, is a tedious problem. In this paper, a service selection method based on Constraint Satisfaction Problem (CSP) formalism is proposed. The services are considered as variables and domains; and the user context, preferences and providers characteristics are considered as constraints. The Backtrack algorithm is used to solve the problem to find the best service and provider which matches the user requirements. Even though this algorithm has an exponential complexity, but its use guarantees that the service, that best matches the user requirements, will be found. A comparison of the proposed method with the existing solutions finishes the paper.

Keywords: ubiquitous computing, services selection, constraint satisfaction problem, backtrack algorithm

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Authors: Jong Han Joo, Jung Hoon Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

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In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. We propose a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector

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Authors: D. K. Rao, M. G. M. Khan, K. G. Reddy

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The focus of this paper is to develop a technique of solving a combined problem of determining Optimum Strata Boundaries (OSB) and Optimum Sample Size (OSS) of each stratum, when the population understudy is skewed and the study variable has a Pareto frequency distribution. The problem of determining the OSB is formulated as a Mathematical Programming Problem (MPP) which is then solved by dynamic programming technique. A numerical example is presented to illustrate the computational details of the proposed method. The proposed technique is useful to obtain OSB and OSS for a Pareto type skewed population, which minimizes the variance of the estimate of population mean.

Keywords: stratified sampling, optimum strata boundaries, optimum sample size, pareto distribution, mathematical programming problem, dynamic programming technique

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Authors: I. A. Farhat

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The dynamic economic dispatch (DED) problem is one of the complex, constrained optimization problems that have nonlinear, con-convex and non-smooth objective functions. The purpose of the DED is to determine the optimal economic operation of the committed units while meeting the load demand. Associated to this constrained problem there exist highly nonlinear and non-convex practical constraints to be satisfied. Therefore, classical and derivative-based methods are likely not to converge to an optimal or near optimal solution to such a dynamic and large-scale problem. In this paper, an Artificial Immune System technique (AIS) is implemented and applied to solve the DED problem considering the transmission power losses and the valve-point effects in addition to the other operational constraints. To demonstrate the effectiveness of the proposed technique, two case studies are considered. The results obtained using the AIS are compared to those obtained by other methods reported in the literature and found better.

Keywords: artificial immune system, dynamic economic dispatch, optimal economic operation, large-scale problem

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Authors: R. Berrached, H. Ait Mahamed, A. Iddou

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Water pollution is nowadays a serious problem, due to the increasing scarcity of water and thus to the impact induced by such pollution on the human health. Various techniques are made use of to deal with water pollution. Among the most used ones, some can be enumerated: the bacterian bed, the activated mud, the Lagunage as biological processes and coagulation-floculation as a physic-chemical process. These processes are very expensive and an treatment efficiency which decreases along with the increase of the initial pollutants’ concentration. This is the reason why research has been reoriented towards the use of a process by adsorption as an alternative solution instead of the other traditional processes. In our study, we have tempted to exploit the characteristics of two metallic hydroxides Al and Fe to purify contaminated water by two industrial dyes SBL blue and SRL-150 orange. Results have shown the efficiency of the two materials on the blue SBL dye.

Keywords: Metallic Hydroxydes, industrial dyes, purification, lagunage

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Authors: Saeed Kamarian, Mahmoud Shakeri

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Sandwich structures are used in a variety of engineering applications including aircraft, construction and transportation where strong, stiff and light structures are required. In this paper, frequency maximization of Functionally Graded Sandwich (FGS) beams resting on Pasternak foundations is investigated. A generalized power-law distribution with four parameters is considered for material distribution through the thicknesses of face layers. Since the search space is large, the optimization processes becomes so complicated and too much time consuming. Thus a novel meta–heuristic called Imperialist Competitive Algorithm (ICA) which is a socio-politically motivated global search strategy is implemented to improve the speed of optimization process. Results show the success of applying ICA for engineering problems especially for design optimization of FGM sandwich beams.

