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
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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-05-09-2020-11075
Total View : 321

Title : Recognizing System of Masked Faces in Social Distance in the New Normal Era Using the Viola-Jones Method Based on the Haar-Cascade Classifier

Abstract :

New Normal is a New order that can adapt to COVID-19. Indonesian people must maintain productivity in the midst of the COVID-19 corona virus pandemic. To realize the new normal scenario, the Indonesian Government and experts have formulated a protocol or Standard Operational Procedure (SOP) to ensure that people can return to their activities, but remain safe from COVID-19. One of the health protocols is to require people to wear masks. Several previous studies have designed a facial pattern recognition system, but to detect facial patterns using masks has not been the optimal solution. Therefore, this study has tried to design and analyze a facial pattern recognition system using masks using the Viola Jones method with the Haar Cascade Classifier. The Haar Cascade Classifier method is used to recognize facial patterns based on haar wavelets. The haar-like feature method is made easier with the cascade classifier adaboost. Meanwhile, the Viola Jones method is used for object detection methods by combining Haar Like Feature and has high accuracy and better performance than other eigen faces algorithms. The purpose of this study is to help the performance of the level of security in selecting facial patterns into a room that has complied with health protocols in the new normal era or not. From the test results with 50 face samples, the accuracy percentage is 92.3% and it takes a relatively short time to recognize faces using masks, which is an average of 15 seconds per sample tested

Full article
Journal ID : TRKU-04-09-2020-11074
Total View : 344

Title : The Relationship of Causal Factors Affecting the Administration Efficiency of Thailand: Case of Greenhouse Gas Emission under Thai Law

Abstract :

This study aims to analyze the forecasting the GHG emission, population, GDP growth of energy consumption in the Industries sectors. The scope of the study covers the analysis of energy consumption, and the forecasting of GHG emission population, GDP growth of energy consumption for the next 10 years (2016-2025), and 20 years (2016-2035) by using Vector Autoregressive Model: VAR Model from the Input-output table of Thailand. The result show that petroleum has the highest level of energy consumption, followed by Other Petroleum Products, Cement, Ceramic and Earthen Wares, Cosmetic, fertilizer and pesticides, soap and cleaning preparations, rubber sheet and block rubber, and petroleum refineries, respectively. The prediction results show that these models are effective in forecasting measured by using RMSE, MAE, and MAPE. The results forecast of each model are as follows: 1) Model 1(2,1,1) shows that GHG emission will, increasing steadily to 25.71% by the year 2025 in comparison to 2016.2) Model 2 (2,1,2) shows that GHG emission will rise steadily, increasing to 45.20% by the year 2035 in comparison to 2016

Full article

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