Search results for: optimal number

Authors: Egor E. Nuzhin, Nikolay V. Brilliantov

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We propose an approach for addressing Reinforcement Learning (RL) problems. It combines the ideas of umbrella sampling, borrowed from Monte Carlo technique of computational physics and chemistry, with optimal control methods, and is realized on the base of neural networks. This results in a powerful algorithm, designed to solve hard RL problems – the problems, with long-time delayed reward, state-traps sticking and a lack of terminal states. It outperforms the prominent algorithms, such as PPO, RND, iLQR and VI, which are among the most efficient for the hard problems. The new algorithm deals with a continuous ensemble of agents and expected return, that includes the ensemble entropy. This results in a quick and efficient search of the optimal policy in terms of ”exploration-exploitation trade-off” in the state-action space.

Keywords: umbrella sampling, reinforcement learning, policy gradient, dynamic programming

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Authors: Mohammed A. Hajeeh

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Pumping systems are an integral part of water desalination plants, their effective functioning is vital for the operation of a plant. In this research work, the reliability and availability of pressurized pumps in a reverse osmosis desalination plant are studied with the objective of finding configurations that provides optimal performance. Six configurations of a series system with different number of warm and cold standby components were examined. Closed form expressions for the mean time to failure (MTTF) and the long run availability are derived and compared under the assumption that the time between failures and repair times of the primary and standby components are exponentially distributed. Moreover, a cost/ benefit analysis is conducted in order to identify a configuration with the best performance and least cost. It is concluded that configurations with cold standby components are preferable especially when the pumps are of the size.

Keywords: availability, cost/benefit, mean time to failure, pumps

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Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

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Authors: Fuad M. Alkoot

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DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

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Authors: Julius M. Ndambuki, Gislar E. Kifanyi, Samuel N. Odai, Charles Gyamfi

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Conjunctive management of surface and groundwater resources is a challenging task due to the spatial and temporal variability nature of hydrology as well as hydrogeology of the water storage systems. Surface water-groundwater hydrogeology is highly uncertain; thus it is imperative that this uncertainty is explicitly accounted for, when managing water resources. Various methodologies have been developed and applied by researchers in an attempt to account for the uncertainty. For example, simulation-optimization models are often used for conjunctive water resources management. However, direct application of such an approach in which all realizations are considered at each iteration of the optimization process leads to a very expensive optimization in terms of computational time, particularly when the number of realizations is large. The aim of this paper, therefore, is to introduce and apply an efficient approach referred to as Retrospective Optimization Approximation (ROA) that can be used for optimizing conjunctive use of surface water and groundwater over a multiple hydrogeological model simulations. This work is based on stochastic simulation-optimization framework using a recently emerged technique of sample average approximation (SAA) which is a sampling based method implemented within the Retrospective Optimization Approximation (ROA) approach. The ROA approach solves and evaluates a sequence of generated optimization sub-problems in an increasing number of realizations (sample size). Response matrix technique was used for linking simulation model with optimization procedure. The k-means clustering sampling technique was used to map the realizations. The methodology is demonstrated through the application to a hypothetical example. In the example, the optimization sub-problems generated were solved and analysed using “Active-Set” core optimizer implemented under MATLAB 2014a environment. Through k-means clustering sampling technique, the ROA – Active Set procedure was able to arrive at a (nearly) converged maximum expected total optimal conjunctive water use withdrawal rate within a relatively few number of iterations (6 to 7 iterations). Results indicate that the ROA approach is a promising technique for optimizing conjunctive water use of surface water and groundwater withdrawal rates under hydrogeological uncertainty.

