Search results for: block layout problem

Authors: Carla Van De Sande, Jana Vandenberg

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Just like physical skills, cognitive skills grow rusty over time unless they are regularly used and practiced, so academic breaks can have negative consequences on student learning and success. The Keeping in School Shape (KiSS) program is an engaging, accessible, and cost-effective intervention that harnesses the benefits of retrieval practice by using technology to help students maintain proficiency over breaks from school by delivering a daily review problem via text message or email. A growth mindset is promoted through feedback messages encouraging students to try again if they get a problem wrong and to take on a challenging problem if they get a problem correct. This paper reports on the relationship between confidence, accuracy, and decision-making during the implementation of the KiSS Program at a large university during winter break for students enrolled in an engineering introductory Calculus course sequence.

Keywords: growth mindset, learning loss, on-the-go learning, retrieval practice

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Authors: F. Hamidi, N. Amiri, H. Mishmast Nehi

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The Bilevel Programming (BP) model has been presented for a decision making process that consists of two decision makers in a hierarchical structure. In fact, BP is a model for a static two person game (the leader player in the upper level and the follower player in the lower level) wherein each player tries to optimize his/her personal objective function under dependent constraints; this game is sequential and non-cooperative. The decision making variables are divided between the two players and one’s choice affects the other’s benefit and choices. In other words, BP consists of two nested optimization problems with two objective functions (upper and lower) where the constraint region of the upper level problem is implicitly determined by the lower level problem. In real cases, the coefficients of an optimization problem may not be precise, i.e. they may be interval. In this paper we develop an algorithm for solving interval bilevel linear fractional programming problems. That is to say, bilevel problems in which both objective functions are linear fractional, the coefficients are interval and the common constraint region is a polyhedron. From the original problem, the best and the worst bilevel linear fractional problems have been derived and then, using the extended Charnes and Cooper transformation, each fractional problem can be reduced to a linear problem. Then we can find the best and the worst optimal values of the leader objective function by two algorithms.

Keywords: best and worst optimal solutions, bilevel programming, fractional, interval coefficients

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Authors: María L. Jalón, Feargal Brennan

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A non-stationary stochastic optimization methodology is applied to an OWC (oscillating water column) to find the design that maximizes the wave energy extraction. Different temporal cycles are considered to represent the long-term variability of the wave climate at the site in the optimization problem. The results of the non-stationary stochastic optimization problem are compared against those obtained by a stationary stochastic optimization problem. The comparative analysis reveals that the proposed non-stationary optimization provides designs with a better fit to reality. However, the stationarity assumption can be adequate when looking at averaged system response.

Keywords: non-stationary stochastic optimization, oscillating water, temporal variability, wave energy

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Authors: Antonin Ponsich, Eric Alfredo Rincon Garcia, Roman Anselmo Mora Gutierrez, Miguel Angel Gutierrez Andrade, Sergio Gerardo De Los Cobos Silva, Pedro Lara Velzquez

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The electoral zone design problem consists in redrawing the boundaries of legislative districts for electoral purposes in such a way that federal or state requirements are fulfilled. In Mexico, this process has been historically carried out by the National Electoral Institute (INE), by optimizing an integer nonlinear programming model, in which population equality and compactness of the designed districts are considered as two conflicting objective functions, while contiguity is included as a hard constraint. The solution technique used by the INE is a Simulated Annealing (SA) based algorithm, which handles the multi-objective nature of the problem through an aggregation function. The present work represents the first intent to apply a classical Multi-Objective Evolutionary Algorithm (MOEA), the second version of the Non-dominated Sorting Genetic Algorithm (NSGA-II), to this hard combinatorial problem. First results show that, when compared with the SA algorithm, the NSGA-II obtains promising results. The MOEA manages to produce well-distributed solutions over a wide-spread front, even though some convergence troubles for some instances constitute an issue, which should be corrected in future adaptations of MOEAs to the redistricting problem.