Keywords: sandwich beam, functionally graded materials, optimization, imperialist competitive algorithm

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Authors: Asma Ben Yaghlane, Mohamed Naceur Azaiez

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We consider the problem of attacks on networks. We define the concept of system survivability in networks in the presence of intelligent threats. Our setting of the problem assumes a flow to be sent from one source node to a destination node. The attacker attempts to disable the network by preventing the flow to reach its destination while the defender attempts to identify the best path-set to use to maximize the chance of arrival of the flow to the destination node. Our concept is shown to be different from the classical concept of network reliability. We distinguish two types of network survivability related to the defender and to the attacker of the network, respectively. We prove that the defender-based-network survivability plays the role of a lower bound while the attacker-based-network survivability plays the role of an upper bound of network reliability. We also prove that both concepts almost never agree nor coincide with network reliability. Moreover, we use the shortest-path problem to determine the defender-based-network survivability and the min-cut problem to determine the attacker-based-network survivability. We extend the problem to a variety of models including the minimum-spanning-tree problem and the multiple source-/destination-network problems.

Keywords: defense/attack strategies, information, networks, reliability, survivability

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Authors: Ali Gharaee, Mohammad Reza Khosravi Nikou, Bagher Anvaripour, Ali Asghar Mahjoobi

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Soil contamination by petroleum hydrocarbon (PHC) is a major concern facing the oil and gas industry. Particularly, condensate liquids have been found to contaminate soil at gas production sites. The remediation of PHCs is a difficult challenge due to the complex interaction between contaminant and soil. A study has been conducted to enhance degradation of PHCs by Fenton oxidation and using Nanoscale Zero-Valent Iron as catalyst. The various operating conditions such as initial H2O2 concentration, nZVI dosage, reaction time, and initial contamination dose were investigated. Central composite design was employed to optimize and analyze the effect of operational parameters on the PHC removal efficiency. It was found that optimal molar ratio of H2O2/Fe0 was 58 with maximum TPH removal of 84% and 3hr reaction time and initial contaminant concentration was 15g oil /kg soil. Based on the results, combination of Nanoscale ZVI and Fenton has proved to be a promising remedy for contaminated soil.

Keywords: oil contaminated Soil, fenton oxidation, zero valent iron nano-particles

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Authors: Abbas Mirakhorli

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A hub covering problem is a type of hub location problem that tries to maximize the coverage area with the least amount of installed hubs. There have not been many studies in the literature about multi-objective hubs covering location problems. Thus, in this paper, a bi-objective model for the hub covering problem is presented. The two objectives that are considered in this paper are the minimization of total transportation costs and the maximization of coverage of origin-destination nodes. A genetic algorithm is presented to solve the model when the number of nodes is increased. The genetic algorithm is capable of solving the model when the number of nodes increases by more than 20. Moreover, the genetic algorithm solves the model in less amount of time.

Keywords: facility location, hub covering, multi-objective optimization, genetic algorithm

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Authors: A. Giannakopoulos, S. B. Buckley

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Problem solving in any field is recognised as a prerequisite for any advancement in knowledge. For example in South Africa it is one of the seven critical outcomes of education together with critical thinking. As a systematic way to problem solving was initiated in mathematics by the great mathematician George Polya (the father of problem solving), more detailed and comprehensive ways in problem solving have been developed. This paper is based on the findings by the author and subsequent recommendations for further research in problem solving and critical thinking. Although the study was done in mathematics, there is no doubt by now in almost anyone’s mind that mathematics is involved to a greater or a lesser extent in all fields, from symbols, to variables, to equations, to logic, to critical thinking. Therefore it stands to reason that mathematical principles and learning cannot be divorced from any field. In management of knowledge situations, the types of problems are similar to mathematics problems varying from simple to analogical to complex; from well-structured to ill-structured problems. While simple problems could be solved by employees by adhering to prescribed sequential steps (the process), analogical and complex problems cannot be proceduralised and that diminishes the capacity of the organisation of knowledge creation and innovation. The low efficiency in some organisations and the low pass rates in mathematics prompted the author to view problem solving as a product. The authors argue that using mathematical approaches to knowledge management problem solving and treating problem solving as a product will empower the employee through further training to tackle analogical and complex problems. The question the authors asked was: If it is true that problem solving and critical thinking are indeed basic skills necessary for advancement of knowledge why is there so little literature of knowledge management (KM) about them and how they are connected and advance KM?This paper concludes with a conceptual model which is based on general accepted principles of knowledge acquisition (developing a learning organisation), knowledge creation, sharing, disseminating and storing thereof, the five pillars of knowledge management (KM). This model, also expands on Gray’s framework on KM practices and problem solving and opens the doors to a new approach to training employees in general and domain specific areas problems which can be adapted in any type of organisation.