Keywords: conjunctive water management, retrospective optimization approximation approach, sample average approximation, uncertainty

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Authors: Ahmed E. Hodaib, Mohamed A. Hashem

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In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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Authors: Eva Štěpánková

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The decision-making process is theoretically clearly defined. Generally, it includes the problem identification and analysis, data gathering, goals and criteria setting, alternatives development and optimal alternative choice and its implementation. In practice however, various modifications of the theoretical decision-making process can occur. The managers can consider some of the phases to be too complicated or unfeasible and thus they do not carry them out and conversely some of the steps can be overestimated. The aim of the paper is to reveal and characterize the perception of the individual phases of decision-making process by the managers. The research is concerned with managers in the military environment–commanders. Quantitative survey is focused cross-sectionally in the individual levels of management of the Ministry of Defence of the Czech Republic. On the total number of 135 respondents the analysis focuses on which of the decision-making process phases are problematic or not carried out in practice and which are again perceived to be the easiest. Then it is examined the reasons of the findings.

Keywords: decision making, decision making process, decision problems, concrete organization

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Authors: Dimitri Golenko-Ginzburg

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A CPM network project with deterministic activity durations, in which activities require homogenous resources with fixed capacities, is considered. The problem is to determine the optimal schedule of starting times for all network activities within their maximal allowable limits (in order not to exceed the network's critical time) to minimize the maximum required resources for the project at any point in time. In case when a non-critical activity may start only at discrete moments with the pregiven time span, the problem becomes NP-complete and an optimal solution may be obtained via a look-over algorithm. For the case when a look-over requires much computational time an approximate algorithm is suggested. The algorithm's performance ratio, i.e., the relative accuracy error, is determined. Experimentation has been undertaken to verify the suggested algorithm.

Keywords: resource smoothing problem, CPM network, lookover algorithm, lexicographical order, approximate algorithm, accuracy estimate

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Authors: Khyati Sharma, A. Satyanarayana Reddy

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The topic of how many subgroups exist within a certain finite group naturally arises in the study of finite groups. Over the years, different researchers have investigated this issue from a variety of angles. The significant contributions of the key mathematicians over the time have been summarized in this article. To this end, we classify finite groups into three categories viz. (a) Groups for which the number of subgroups is less than |G|, (b) equals to |G|, and finally, (c) greater than |G|. Because every element of a finite group generates a cyclic subgroup, counting cyclic subgroups is the most important task in this endeavor. A brief survey on the number of cyclic subgroups of finite groups is also conducted by us. Furthermore, we also covered certain arithmetic relations between the order of a finite group |G| and the number of its distinct cyclic subgroups |C(G)|. In order to provide pertinent context and possibly reveal new novel areas of potential research within the field of research on finite groups, we finally pose and solicit a few open questions.

Keywords: abstract algebra, cyclic subgroup, finite group, subgroup

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Authors: Wheyming Song, Hung-Hsiang Lin, Scott Lian

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In this research, we investigate the optimal dispatching rule for machines and manpower allocation in the solar ingot-wafer systems. The performance of the method is measured by the sales profit for each dollar paid to the operators in a one week at steady-state. The decision variables are identification-number of machines and operators when each job is required to be served in each process. We propose a rule which is a function of operator’s ability, corresponding salary, and standing location while in the factory. The rule is named ‘Multi-nominal distribution dispatch rule’. The proposed rule performs better than many traditional rules including generic algorithm and particle swarm optimization. Simulation results show that the proposed Multi-nominal distribution dispatch rule improvement on the sales profit dramatically.

Keywords: dispatching, solar ingot, simulation, flexsim

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Authors: Davood Shishebori, Mohammad Saber Fallah Nezhad, Sina Seifi

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In this paper, a variable multiple dependent state (MDS) sampling plan is developed based on the process capability index using Bayesian approach. The optimal parameters of the developed sampling plan with respect to constraints related to the risk of consumer and producer are presented. Two comparison studies have been done. First, the methods of double sampling model, sampling plan for resubmitted lots and repetitive group sampling (RGS) plan are elaborated and average sample numbers of the developed MDS plan and other classical methods are compared. A comparison study between the developed MDS plan based on Bayesian approach and the exact probability distribution is carried out.