Keywords: multi-objective optimization, NSGA-II, redistricting, zone design problem

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Authors: Marco Soto-Arriaza, Eduardo Cena-Ahumada, Jaime Melendez-Rojel

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Background: Liposomes have been widely used as a model of lipid bilayer to study the physicochemical properties of biological membrane, encapsulation, transport and release of different molecules. Furthermore, extensive research has focused on improving the efficiency in the transport of drugs, developing tools that improve the release of the encapsulated drug from liposomes. In this context, the enzymatic activity of PLA₂, despite having been shown to be an effective tool to promote the release of drugs from liposomes, is still an open field of research. Aim: The aim of the present study is to explore the effect of cholesterol (Cho) and amphipathic di- and tri-block copolymers, on calcein release mediated by enzymatic activity of PLA2 in Dipalmitoylphosphatidylcholine (DPPC) liposomes under physiological conditions. Methods: Different dispersions of DPPC, cholesterol, di-block POE₄₅-PCL₅₂ or tri-block PCL₁₂-POE₄₅-PCL₁₂ were prepared by the extrusion method after five freezing/thawing cycles; in Phosphate buffer 10mM pH 7.4 in presence of calcein. DPPC liposomes/Calcein were centrifuged at 15000rpm 10 min to separate free calcein. Enzymatic activity assays of PLA₂ were performed at 37°C using the TBS buffer pH 7.4. The size distribution, polydispersity, Z-potential and Calcein encapsulation of DPPC liposomes was monitored. Results: PLA₂ activity showed a slower kinetic of calcein release up to 20 mol% of cholesterol, evidencing a minimum at 10 mol% and then a maximum at 18 mol%. Regardless of the percentage of cholesterol, up to 18 mol% a one-hundred percentage release of calcein was observed. At higher cholesterol concentrations, PLA₂ showed to be inefficient or not to be involved in calcein release. In assays where copolymers were added in a concentration lower than their cmc, a similar behavior to those showed in the presence of Cho was observed, that is a slower kinetic in calcein release. In both experimental approaches, a one-hundred percentage of calcein release was observed. PLA₂ was shown to be sensitive to the 4-(4-Octadecylphenyl)-4-oxobutenoic acid inhibitor and calcium, reducing the release of calcein to 0%. Cell viability of HeLa cells decreased 7% in the presence of DPPC liposomes after 3 hours of incubation and 17% and 23% at 5 and 15 hours, respectively. Conclusion: Calcein release from DPPC liposomes, mediated by PLA₂ activity, depends on the percentage of cholesterol and the presence of copolymers. Both, cholesterol up to 20 mol% and copolymers below it cmc could be applied to the regulation of the kinetics of antitumoral drugs release without inducing cell toxicity per se.

Keywords: amphipathic copolymers, calcein release, cholesterol, DPPC liposome, phospholipase A₂

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Authors: P. Parthiban, Sonu Rajak, N. Kannan, R. Dhanalakshmi

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This paper deals with the Vehicle Routing Problem (VRP) with environmental considerations which is called Pollution Routing Problem (PRP). The objective is to minimize the operational and environmental costs. It consists of routing a number of vehicles to serve a set of customers, and determining fuel consumption, driver wages and their speed on each route segment, while respecting the capacity constraints and time windows. In this context, we presented an Ant Colony Optimization (ACO) approach, combined with a Speed Optimization Algorithm (SOA) to solve the PRP. The proposed solution method consists of two stages. Stage one is to solve a Vehicle Routing Problem with Time Window (VRPTW) using ACO and in the second stage a SOA is run on the resulting VRPTW solutions. Given a vehicle route, the SOA consists of finding the optimal speed on each arc of the route in order to minimize an objective function comprising fuel consumption costs and driver wages. The proposed algorithm tested on benchmark problem, the preliminary results show that the proposed algorithm is able to provide good solutions.

