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.

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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 Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology Research Journal of Chemistry and Environment

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-16-10-2020-11243
Total View : 394

Title : Prediction of Surface Roughness in CNC Turning Process using Adaptive Neural Fuzzy Inference System

Abstract :

This paper presents the methodology of surface roughness inspection in CNC Turning process. Adaptive Neural Fuzzy Inference System classifier utilizes to predict the high accuracy roughness value with insisting of surface roughness image. The vision system captures the image and determines the mean value by using ANFIS algorithm. Training sets variables speed, depth of cut, feed rate and mean value are feed as the input and manual stylus probe surface roughness value feed as the output. After the simulation process, the testing input performed and finally getting the vision measurement value. This higher accuracy (above 95%) and low error rate (below 4%) can be achieved by using the ANFIS classifier, which is predominantly helpful for the industry to measure the surface roughness.  Assign the quality of the product by evaluating the manual stylus probe and vision measurement value.

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Journal ID : TRKU-14-10-2020-11241
Total View : 369

Title : Content and Stability Evaluation of Anthocyanins Extracted from Red Dragon Fruit (Hylocereus Costaricensis) as a Natural Dye

Abstract :

Flesh and skin of red dragon fruits contain anthocyanins which are potential as a natural dye. This study aimed to improve the stability of anthocyanins using the copigmentation method. The stages on this study were maceration, extraction, evaporation, and copigmentation. The anthocyanins levels in the sample were determined by measuring the absorbance using UV-Vis spectroscopy. Copigmentation was carried out by adding anthocyanins with alum, Al2(SO4)3, in ratio of 1:1; 1:2; and 1: 3 by volume. Stability of the color was tested by storing of the solutions and the cotton fabrics at room temperature for 0, 3, and 6 days. The results analysis showed that the anthocyanin levels in flesh and skin of red dragon fruit were 13.20 mg/100 g and 5.37 mg/100 g. Stability of anthocyanin with copigment alum Al2(SO4)3 in a ratio of 1:1, 1:2, and 1:3 and a storage time of 0, 3, and 6 days of the cotton fabrics showed decreasing in color intensity due to the degradation and temperature. The color change in the copigmented extract to yellow compared to the pure anthocyanin

Full article