Technology Reports of Kansai University

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.

Google Scholar

Submission Deadline

Volume - 66 , Issue 01
20 Jan 2024

Upcoming Publication

Volume - 66 , Issue 01
31 Jan 2024

Aim and Scope

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:

Electrical Engineering and Telecommunication Section:

Electrical Engineering, Telecommunication Engineering, Electro-mechanical System Engineering, Biological Biosystem Engineering, Integrated Engineering, Electronic Engineering, Hardware-software co-design and interfacing, Semiconductor chip, Peripheral equipments, Nanotechnology, Advanced control theories and applications, Machine design and optimization , Turbines micro-turbines, FACTS devices , Insulation systems , Power quality , High voltage engineering, Electrical actuators , Energy optimization , Electric drives , Electrical machines, HVDC transmission, Power electronics.

Computer Science Section :

Software Engineering, Data Security , Computer Vision , Image Processing, Cryptography, Computer Networking, Database system and Management, Data mining, Big Data, Robotics , Parallel and distributed processing , Artificial Intelligence , Natural language processing , Neural Networking, Distributed Systems , Fuzzy logic, Advance programming, Machine learning, Internet & the Web, Information Technology , Computer architecture, Virtual vision and virtual simulations, Operating systems, Cryptosystems and data compression, Security and privacy, Algorithms, Sensors and ad-hoc networks, Graph theory, Pattern/image recognition, Neural networks. Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Fa yi xue za zhi

Civil and architectural engineering :

Architectural Drawing, Architectural Style, Architectural Theory, Biomechanics, Building Materials, Coastal Engineering, Construction Engineering, Control Engineering, Earthquake Engineering, Environmental Engineering, Geotechnical Engineering, Materials Engineering, Municipal Or Urban Engineering, Organic Architecture, Sociology of Architecture, Structural Engineering, Surveying, Transportation Engineering.

Mechanical and Materials Engineering :

kinematics and dynamics of rigid bodies, theory of machines and mechanisms, vibration and balancing of machine parts, stability of mechanical systems, mechanics of continuum, strength of materials, fatigue of materials, hydromechanics, aerodynamics, thermodynamics, heat transfer, thermo fluids, nanofluids, energy systems, renewable and alternative energy, engine, fuels, nanomaterial, material synthesis and characterization, principles of the micro-macro transition, elastic behavior, plastic behavior, high-temperature creep, fatigue, fracture, metals, polymers, ceramics, intermetallics.

Chemical Engineering :

Chemical engineering fundamentals, Physical, Theoretical and Computational Chemistry, Chemical engineering educational challenges and development, Chemical reaction engineering, Chemical engineering equipment design and process design, Thermodynamics, Catalysis & reaction engineering, Particulate systems, Rheology, Multifase flows, Interfacial & colloidal phenomena, Transport phenomena in porous/granular media, Membranes and membrane science, Crystallization, distillation, absorption and extraction, Ionic liquids/electrolyte solutions.

Food Engineering :

Food science, Food engineering, Food microbiology, Food packaging, Food preservation, Food technology, Aseptic processing, Food fortification, Food rheology, Dietary supplement, Food safety, Food chemistry.

Physics Section:

Astrophysics, Atomic and molecular physics, Biophysics, Chemical physics, Civil engineering, Cluster physics, Computational physics, Condensed matter, Cosmology, Device physics, Fluid dynamics, Geophysics, High energy particle physics, Laser, Mechanical engineering, Medical physics, Nanotechnology, Nonlinear science, Nuclear physics, Optics, Photonics, Plasma and fluid physics, Quantum physics, Robotics, Soft matter and polymers.

Mathematics Section:

Actuarial science, Algebra, Algebraic geometry, Analysis and advanced calculus, Approximation theory, Boundry layer theory, Calculus of variations, Combinatorics, Complex analysis, Continuum mechanics, Cryptography, Demography, Differential equations, Differential geometry, Dynamical systems, Econometrics, Fluid mechanics, Functional analysis, Game theory, General topology, Geometry, Graph theory, Group theory, Industrial mathematics, Information theory, Integral transforms and integral equations, Lie algebras, Logic, Magnetohydrodynamics, Mathematical analysis.

Latest Articles of

Technology Reports of Kansai University

Journal ID : TRKU-24-11-2020-11335
Total View : 423

Title : A New Density-Based Method for Clustering Data Stream Using Genetic Algorithm

Abstract :

Density-based methods have appeared as a practical approach for the clustering of data streams. While various density-based algorithms have recently been developed for data stream clustering, these algorithms are not without problems. The efficiency of the clustering is considerably reduced when an insufficient distance function is used. In addition, the majority of the approaches is their non-autonomous nature, which means they need manual tuning of their internal parameters. Unfortunately, the tuning process requires considerable effort and parameter results might become invalid after a certain time due to statistical changes in data or concept drift characteristics. In this study, we propose a new Density-based method for Clustering Data stream using Genetic Algorithm (DCDGA). This method using a Genetic Algorithm (GA) to adjust suitable parameters for the cluster radius and minimum density threshold to cover the density clusters more accurately. A Chebychev distance function is also introduced to calculate the distance between the Core Micro-Clusters (CMCs) center and the arriving data point. The proposed method was evaluated using an artificial and real dataset with different evaluation metrics. The experimental results were compared with another online density-based clustering. The recommended method provides an effective solution for improving the quality of clusters.

Full article
Journal ID : TRKU-24-11-2020-11334
Total View : 445

Title : Cholesterol Level Detection with Expert System and Eyelid Image Processing using SURF (Speed-Up Robust Feature)

Abstract :

Every human being has cholesterol in their body system; it depends on managing the cholesterol. Some people have more LDL (low-density lipoprotein) over the HDL (High-Density Lipoprotein); LDL is also called bad cholesterol. When a person has more LDL over the HDL, it can cause many health problems, so we designed a system that can detect cholesterol itself to prevent the bad cholesterol can do to the human body system. There's a condition when a person has more LDL over the HDL, and he doesn't have good blood circulation. Somehow the fat in his body showed up in the eyelid, the fat forced to push through the surface of the skin. Not every person can have xanthelasma. It's a kind of abnormalities in a person's body, but when a person has a xanthelasma in their eyelid, we recommend him to meet a doctor because that thing in his eyes is removable. Usually, the person who has xanthelasma in his eyelids have move LDL over the HDL, but they don't realize it. o that a program is made to detect cholesterol levels with an expert system using the certainty factor method and image processing of the eyelids with the SURF algorithm. The accuracy of the Certainty Factor algorithm is 100%. The accuracy of the SURF and clustering methods is 93.33%.

Full article