Keywords: MDS sampling plan, RGS plan, sampling plan for resubmitted lots, process capability index (PCI), average sample number (ASN), Bayesian approach

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Authors: Neha Sharma, Kanthi K. Kondepudi, Naveen Gupta

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Phytases are phytate specific phosphatases catalyzing the step-wise dephosphorylation of phytate, which acts as an anti-nutritional factor in food due to its strong binding capacity to minerals. In recent years microbial phytases have been explored for improving nutritional quality of food. But the major limitation is acceptability of phytases from these microorganisms. Therefore, efforts are being made to isolate organisms which are generally regarded as safe for human consumption such as Lactic Acid Bacteria (LAB). Phytases from these organisms will have an edge over other phytase sources due to its probiotic attributes. Only few LAB have been reported to give phytase activity that too is generally seen as intracellular. LAB producing extracellular phytase will be more useful as it can degrade phytate more effectively. Moreover, enzyme from such isolate will have application in food processing also. Only few species of Lactobacillus producing extracellular phytase have been reported so far. This study reports the isolation of a probiotic strain of Lactobacillus fermentum spp KA1 which produces extracellular phytase. Conditions for the optimal production of phytase have been optimized and the enzyme production resulted in an approximately 13-fold increase in yield. The phytate degradation potential of extracellular phytase in rice bran has been explored and conditions for optimal degradation were optimized. Under optimal conditions, there was 43.26% release of inorganic phosphate and 6.45% decrease of phytate content.

Keywords: Lactobacillus, phytase, phytate reduction, rice bran

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Authors: M. S. Aparna, Pushparaj Shetty D.

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Nowadays social networking sites have become so popular that the producers or the sellers look for these sites as one of the best options to target the right audience to market their products. There are several tools available to monitor or analyze the social networks. Our task is to identify the right community web pages and find out the behavior analysis of the members by using these tools and formulate an appropriate strategy to market the products or services to achieve the set goals. The advertising becomes more effective when the information of the product/ services come from a known source. The strategy explores great buying influence in the audience on referral marketing. Our methodology proceeds with critical budget analysis and promotes viral influence propagation. In this context, we encompass the vital bits of budget evaluation such as the number of optimal seed nodes or primary influential users activated onset, an estimate coverage spread of nodes and maximum influence propagating distance from an initial seed to an end node. Our proposal for Buyer Prediction mathematical model arises from the urge to perform complex analysis when the probability density estimates of reliable factors are not known or difficult to calculate. Order Statistics and Buyer Prediction mapping function guarantee the selection of optimal influential users at each level. We exercise an efficient tactics of practicing community pages and user behavior to determine the product enthusiasts on social networks. Our approach is promising and should be an elementary choice when there is little or no prior knowledge on the distribution of potential buyers on social networks. In this strategy, product news propagates to influential users on or surrounding networks. By applying the same technique, a user can search friends who are capable to advise better or give referrals, if a product interests him.

Keywords: viral marketing, social network analysis, community web pages, buyer prediction, influence propagation, budget constraints

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Authors: Aigul Manapova

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We consider an optimal control problem in the higher coefficient of nonlinear equations with a divergent elliptic operator and unbounded nonlinearity, and the Dirichlet boundary condition. The conditions imposed on the coefficients of the state equation are assumed to hold only in a small neighborhood of the exact solution to the original problem. This assumption suggests that the state equation involves nonlinearities of unlimited growth and considerably expands the class of admissible functions as solutions of the state equation. We obtain formulas for the first partial derivatives of the objective functional with respect to the control functions. To calculate the gradients the numerical solutions of the state and adjoint problems are used. We also prove that the gradient of the cost function is Lipchitz continuous.

