Computationally highly efficient mixture of adaptive filters

We introduce a new combination approach for the mixture of adaptive filters based on the set-membership filtering (SMF) framework. We perform SMF to combine the outputs of several parallel running adaptive algorithms and propose unconstrained, affinely constrained and convexly constrained combination weight configurations. Here, we achieve better trade-off in terms of the transient and steady-state convergence performance while providing significant computational reduction. Hence, through the introduced approaches, we can greatly enhance the convergence performance of the constituent filters with a slight increase in the computational load. In this sense, our approaches are suitable for big data applications where the data should be processed in streams with highly efficient algorithms. In the numerical examples, we demonstrate the superior performance of the proposed approaches over the state of the art using the well-known datasets in the machine learning literature.     

Planning of capacity,production and inventory decisions in a generic reverse supply chain under uncertain demand and returns

There is a growing interest for the design and operation of reverse supply chain systems due to the cost and the legislation issues. In this paper, we address the disassembly, refurbishing and production operations in a reverse supply chain setting for modular products such as computers and mobile phones considering the uncertainties in this system, which are the return amounts of the used products and demand for final products. We develop a large-scale mixed integer programming model in order to capture all characteristics of this system, and use two-stage stochastic optimisation and robust optimisation approaches to analyse the system behaviour. In the first stage, we focus on the strategic decisions about the capacities at disassembly and refurbishing sites considering different scenarios regarding the uncertainties in the system. In the second stage, we analyse the operational decisions such as production, inventory and disposal rates. We observe through our extensive numerical analysis that the randomness of demand and return values effect the performance of the system substantially and the uncertainty of the return amounts of used products is much more important than the uncertainty of demand in this system.     

Integrated maintenance and mission planning using remaining useful life information

The modern world requires high reliability and availability with minimum ownership cost for complex industrial systems (high-value assets). Maintenance and mission planning are two major interrelated tasks affecting availability and ownership cost. Both tasks play critical roles in cost savings and effective utilization of the assets, and cannot be performed without taking each other into consideration. Maintenance schedule may make an asset unavailable or too risky to use for a mission. Mission type and duration affect the health of the system, which affects the maintenance schedule. This article presents a mathematical formulation for integrated maintenance and mission planning for a fleet of high-value assets, using their current and forecast health information. An illustrative example for a fleet of unmanned aerial vehicles is demonstrated and evolutionary-based solutions are presented.     

A processable rainbow mimic fluorescent polymer and its unprecedented coloration efficiency in electrochromic device

A processable rainbow mimic fluorescent polymer (PSNSF) based on 1-(9H-fluoren-2-yl)-2,5-di(thiophen-2-yl)-1H-pyrrole (SNSF) was synthesized via electrochemical polymerization in a mixture of ethanol and CH₂Cl₂ solution containing 0.1 M LiClO₄. Characterization was carried out using cyclic voltammetry, UV-vis and FT-IR spectroscopic techniques. Also, an electrochromic device based on PSNSF was studied, which exhibits high coloration efficiency (CE), high redox stability (retaining 98.6% of its optical activity after 4000th switch) and very low response time (less than 0.5 s).     

