Autonomous vacuum cleaner

This paper presents the results of the development of an autonomous mobile robot, designed according to some new concepts established in this field during the last decade. These principles can be found in other works based on the constructivist approach, artificial life, subsumption architecture and other bottom-up methodologies. These ideas have been applied to the complete robot design, spanning from the shape of the robot to the sensors, from the electronics to the software control structure. By this way we have developed what we call an “Application Specific Mobile Robot” (ASMR). The target application is a domestic autonomous vacuum cleaner. Despite the actual limitations of the final robot, this work shows how this methodology can bring many interesting results.     

三间院

项目位于扬州新开发区,邻近2500年历史的京杭大运河。3个社区院落坐落在新建的电讯中心（西部）和农田（东部）之间。院落的中心是公司和当地村民娱乐、餐饮和聚会的地区。     

Generalized Normalized Euclidean Distance Based Fuzzy Soft Set Similarity for Data Classification

Classification is one of the data mining processes used to predict predetermined target classes with data learning accurately. This study discusses data classification using a fuzzy soft set method to predict target classes accurately. This study aims to form a data classification algorithm using the fuzzy soft set method. In this study, the fuzzy soft set was calculated based on the normalized Hamming distance. Each parameter in this method is mapped to a power set from a subset of the fuzzy set using a fuzzy approximation function. In the classification step, a generalized normalized Euclidean distance is used to determine the similarity between two sets of fuzzy soft sets. The experiments used the University of California (UCI) Machine Learning dataset to assess the accuracy of the proposed data classification method. The dataset samples were divided into training (75% of samples) and test (25% of samples) sets. Experiments were performed in MATLAB R2010a software. The experiments showed that: (1) The fastest sequence is matching function, distance measure, similarity, normalized Euclidean distance, (2) the proposed approach can improve accuracy and recall by up to 10.3436% and 6.9723%, respectively, compared with baseline techniques. Hence, the fuzzy soft set method is appropriate for classifying data.

     

Graphene oxide influence on selected properties of polymer fuel cells based on Nafion

Graphene oxide (GO) was used as an additive to the anode, to modify the electrochemical properties of polymer fuel cells (PEMFC) based on Nafion. GO was obtained by modified Hummers method and fully characterized by Raman, FTIR, X-ray, TEM, electrochemically (CV) and Surface Area and Porosity Analyzer. PEMFC with a GO-based anode containing about 30% less Pt, was constructed and compared with a cell with standard anodes. The electrodes were electrochemically tested at 25 and 60 °C. A maximum power density of 134 mW/cm² with a current density of 374 mA/cm² was achieved for PEMFC with GO-based anode at 60 °C. The electrochemical surface area (ECSA) of the PEMFC with GO-based anode was about two times higher than that of the reference device. The electrochemical characterization as well as the Brunauer–Emmett–Teller (BET) and Barrett–Joyner–Halenda (BJH) analysis indicate that GO in the anode reduced Pt agglomeration, as a consequence of the increased surface area and decreased average pore width, compared with the reference electrode. Well-fitted equivalent circuits were proposed and discussed after an electrochemical impedance spectroscopy study of the constructed devices.