Keywords: ant colony optimization, CO2 emissions, combinatorial optimization, speed optimization, vehicle routing

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Authors: Imen Boudali, Marwa Ragmoun

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The Vehicle Routing Problem with Hard Time Windows (VRPHTW) is a basic distribution management problem that models many real-world problems. The objective of the problem is to deliver a set of customers with known demands on minimum-cost vehicle routes while satisfying vehicle capacity and hard time windows for customers. In this paper, we propose to deal with our optimization problem by using a new hybrid stochastic algorithm based on two metaheuristics: Chemical Reaction Optimization (CRO) and Greedy Randomized Adaptive Search Procedure (GRASP). The first method is inspired by the natural process of chemical reactions enabling the transformation of unstable substances with excessive energy to stable ones. During this process, the molecules interact with each other through a series of elementary reactions to reach minimum energy for their existence. This property is embedded in CRO to solve the VRPHTW. In order to enhance the population diversity throughout the search process, we integrated the GRASP in our method. Simulation results on the base of Solomon’s benchmark instances show the very satisfactory performances of the proposed approach.

Keywords: Benchmark Problems, Combinatorial Optimization, Vehicle Routing Problem with Hard Time Windows, Meta-heuristics, Hybridization, GRASP, CRO

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Authors: Armin Amindari

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Hermetic compressors are used widely for refrigeration, heat pump, and air conditioning applications. With the improvement of energy conservation and environmental protection requirements, inverter compressors that operates at different speeds have become increasingly attractive in the industry. Although speed change capability is more efficient, passing through resonant frequencies may lead to excessive vibrations. In this work, an integrated vibration control approach based on flexible multi-body dynamics theory is used for optimizing the vibration amplitudes of the compressor at different operating speeds. To examine the compressor vibrations, all the forces and moments exerted on the cylinder block were clarified and minimized using balancers attached to the upper and lower ends of the motor rotor and crankshaft. The vibration response of the system was simulated using Motionview™ software. In addition, mass-spring optimization was adopted to shift the resonant frequencies out of the operating speeds. The modal shapes of the system were studied using Optistruct™ solver. Using this approach, the vibrations were reduced up to 56% through dynamic simulations. The results were in high agreement with various experimental test data. In addition, the vibration resonance problem observed at low speeds was solved by shifting the resonant frequencies through optimization studies.

Keywords: vibration, MBD, compressor, hermetic

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Authors: Alaa Sheta

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Economic Load Dispatch (ELD) is one of the vital optimization problems in power system planning. Solving the ELD problems mean finding the best mixture of power unit outputs of all members of the power system network such that the total fuel cost is minimized while sustaining operation requirements limits satisfied across the entire dispatch phases. Many optimization techniques were proposed to solve this problem. A famous one is the Quadratic Programming (QP). QP is a very simple and fast method but it still suffer many problem as gradient methods that might trapped at local minimum solutions and cannot handle complex nonlinear functions. Numbers of metaheuristic algorithms were used to solve this problem such as Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO). In this paper, another meta-heuristic search algorithm named Differential Evolution (DE) is used to solve the ELD problem in power systems planning. The practicality of the proposed DE based algorithm is verified for three and six power generator system test cases. The gained results are compared to existing results based on QP, GAs and PSO. The developed results show that differential evolution is superior in obtaining a combination of power loads that fulfill the problem constraints and minimize the total fuel cost. DE found to be fast in converging to the optimal power generation loads and capable of handling the non-linearity of ELD problem. The proposed DE solution is able to minimize the cost of generated power, minimize the total power loss in the transmission and maximize the reliability of the power provided to the customers.

Keywords: economic load dispatch, power systems, optimization, differential evolution

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Authors: Tunjo Perić, Franjo Bratić

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In this paper the goal programming methodology for solving multiple objective problem of the technological variants and production plan optimization has been applied. The optimization criteria are determined and the multiple objective linear programming model for solving a problem of the technological variants and production plan optimization is formed and solved. Then the obtained results are analysed. The obtained results point out to the possibility of efficient application of the goal programming methodology in solving the problem of the technological variants and production plan optimization. The paper points out on the advantages of the application of the goal programming methodolohy compare to the Surrogat Worth Trade-off method in solving this problem.