Keywords: cost functional, differentiability, divergent elliptic operator, optimal control, unbounded nonlinearity

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Authors: Defne Akinci Midas

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The aim of this study was to determine the minimum, and maximum number of words that would be sufficient to fulfill the writing task in the local English Proficiency Exam (EPE) produced and administered at the Middle East Technical University, Ankara, Turkey. The relationship between the number of words and the scores of the written products that had been awarded by two raters in three online EPEs administered in 2020 was examined. The means, standard deviations, percentages, range, minimum and maximum scores as well as correlations of the scores awarded to written products with the words that amount to 0-50, 51-100, 101-150, 151-200, 201-250, 251-300, and so on were computed. The results showed that the raters did not award a full score to texts that had fewer than 100 words. Moreover, the texts that had around 200 words were awarded the highest scores. The highest number of words that earned the highest scores was about 225, and from then onwards, the scores were either stable or lower. A positive low to moderate correlation was found between the number of words and scores awarded to the texts. We understand that the idea of ‘the longer, the better’ did not apply here. The results also showed that words between 101 to about 225 were sufficient to fulfill the writing task to fully display writing skills and language ability in the specific case of this exam.

Keywords: English proficiency exam, number of words, scoring, writing task

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Authors: Radoslaw Pytlak, Damian Suski

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The aim of the paper is to provide a computational tool for planning a haemodialysis process. It is shown that optimization methods can be used to obtain the most effective treatment focused on removing both urea and phosphorus during the process. In order to achieve that, the IV–compartment model of phosphorus kinetics is applied. This kinetics model takes into account a rebound phenomenon that can occur during haemodialysis and results in a hybrid model of the process. Furthermore, vector fields associated with the model equations are such that it is very likely that using the most intuitive objective functions in the planning problem could lead to solutions which include sliding motions. Therefore, building computational tools for solving the problem of planning a haemodialysis process has required constructing numerical algorithms for solving optimal control problems with hybrid systems. The paper concentrates on minimum time control of hybrid systems since this control objective is the most suitable for the haemodialysis process considered in the paper. The presented approach to optimal control problems with hybrid systems is different from the others in several aspects. First of all, it is assumed that a hybrid system can exhibit sliding modes. Secondly, the system’s motion on the switching surface is described by index 2 differential–algebraic equations, and that guarantees accurate tracking of the sliding motion surface. Thirdly, the gradients of the problem’s functionals are evaluated with the help of adjoint equations. The adjoint equations presented in the paper take into account sliding motion and exhibit jump conditions at transition times. The optimality conditions in the form of the weak maximum principle for optimal control problems with hybrid systems exhibiting sliding modes and with piecewise constant controls are stated. The presented sensitivity analysis can be used to construct globally convergent algorithms for solving considered problems. The paper presents numerical results of solving the haemodialysis planning problem.

Keywords: haemodialysis planning process, hybrid systems, optimal control, sliding motion

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Authors: Ali Hosseini

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Paralleling is a mechanism to decrease the time necessary to execute the programs. Sorting is one of the important operations to be used in different systems in a way that the proper function of many algorithms and operations depend on sorted data. CRCW_SORT algorithm executes ‘N’ elements sorting in O(1) time on SIMD (Single Instruction Multiple Data) computers with n^2/2-n/2 number of processors. In this article having presented a mechanism by dividing the input string by the hinge element into two less strings the number of the processors to be used in sorting ‘N’ elements in O(1) time has decreased to n^2/8-n/4 in the best state; by this mechanism the best state is when the hinge element is the middle one and the worst state is when it is minimum. The findings from assessing the proposed algorithm by other methods on data collection and number of the processors indicate that the proposed algorithm uses less processors to sort during execution than other methods.

Keywords: CRCW, SIMD (Single Instruction Multiple Data) computers, parallel computers, number of the processors

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Authors: Andreja Benko

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Article presents a short overview of the architects’ profession over time with outlined work of the architectural theoreticians. In the continuation is described a former affiliation of Slovenia as well as the spatial planning documents that were in use until the Slovenia joint Yugoslavia (last part in 1919). This legislation from former Austro-Hungarian monarchy was valid almost until 1950 in some parts of Yugoslavia even longer. Upon that will be mentioned some valid Slovenian spatial documents which will be compared with the German legislation. Analysed will be the number of architect and spatial planners in Slovenia and also their number upon certain region in Slovenia. Based on that will be given also the number from statistical office of Slovenia of the number of buildings between years 2007 and 2012, and described also the collapse of the major construction companies in Slovenia and consequences of that. At the end will be outlined the morality and ethics by spatial interventions and lack of the architectural law in Slovenia as well as the problematic of minimal collaboration between the Ministry of infrastructure and spatial planning with the profession.

