Search results for: objective matrix.

Authors: Mehdi Seifbarghy, Keyvan Roshan

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Main goal of preventive healthcare problems are at decreasing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The levels of establishment and staffing costs along with summation of the travel and waiting time that clients spent are considered as objectives functions of the proposed nonlinear integer programming model. In this paper, we have proposed a bi-objective mathematical model for designing a network of preventive healthcare facilities so as to minimize aforementioned objectives, simultaneously. Moreover, each facility acts as M/M/1 queuing system. The number of facilities to be established, the location of each facility, and the level of technology for each facility to be chosen are provided as the main determinants of a healthcare facility network. Finally, to demonstrate performance of the proposed model, four multi-objective decision making techniques are presented to solve the model.

Keywords: Preventive healthcare problems, Non-linear integer programming models, Multi-objective decision making techniques

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Authors: Mohamed Zakaulla, A. R. Anwar Khan

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Al6061 alloy base matrix, reinforced with particles of silicon carbide (10 wt %) and Graphite powder (1wt%), known as hybrid composites have been fabricated by liquid metallurgy route (stir casting technique) and optimized at different parameters like applied load, sliding speed and sliding distance by taguchi method. A plan of experiment generated through taguchi technique was used to perform experiments based on L27 orthogonal array. The developed ANOVA and regression equations are used to find the optimum coefficient of friction and wear under the influence of applied load, sliding speed and sliding distance. On the basis of “smaller the best” the dry sliding wear resistance was analysed and finally confirmation tests were carried out to verify the experimental results.

Keywords: Analysis of variance, dry sliding wear, Hybrid composite, orthogonal array, Taguchi technique.

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Authors: Djamal Atlaoui, Youcef Bouafia

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This work deals with the experimental study of the mechanical behavior, by shear tests (fracture shear), elements of concrete beams reinforced with fibers in chips. These fibers come from the machining waste of the steel parts. The shear tests are carried out on prismatic specimens of dimensions 10 x 20 x 120 cm³. The fibers are characterized by mechanical resistance and tearing. The optimal composition of the concrete was determined by the workability test. Two fiber contents are selected for this study (W = 0.6% and W = 0.8%) and a BT control concrete (W = 0%) of the same composition as the matrix is developed to serve as a reference with a sand-to-gravel ratio (S/G) of concrete matrix equal to 1. The comparison of the different results obtained shows that the chips fibers confer a significant ductility to the material after cracking of the concrete. Also, the fibers used limit diagonal cracks in shear and improve strength and rigidity.

Keywords: Characterization, chips fibers, cracking mode, ductility, undulation, shear.

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Authors: Delaram Jarchi, Reza Boostani

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Linear Discrimination Analysis (LDA) is a linear solution for classification of two classes. In this paper, we propose a variant LDA method for multi-class problem which redefines the between class and within class scatter matrices by incorporating a weight function into each of them. The aim is to separate classes as much as possible in a situation that one class is well separated from other classes, incidentally, that class must have a little influence on classification. It has been suggested to alleviate influence of classes that are well separated by adding a weight into between class scatter matrix and within class scatter matrix. To obtain a simple and effective weight function, ordinary LDA between every two classes has been used in order to find Fisher discrimination value and passed it as an input into two weight functions and redefined between class and within class scatter matrices. Experimental results showed that our new LDA method improved classification rate, on glass, iris and wine datasets, in comparison to different versions of LDA.

Keywords: Discriminant vectors, weighted LDA, uncorrelation, principle components, Fisher-face method, Bootstarp method.

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Authors: Mansour Nikkhah-Bahrami, Masih Loghmani, Mostafa Pooyanfar

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In this paper, an analytical approach for free vibration analysis of four edges simply supported rectangular Kirchhoff plates is presented. The method is based on wave approach. From wave standpoint vibration propagate, reflect and transmit in a structure. Firstly, the propagation and reflection matrices for plate with simply supported boundary condition are derived. Then, these matrices are combined to provide a concise and systematic approach to free vibration analysis of a simply supported rectangular Kirchhoff plate. Subsequently, the eigenvalue problem for free vibration of plates is formulated and the equation of plate natural frequencies is constructed. Finally, the effectiveness of the approach is shown by comparison of the results with existing classical solution.

