A note on “A new method for ranking discovered rules from data mining by DEA”, and a full ranking approach

In a recent paper by Toloo et al. [Toloo, M., Sohrabi, B., & Nalchigar, S. (2009). A new method for ranking discovered rules from data mining by DEA. Expert Systems with Applications, 36, 8503–8508], they proposed a new integrated data envelopment analysis model to find most efficient association rule in data mining. Then, utilizing this model, an algorithm is developed for ranking association rules by considering multiple criteria. In this paper, we show that their model only selects one efficient association rule by chance and is totally depended on the solution method or software is used for solving the problem. In addition, it is shown that their proposed algorithm can only rank efficient rules randomly and will fail to rank inefficient DMUs. We also refer to some other drawbacks in that paper and propose another approach to set up a full ranking of the association rules. A numerical example illustrates some contents of the paper.     

New approaches for determining a common set of weights for a voting system

Data Envelopment Analysis (DEA) is one of the methods that have been proposed to determine the weights in a ranked voting system. DEA solves one model corresponding to each candidate and evaluates candidates with their own weights. However, sometimes solving only one model, and evaluating the candidates based on a common set of weights, is preferred. In this paper, some drawbacks of existing models are explained and new approaches for determining a common set of weights are proposed. Numerical examples are utilized to illustrate the content of the paper.     

Physical and mechanical properties of a poly-3-hydroxybutyrate-coated nanocrystalline hydroxyapatite scaffold for bone tissue engineering

A major challenge for tissue engineers is the design of scaffolds with appropriate physical and mechanical properties. The present research discusses the formation of ceramic scaffolding in tissue engineering. Hydroxyapatite (HAp) powder was made from bovine bone by thermal treatment at 900?°C; 40, 50 and 60%wt porous HAp was then produced using the polyurethane sponge replication method. Scaffolds were coated with poly-3-hydroxybutyrate (P3HB) for 30?s and 1?min in order to increase the scaffold??s mechanical properties. XRD, SEM and FT-IR were used to study phase structure, morphology and agent groups, respectively. In XRD and FT-IR data, established hydrogen bands between polymer and ceramic matrix confirm that the scaffold is formed as a composite. The scaffold obtained with 50%wt HAp and a 30?s coating was 90% porous, with an average diameter of 100?C400???m, and demonstrated a compressive strength and modulus of 1.46 and 21.27?MPa, respectively. Based on these results, this scaffold is optimised for the aforementioned properties and can be utilised in bone tissue engineering.     

Urban expansion modeling using an enhanced decision tree algorithm

Decision tree (DT) algorithms have been applied for classification and change detection in various geospatial studies and more recently, for urban expansion and land use/land cover (LULC) change modeling. However, these studies have not elaborated on specification of DT algorithms regarding data sampling, predictor variables, model configuration, and model evaluation. The focus of this study is to explore several balanced and unbalanced sampling methods, various predictor variables, different configurations of stopping rules, and reliable evaluation metrics to enhance the performance of classification and regression tree (CART), one of the most efficacious DT algorithms, for urban expansion modeling. The implementation of the model in the Triangle Region, North Carolina (NC) State, over the period of 2001 to 2011 demonstrates a striking performance with the training accuracy of 97%, the testing accuracy of 94%, and the Kappa value of 0.80. This performance was achieved using a training dataset containing all changed land cells and three times of that randomly selected from unchanged land cells and regulating the minimum number of records in a leaf node equal to 1, the minimum number of records in a parent node equal to 2, and the value of 10,000 for the maximum number of splits. The CART DT algorithm indicates that proximity to built areas, proximity to highways, current LULC type, elevation, and distance to water bodies are the most significant predictor variables for the urban expansion prediction in the study area.

     

Polyhydroxybutyrate/chitosan/bioglass nanocomposite as a novel electrospun scaffold: fabrication and characterization

Scaffolds and their features play a central role in tissue engineering; so this study is based on the production of a series of electrospun PHB/Chitosan/nBG nanocomposite scaffolds with 9 wt% polyhydroxybutyrate, 10, 15 and 20 wt% chitosan and 7.5, 10 and 15 wt% nanobioglass (nBG). Electrospinning process was performed with optimal conditions of spinning machine including voltage of 16 kV, syringe-collector spacing of 16 cm, and output rate of 1 µl per hour. The developed phases and the formation of chemical bonds between ceramic and polymer bands were studied through XRD and FTIR analyses. The FE-SEM and TEM analyses showed uniform morphology of nanofibers and dispersion of bioglass nanoparticles in the fiber structure. The presence of 10 wt% bioglass nanoparticles and 15 wt% chitosan increased the tensile strength of fibers to 3.42 MPa, which was about four times greater than strength of control sample (pure PHB). The developed fibers were kept 28 days in SBF solution and 60 days in PBS solution to assess their bioactivity and biodegradability. The results showed that the presence of bioglass nanoparticles leads to a dramatic increase in absorption of calcium and phosphorus ions and weight loss of scaffold. The developed scaffold can be used for bone and teeth tissue engineering applications.     