Keywords: goal programming, multi objective programming, production plan, SWT method, technological variants

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Authors: Samia Kouki

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Solving NP-hard combinatorial optimization problems by exact search methods, such as Branch-and-Bound, may degenerate to complete enumeration. For that reason, exact approaches limit us to solve only small or moderate size problem instances, due to the exponential increase in CPU time when problem size increases. One of the most promising ways to reduce significantly the computational burden of sequential versions of Branch-and-Bound is to design parallel versions of these algorithms which employ several processors. This paper describes a parallel Branch-and-Bound algorithm called GALB for solving the classical permutation flowshop scheduling problem as well as its implementation on a Grid computing infrastructure. The experimental study of our distributed parallel algorithm gives promising results and shows clearly the benefit of the parallel paradigm to solve large-scale instances in moderate CPU time.

Keywords: grid computing, permutation flow shop problem, branch and bound, load balancing

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Authors: Shahriyar Keshtgar, Mahmoud Reza Heyhat, Sasan Bagheri, Ebrahim Gholami, Seyed Naser Raiisosadat

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The eastern Iranian range is a Z-shaped sigmoidal outcrop appearing with a NS-trending general strike on the satellite images, has already been known as the Sistan suture zone, recently identified as the product of an orogenic event introduced either by the Paleogene or Sistan orogen names. The flysch sedimentary basin of eastern Iran was filled by a huge volume of fine-grained Eocene turbiditic sediments, smaller amounts of pelagic deposits and Cretaceous ophiolitic slices, which are entirely remnants of older accretionary prisms appeared in a fold-thrust belt developed onto a subduction zone under the Lut/Afghan block, portions of the Cimmerian superterrane. In these ranges, there are Triassic sedimentary and carbonate sequences (equivalent to Nayband and Shotori Formations) along with scattered outcrops of Permian limestones (equivalent to Jamal limestone) and greenschist-facies metamorphic rocks, probably belonging to the basement of the Lut block, which have tectonic contacts with younger rocks. Moreover, the younger Eocene detrital-volcanic rocks were also thrusted onto the Cretaceous or younger turbiditic deposits. The first generation folds (parallel folds) and thrusts with slaty cleavage appeared parallel to the NE edge of the Lut block. Structural analysis shows that the most vergence of thrusts is toward the southeast so that the Permo-Triassic units in Lut have been thrusted on the younger rocks, including older (probably Jurassic) granites. Additional structural studies show that the regional transport direction in this deformation event is from northwest to the southeast where, from the outside to the inside of the orogen in the Sechengi area. Younger thrusts of the second deformation event were either directly formed as a result of the second deformation event, or they were older thrusts that reactivated and folded so that often, two sets or more slickenlines can be recognized on the thrust planes. The recent thrusts have been redistributed in directions nearly perpendicular to the edge of the Lut block and parallel to the axial surfaces of the northwest second generation large-scale folds (radial folds). Some of these younger thrusts follow the out-of-the-syncline thrust system. The both axial planes of these folds and associated penetrative shear cleavage extended towards northwest appeared with both northeast and southwest dips parallel to the younger thrusts. The large-scale buckling with the layer-parallel stress field has created this deformation event. Such consecutive deformation events perpendicular to each other cannot be basically explained by the simple linear orogen models presented for eastern Iran so far and are more consistent with the oroclinal buckling model.