Keywords: Kirchhoff plate, propagation matrix, reflection matrix, vibration analysis.

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Authors: Soottipoom Yaowiwat, Manoj Lohatepanont, Proadpran Punyabukkana

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Several approaches such as linear programming, network modeling, greedy heuristic and decision support system are well-known approaches in solving irregular airline operation problem. This paper presents an alternative approach based on Multi Objective Micro Genetic Algorithm. The aim of this research is to introduce the concept of Multi Objective Micro Genetic Algorithm as a tool to solve irregular airline operation, combine and reroute problem. The experiment result indicated that the model could obtain optimal solutions within a few second.

Keywords: Irregular Airline Operation, Combine and RerouteRoutine, Genetic Algorithm, Micro Genetic Algorithm, Multi ObjectiveOptimization, Evolutionary Algorithm.

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Authors: S. Ghanaraja, Subrata Ray, S. K. Nath

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Particle reinforced Metal Matrix Composite (MMC) succeeds in synergizing the metallic matrix with ceramic particle reinforcements to result in improved strength, particularly at elevated temperatures, but adversely it affects the ductility of the matrix because of agglomeration and porosity. The present study investigates the outcome of tensile properties in a cast and hot forged composite reinforced simultaneously with coarse and fine particles. Nano-sized alumina particles have been generated by milling mixture of aluminum and manganese dioxide powders. Milled particles after drying are added to molten metal and the resulting slurry is cast. The microstructure of the composites shows good distribution of both the size categories of particles without significant clustering. The presence of nanoparticles along with coarser particles in a composite improves both strength and ductility considerably. Delay in debonding of coarser particles to higher stress is due to reduced mismatch in extension caused by increased strain hardening in presence of the nanoparticles. However, higher addition of powder mix beyond a limit results in deterioration of mechanical properties, possibly due to clustering of nanoparticles. The porosity in cast composite generally increases with the increasing addition of powder mix as observed during process and on forging it has got reduced. The base alloy and nanocomposites show improvement in flow stress which could be attributed to lowering of porosity and grain refinement as a consequence of forging.

Keywords: Aluminum, alumina, nanoparticle reinforced composites, porosity.

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Authors: V. Masilamani, Kamala Krithivasan

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We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object (crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject (crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections.

Keywords: 3D-Binary Matrix Reconstruction, Computed Tomography, Discrete Tomography, Integral Max Flow Problem.

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Authors: Paschal A. Ubi, Salawu Abdul Rahman Asipita

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Sustainability and eco-friendly requirement of engineering materials are sort for in recent times, thus giving rise to the development of bio-composites. However, the natural fibres to matrix interface interactions remain a key issue in getting the desired mechanical properties from such composites. Treatment of natural fibres is essential in improving matrix to filler adhesion, hence improving its mechanical properties. In this study, investigations were carried out to determine the effect of sodium hydroxide treatment on the tensile, flexural, impact and hardness properties of crushed and uncrushed Luffa cylindrica fibre reinforced recycled low density polyethylene composites. The LC (Luffa cylindrica) fibres were treated with 0%, 2%, 4%, 6%, 8% and 10% wt. sodium hydroxide (NaOH) concentrations for a period of 24 hours under room temperature conditions. A formulation ratio of 80/20 g (matrix to reinforcement) was maintained for all developed samples. Analysis of the results showed that the uncrushed luffa fibre samples gave better mechanical properties compared with the crushed luffa fibre samples. The uncrushed luffa fibre composites had a maximum tensile and flexural strength of 7.65 MPa and 17.08 Mpa respectively corresponding to a young modulus and flexural modulus of 21.08 MPa and 232.22 MPa for the 8% and 4% wt. NaOH concentration respectively. Results obtained in the research showed that NaOH treatment with the 8% NaOH concentration improved the mechanical properties of the LC fibre reinforced composites when compared with other NaOH treatment concentration values.

Keywords: Flexural strength, LC fibres, LC/rLDPE composite, Tensile strength.