Keywords: critical thinking, knowledge management, mathematics, problem solving

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Authors: S. Kazadi, A. An, B. Shen

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We investigate the fitness of a male and female permanent magnetic levitation support for use as an axle on a rotor for a levitating motor. The support enables passive thrust and axial support for the axle as a result of the unique arrangement of permanent magnets. As the axial and thrust bearing aspects are derived from magnetic repulsion, it is not immediately clear that the repulsion is stiff enough to enable even low power motors. This paper describes the design and performance of two low power motors based on the magnetic levitation support. We find that our low power motors, with rotational speeds of 618 and 833 rpms, exhibit performance free from excess vibrations that might hinder performance. This means that the actuation of the motors is adequately stabilized by the axle and results in motors capable of being utilized despite the levitation support.

Keywords: levitating motor, magnetic levitation support, fitness, axle

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Authors: Krasimir Ivanov, Elitsa Kolentsova, Nguyen Nguyen, Alexander Peltekov, Violina Angelova

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The nanosized zinc hydroxide nitrate has been recently estimated as perspective foliar fertilizer, which has improved zinc solubility, but low phytotoxicity, in comparison with ZnO and other Zn containing compounds. The main problem is obtaining of stable particles with dimensions less than 100 nm. This work studies the effect of preparation conditions on the chemical compositions and particle size of the zinc hydroxide nitrates, prepared by precipitation. Zn(NO3)2.6H2O and NaOH with concentrations, ranged from 0.2 to 3.2M and the initial OH/Zn ratio from 0.5 to 1.6 were used at temperatures from 20 to 60 °C. All samples were characterized in detail by X-ray diffraction, scanning electron microscopy, differential thermal analysis and ICP. Stability and distribution of the zinc hydroxide nitrate particles were estimated too.

Keywords: zinc hydroxide nitrate, nanoparticles, preparation, foliar fertilizer

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Authors: H. Abdolvand, M. Riazat, H. Sohrabi, G. Faraji

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An experimental investigation into the Tube Backward Extrusion (TBE) process on AZ31 magnesium alloy is studied. Microstructures and grain size distribution of the specimens before and after TBE process are investigated by optical microscopy. Tensile and Vickers microhardness tests along extrusion direction were performed at room temperature. It is found that the average grain size is refined remarkably from the initial 33 µm down to 3.5 µm after TBE process. Also, the microhardness increased significantly to 58 HV after the process from an initial value of 36 HV.

Keywords: tube backward extrusion, AZ31, grain size distribution, grain refinement

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Authors: Robespierre Chavez, Eden Bojorquez, Alfredo Reyes-Salazar

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This study compares the seismic response of regular and vertically irregular steel frames determined by nonlinear time history analysis and by using several sets of earthquake records, which are divided in two categories: The first category having 20 stiff-soil ground motion records obtained from the NGA database, and the second category having 30 soft-soil ground motions recorded in the Lake Zone of Mexico City and exhibiting a dominant period (Ts) of two seconds. The steel frames in both format regular and irregular were designed according to the Mexico City Seismic Design Provisions (MCSDP). The effects of irregularity throught the height on the maximum interstory drifts are estimated.

