Novel colloidal nanofiber electrolytes from PVA‐organoclay/poly(MA‐alt‐MVE), and their NaOH and Ag‐carrying polymer complexes

Novel multifunctional polymer nanofiber electrolytes with covalence crosslinked structures from various solution blends of reactive intercalated poly(vinyl alcohol)/octadecylamine montmorillonite (as a matrix polymer), poly(maleic anhydride‐alt‐methyl vinyl ether) (as a partner polymer) and their NaOH‐absorbing and Ag‐carrying polymer complexes were fabricated via electrospinning. Chemical, physical, morphological, and electrical properties of nanofiber structures were investigated by FTIR, XRD, SEM, and electrical analysis methods. Ag precursors in fiber composites significantly improved phase separation processing, fiber morphologies, diameter distributions, and electrical properties of the fibers. In situ generation of Ag nanoparticles and their distribution on nanofiber surfaces during fiber formation occurred via complex formation between silver cations and electronegative functional groups from both matrix and partner polymers as stabilizing/reducing agents. Electrical resistance and conductivity strongly depended on matrix/partner polymer ratios and absorption time of NaOH solution on nanofibers. Addition of NaOH changed the electrical properties of fiber structures from almost dielectric state to excellent conductivity form. The fabricated unique nanofiber electrolytes are promising candidates for applications in power and fuel cell nanotechnology, electrochemical, and bioengineering processes as reactive semiconductive platforms. POLYM. ENG. SCI., 56:204–213, 2016. © 2015 Society of Plastics Engineers     

Dynamic Modeling and Hydrodynamic Performance of Biomimetic Underwater Robot Locomotion

We developed a dynamic model of a Nitinol artificial muscle activated biomimetic robot. The robot was reverse engineered from the American lobster and built in the Biomimetic Underwater Robot Program at Northeastern University. It is intended for autonomous remote-sensing operations in shallow waters. An experimentally based Nitinol artificial muscle model was integrated into the robot dynamic model. The hydrodynamic characteristics of the robot were determined experimentally. The muscle control signals were generated by utilizing a readily available biomimetic control architecture. The effects of the timing parameters were investigated. Simulations indicate that the developed robot is able to locomote with high stability. It can walk against constant currents and surge.     

A new DEA approach to fully rank DMUs with an application to MBA programs

Data envelopment analysis (DEA) can be used to evaluate the efficiencies of decision‐making units (DMUs) in various areas like education, healthcare, and energy. Several DEA methods are proposed for this purpose; however, some of these methods cannot provide a full ranking and others often overlook some considerations that arise with special characteristics of DMUs. We propose a new DEA‐based approach to achieve a full ranking of DMUs. Our approach takes various issues into account such as the initial efficiency score of the DMU, the DMUs that should be removed from the set for it to become efficient (if any) and its effects on the efficiency scores of other DMUs. We demonstrate the shortcomings of several other DEA methods and discuss how our approach overcomes these. We apply our approach to evaluate 50 MBA programs from Financial Times 2018 rankings and compare the results with the evaluations of other methods. As opposed to some methods, our approach has the advantage of differentiating between all efficient DMUs as well as inefficient ones. In addition, the results demonstrate that we can achieve a consistent ranking that considers different aspects of the problem setting. The generated scores are also used to sort DMUs in classes of preference.     

Supervised fuzzy logic modeling for building earthquake hazard assessment

Building hazard assessment prior to earthquake occurrence exposes interesting problems especially in earthquake prone areas. Such an assessment provides an early warning system for building owners as well as the local and central administrators about the possible hazards that may occur in the next scenario earthquake event, and hence pre- and post-earthquake preparedness can be arranged according to a systematic program. For such an achievement, it is necessary to have efficient models for the prediction of hazard scale of each building within the study area. Although there are subjective intensity index methods for such evaluations, the objective of this paper is to propose a useful tool through fuzzy logic (FL) to classify the buildings that would be vulnerable to earthquake hazard. The FL is a soft computing intelligent reasoning methodology, which is rapid, simple and easily applicable with logical and rational association between the building-hazard categories and the most effective factors. In this paper, among the most important factors are the story number (building height), story height ratio, cantilever extension ratio, moment of inertia (stiffness), number of frames, column and shear wall area percentages. Their relationships with the five hazard categories are presented through a supervised hazard center classification method. These five categories are “none”, “slight”, “moderate”, “extensive”, and “complete” hazard classes. A new supervised FL classification methodology is proposed similar to the classical fuzzy c-means procedure for the allocation of hazard categories to individual buildings. The application of the methodology is presented for Zeytinburnu quarter of Istanbul City, Turkey. It is observed that out of 747 inventoried buildings 7.6%, 50.0%, 14.6%, 20.1%, and 7.7% are subject to expected earthquake with “none”, “slight”, “moderate”, “extensive”, and “complete” hazard classes, respectively.     