Keywords: architect, history, legislation, Slovenia

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Authors: Paolo Russu

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The purpose of the present paper is to highlight some features of an economic growth model with environmental negative externalities, giving rise to a three-dimensional dynamic system. In particular, we show that the economy, which is based on a Perfect-Substitution Technologies function of production, has no neither indeterminacy nor poverty trap. This implies that equilibrium select by economy depends on the history (initial values of state variable) of the economy rather than on expectations of economies agents. Moreover, by contrast, we prove that the basin of attraction of locally equilibrium points may be very large, as they can extend up to the boundary of the system phase space. The infinite-horizon optimal control problem has the purpose of maximizing the representative agent’s instantaneous utility function depending on leisure and consumption.

Keywords: Hopf bifurcation, open-access natural resources, optimal control, perfect-substitution technologies, Poincarè compactification

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Authors: Ogan Karabas, Suleyman Yigit

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Number of blade and blade type of centrifugal fans are the most decisive factor on the field of application, noise level, suction pressure and outlet mass flow rate. Nowadays, in order to determine these effects on centrifugal fans, numerical studies are carried out in addition to experimental studies. In this study, it is aimed to numerically investigate the changes of suction pressure and outlet mass flow rate values of a centrifugal fan according to the number of blade and blade type. Centrifugal fans of the same size with forward, backward and straight blade type were analyzed by using a simulation program and compared with each other. This analysis was carried out under steady state condition by selecting k-Ɛ turbulence model and air is assumed incompressible. Then, 16, 32 and 48 blade centrifugal fans were again analyzed by using same simulation program, and the optimum number of blades was determined for the suction pressure and the outlet mass flow rate. According to the results of the analysis, it was obtained that the suction pressure in the 32 blade fan was twice the value obtained in the 16 blade fan. In addition, the outlet mass flow rate increased by 45% with the increase in the number of blade from 16 to 32. There is no significant change observed on the suction pressure and outlet mass flow rate when the number of blades increased from 32 to 48. In the light of the analysis results, the optimum blade number was determined as 32.

Keywords: blade type, centrifugal fan, cfd, outlet mass flow rate, suction pressure

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Rahim Ada, Ahmet Tamkoç

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The research was conducted in the “Randomized Complete Block Design” with three replications in research field of Agricultural Faculty, Selcuk University, Konya, Turkey. In study, a total of 9 Cephalaria syriaca promised lines (9, 37, 38, 42, Beyaz 4, 5 Beyaz, 13 Beyaz, 27 Beyaz, Başaklar 2), which were taken from Sivas population, and 1 population were evaluated in two growing seasons (2012-13 and 2013-14). According to the results, the highest plant height, first branch height, first head height, number of branches per plant, number of head per plant, head diameter,1000 seed weight, seed yield, oil content and oil yield were obtained respectively from Başaklar 2 (68.37 cm), Başaklar 2 (37.80 cm), Başaklar 2 (54.83 cm), 37 (7.73 number/plant), 42 (18.03 number/plant), 9 (10.30 mm), Başaklar 2 (19.33 g), 27 Beyaz (1254.2 kg ha-1), Başaklar 2 (28.77%), and 27 Beyaz (357.9 kg ha-1).

Keywords: Cephalaria syriaca, yield, oil, population

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Authors: Pius W. Molo Chin

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Real life problems such as the Huxley equation are always modeled as nonlinear differential equations. These problems need accurate and reliable methods for their solutions. In this paper, we propose a nonstandard finite difference method in time and the Galerkin combined with the compactness method in the space variables. This coupled method, is used to analyze a two dimensional Huxley equation for the existence and uniqueness of the continuous solution of the problem in appropriate spaces to be defined. We proceed to design a numerical scheme consisting of the aforementioned method and show that the scheme is stable. We further show that the stable scheme converges with the rate which is optimal in both the L2 as well as the H1-norms. Furthermore, we show that the scheme replicates the decaying qualities of the exact solution. Numerical experiments are presented with the help of an example to justify the validity of the designed scheme.