Keywords: irregular steel frames, maximum interstory drifts, seismic response, seismic records

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Authors: C. Samita, W. Chalermchai

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This project is aimed to be a preliminary study of using Tapioca Starch as a viscosity modifying agent (VMA) in concrete work. Tapioca starch effects on the viscosity of concrete, which could be investigated from the workability of corresponding mortar. Cement only mortars with water to cement ratio (w/c) 0.25 to 0.48, superplasticizer dosage of 1% to 2.5%, starch concentration of 0%, 0.25% and 0.5%, was tested for workability. Mortar mixes that have equivalent workability (flow diameter of 250 mm, and funnel flow time of 5 seconds) for each starch concentration were identified and checked for concrete properties. Concrete were tested for initial workability, workability loss, bleeding, setting times, and compressive strength. The results showed that all concrete mixes provide same initial workability, however the mix with higher starch concentration provides slower loss. Bleeding occurs when concrete has w/c more than 0.45. For setting times, mixing with higher starch concentration provide longer setting times (around 4 hours in this experiment). Compressive strength of starch concretes which always have higher w/c, are lower than that of cement only concrete as in this experiment initial workability were controlled to be same.

Keywords: viscosity modifying agent(VMA), self-leveling concrete, self-compacting concrete(SCC), low-binder SCC

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Authors: Ayse Cobanoglu

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Working memory can be defined as a workspace that holds and regulates active information in mind. This study investigates individual changes in children's working memory from kindergarten to first grade. The main purpose of the study is whether parental discipline methods and child impulsive/overactive behaviors affect children's working memory initial status and growth rate, controlling for gender, minority status, and socioeconomic status (SES). A linear growth curve model with the first four waves of the Early Childhood Longitudinal Study-Kindergarten Cohort of 2011 (ECLS-K:2011) is performed to analyze the individual growth of children's working memory longitudinally (N=3915). Results revealed that there is a significant variation among students' initial status in the kindergarten fall semester as well as the growth rate during the first two years of schooling. While minority status, SES, and children's overactive/impulsive behaviors influenced children's initial status, only SES and minority status were significantly associated with the growth rate of working memory. For parental discipline methods, such as giving a warning and ignoring the child's negative behavior, are also negatively associated with initial working memory scores. Following that, students' working memory growth rate is examined, and students with lower SES as well as minorities showed a faster growth pattern during the first two years of schooling. However, the findings of parental disciplinary methods on working memory growth rates were mixed. It can be concluded that schooling helps low-SES minority students to develop their working memory.

Keywords: growth curve modeling, impulsive/overactive behaviors, parenting, working memory

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Authors: Julio C. Ferreira, Maria T. A. Steiner

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The aim of this work is to present a solution procedure referred to here as the Multi-objective Optimization for Green Vehicle Routing Problem (MOOGVRP) to provide solutions for a case study. The proposed methodology consists of three stages to resolve Scenario A. Stage 1 consists of the “treatment” of data; Stage 2 consists of applying mathematical models of the p-Median Capacitated Problem (with the objectives of minimization of distances and homogenization of demands between groups) and the Asymmetric Traveling Salesman Problem (with the objectives of minimizing distances and minimizing time). The weighted method was used as the multi-objective procedure. In Stage 3, an analysis of the results is conducted, taking into consideration the environmental aspects related to the case study, more specifically with regard to fuel consumption and air pollutant emission. This methodology was applied to a (partial) database that addresses newspaper distribution in the municipality of Curitiba, Paraná State, Brazil. The preliminary findings for Scenario A showed that it was possible to improve the distribution of the load, reduce the mileage and the greenhouse gas by 17.32% and the journey time by 22.58% in comparison with the current scenario. The intention for future works is to use other multi-objective techniques and an expanded version of the database and explore the triple bottom line of sustainability.