Highly Conductive Carbon Nanotube‐Graphene Hybrid Yarn

An efficient procedure for the fabrication of highly conductive carbon nanotube/graphene hybrid yarns has been developed. To start, arrays of vertically aligned multi‐walled carbon nanotubes (MWNT) are converted into indefinitely long MWNT sheets by drawing. Graphene flakes are then deposited onto the MWNT sheets by electrospinning to form a composite structure that is transformed into yarn filaments by twisting. The process is scalable for yarn fabrication on an industrial scale. Prepared materials are characterized by electron microscopy, electrical, mechanical, and electrochemical measurements. It is found that the electrical conductivity of the composite MWNT‐graphene yarns is over 900 S/cm. This value is 400% and 1250% higher than electrical conductivity of pristine MWNT yarns or graphene paper, respectively. The increase in conductivity is asssociated with the increase of the density of states near the Fermi level by a factor of 100 and a decrease in the hopping distance by an order of magnitude induced by grapene flakes. It is found also that the MWNT‐graphene yarn has a strong electrochemical response with specific capacitance in excess of 111 Fg^?1. This value is 425% higher than the capacitance of pristine MWNT yarn. Such substantial improvements of key properties of the hybrid material can be associated with the synergy of MWNT and graphene layers in the yarn structure. Prepared hybrid yarns can benefit such applications as high‐performance supercapacitors, batteries, high current capable cables, and artificial muscles.     

Ultrasound elastography: a dynamic programming approach

This paper introduces a 2-D strain imaging technique based on minimizing a cost function using dynamic programming (DP). The cost function incorporates similarity of echo amplitudes and displacement continuity. Since tissue deformations are smooth, the incorporation of the smoothness into the cost function results in reduced decorrelation noise. As a result, the method generates high-quality strain images of freehand palpation elastography with up to 10% compression, showing that the method is more robust to signal decorrelation (caused by scatterer motion in high axial compression and nonaxial motions of the probe) in comparison to the standard correlation techniques. The method operates in less than 1 s and is thus also potentially suitable for real time elastography.      

Polypyrrole coatings for corrosion protection of Al alloy2024: influence of electrodeposition methods,solvents, and ZnO nanoparticle concentrations

Since ZnO nanoparticles increase the electrical conductivity of the polypyrrole (PPy) coatings, an investigation was carried out to evaluate the effect of ZnO nanoparticles loading on the corrosion protection performance of PPy coatings on AA2024 Al alloy in 3.5% NaCl solution. At first, some measurements were carried out to find the best experimental conditions containing the electrodeposition method, electrosynthesis solvent composition, and ZnO nanoparticles’ concentration for preparing the optimum PPy coating on Al alloy2024. Three different methods of electrodeposition, namely: cyclic voltammetry, galvanostatic, and potentiostatic techniques were analyzed. The anti-corrosion performance of the PPy coatings was evaluated by electrochemical impedance spectroscopy and Tafel polarization methods. The PPy prepared by potentiostatic method exhibited the best performance against corrosion of Al alloy2024 in 3.5% NaCl solution. Then, different mixtures of H₂O/ethanol were tested as electrosynthesis solvents for preparation of PPy coatings on the alloy by optimized electrodeposition mode (i.e., potentiostatic). In evaluation of the prepared coatings, the pure water was introduced as the optimum solvent in electrodeposition of PPy. The investigation of different ZnO nanoparticles’ concentrations proved that the PPy coating containing 0.025% ZnO nanoparticles was the optimum coating against the corrosion of Al alloy in NaCl solution. Finally, the long-term evaluation of the corrosion protection performance of the coatings revealed that the optimum coating provided suitable protection against corrosion up to 14 days after immersion.

     

Conditional Control Charts for Monitoring the Weibull Shape Parameter under Progressively Type II Censored Data

In this paper, (i) we propose new conditional Shewhart‐type control charts for monitoring the shape parameter of the Weibull distribution under a progressively type II censoring strategy, and (ii) we generalize the control charts proposed by Guo and Wang¹ for the progressively type II censoring case. We provide a comparison between these control charts in terms of the out‐of‐control average run length obtained by simulation for both the known and unknown parameter cases. A real example consisting of data from breaking stress of carbon fibers is also presented for illustration and comparison of the proposed control charts. Copyright © 2014 John Wiley & Sons, Ltd.     

Controlling phase separation of TaxHf1−xC solid solution nanopowders during carbothermal reduction synthesis

Synthesis of single‐phase tantalum hafnium carbide (Ta_xHf_1?xC, 0<x<1) solid solution nanopowders via carbothermal reduction (CTR) reaction is complicated due to the difference in reactivity of parent oxides with carbon and presence of a miscibility gap in TaC‐HfC phase diagram below ~887°C. These can lead to phase separation, ie, formation of two distinct carbides instead of a single‐phase solid solution. In this study, nanocrystalline Ta_xHf_1?xC powders were synthesized via CTR of finely mixed amorphous tantalum‐hafnium oxide(s) and carbon obtained from a low‐cost aqueous solution processing of tantalum pentachloride, hafnium tetrachloride, and sucrose. Particular emphasis was given to investigate the influences of starting compositions and processing conditions on phase separation during the formation of carbide phase(s). It was found that due to the immiscibility of Ta‐Hf oxides and relatively fast CTR reaction, individual nano‐HfC and TaC phases form quickly (within minutes at 1600°C), then go through interdiffusion forming carbide solid solution phase. Moreover, the presence of excess carbon in the CTR product slows down the interdiffusion of Ta and Hf dramatically and delays the solid solution formation, whereas DC electrical field (applied through the use of a spark plasma sintering system) accelerates interdiffusion significantly but leads to more grain growth.