Keywords: Huxley equations, non-standard finite difference method, Galerkin method, optimal rate of convergence

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: In Kyong Yi, Yun Jeong Chae, Jihoon Hwang, Sook-Young Lee, Jong-Yeop Kim

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Background: Pentax airway scope (AWS) is a recently developed video laryngoscope for use in both normal and difficult airways, providing a good laryngeal view. The purpose of this randomized noninferior study was to evaluate the efficacy of the Pentax-AWS regarding intubation time, laryngeal view and ease of intubation in pediatric patients with normal airway, compared to Macintosh laryngoscope. Method: A total of 136 pediatric patients aged 1 to 10 with American Society of Anesthesiologists physical status I or II undergoing general anesthesia required orotracheal intubation were randomly allocated into two groups: Macintosh laryngoscope (n =68) and Pentax AWS (n=68). Anesthesia was induced with propofol, rocuronium, and sevoflurane. The primary outcome was intubation time. Cormack-Lehane laryngeal view grade, application of optimal laryngeal external manipulation (OELM), intubation difficulty scale (IDS), intubation failure rate and adverse events were also measured. Result: No significant difference was observed between the two groups regarding intubation time (Macintosh; 23[22-26] sec vs. Pentax; 23.5[22-27.75] sec, p=0.713). As for the laryngeal view grade, the Pentax group showed less number of grade 2a or higher grade cases compared to the Macintosh group (1/2a/2b/3; 52.9%/41.2%/4.4%/1.5% vs. 98.5%/1.5%/0%/0%, p=0.000). No optimal laryngeal external manipulation application was required in the Pentax group (38.2% vs. 0%, p=0.000). Intubation difficulty scale resulted in lower values for Pentax group (0 [0-2] vs. 0 [0-0.55], p=0.001). Failure rate was not different between the two groups (1.5% vs. 4.4%, p=0.619). Adverse event-wise, slightly higher incidence of bleeding (1.5% vs. 5.9%, p=0.172) and teeth injury (0% vs. 5.9%, p=0.042) occurred in the Pentax group. Conclusion: In conclusion, Pentax-AWS provided better laryngeal view, similar intubation time and similar success rate compared with Macintosh laryngoscope in children with normal airway. However, the risk of teeth injury might increase and warrant special attention.

Keywords: Pentax-AWS, pediatric, video laryngoscope, intubation

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Authors: Samah Benmerbi, Kamal Amroun, Abdelkamel Tari

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The increasing number of Web service (WS)providers throughout the globe, have produced numerous Web services providing the same or similar functionality. Therefore, there is a need of tools developing the best answer of queries by selecting and composing services with total transparency. This paper reviews various QoS based Web service selection mechanisms and architectures which facilitate qualitatively optimal selection, in other fact Web service composition is required when a request cannot be fulfilled by a single web service. In such cases, it is preferable to integrate existing web services to satisfy user’s request. We introduce an automatic Web service composition method based on hypergraph decomposition using hypertree decomposition method. The problem of selection and the composition of the web services is transformed into a resolution in a hypertree by exploring the relations of dependency between web services to get composite web service via employing an execution order of WS satisfying global request.

Keywords: web service, web service selection, web service composition, QoS, hypergraph decomposition, BE hypergraph decomposition, hypertree resolution

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Authors: P.J. Jiji, B.V. Murlimanju, Latha V. Prabhu, Mangala M. Pai

