Literature Review of The Store Windows Display Influences on Consumers Attractiveness Through the Layout Design

Windows display is one of the important aspect in retail design in order to increase consumer product awareness. The store windows design had been varied especially with the creative visual merchandiser in managing a visual approach of store windows display. Flat type store windows display often used in Bandung Retail, and has characteristic of its own retail brand image to improve attractiveness. Layout design of a store windows display has an important role for the influence of consumer behavior especially in shopping attitudes. This research identify the effects of WAKAI and MANGO store windows display at Trans Studio Mall on consumer attractiveness through the implementation of layout design principles Keywords Store Windows, Retail, Attractiveness, Layout design

Classification of Arrhythmia by Using Deep Learning with 2-D ECG Spectral Image Representation

The electrocardiogram (ECG) is one of the most extensively employed signals used in the diagnosis and prediction of cardiovascular diseases (CVDs). The ECG signals can capture the heart's rhythmic irregularities, commonly known as arrhythmias. A careful study of ECG signals is crucial for precise diagnoses of patients' acute and chronic heart conditions. In this study, we propose a two-dimensional (2-D) convolutional neural network (CNN) model for the classification of ECG signals into eight classes; namely, normal beat, premature ventricular contraction beat, paced beat, right bundle branch block beat, left bundle branch block beat, atrial premature contraction beat, ventricular flutter wave beat, and ventricular escape beat. The one-dimensional ECG time series signals are transformed into 2-D spectrograms through short-time Fourier transform. The 2-D CNN model consisting of four convolutional layers and four pooling layers is designed for extracting robust features from the input spectrograms. Our proposed methodology is evaluated on a publicly available MIT-BIH arrhythmia dataset. We achieved a state-of-the-art average classification accuracy of 99.11\%, which is better than those of recently reported results in classifying similar types of arrhythmias. The performance is significant in other indices as well, including sensitivity and specificity, which indicates the success of the proposed method.Comment: 14 pages, 5 figures, accepted for future publication in Remote Sensing MDPI Journa

Chemical Synthesis of Nano-Sized particles of Lead Oxide and their Characterization Studies

The quantum dots of semiconductor display novel and interesting phenomena that have not been in the bulk material. The color tunability is one of the most attractive characteristics in II-VI semiconductor nanoparticles such as CdS, ZnS, CdSe, ZnSe and PbO. In this work, the semiconductor lead oxide nanoparticles are prepared by chemical method. The average particle size, specific surface area, crystallinity index are estimated from XRD analysis. The structural, functional groups and optical characters are analyzed with using of SEM, FTIR and UV- Visible techniques. The optical band gap value has also been determined.Comment: 8 pages, 5 figures, 2 table