Technology Reports of Kansai University (ISSN: 04532198) is a monthly peer-reviewed and open-access international Journal. It was first built in 1959 and officially in 1975 till now by kansai university, japan. The journal covers all sort of engineering topic, mathematics and physics. Technology Reports of Kansai University (TRKU) was closed access journal until 2017. After that TRKU became open access journal. TRKU is a scopus indexed journal and directly run by faculty of engineering, kansai university.
Technology Reports of Kansai University (ISSN: 04532198) is a peer-reviewed journal. The journal covers all sort of engineering topic as well as mathematics and physics. the journal's scopes are
in the following fields but not limited to:
Gandaria (Bouea macrophylla, Griffith) is a tropical Maluku fruit that is generally found on Ambon and Saparua Islands. Gandaria is one of the plants that are appealing to the Maluku community on Ambon Island, because in general the community not only consumes gandaria fruit but the stems and roots of the gandaria plant are also utilized in people's lives. The system of utilization of plants by local communities which in their application is beneficial to people's lives is referred to as ethnobotany. This ethnobotany research aims to see the extent of the use of gandaria plants in the lives of Maluku people on Ambon Island. In this research the development Participatory Rural Appraisal tools, which involves the active role of the community in research wherein, community involvement is obtained through interviews. From the results of the study it was found that 100% of the people in each sub-district used the gandaria plants as food, 89.1% were used as economic producers, 72.2% as firewood, and 29.1% as handicrafts. Based on the percentage of utilization, it can be indicated that the gandaria plant is one of the plants that are in demand by the local community on Ambon Island
The procedure of electroencephalography (EEG) is a famous process in neuroscience that is utilized for extracting the activity of brain signals related to voluntary and involuntary actions. The systems of BCI are capable of making the persons control any external device remotely utilizing the signals of the brain with no neurophysical interference. Many techniques used for isolating noise from EEG signals like filters and blind source separation. The main problem is Artifacts (noise) such as Electrocardiography (ECG), electromyography (EMG), electrooculography (EOG) and power line (LN). Added to EEG signals and affect the performance of the system. Separating these signals into individual components to delete the artifacts is complicated. In this paper on the combination between stone-blind source separation and bandpass filter has been implemented bandpass filter was used and an algorithm based on a stone-blind source separation algorithm is presented for extracting the features from EEG based recorded brain signals. These features are extracted for Motor imagery; the function is the index finger motions to left or right. The proposed system also verified based on two Classifiers. The obtained results the precision rate were (77% by Hoeffding Tree Classifier) while the precision rate was (58% by Random forest)