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Authors: Jeng-Shin Sheu, Jenn-Kaie Lain, Tai-Kuo Woo, Jyh-Horng Wen

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The least mean square (LMS) algorithmis one of the most well-known algorithms for mobile communication systems due to its implementation simplicity. However, the main limitation is its relatively slow convergence rate. In this paper, a booster using the concept of Markov chains is proposed to speed up the convergence rate of LMS algorithms. The nature of Markov chains makes it possible to exploit the past information in the updating process. Moreover, since the transition matrix has a smaller variance than that of the weight itself by the central limit theorem, the weight transition matrix converges faster than the weight itself. Accordingly, the proposed Markov-chain based booster thus has the ability to track variations in signal characteristics, and meanwhile, it can accelerate the rate of convergence for LMS algorithms. Simulation results show that the LMS algorithm can effectively increase the convergence rate and meantime further approach the Wiener solution, if the Markov-chain based booster is applied. The mean square error is also remarkably reduced, while the convergence rate is improved.

Keywords: LMS, Markov chain, convergence rate, accelerator.

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Authors: Badr M. Alshammari, T. Guesmi

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In this paper, the concept of a non-dominated sorting multi-objective particle swarm optimization with local search (NSPSO-LS) is presented for the optimal design of multimachine power system stabilizers (PSSs). The controller design is formulated as an optimization problem in order to shift the system electromechanical modes in a pre-specified region in the s-plan. A composite set of objective functions comprising the damping factor and the damping ratio of the undamped and lightly damped electromechanical modes is considered. The performance of the proposed optimization algorithm is verified for the 3-machine 9-bus system. Simulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and superiority of the NSPSO-LS algorithm in tuning PSSs over a wide range of loading conditions and large disturbance compared to the classic PSO technique and genetic algorithms.

Keywords: Multi-objective optimization, particle swarm optimization, power system stabilizer, low frequency oscillations.

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Authors: Rita SahaRay, Ganesh Dutta

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In this article, experimental situations are considered where a main effects plan is to be used to study m two-level factors using n runs which are partitioned into b blocks, not necessarily of same size. Assuming the block sizes to be even for all blocks, for the case n ≡ 2 (mod 4), optimal designs are obtained with respect to type 1 and type 2 optimality criteria in the class of designs providing estimation of all main effects orthogonal to the block effects. In practice, such orthogonal estimation of main effects is often a desirable condition. In the wider class of all available m two level even sized blocked main effects plans, where the factors do not occur at high and low levels equally often in each block, E-optimal designs are also characterized. Simple construction methods based on Hadamard matrices and Kronecker product for these optimal designs are presented.

Keywords: Design matrix, Hadamard matrix, Kronecker product, type 1 criteria, type 2 criteria.

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Authors: M. Ramachandra, G. Dilip Maruthi, R. Rashmi

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This paper aims to study the corrosion property of aluminum matrix nanocomposite of an aluminum alloy (Al-6061) reinforced with zirconium dioxide (ZrO₂) particles. The zirconium dioxide particles are synthesized by solution combustion method. The nanocomposite materials are prepared by mechanical stir casting method, varying the percentage of n-ZrO₂ (2.5%, 5% and 7.5% by weight). The corrosion behavior of base metal (Al-6061) and Al/ZrO₂ nanocomposite in seawater (3.5% NaCl solution) is measured using the potential control method. The corrosion rate is evaluated by Tafel extrapolation technique. The corrosion potential increases with the increase in wt.% of n-ZrO₂ in the nanocomposite which means the decrease in corrosion rate. It is found that on addition of n-ZrO2 particles to the aluminum matrix, the corrosion rate has decreased compared to the base metal.

Keywords: Al6061 alloy, corrosion, solution combustion, stir casting, Potentiostat, Zirconium Dioxide.

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Authors: Nurnadiah Z., Lazim A.