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Background: The lunate bone dislocation can lead to the compression of the median nerve and subsequent carpal tunnel syndrome. The dislocation can interrupt the vasculature and would cause avascular necrosis. The objective of the present study was to study the morphology and number of the nutrient foramina in the cadaveric dried lunate bones of the Indian population. Methods: The present study included 28 lunate bones (13 right sided and 15 left sided) which were obtained from the gross anatomy laboratory of our institution. The bones were macroscopically observed for the nutrient foramina and the data was collected with respect to their number. The tabulation of the data and analysis were done. Results: All of our specimens (100%) exhibited the nutrient foramina over the non-articular surfaces. The foramina were observed only over the palmar and dorsal surfaces of the lunate bones. The foramen ranged between 2 and 10. The foramina were more in number over the dorsal surface (average number 3.3) in comparison to the palmar surface (average number 2.4). Conclusion: We believe that the present study has provided important data about the nutrient foramina of the lunate bones. The data is enlightening to the orthopedic surgeon and would help in the hand surgeries. The morphological knowledge of the vasculature, their foramina of entry and their number is required to understand the concepts in the lunatomalacia and Kienbock’s disease.

Keywords: avascular necrosis, foramen, lunate, nutrient

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Authors: Tomoaki Hashimoto

Abstract:

Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: Merfat Algethami, Anton Blencowe, Bryce Feltis, Stephen Best, Moshi Geso

Abstract:

Nano-materials with high atomic number atoms have been demonstrated to enhance the effective radiation dose and thus potentially could improve therapeutic efficacy in radiotherapy. The optimal nanoparticulate agents require high X-ray absorption coefficients, low toxicity, and should be cost effective. The focus of our research is the development of a nanoparticle therapeutic agent that can be used in radiotherapy to provide optimal enhancement of the radiation effects on the target. In this study, we used bismuth (Bi) nanoparticles coated with starch and bismuth sulphide nanoparticles (Bi2S3) coated with polyvinylpyrrolidone (PVP). These NPs are of low toxicity and are one of the least expensive heavy metal-based nanoparticles. The aims of this study were to synthesise Bi2S3 and Bi NPs, and examine their cytotoxicity to human lung adenocarcinoma epithelial cells (A549). The dose enhancing effects of NPs on A549 cells were examined at both KV and MV energies. The preliminary results revealed that bismuth based nanoparticles show increased radio-sensitisation of cells, displaying dose enhancement with KV X-ray energies and to a lesser degree for the MV energies. We also observed that Bi NPs generated a greater dose enhancement effect than Bi2S3 NPs in irradiated A549 cells. The maximum Dose Enhancement Factor (DEF) was obtained at lower energy KV range when cells treated with Bi NPs (1.5) compared to the DEF of 1.2 when cells treated with Bi2S3NPs. Less radiation dose enhancement was observed when using high energy MV beam with higher DEF value of Bi NPs treatment (1.26) as compared to 1.06 DEF value with Bi2S3 NPs. The greater dose enhancement was achieved at KV energy range, due the effect of the photoelectric effect which is the dominant process of interaction of X-ray. The cytotoxic effect of Bi NPs on enhancing the X-ray dose was higher due to the higher amount of elemental Bismuth present in Bi NPs compared to Bi2S3 NPs. The results suggest that Bismuth based NPs can be considered as valuable dose enhancing agents when used in clinical applications.

Keywords: A549 lung cancer cells, Bi2S3 nanoparticles, dose enhancement effect, radio-sensitising agents

Procedia PDF Downloads 275

Authors: Mehmet Hakan Karaata, Ali Hamdan, Omer Yusuf Adam Mohamed

Abstract:

Consider a distributed system that delivers messages from a process to another. Such a system is often required to deliver each message to its destination regardless of whether or not the system components experience arbitrary forms of faults. In addition, each message received by the destination must be a message sent by a system process. In this paper, we first identify the necessary and sufficient conditions to detect some restricted form of Byzantine faults referred to as modifying Byzantine faults. An observable form of a Byzantine fault whose effect is limited to the modification of a message metadata or content, timing and omission faults, and message replay is referred to as a modifying Byzantine fault. We then present a distributed protocol to detect modifying Byzantine faults using optimal number of messages over node-disjoint paths.

Keywords: Byzantine faults, distributed systems, fault detection, network protocols, node-disjoint paths

Procedia PDF Downloads 449