Keywords: Asymmetric Traveling Salesman Problem, Green Vehicle Routing Problem, Multi-objective Optimization, p-Median Capacitated Problem

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Authors: Md. Zahidul Islam, Mohamed Shujau Abdul Hakeem

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Illegal immigrants’ problem is a big problem all over the world including Maldives. Nowadays, it is turned into a major problem for Maldives. Many illegal immigrants are staying in Maldives from different countries such as Bangladesh, India, Pakistan, Nepal, Philippines and Sri Lanka. The aim of this article is to highlight the present situation of illegal immigrant in Maldives. At the same time, this article also tries to explain the legal protection of illegal immigrant. The research will adopt qualitative methods of research. The qualitative method involves doctrinal. As a doctrinal research, author used secondary sources. As secondary sources, the author used journal articles, newspapers and other useful materials to help the purpose of this research. Government agencies have to more concern to solve this problem.

Keywords: critical appraisal, illegal immigrants, Maldives, overview

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Authors: Bezhan Ghvaberidze

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A fuzzy multi-objective facility location-selection problem (FLSP) under uncertain and extreme environments based on possibility theory is developed. The model’s uncertain parameters in the q-rung orthopair fuzzy values are presented and transformed in the Dempster-Shaper’s belief structure environment. An objective function – distribution centers’ selection ranking index as an extension of Dempster’s extremal expectations under discrimination q-rung orthopair fuzzy information is constructed. Experts evaluate each humanitarian aid from distribution centers (HADC) against each of the uncertain factors. HADCs location problem is reduced to the bicriteria problem of partitioning the set of customers by the set of centers: (1) – Minimization of transportation costs; (2) – Maximization of centers’ selection ranking indexes. Partitioning type constraints are also constructed. For an illustration of the obtained results, a numerical example is created from the facility location-selection problem.

Keywords: FLSP, multi-objective combinatorial optimization problem, evidence theory, HADC, q-rung orthopair fuzzy set, possibility theory

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Authors: Zhenjie Liu

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This paper investigates the existence and uniqueness of solutions for singular higher order boundary value problems on time scales by using mixed monotone method. The theorems obtained are very general. For the different time scale, the problem may be the corresponding continuous or discrete boundary value problem.

Keywords: mixed monotone operator, boundary value problem, time scale, green's function, positive solution, singularity

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Authors: Khabat M. Ahmad

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This experiment focuses on the reduction of permeability (formation damage) as a result of fines migration by changing pH and flow rate on core plugs selected from sandstone reservoir of Pannonian basin (Upper Miocene, East Hungary). The main objective of coreflooding experiments was to investigate the influence of both high and low pH fluids and the flow rate on stability of clay minerals. The selected core samples were examined by X-ray powder diffraction (XRD) for bulk mineralogical and clay mineral composition. The shape, position, distribution and type of clay minerals within the core samples were diagnosed by scanning electron microscopy and energy dispersive spectroscopy (SEM- EDS). The basic petrophysical properties such as porosity and initial permeability were determined prior to experiments. The special core analysis (influence of pH and flow rate) on permeability reduction was examined through a series of laboratory coreflooding experiments, testing for acidic (3) and alkaline (11) solutions at different flow rates (50, 100 and 200 ml/h). Permeability in continuously reduced for pH 11 to more than 50 % of initial permeability. However, at pH 3 after a slow decrease, a significant increase is observed, to more than 40 % of initial permeability. The variation is also influenced by flow rate.

Keywords: flow rate, pH, permeability, fine migration, formation damage, XRD, SEM- EDS

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Authors: Ashish Shrivastava, C. Pandu Rangan

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In this paper, we consider The Hospitals Residents problem with Social Stability (HRSS), where hospitals and residents can communicate only through the underlying social network. Those residents and hospitals which don not have any social connection between them can not communicate and hence they cannot be a social blocking pair with respect to a socially stable matching in an instance of hospitals residents problem with social stability. In large scale matching like NRMP or Scottish medical matching scheme etc. where set of agents, as well as length of preference lists, are very large, social stability is a useful notion in which members of a blocking pair could block a matching if and only if they know the existence of each other. Thus the notion of social stability in hospitals residents problem allows us to increase the cardinality of the matching without taking care of those blocking pairs which are not socially connected to each other. We know that finding a maximum cardinality socially stable matching, in an instance, of HRSS is NP-hard. This motivates us to solve this problem with bounded length preference lists on one side. In this paper, we have presented a polynomial time algorithm to compute maximum cardinality socially stable matching in a HRSS instance where residents can give at most two length and hospitals can give unbounded length preference list. Preference lists of residents and hospitals will be strict in nature.