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The design of weight is one of the important parts in fuzzy decision making, as it would have a deep effect on the evaluation results. Entropy is one of the weight measure based on objective evaluation. Non--probabilistic-type entropy measures for fuzzy set and interval type-2 fuzzy sets (IT2FS) have been developed and applied to weight measure. Since the entropy for (IT2FS) for decision making yet to be explored, this paper proposes a new objective weight method by using entropy weight method for multiple attribute decision making (MADM). This paper utilizes the nature of IT2FS concept in the evaluation process to assess the attribute weight based on the credibility of data. An example was presented to demonstrate the feasibility of the new method in decision making. The entropy measure of interval type-2 fuzzy sets yield flexible judgment and could be applied in decision making environment.

Keywords: Objective weight, entropy weight, multiple attributedecision making, type-2 fuzzy sets, interval type-2 fuzzy sets

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Authors: Phruksaphanrat B.

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This research proposes a Preemptive Possibilistic Linear Programming (PPLP) approach for solving multiobjective Aggregate Production Planning (APP) problem with interval demand and imprecise unit price and related operating costs. The proposed approach attempts to maximize profit and minimize changes of workforce. It transforms the total profit objective that has imprecise information to three crisp objective functions, which are maximizing the most possible value of profit, minimizing the risk of obtaining the lower profit and maximizing the opportunity of obtaining the higher profit. The change of workforce level objective is also converted. Then, the problem is solved according to objective priorities. It is easier than simultaneously solve the multiobjective problem as performed in existing approach. Possible range of interval demand is also used to increase flexibility of obtaining the better production plan. A practical application of an electronic company is illustrated to show the effectiveness of the proposed model.

Keywords: Aggregate production planning, Fuzzy sets theory, Possibilistic linear programming, Preemptive priority

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

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The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: Constraint parameters, derivative matrix, magnetocardiography, regular term, total variation.

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Authors: Mohamed Hamdaoui, Jean-Baptiste Mouret, Stephane Doncieux, Pierre Sagaut

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The aim of this work is to present a multi-objective optimization method to find maximum efficiency kinematics for a flapping wing unmanned aerial vehicle. We restrained our study to rectangular wings with the same profile along the span and to harmonic dihedral motion. It is assumed that the birdlike aerial vehicle (whose span and surface area were fixed respectively to 1m and 0.15m2) is in horizontal mechanically balanced motion at fixed speed. We used two flight physics models to describe the vehicle aerodynamic performances, namely DeLaurier-s model, which has been used in many studies dealing with flapping wings, and the model proposed by Dae-Kwan et al. Then, a constrained multi-objective optimization of the propulsive efficiency is performed using a recent evolutionary multi-objective algorithm called є-MOEA. Firstly, we show that feasible solutions (i.e. solutions that fulfil the imposed constraints) can be obtained using Dae-Kwan et al.-s model. Secondly, we highlight that a single objective optimization approach (weighted sum method for example) can also give optimal solutions as good as the multi-objective one which nevertheless offers the advantage of directly generating the set of the best trade-offs. Finally, we show that the DeLaurier-s model does not yield feasible solutions.

Keywords: Flight physics, evolutionary algorithm, optimization, Pareto surface.

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Authors: AbdulLateef A. Olanrewaju, Mohd F. Khamidi, Arazi Idrus

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This paper is part of an ongoing research on the development of systemic maintenance management model Malaysian university buildings. In order to achieve this aim, there is a need to develop a performance model against which services are measure. Measuring performance is a significant part of maintenance management service delivery. Maintenance organization needs to know where they are in order to provide user-driven services and to enhance productivity. The aim of this paper is to formulate a template or model for university maintenance organization in Malaysia. The model is based on literature review and survey questionnaire and has been validated. Through grounded theory, this paper developed a 8 points matrix for the university maintenance organizations for measuring and improving their service delivery. The potential of the model is guide and assists towards providing value added service delivery through initiating maintenance according to user value system rather than on the condition of the building.

Keywords: Performance matrix, university buildings, users, maintenance organization

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Authors: C. Yesubai Rubavathi, R. Ravi

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This paper presents the local mesh co-occurrence patterns (LMCoP) using HSV color space for image retrieval system. HSV color space is used in this method to utilize color, intensity and brightness of images. Local mesh patterns are applied to define the local information of image and gray level co-occurrence is used to obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence pattern extracts the local directional information from local mesh pattern and converts it into a well-mannered feature vector using gray level co-occurrence matrix. The proposed method is tested on three different databases called MIT VisTex, Corel, and STex. Also, this algorithm is compared with existing methods, and results in terms of precision and recall are shown in this paper.