Keywords: thrust, tectonic vergence, orocline buckling, sechangi, eastern iranian ranges

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Authors: Ken Hampshire, Thomas Mazzuchi, Shahram Sarkani

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As a subset of metaheuristics, nature-inspired optimization algorithms such as particle swarm optimization (PSO) have shown promise both in solving intractable problems and in their extensibility to novel problem formulations due to their general approach requiring few assumptions. Unfortunately, single instantiations of algorithms require detailed tuning of parameters and cannot be proven to be best suited to a particular illustrative problem on account of the “no free lunch” (NFL) theorem. Using these algorithms in real-world problems requires exquisite knowledge of the many techniques and is not conducive to reconciling the various approaches to given classes of problems. This research aims to present a unified view of PSO-based approaches from the perspective of relevant systems engineering problems, with the express purpose of then eliciting the best solution for any problem formulation in an ensemble learning bucket of models approach. The central hypothesis of the research is that extending the PSO algorithms found in the literature to real-world optimization problems requires a general ensemble-based method for all problem formulations but a specific implementation and solution for any instance. The main results are a problem-based literature survey and a general method to find more globally optimal solutions for any systems engineering optimization problem.

Keywords: particle swarm optimization, nature-inspired optimization, metaheuristics, systems engineering, ensemble learning

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Authors: Bruno Baptista, Andreia S. R. Oliveira, Patricia V. Mendonca, Jorge F. J. Coelho, Fani Sousa

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Drug delivery systems are designed to allow adequate protection and controlled delivery of drugs to specific locations. These systems aim to reduce side effects and control the biodistribution profile of drugs, thus improving therapeutic efficacy. This study involved the synthesis of polymeric nanoparticles, based on amphiphilic diblock copolymers, comprising a biocompatible, poly (oligo (ethylene oxide) methyl ether methacrylate (POEOMA) as hydrophilic segment and a pH-sensitive block, the poly (2-diisopropylamino)ethyl methacrylate) (PDPA). The objective of this work was the development of polymeric pH-responsive nanoparticles to encapsulate and carry small RNAs as a model to further develop non-coding RNAs delivery systems with therapeutic value. The responsiveness of PDPA to pH allows the electrostatic interaction of these copolymers with nucleic acids at acidic pH, as a result of the protonation of the tertiary amine groups of this polymer at pH values below its pKa (around 6.2). Initially, the molecular weight parameters and chemical structure of the block copolymers were determined by size exclusion chromatography (SEC) and nuclear magnetic resonance (1H-NMR) spectroscopy, respectively. Then, the complexation with small RNAs was verified, generating polyplexes with sizes ranging from 300 to 600 nm and with encapsulation efficiencies around 80%, depending on the molecular weight of the polymers, their composition, and concentration used. The effect of pH on the morphology of nanoparticles was evaluated by scanning electron microscopy (SEM) being verified that at higher pH values, particles tend to lose their spherical shape. Since this work aims to develop systems for the delivery of non-coding RNAs, studies on RNA protection (contact with RNase, FBS, and Trypsin) and cell viability were also carried out. It was found that they induce some protection against constituents of the cellular environment and have no cellular toxicity. In summary, this research work contributes to the development of pH-sensitive polymers, capable of protecting and encapsulating RNA, in a relatively simple and efficient manner, to further be applied on drug delivery to specific sites where pH may have a critical role, as it can occur in several cancer environments.

Keywords: drug delivery systems, pH-responsive polymers, POEOMA-b-PDPA, small RNAs

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Authors: Tun Myat Aung, Ni Ni Hla

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This paper begins by describing basic properties of finite field and elliptic curve cryptography over prime field and binary field. Then we discuss the discrete logarithm problem for elliptic curves and its properties. We study the general common attacks on elliptic curve discrete logarithm problem such as the Baby Step, Giant Step method, Pollard’s rho method and Pohlig-Hellman method, and describe in detail experiments of these attacks over prime field and binary field. The paper finishes by describing expected running time of the attacks and suggesting strong elliptic curves that are not susceptible to these attacks.c

Keywords: discrete logarithm problem, general attacks, elliptic curve, prime field, binary field

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Authors: Ramya P, Lino Abraham Varghese, S. Bose

