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.

Submission Deadline

Volume - 62 , Issue 10
08 Nov 2020

Upcoming Publication

Volume - 62 , Issue 08
30 Sep 2020

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.

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-13-06-2020-10805
Total View : 358

Title : Classification of Normal and Abnormal Heart Sound using Continuous Wavelet Transform and ResNet-50

Abstract :

Heart sound is the sound produced from the mechanical activity of the heart. Some researchers say the sound of the heart occurs from the opening and closing of the heart valve; some researchers say it occurs due to the eddy flow of blood in the heart chamber. Heart in a healthy condition produces certain heart sounds, while an unhealthy heart produces different heart sounds. Various studies have tried to develop a method for classifying heart sounds using digital signal processing methods. The proposed method generally consists of the feature extraction method and classifier. In this study, continuous wavelet transforms and residual neural network (ResNet-50) were used to classify normal and abnormal heart sounds. The lowest error-rate of 0.066 was achieved using 130x130 features. This result was quite competitive compared to previous research. The proposed method is ready to be tested on a dataset with more heart sounds abnormalities

Full article
Journal ID : TRKU-13-06-2020-10804
Total View : 429

Title : Numerical Simulation of the Air Content of a Two-Phase Flow in a Non-Return Valve for the Correction of Billing Measures in Domestic Drinking Water Networks

Abstract :

Drinking water distribution networks distribute a water-air mixture through the pipes given the inherent conditions of fluid conduction. These air bubbles are measured by the volumetric meters that are used to bill water consumption. Inaccurate measurements are detrimental for both the client and the supplier. However, there are non-return valves that have the ability to reduce the size of air bubbles traveling through the water lines to improve the accuracy of these meter readings. In this investigation, a CFD simulation of the behavior of the pressure and the volumetric fraction of the biphasic water-air flow was performed to estimate the performance of these devices based on the monitoring of these two variables. It was observed that the non-return valve operating with a water-air ratio of 90/10 respectively and at an average flow rate of 1.35 m/s in the pipeline, the size of the air bubbles and their volumetric fraction is reduced from concentrations from 80% to 45%. The results of the pressure drop of the non-return valve suggest that for the stem equilibrium position it produces a pressure drop of 9 PSI in the two-phase water-air flow stream

Full article