Keywords: Content-based image retrieval system, HSV color space, gray level co-occurrence matrix, local mesh pattern.

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Authors: J. Prakash, K. Rajesh

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In this paper, we introduce a new method for elliptical object identification. The proposed method adopts a hybrid scheme which consists of Eigen values of covariance matrices, Circular Hough transform and Bresenham-s raster scan algorithms. In this approach we use the fact that the large Eigen values and small Eigen values of covariance matrices are associated with the major and minor axial lengths of the ellipse. The centre location of the ellipse can be identified using circular Hough transform (CHT). Sparse matrix technique is used to perform CHT. Since sparse matrices squeeze zero elements and contain a small number of nonzero elements they provide an advantage of matrix storage space and computational time. Neighborhood suppression scheme is used to find the valid Hough peaks. The accurate position of circumference pixels is identified using raster scan algorithm which uses the geometrical symmetry property. This method does not require the evaluation of tangents or curvature of edge contours, which are generally very sensitive to noise working conditions. The proposed method has the advantages of small storage, high speed and accuracy in identifying the feature. The new method has been tested on both synthetic and real images. Several experiments have been conducted on various images with considerable background noise to reveal the efficacy and robustness. Experimental results about the accuracy of the proposed method, comparisons with Hough transform and its variants and other tangential based methods are reported.

Keywords: Circular Hough transform, covariance matrix, Eigen values, ellipse detection, raster scan algorithm.

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Authors: F. Alborzi, H. Vafaei, M.H. Gholami, M.M. S. Esfahani

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In this article, the design of a Supply Chain Network (SCN) consisting of several suppliers, production plants, distribution centers and retailers, is considered. Demands of retailers are considered stochastic parameters, so we generate amounts of data via simulation to extract a few demand scenarios. Then a mixed integer two-stage programming model is developed to optimize simultaneously two objectives: (1) minimization the fixed and variable cost, (2) maximization the service level. A weighting method is utilized to solve this two objective problem and a numerical example is made to show the performance of the model.

Keywords: Mixed Integer Programming, Multi-objective Optimization, Stochastic Demand, Supply Chain Design, Two Stage Programming

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Authors: A. D'Alessandro, F. Ubertini, A. L. Materazzi

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In the field of civil engineering, Structural Health Monitoring is a topic of growing interest. Effective monitoring instruments permit the control of the working conditions of structures and infrastructures, through the identification of behavioral anomalies due to incipient damages, especially in areas of high environmental hazards as earthquakes. While traditional sensors can be applied only in a limited number of points, providing a partial information for a structural diagnosis, novel transducers may allow a diffuse sensing. Thanks to the new tools and materials provided by nanotechnology, new types of multifunctional sensors are developing in the scientific panorama. In particular, cement-matrix composite materials capable of diagnosing their own state of strain and tension, could be originated by the addition of specific conductive nanofillers. Because of the nature of the material they are made of, these new cementitious nano-modified transducers can be inserted within the concrete elements, transforming the same structures in sets of widespread sensors. This paper is aimed at presenting the results of a research about a new self-sensing nanocomposite and about the implementation of smart sensors for Structural Health Monitoring. The developed nanocomposite has been obtained by inserting multi walled carbon nanotubes within a cementitious matrix. The insertion of such conductive carbon nanofillers provides the base material with piezoresistive characteristics and peculiar sensitivity to mechanical modifications. The self-sensing ability is achieved by correlating the variation of the external stress or strain with the variation of some electrical properties, such as the electrical resistance or conductivity. Through the measurement of such electrical characteristics, the performance and the working conditions of an element or a structure can be monitored. Among conductive carbon nanofillers, carbon nanotubes seem to be particularly promising for the realization of self-sensing cement-matrix materials. Some issues related to the nanofiller dispersion or to the influence of the nano-inclusions amount in the cement matrix need to be carefully investigated: the strain sensitivity of the resulting sensors is influenced by such factors. This work analyzes the dispersion of the carbon nanofillers, the physical properties of the fresh dough, the electrical properties of the hardened composites and the sensing properties of the realized sensors. The experimental campaign focuses specifically on their dynamic characterization and their applicability to the monitoring of full-scale elements. The results of the electromechanical tests with both slow varying and dynamic loads show that the developed nanocomposite sensors can be effectively used for the health monitoring of structures.

