Abstract-LineSmoothing is the process of curving lines to make them look smoother, better to say it is the representation of a polyline so that fewer points represent the caricature of the line. It also usually reduces the noise in a signal. This can apply to a vector, spline, or a list of points corresponding to a line or signal. Many algorithms are available for automated line smoothing that is commonly seen as a comparatively simple operation; however, instructions for using these algorithms are often complex. In this paper, we present a new method as a basic technique that can efficiently smooth a list of points. We focus on preserving characteristics of the line while avoiding any distortions. Our goal is to demonstrate a flexible method to preserve features of the input based on its characteristics with fewer constants. Since this technique can apply to both vectors and lists of points, it is also useful in map generalization. Selected test examples are illustrated and discussed, followed by an assessment of the models. Finally, results of the proposed method are examined, showing more stable preservation and better noise reduction compared to the available methods reported in the literature.

The best‐recorded performance of perovskite‐based solar cells (PSCs) in regular mesoscopic architecture is generally associated with the use of the common 2,2′,7,7′‐tetrakis[N,N‐di(4‐methoxyphenyl)amino]‐9,9′‐spirobifluorene (Spiro‐OMeTAD). However, the need for lithium‐based hygroscopic dopants hinders the chemical and environmental stability of the devices. This work presents a passivated stable PSC device based on a dopant‐free poly(3‐hexylthiophene) (P3HT) hole transport layer. By introducing a poly(N,N′‐bis‐4‐butylphenyl‐N,N′‐biphenyl)benzidine (polyTPD) interlayer at the perovskite/P3HT interface, the parameters of the low‐performance pristine P3HT‐based cells are improved. This introduction leads to optimizing the P3HT film morphology, interfacial defects, and charge extraction, along with a significant suppression of interfacial recombination and enhancement of the cell power conversion efficiency (PCE) from 7% to 10.65%. Further, an improvement is observed in open‐circuit voltage and the fill factor, increasing from 0.912 to 0.95 V and from 59.2% to 61.1%, respectively. Moreover, the noncapsulated passivated PSC devices exhibit higher operational stability. Examinations show that devices in a dark controlled environment (10–15% humidity) can retain 82% of their initial PCE for 450 h, and 73% of their initial PCE when thermally stressed at 60 °C temperature under ambient conditions (25–35% humidity) for 264 h.

Often, nonlinearity exists in the financial markets while Artificial Neural Network (ANN) could be used to expect equity market returns for the next years. ANN has been improved its ability to forecast the daily stock exchange rate and to investigate several feeds using the back propagation algorithm. The proposed research utilized five neural network models, Elman network, Multilayer Perceptron (MLP) network, Elman network with Self-Optimizing Map (SOM), MLP with SOM filter and simple linear regression, for estimating new values. Results were examined to investigate the predicting ability and to provide an effective feeds for future values. The result of the proposed simulation showed that SOM could greatly improve the convergence of the neuron networks; whereas Elman network did a better performance to capture the temporal pattern of the symbolic streams generated by SOM.A benchmark of linear regression model was also employed to show the ability of neural network models to generate higher accuracy in forecasting financial market index.