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By cloud storage services, the data can be stored in the cloud, and can be shared across multiple users. Due to the unexpected hardware/software failures and human errors, which make the data stored in the cloud be lost or corrupted easily it affected the integrity of data in cloud. Some mechanisms have been designed to allow both data owners and public verifiers to efficiently audit cloud data integrity without retrieving the entire data from the cloud server. But public auditing on the integrity of shared data with the existing mechanisms will unavoidably reveal confidential information such as identity of the person, to public verifiers. Here a privacy-preserving mechanism is proposed to support public auditing on shared data stored in the cloud. It uses group signatures to compute verification metadata needed to audit the correctness of shared data. The identity of the signer on each block in shared data is kept confidential from public verifiers, who are easily verifying shared data integrity without retrieving the entire file. But on demand, the signer of the each block is reveal to the owner alone. Group private key is generated once by the owner in the static group, where as in the dynamic group, the group private key is change when the users revoke from the group. When the users leave from the group the already signed blocks are resigned by cloud service provider instead of owner is efficiently handled by efficient proxy re-signature scheme.

Keywords: data integrity, dynamic group, group signature, public auditing

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Authors: Ernesto Linan, Linda Cruz, Lucero Becerra

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In this paper, a new hybridized algorithm based on Chemical Reaction Optimization and Simulated Annealing is proposed to solve the alignment sequence Problem. The Chemical Reaction Optimization is a population-based meta-heuristic algorithm based on the principles of a chemical reaction. Simulated Annealing is applied to solve a large number of combinatorial optimization problems of general-purpose. In this paper, we propose hybridization between Chemical Reaction Optimization algorithm and Simulated Annealing in order to solve the Sequence Alignment Problem. An initial population of molecules is defined at beginning of the proposed algorithm, where each molecule represents a sequence alignment problem. In order to simulate inter-molecule collisions, the process of Chemical Reaction is placed inside the Metropolis Cycle at certain values of temperature. Inside this cycle, change of molecules is done due to collisions; some molecules are accepted by applying Boltzmann probability. The results with the hybrid scheme are better than the results obtained separately.

Keywords: chemical reaction optimization, sequence alignment problem, simulated annealing algorithm, metaheuristics

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Authors: Rouhallah Bagheri, Morteza Mahmoudi, Hadi Moheb-Alizadeh

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This paper aims at developing a multi-objective model for supplier selection and order allocation problem in stochastic environment, where purchasing cost, percentage of delivered items with delay and percentage of rejected items provided by each supplier are supposed to be stochastic parameters following any arbitrary probability distribution. In this regard, dependent chance programming is used which maximizes probability of the event that total purchasing cost, total delivered items with delay and total rejected items are less than or equal to pre-determined values given by decision maker. The abovementioned stochastic multi-objective programming problem is then transformed into a stochastic single objective programming problem using minimum deviation method. In the next step, the further problem is solved applying a genetic algorithm, which performs a simulation process in order to calculate the stochastic objective function as its fitness function. Finally, the impact of stochastic parameters on the given solution is examined via a sensitivity analysis exploiting coefficient of variation. The results show that whatever stochastic parameters have greater coefficients of variation, the value of the objective function in the stochastic single objective programming problem is deteriorated.

Keywords: supplier selection, order allocation, dependent chance programming, genetic algorithm

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

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Authors: Zhanar Imanova

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Masses of real celestial bodies change anisotropically and reactive forces appear, and they need to be taken into account in the study of these bodies' dynamics. We studied the two-planet problem of three bodies with variable masses in the presence of reactive forces and obtained the equations of perturbed motion in Newton’s form equations. The motion equations in the orbital coordinate system, unlike the Lagrange equation, are convenient for taking into account the reactive forces. The perturbing force is expanded in terms of osculating elements. The expansion of perturbing functions is a time-consuming analytical calculation and results in very cumber some analytical expressions. In the considered problem, we obtained expansions of perturbing functions by small parameters up to and including the second degree. In the non resonant case, we obtained evolution equations in the Newton equation form. All symbolic calculations were done in Wolfram Mathematica.

Keywords: two-planet, three-body problem, variable mass, evolutionary equations

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Authors: Ekta Jain, Kalpana Dahiya, Vanita Verma

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This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory.

