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:
Kongzhi yu Juece/Control and Decision
Azerbaijan Medical Journal
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery
Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology
Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering)
Zhonghua yi shi za zhi (Beijing, China : 1980)
Changjiang Liuyu Ziyuan Yu Huanjing/Resources and Environment in the Yangtze Valley
Tobacco Science and Technology
Shenyang Jianzhu Daxue Xuebao (Ziran Kexue Ban)/Journal of Shenyang Jianzhu University (Natural Science)
General Medicine (ISSN:1311-1817)
High-dimensional data is interpreted with a considerable number of features, and new problems are presented in groups. The so-called "high dimension" is initially created to explain the common increase in time complexity of many computational problems, and therefore the performance of general aggregation algorithms is unsuccessful. Accordingly, many works focused on introducing new technologies and aggregation algorithms to process data with higher dimensions. Standard algorithms for all aggregate algorithms are the fact that they need a different essential evaluation of the similarity between data objects. However, current aggregation algorithms still have some open research problems. In this review work, they provide a summary of the results of the high-dimensional data space and its effects on different aggregation algorithms. It also provides a detailed overview of several grouping algorithms with several types: subspace methods, model-based grouping, density-based grouping methods, partition-based grouping methods, etc., including a more detailed description of the recent work of its advantages and disadvantages in Solve the problem of higher-dimensional data. The scope of future work is also discussed at the end of the work to expand existing compilation methods and algorithms
In this work, we study the influence of the millet pod on the compressive strength of clay bricks from the Maradi region. These compressed bricks are stabilized by the percentage of cement (4 %). A geotechnical characterization was carried out and allowed the classification of the clay which was used to make these bricks. It appears that the material under study is plastic clay and can be classified according to the "AASHTO" (American Association of State Highway and Transportation Officials) classification, A-7-6 (18). The measurements have shown that the values of the compressive strength vary between 2.41 MPa and 5.18 MPa. The optimal value is obtained with 4 % of millet pod