Keywords: Carbon nanotubes, self-sensing nanocomposites, smart cement-matrix sensors, structural health monitoring.

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Authors: Jing Meng, Peiyong Zhu, Houbiao Li

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Many problems in science and engineering field require the solution of shifted linear systems with multiple right hand sides and multiple shifts. To solve such systems efficiently, the implicitly restarted global GMRES algorithm is extended in this paper. However, the shift invariant property could no longer hold over the augmented global Krylov subspace due to adding the harmonic Ritz matrices. To remedy this situation, we enforce the collinearity condition on the shifted system and propose shift implicitly restarted global GMRES. The new method not only improves the convergence but also has a potential to simultaneously compute approximate solution for the shifted systems using only as many matrix vector multiplications as the solution of the seed system requires. In addition, some numerical experiments also confirm the effectiveness of our method.

Keywords: Shifted linear systems, global Krylov subspace, GLGMRESIR, GLGMRESIRsh, harmonic Ritz matrix, harmonic Ritz vector.

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Authors: Jan Busch, Peter Nyhuis

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Considering the challenges of short product life cycles and growing variant diversity, cost minimization and manufacturing flexibility increasingly gain importance to maintain a competitive edge in today’s global and dynamic markets. In this context, an aerodynamic part feeding system for high-speed industrial assembly applications has been developed at the Institute of Production Systems and Logistics (IFA), Leibniz Universitaet Hannover. The aerodynamic part feeding system outperforms conventional systems with respect to its process safety, reliability, and operating speed. In this paper, a multi-objective optimisation of the aerodynamic feeding system regarding the orientation rate, the feeding velocity, and the required nozzle pressure is presented.

Keywords: Aerodynamic feeding system, genetic algorithm, multi-objective optimization.

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Authors: A. I. Alateyah, H. N. Dhakal, Z. Y. Zhang

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The mechanical properties including flexural and tensile of neat vinyl ester and polymer based on layered silicate nanocomposite materials are discussed. The addition of layered silicate into the polymer matrix increased the tensile and flexural modulus up to 1 wt.% clay loading. The incorporation of more clay resulted in decreasing the mechanical properties which was traced to the existence of aggregation layers. Likewise, up to 1 wt.% clay loading, the thermal behaviour showed significant improvements and at higher clay loading the thermal pattern was reduced. The aggregation layers imparted a negative impact on the overall mechanical and thermal properties. Wide Angle X-ray Diffraction, Scanning Electron Microscopy and Transmission Electron Microscopy were utilised in order to characterise the interlamellar structure of nanocomposites.

Keywords: Vinyl ester, nanocomposites, layered silicate, mechanical properties, thermal analysis.

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Authors: Jiri Plocek, Petr Holec, Simona Kubickova, Barbara Pacakova, Irena Matulkova, Alice Mantlikova, Ivan Nemec, Daniel Niznansky, Jana Vejpravova

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This article presents summary on preparation and characterization of zinc, copper, cadmium and cobalt chromite nanocrystals, embedded in an amorphous silica matrix. The ZnCr2O4/SiO2, CuCr2O4/SiO2, CdCr2O4/SiO2 and CoCr2O4/SiO2 nanocomposites were prepared by a conventional sol-gel method under acid catalysis. Final heat treatment of the samples was carried out at temperatures in the range of 900−1200 ◦C to adjust the phase composition and the crystallite size, respectively. The resulting samples were characterized by Powder X-ray diffraction (PXRD), High Resolution Transmission Electron Microscopy (HRTEM), Raman/FTIR spectroscopy and magnetic measurements. Formation of the spinel phase was confirmed in all samples. The average size of the nanocrystals was determined from the PXRD data and by direct particle size observation on HRTEM; both results were correlated. The mean particle size (reviewed by HRTEM) was in the range from ∼4 to 46 nm. The results showed that the sol-gel method can be effectively used for preparation of the spinel chromite nanoparticles embedded in the silica matrix and the particle size is driven by the type of the cation A2+ in the spinel structure and the temperature of the final heat treatment. Magnetic properties of the nanocrystals were found to be just moderately modified in comparison to the bulk phases.