Rubber effect on metallic dampers used on the supports of steel cross members

There are many strengthening methods made with steel cross members for strengthening the structures with inadequate earthquake behavior. This type of strengthening methods is also effective in buckling of the cross members in the behavior of the structural frames. This buckling may cause partial or complete collapse of the structure. Thus, it is quite important to prevent and limit the formation of buckling in steel crosses. At the TEC 2018, the insulation unit is defined as the elements that can exhibit flexible behavior on the horizontal direction and rigid behavior on the vertical direction under the effect of earthquake loads. The basic principle of using insulation units is that these members can dissipate energy in the carrier system. The originality of this study is to experimentally investigate the damper behavior created by using cylindrical rubber wedges, which can be easily found in the automotive industry, in combination with steel plates and bolts. In this experimental study, the contribution of seismic insulators to the structural element to be strengthened was investigated. The insulators used in this study are considered by analogy with lead-core rubber insulators. As such seismic lead-core rubber insulators move under the influence of lateral loads, the lead core inside makes plastic deformation, thus increasing the damping rate. In this insulator study, it is aimed to use U plates or bolts instead of lead core. While vertical loads are covered by rubber support, horizontal loads will be damped due to plastic deformation of U plates or bolts. The five types of seismic dampers were used as 10 B-type rubber wedge mounted damper (SR), 2 U-type steel plates damper (SP), 10 M6 steel bolted damper (SB), 2 U-type steel plates and 10 B-type rubber wedge mounted damper (SPR), 10 M6 steel bolted, and 10 C-type rubber wedge mounted damper (SBR). These specimens were tested under lateral loading and constant vertical loading. The results obtained at the end of the tests shall be compared considering the strength, stiffness, and dissipated energy capacities of the specimens.     

The effects of the welding current on heat input,nugget geometry,and the mechanical and fractural properties of resistance spot welding on Mg/Al dissimilar materials

Investigating the joining capability of magnesium AZ31 alloy sheets and aluminium 1350 alloy sheets with the application of resistance spot welding was the objective of this study. The weld current values used in the welding process of Al–Mg sheets were 22, 23, 25, 27, 29, 31, and 33 kA. The studies examined the nugget geometries of joined specimens, recorded the scanning electron microscopy (SEM) images of the welded zone and the fracture surface, and recorded the energy-dispersive spectroscopy (EDS, semi-quantitative) analyses. The results of the experiment confirmed that nugget geometry was different for the Al and Mg sides. Tensile shear tests carried out on the welded joints determined their strength and failure mode. The increase in the weld current and duration resulted in an increase in the nugget size and the weld strength. According to observations, the tensile load bearing capacity (TLBC) increased up to 29 kA of the weld current value. It was also found that tearing during fracture occurred in two different ways.     

Genetic algorithm‐based scheduling in cognitive radio networks under interference temperature constraints

The proliferation of wireless technologies and services has intensified the demand for the radio spectrum. However, the currently existing fixed spectrum assignment policy leads to an inefficient and unevenly distributed spectrum utilization. Cognitive radio paradigm has been proposed to alleviate these drawbacks by employing dynamic spectrum access (DSA) methodology. Federal Communications Commission (FCC) has proposed the interference temperature model, which enables the unlicensed users to utilize the licensed frequencies simultaneously with the licensed users as long as they conform to the interference temperature constraints. Recently, throughput and delay optimal schedulers that meet the interference temperature constraints in cognitive radio networks have been formulated in the literature. However, these schedulers have high computational complexity. In this paper, we propose genetic algorithm (GA)‐based suboptimal methods addressing these throughput and delay optimal scheduling problems. The simulation results corroborate that our GA‐based approach yields very close performance to the optimal solutions and operates with much lower complexity. Copyright © 2010 John Wiley & Sons, Ltd.     

Multi‐level reranking approach for bug localization

Bug fixing has a key role in software quality evaluation. Bug fixing starts with the bug localization step, in which developers use textual bug information to find location of source codes which have the bug. Bug localization is a tedious and time consuming process. Information retrieval requires understanding the programme's goal, coding structure, programming logic and the relevant attributes of bug. Information retrieval (IR) based bug localization is a retrieval task, where bug reports and source files represent the queries and documents, respectively. In this paper, we propose BugCatcher, a newly developed bug localization method based on multi‐level re‐ranking IR technique. We evaluate BugCatcher on three open source projects with approximately 3400 bugs. Our experiments show that multi‐level reranking approach to bug localization is promising. Retrieval performance and accuracy of BugCatcher are better than current bug localization tools, and BugCatcher has the best Top N, Mean Average Precision (MAP) and Mean Reciprocal Rank (MRR) values for all datasets.