Energy and entropy-based feature extraction for locating fault on transmission lines by using neural network and wavelet packet decomposition

The aim of this paper is to estimate the fault location on transmission lines quickly and accurately. The faulty current and voltage signals obtained from a simulation are decomposed by wavelet packet transform (WPT). The extracted features are applied to artificial neural network (ANN) for estimating fault location. As data sets increase in size, their analysis become more complicated and time consuming. The energy and entropy criterion are applied to wavelet packet coefficients to decrease the size of feature vectors. The test results of ANN demonstrate that the applying of energy criterion to current signals after WPT is a very powerful and reliable method for reducing data sets in size and hence estimating fault locations on transmission lines quickly and accurately.     

On-chip template training system and image processing applications using iterative annealing on ACE16k chip

Cellular neural networks proved to be a useful parallel computing system for image processing applications. Cellular neural networks (CNNs) constitute a class of recurrent and locally coupled arrays of identical cells. The connectivity among the cells is determined by a set of parameters called templates. CNN templates are the key parameters to perform a desired task. One of the challenging problems in designing templates is to find the optimal template that functions appropriately for the solution of the intended problem. In this paper, we have implemented the Iterative Annealing Optimization Method on the analog CNN chip to find an optimum template by training a randomly selected initial template. We have been able to show that the proposed system is efficient to find the suitable template for some specific image processing applications.     

Functional polyamides

Summary Polymerization of azo initiators having dinitrile functions such as 2,2-azobis(isobutyronitrile) (AIBN) with formaldehyde in the presence of sulfuric acid were carried out in order to permit the synthesis of polyamides containing thermolabile azo groups.The obtained polyamides have appropriate initiating functionality for subsequent free radical polymerization.     

Efficient and Stable Inverted Wide-Bandgap Perovskite Solar Cells and Modules Enabled by Hybrid Evaporation-Solution Method

Wide-bandgap perovskite solar cells (WBG-PSCs), when partnered with Si bottom cells in tandem configuration, can provide efficiencies up to 44%; yet, the development of stable, efficient, and scalable WBG-PSCs is required. Here, the utility of the hybrid evaporation-solution method (HESM) is investigated to meet these demanding requirements via its unique advantages including ease of control and reproducibility. A PbI₂/CsBr layer is co-evaporated followed by coating of organic-halide solutions in a green solvent. Bandgaps between 1.55–1.67 eV are systematically screened by varying CsBr and MABr content. Champion efficiencies of 21.06% and 20.35% in cells and 19.83% and 18.73% in mini-modules (16 cm²) for perovskites with 1.64 and 1.67 eV bandgaps are achieved, respectively. Additionally, 18.51%-efficient semi-transparent WBG-PSCs are implemented in 4T perovskite/bifacial silicon configuration, reaching a projected power output of 30.61 mW cm⁻² based on PD IEC TS 60904-1-2 (BiFi200) protocol. Despite similar bandgaps achieved by incorporating Br via MABr solution and/or CsBr evaporation, PSCs having a perovskite layer without MABr addition show significantly higher thermal and moisture stability. This study proves scalable, high-performance, and stable WBG-PSCs are enabled by HESM, hence their use in tandems and in emerging applications such as indoor photovoltaics are now within reach.     

Efficient and Thermally Stable Wide Bandgap Perovskite Solar Cells by Dual-Source Vacuum Deposition

Wide bandgap perovskites are being widely studied in view of their potential applications in tandem devices and other semitransparent photovoltaics. Vacuum deposition of perovskite thin films is advantageous as it allows the fabrication of multilayer devices, fine control over thickness and purity, and it can be upscaled to meet production needs. However, the vacuum processing of multicomponent perovskites (typically used to achieve wide bandgaps) is not straightforward, because one needs to simultaneously control several thermal sources during the deposition. Here a simplified dual-source vacuum deposition method to obtain wide bandgap perovskite films is shown. The solar cells obtained with these materials have similar or even larger efficiency as those including multiple A-cations, but are much more thermally stable, up to 3500 h at 85 °C for a perovskite with a bandgap of 1.64 eV. With optimized thickness, record efficiency of >19% and semitransparent devices with stabilized power output in excess of 17% are achieved.     

Seeding approach to noble metal decorated conducting polymer nanofiber network

Metal displacement reactions between conducting polymers-"synthetic metals"-and noble metals (Pt, Au and Ag) have been demonstrated using a seeding polymerization technique, to produce a synthetic metal nanofiber network decorated with noble metal nanoparticles, in one-step.     

Classification and modeling for in-plant milk-run distribution systems

Material handling is one of the most important issues that should be taken into account for eliminating waste and reducing the cost. It is one of the seven wastes defined in the concept of lean manufacturing. In this study, for a lean material handling system under the lean manufacturing conditions such as pull-based and repetitive manufacturing, a system consisting of periodically moving vehicles in certain routes is taken into consideration. This system is also called milk-run distribution system. Application of milk-run distribution systems in plants standardizes the material handling system and eliminates the waste. Although there are huge numbers of studies related with inbound and outbound logistics, there are few studies especially related with milk-run applications in the manufacturing area. Within this study, based on the observations in real manufacturing environment and limited literature, the milk-run distribution problem in the plants is categorized and explained. For one of the main categories, modeling is performed. The objective of the developed models is to minimize the number of vehicles and the distance traversed. A numerical example inspired by real applications is presented for showing the applicability of the developed models.     

Classification of design parameters for E-commerce websites: A novel fuzzy Kano approach

Websites have gained vital importance for organizations along with the growing competition in the world market. It is known that usability requirements heavily depend on the type, audience and purpose of websites. For the e-commerce environment, usability assessment of a website is required to figure out the impact of website design on customer purchases. Thus, usability assessment and design of online pages have become the subject of many scientific studies. However, in any of these studies, design parameters were not identified in such a detailed way, and they were not classified in line with customer expectations to assess the overall usability of an e-commerce website. This study therefore aims to analyze and classify design parameters according to customer expectations in order to evaluate the usability of e-commerce websites in a more comprehensive manner. Four websites are assessed using the proposed novel approach with respect to the identified design parameters and the usability scores of the websites are examined. It is revealed that the websites with high usability score are more preferred by customers. Therefore, it is indicated that usability of e-commerce websites affects customer purchases.