Keywords: Chromite, Fourier transform infrared spectroscopy, agnetic properties, nanocomposites, Raman spectroscopy, Rietveld refinement, sol-gel method, spinel.

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Authors: Tristan O’Neill, Trina Myers, Jarrod Trevathan

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The Tropical Data Hub (TDH) is a virtual research environment that provides researchers with an e-research infrastructure to congregate significant tropical data sets for data reuse, integration, searching, and correlation. However, researchers often require data and metadata synthesis across disciplines for cross-domain analyses and knowledge discovery. A triplestore offers a semantic layer to achieve a more intelligent method of search to support the synthesis requirements by automating latent linkages in the data and metadata. Presently, the benchmarks to aid the decision of which triplestore is best suited for use in an application environment like the TDH are limited to performance. This paper describes a new evaluation tool developed to analyze both features and performance. The tool comprises a weighted decision matrix to evaluate the interoperability, functionality, performance, and support availability of a range of integrated and native triplestores to rank them according to requirements of the TDH.

Keywords: Virtual research environment, Semantic Web, performance analysis, tropical data hub.

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Authors: Sarabjeet Singh Sidhu, Ajay Batish, Sanjeev Kumar

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This paper reports the optimal process conditions for machining of three different types of MMC’s 65vol%SiC/A356.2; 10vol%SiC-5vol%quartz/Al and 30vol%SiC/A359 using PMEDM process. MRR, TWR, SR and surface integrity were evaluated after each trial and contributing process parameters were identified. The four responses were then collectively optimized using TOPSIS and optimal process conditions were identified for each type of MMC. The density of reinforced particles shields the matrix material from spark energy hence the high MRR and SR was observed with lowest reinforced particle. TWR was highest with Cu-Gr electrode due to disintegration of the weakly bonded particles in the composite electrode. Each workpiece was examined for surface integrity and ranked as per severity of surface defects observed and their rankings were used for arriving at the most optimal process settings for each workpiece. 

Keywords: Metal matrix composites (MMCs), Metal removal rate (MRR), Surface roughness (SR), Surface integrity (SI), Tool wear rate (TWR), Technique for order preference by similarity to ideal solution (TOPSIS).

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Authors: Daohong Yang, Xiang Zhang, Wanting Zhou, Lei Li

Abstract:

Visual Simultaneous Localization and Mapping (VSLAM) is a technology that gathers information about the surrounding environment to ascertain its own position and create a map. It is widely used in computer vision, robotics, and various other fields. Many visual SLAM systems, such as OBSLAM3, utilize a constant velocity motion model. The utilization of this model facilitates the determination of the initial pose of the current frame, thereby enhancing the efficiency and precision of feature matching. However, it is often difficult to satisfy the constant velocity motion model in actual situations. This can result in a significant deviation between the obtained initial pose and the true value, leading to errors in nonlinear optimization results. Therefore, this paper proposes a motion model based on acceleration that can be applied to most SLAM systems. To provide a more accurate description of the camera pose acceleration, we separate the pose transformation matrix into its rotation matrix and translation vector components. The rotation matrix is now represented by a rotation vector. We assume that, over a short period, the changes in rotating angular velocity and translation vector remain constant. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of the constant velocity model is analyzed theoretically. Finally, we apply our proposed approach to the ORBSLAM3 system and evaluate two sets of sequences from the TUM datasets. The results show that our proposed method has a more accurate initial pose estimation, resulting in an improvement of 6.61% and 6.46% in the accuracy of the ORBSLAM3 system on the two test sequences, respectively.

Keywords: Error estimation, constant acceleration motion model, pose estimation, visual SLAM.

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Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l_2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: Hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation.

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