Keywords: assignment, imbalanced, priority, time minimization

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Authors: Ahmet Faruk Akyuz, Hasan Sakir Bilge

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Depth estimation using stereo images is a challenging problem in computer vision. Many different studies have been carried out to solve this problem. With advancing machine learning, tackling this problem is often done with neural network-based solutions. The images used in these studies are mostly in the visible spectrum. However, the need to use the Infrared (IR) spectrum for depth estimation has emerged because it gives better results than visible spectra in some conditions. At this point, we recommend using thermal-thermal (IR) image pairs for depth estimation. In this study, we used two well-known networks (PSMNet, FADNet) with minor modifications to demonstrate the viability of this idea.

Keywords: thermal stereo matching, deep neural networks, CNN, Depth estimation

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Authors: Zhang Tianci, Ding Meng, Zuo Hongfu, Zeng Lina, Sun Zejun

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Automation of airport operations can greatly improve ground movement efficiency. In this paper, we study the speed profile design problem for advanced airport ground movement control and guidance. The problem is constrained by the surface four-dimensional trajectory generated in taxi planning. A decomposed approach of two stages is presented to solve this problem efficiently. In the first stage, speeds are allocated at control points which ensure smooth speed profiles can be found later. In the second stage, detailed speed profiles of each taxi interval are generated according to the allocated control point speeds with the objective of minimizing the overall fuel consumption. We present a swarm intelligence based algorithm for the first-stage problem and a discrete variable driven enumeration method for the second-stage problem since it only has a small set of discrete variables. Experimental results demonstrate the presented methodology performs well on real world speed profile design problems.

Keywords: airport ground movement, fuel consumption, particle swarm optimization, smoothness, speed profile design

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Authors: Sabri Sulaiman, Siti Hajar Abu Bakar Ah, Haris Abd Wahab

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Street children is a global phenomenon and declared as a social problem by social researcher and scholars across the world. The insecure street environment exposes street children into various risk factors. One of them is the health and psychological problem. The objective of this study is to assess the health problem and psychological wellbeing of street children in Kuala Lumpur, Malaysia. The cross-sectional study involved 303 street children in Chow Kit, Kuala Lumpur. The study confirmed that the majority (95.7%) of street children who participated in the study have a health problem. The findings also demonstrated that the majority of them have issues related to their psychological wellbeing. The inputs from this study are instrumental for the suggestion of specific intervention to improve the health and psychology wellbeing of street children in Malaysia. Agencies which are responsible for the street children well-being can utilise the inputs to framing and improving the social care programmes for the children.

Keywords: street children, health status, psychology wellbeing, homeless

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Authors: Abdulaziz Alageel, Martino Luis, Shuya Zhong

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The main focus of this research study is on the challenges faced in decision-making in a supply chain network regarding the facility location while considering carbon emissions. The study aims (i) to locate facilities (i.e., distribution centeres) in a continuous space considering limitations of capacity and the costs associated with opening and (ii) to reduce the cost of carbon emissions by selecting the mode of transportation. The problem is formulated as mixed-integer linear programming. This study hybridised a greedy randomised adaptive search (GRASP) and variable neighborhood search (VNS) to deal with the problem. Well-known datasets from the literature (Brimberg et al. 2001) are used and adapted in order to assess the performance of the proposed method. The proposed hybrid method produces encouraging results based on computational analysis. The study also highlights some research avenues for future recommendations.

Keywords: supply chain, facility location, weber problem, sustainability

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Authors: Shikha Gupta, Suneet Kathuria, Supriya Sampley, Sunil Katyal