Keywords: matching under preference, socially stable matching, the hospital residents problem, the stable marriage problem

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Authors: Adel Bouchakhchoukha, Hakim Akeb

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In this work, we propose a hybrid heuristic in order to solve the Team Orienteering Problem (TOP). Given a set of points (or customers), each with associated score (profit or benefit), and a team that has a fixed number of members, the problem to solve is to visit a subset of points in order to maximize the total collected score. Each member performs a tour starting at the start point, visiting distinct customers and the tour terminates at the arrival point. In addition, each point is visited at most once, and the total time in each tour cannot be greater than a given value. The proposed heuristic combines beam search and a local optimization strategy. The algorithm was tested on several sets of instances and encouraging results were obtained.

Keywords: team orienteering problem, vehicle routing, beam search, local search

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Authors: Yasir Karabacak

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Objective: The aim of periodontal therapy is to control and eliminate inflammation in order halt disease progression. The initial periodontal therapy (IPT) including scaling and root planing (SRP) can control periodontal disease in most cases of periodontitis; also maintaining good oral hygiene by the patient is fundamental. The aim of this case report is to present IPT and to present 3-month follow-up results in a patient with periodontitis. Materials and Methods IPT of a 63-year-old non-smoker male with generalized periodontitis is presented. The patient had no history of systemic disease. The intraoral examination reveals marked gingival inflammation as well as plaque accumulation and significant calculus deposits. On radiographic examination, severe bone loss was evident. The patient was diagnosed with generalized advanced periodontitis. Initial periodontal therapy including oral hygiene instructions and quadrant-based SRP under local anesthesia was performed using hand and ultrasonic instruments. No antibiotics were prescribed. The patient was recalled 4 weeks after IPT. Results Favorable clinical improvement was obtained. Gingival inflammation was resolved significantly. A reduction of the mean probing depth from 2.4 mm at baseline to 1.9 mm was observed. The patient presented with a good standard of oral hygiene. The plaque scores decreased from 54.0% at baseline to 17.0%. In addition, the percentage of sites with bleeding on probing decreased from 80.0% at baseline to 44.0%. The patient was scheduled for maintenance therapy every three months. Conclusion: The level of oral hygiene has a great impact on periodontal treatment outcome and supports periodontal therapy properly.

Keywords: initial periodontal, therapy and follow-up in a periodontitis, patient, a case report

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Authors: Chong-Yang Qiao, Teeravarunyou Sakol

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Current production-oriented factories need maintenance operators to work in shifts monitoring and inspecting complex systems and different equipment in the situation of mechanical breakdown. Augmented reality (AR) is an emerging technology that embeds data into the environment for situation awareness to help maintenance operators make decisions and solve problems. An application was designed to identify the problem of steam generators and inspection centrifugal pumps. The objective of this research was to find the best medium of AR and type of problem solving strategies among analogy, focal object method and mean-ends analysis. Two scenarios of inspecting leakage were temperature and vibration. Two experiments were used in usability evaluation and future innovation, which included decision-making process and problem-solving strategy. This study found that maintenance operators prefer build-in magnifier to zoom the components (55.6%), 3D exploded view to track the problem parts (50%), and line chart to find the alter data or information (61.1%). There is a significant difference in the use of analogy (44.4%), focal objects (38.9%) and mean-ends strategy (16.7%). The marked differences between maintainers and operators are of the application of a problem solving strategy. However, future work should explore multimedia information retrieval which supports maintenance operators for decision-making.

Keywords: augmented reality, situation awareness, decision-making, problem-solving

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