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:
Sparse Representation Classifier (SRC) is one of the popular and efficient methods of classification for biometric traits. Redundant dictionaries for training samples are created in SRC classification which requires complex mathematical computation. This complexity further increases when the entire training set of samples is used for the classification of the test sample. In this paper, an efficient heart sound recognition algorithm is proposed based on a combination of the two classification methods, namely, Nearest Centroid Neighbor and Sparse Representation Classification (kNCN-SRC). In this method, firstly, k nearest centroid neighbors for the test sample are computed, and then the test sample is classified by sparse representation classification with respect to the k selected nearest neighbors. The proposed kNCN-SRC method showed a significantly increased recognition rate of 8.63% when compared to that of the SRC. This improved recognition rate is due to the selection of nearest neighbors as training signals for classification by SRC. Also, as the selection of training signals is based on the nearest centroid neighbor, this improves the recognition rate as the best training signals are selected for classification by SRC. The findings of the present study showed that the kNCN-SRC classification method demonstrated an improved recognition rate and was found to be a more suitable classifier than SRC for heart sound biometric systems
urban centers are in continuous development due to different circumstances from the past till now, and sometimes due to the needs or for a specific reason enormous changes have been occurred. When changes occurred in the transportation means and cities expanded some of the major changes were developing of new areas and new axis. The research aims to identify the role of morphological changes and their mechanism and how they impact on the changes of the structure of the city however there is lack of clear vision about the mechanism of how change in land uses in the traditional area that consequently affects the changes of urban structure. The research is based on the hypothesis that states; the structural characteristics of the traditional center of Sulaimani city as one of a major city in Kurdistan region on Iraq (KRI) including the space organization has been to change the effect of the morphological changes represented by changing of land uses from residential form to commercial or services area, The city of Sulaimani was chosen for the case study since it is regarded as a model for the urban structure that testified structural changes at a partial and a whole level. The space syntax methodology has been adopted for the identification and characterization of space organization properties and changing in city structure, the case study area has been studied during three different periods of time to analyses the changes that has been occurred in the area. Finally, the study found the effect of changes in the morphology, which is clearly obvious according to the distinctive changes happened in the area was reflecting the structural system