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Opioids are being increasingly used these days as adjuvants to local anesthetics in spinal anesthesia. The aim of this prospective, randomized, double‑blind study is to compare the effects of adding sufentanil or fentanyl to low dose bupivacaine in spinal anesthesia for endoscopic urological procedures. A total of 90 elective endoscopic urological surgery patients, 40‑80 years old, received spinal anesthesia with 7.5 mg hyperbaric bupivacaine 0.5% (Group A) or by adding sufentanil 10 μg (Group B) or fentanyl 25 μg (Group C) to 5 mg hyperbaric bupivacaine 0.5%. These groups were compared in terms of the quality of spinal anesthesia as well as analgesia. Analysis of variance and Chi‑square test were used for Statistical analysis. The onset of sensory and motor blockade was significantly rapid in Group A as compared with Groups B and C. The maximum upper level of sensory block was higher in Group A patients than Groups B and C patients. Quality of analgesia was significantly better and prolonged in sufentanil group as compared with other two groups. Motor block was more intense and prolonged in Group A as compared with Groups B and C patients. Request for post‑operative analgesic was significantly delayed in Group B patients. Hence in conclusions, spinal anesthesia for endoscopic urological procedures in elderly patients using low dose bupivacaine (5 mg) combined with 10 μg sufentanil is associated with a lower incidence of hemodynamic instability, better quality and prolonged duration as compared to that by adding 25 μg fentanyl.

Keywords: adjuvants, bupivacaine, fentanyl, intrathecal, low dose spinal, sufentanil

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Authors: Natalia D. Vaysfel’d, Zinaida Y. Zhuravlova

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The loaded plane elastic semistrip, the lateral boundaries of which are fixed, is considered. The integral transformations are applied directly to Lame’s equations. It leads to one dimensional boundary value problem in the transformations’ domain which is formulated as a vector one. With the help of the matrix differential calculation’s apparatus and apparatus of Green matrix function the exact solution of a vector problem is constructed. After the satisfying the boundary condition at the semi strip’s edge the problem is reduced to the solving of the integral singular equation with regard of the unknown stress at the semis trip’s edge. The equation is solved with the orthogonal polynomials method that takes into consideration the real singularities of the solution at the ends of integration interval. The normal stress at the edge of the semis trip were calculated and analyzed.

Keywords: semi strip, Green's Matrix, fourier transformation, orthogonal polynomials method

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Authors: Sutanto, Alexander Christy, N. Sutrisno

Abstract:

The demand of a product is linearly dependent on the price and quality of the product. It is analog to the demand of the employee in job-seeker problem. This paper address a closed-loop supply chain (CLSC) where a university plays role as manufacturer that produce graduates as job-seeker according to the demand and promote them to a certain corporation through a trial. Unemployed occurs when the job-seeker failed the trial or dismissed. A third party accomodates the unemployed and sends them back to the university to increase their quality through training.

Keywords: CLSC, price, quality, job-seeker problem

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Authors: M. S. Thakur, Mohit Shukla

Abstract:

A channel/tunnel, which carries the water to the penstock/pressure shaft is called headrace tunnel (HRT). It is necessary to know the general topography, geology of the area, state of stress and other mechanical properties of the strata. For this certain topographical and geological investigations, in-situ and laboratory tests, and observations are required to be done. These investigations play an important role in a tunnel design as these help in deciding the optimum layout, shape and size and support requirements of the tunnel. The paper includes inputs from Nathpa Jhakri Hydeoelectric project which is India’s highest capacity (1500 MW) operating hydroelectric project. The paper would help the design engineers with various new concepts and preparedness against geological surprises.

Keywords: tunnelling, geology, HRT, rockmass

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Authors: Eugene Stepanov, Arcady Ponosov

Abstract:

To model gene regulatory networks one uses ordinary differential equations with switching nonlinearities, where the initial value problem is known to be well-posed if the trajectories cross the discontinuities transversally. Otherwise, the initial value problem is usually ill-posed, which lead to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid dynamical systems, rather than switched ones, to regularize the problem. 'Hybridization' of the switched system means that one attaches a dynamic discrete component ('automaton'), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness of the initial value problem making it well-posed. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. Several examples are provided in the presentation, which support the suggested analysis. The method can also be of interest in other applied fields, where differential equations contain switchings, e.g. in neural field models.

Keywords: hybrid dynamical systems, ill-posed problems, singular perturbation analysis, switching nonlinearities

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