A Multiband CPW-Fed Slot Antenna with Fractal Stub and Parasitic Line

This paper presents a multiband CPW-fed slot antenna with fractal stub and parasitic line. The conventional wideband slot antenna with fractal stub is modified by inserting the parasitic line surrounding the fractal stub that affects the attribution to be a multiband operation suitable for some applications in wireless communication systems. The parasitic line surrounding the fractal stub can generate a dual-notched frequency that can be controlled by varying the parameters of the parasitic structure. The lengths of slit and stub on both sides of the parasitic line can control the lower and higher notched frequencies, respectively. Additionally, the prototype of the proposed antenna can operate and cover the applications of DCS 1800, WiMAX IEEE 802.16, WLAN IEEE 802.11a/b/g, and IMT advance system

Recommendation and Sentiment Analysis Based on Consumer Review and Rating

Accurate analysis and recommendation on products based on online reviews and rating data play an important role in precisely targeting suitable consumer segmentations and therefore can promote merchandise sales. This study uses a recommendation and sentiment classification model for analyzing the data of beer product based on online beer reviews and rating dataset of beer products and uses them to improve the recommendation performance of the recommendation model for different customer needs. Among them, the beer recommendation is based on rating data; 10 classification models are compared in text sentiment analysis, including the conventional machine learning models and deep learning models. Combining the two analyses can increase the credibility of the recommended beer and help increase beer sales. The experiment proves that this method can filter the products with more negative reviews in the recommendation algorithm and improve user acceptance