Optimization automating monitoring based on classification for rolling bearing

This work presents an automated and optimized methodology for detection and tracking real-time rolling bearings defects. It contains three sequential loops. The first loop is the initialization, as well as the constitution of a class called healthy. It starts by extraction of features from the acquisition signals, then select the most correlated features to reduce the unimportant features by the Relief method, normalization data by z-score, and reduce the dimension by t-SNE method, ended with a calculation of OPTICS parameter’s Epsilon and Minpts. The second loop is the detection, which has the same initialization steps, besides, OPTICS for data classification. The third loop is the follow-up: this phase consists of projecting the matrix of defect features into the final base that has made it possible to detect the defect class and to track the evolution of this class over time. The proposed methodology has been validated numerically and experimentally for rolling bearing in the outer race

Initial location selection of electric vehicles charging infrastructure in urban city through clustering algorithm

Transportation is one of the critical sectors worldwide, mainly based on fossil fuels, especially internal combustion engines. In a developing country, heightened dependence on fossil fuels affected energy sustainability issues, greenhouse gas emissions, and increasing state budget allocation towards fuel subsidies. Moreover, shifting to electric vehicles (EVs) with alternative energy, primely renewable energy sources, is considered a promising alternative to decreasing dependence on fossil fuel consumption. The availability of a sufficient EV charging station infrastructure is determined as an appropriate strategy and rudimentary requirement to optimize the growth of EV users, especially in urban cities. This study aims to utilize the k-mean algorithm’s clustering method to group and select a potential EV charging station location in Jakarta an urban city in Indonesia. This study proposed a method for advancing the layout location’s comprehensive suitability. An iterative procedure determines the most suitable value for K as centroids. The K value is evaluated by cluster silhouette coefficient scores to acquire the optimized numeral of clusters. The results show that 95 potential locations are divided into 19 different groups. The suggested initial EV charging station location was selected and validated by silhouette coefficient scores. This research also presents the maps of the initially selected locations and clustering

A novel EEG based linguistic BCI

While a human being can think coherently, physical limitations no matter how severe, should never become disabling. Thinking and cognition are performed and expressed through language, which is the most natural form of human communication. The use of covert speech tasks for BCIs has been successfully achieved for invasive and non-invasive systems. In this work, by incorporating the most recent discoveries on the spatial, temporal, and spectral signatures of word production, a novel system is designed, which is custom-build for linguistic tasks. Other than paying attention and waiting for the onset cue, this BCI requires absolutely no cognitive effort from the user and operates using automatic linguistic functions of the brain in the first 312ms post onset, which is also completely out of the control of the user and immune from inconsistencies. With four classes, this online BCI achieves classification accuracy of 82.5%. Each word produces a signature as unique as its phonetic structure, and the number of covert speech tasks used in this work is limited by computational power. We demonstrated that this BCI can successfully use wireless dry electrode EEG systems, which are becoming as capable as traditional laboratory grade systems. This frees the potential user from the confounds of the lab, facilitating real-world application. Considering that the number of words used in daily life does not exceed 2000, the number of words used by this type of novel BCI may indeed reach this number in the future, with no need to change the current system design or experimental protocol. As a promising step towards noninvasive synthetic telepathy, this system has the potential to not only help those in desperate need, but to completely change the way we communicate with our computers in the future as covert speech is much easier than any form of manual communication and control