Efficient retrieval of replicated data

Declustering is a common technique used to reduce query response times. Data is declustered over multiple disks and query retrieval can be parallelized. Most of the research on declustering is targeted at spatial range queries and investigates schemes with low additive error. Recently, declustering using replication has been proposed to reduce the additive overhead. Replication significantly reduces retrieval cost of arbitrary queries. In this paper, we propose a disk allocation and retrieval mechanism for arbitrary queries based on design theory. Using the proposed c-copy replicated declustering scheme, buckets can be retrieved using at most k disk accesses. Retrieval algorithm is very efficient and is asymptotically optimal with complexity for a query Q. In addition to the deterministic worst-case bound and efficient retrieval, proposed algorithm handles nonuniform data, high dimensions, supports incremental declustering and has good fault-tolerance property. Experimental results show the feasibility of the algorithm. Recommended by: Sunil Prabhakar     

Honeymoon with IWBs: A qualitative insight in primary students' views on instruction with interactive whiteboard

The main purpose of this study was to investigate the views of primary students about interactive whiteboard [IWB] use in their classes from attitudinal and pedagogical perspectives. Research was designed as an empirical approach to phenomenology. Data was collected from fifty primary students (fourth to eighth) through focus group interviews. Nvivo 9 qualitative data analysis software was used to analyze data. Results showed that students like instruction with IWB especially for such reasons/capabilities as practical and economical use, better visual presentation, and test-based use. Students were predominantly uncomfortable with the technical problems. They believed that instruction with IWB positively impacted their learning especially because of visualization and contextualization, effective presentation, test-based use, and motivational factors. Finally it was inferred that IWBs were not used to their full potential, and both technical problems and common practices indicated that teachers were still at an initial stage of transmission to instruction with IWB and they needed both technical and pedagogical training.     

Single machine scheduling with unequal release date using neuro-dominance rule

A neuro-dominance rule (NDR) for single machine total weighted tardiness problem with unequal release date is presented by the author. To obtain the NDR, backpropagation artificial neural network (BPANN) has been trained using 10,000 data and also tested using 10,000 another data. Inputs of the trained BPANN are starting date of the first job (t), processing times (p_i and p_j), due dates (d_i and d_j), weights of the jobs (w_i and w_j) and r_i and r_j release dates of the jobs. Output of the BPANN is a decision of which job should precede. Training set and test set have been obtained using Adjusted Pairwise Interchange method. The proposed NDR provides a sufficient condition for local optimality. It has been proved that if any sequence violates the NDR then violating jobs are switched according to the total weighted tardiness criterion. The proposed NDR is compared to a number of competing heuristics (ATC, COVERT, EDD, SPT, LPT, WDD, WSPT, WPD, CR, FCFS) and meta heuristics (simulated annealing and genetic algorithms) for a set of randomly generated problems. The problem sizes have been taken as 50, 70, 100. NDR is applied 270,000 randomly generated problems. Computational results indicate that the NDR dominates the heuristics and meta heuristics in all runs. Therefore, the NDR can improve the upper and lower bounding schemes.     

Multiobjective evolutionary clustering of Web user sessions: a case study in Web page recommendation

In this study, we experiment with several multiobjective evolutionary algorithms to determine a suitable approach for clustering Web user sessions, which consist of sequences of Web pages visited by the users. Our experimental results show that the multiobjective evolutionary algorithm-based approaches are successful for sequence clustering. We look at a commonly used cluster validity index to verify our findings. The results for this index indicate that the clustering solutions are of high quality. As a case study, the obtained clusters are then used in a Web recommender system for representing usage patterns. As a result of the experiments, we see that these approaches can successfully be applied for generating clustering solutions that lead to a high recommendation accuracy in the recommender model we used in this paper.     

Locational analysis for regionalization of Turkish Red Crescent blood services

After a series of earthquakes in 1999, Turkish Red Crescent (TRC) has engaged in a restructuring for all of its activities, including the blood services. Our study on the blood management system had been started as part of this initiative to restructure the blood services and improve both their effectiveness and efficiency. In the current system of TRC, not much consideration has been given to how the locational decisions affect the performance of blood centers, stations and mobile units. In recent years, however, there has been much discussion regarding the regionalization of the blood management system in Turkey. In this study, we develop several mathematical models to solve the location–allocation decision problems in regionalization of blood services. We report our computational results, obtained by using real data, for TRC blood services.     

Modeling and solving mixed-model assembly line balancing problem with setups. Part I: A mixed integer linear programming model

This paper is the first one of the two papers entitled “modeling and solving mixed-model assembly line balancing problem with setups”, which has the aim of developing the mathematical programming formulation of the problem and solving it with a hybrid meta-heuristic approach. In this current part, a mixed-integer linear mathematical programming (MILP) model for mixed-model assembly line balancing problem with setups is developed. The proposed MILP model considers some particular features of the real world problems such as parallel workstations, zoning constraints, and sequence dependent setup times between tasks, which is an actual framework in assembly line balancing problems. The main endeavor of Part-I is to formulate the sequence dependent setup times between tasks in type-I mixed-model assembly line balancing problem. The proposed model considers the setups between the tasks of the same model and the setups because of the model switches in any workstation. The capability of our MILP is tested through a set of computational experiments. Part-II tackles the problem with a multiple colony hybrid bees algorithm. A set of computational experiments is also carried out for the proposed approach in Part-II.