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 - 63 , Issue 07
10 Jul 2021
Day
Hour
Min
Sec

Upcoming Publication

Volume - 63 , Issue 06
30 Jun 2021

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. Bulletin of National Institute of Health Sciences

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-26-10-2020-11283
Total View : 411

Title : Time Series Forecasting the Quantity of Municipal Solid Waste Generation Using Linear Regression Integrated with Moving Average in Mekelle City - Ethiopia

Abstract :

In highly populated areas like urban areas municipal solid waste (MSW) increases from time to time and it becomes serious issue recently. So it very important to make prediction of the wastes for designing and preparing enough land fill or any other mechanism used to store wastes, to hire enough man power and management system and preparing materials necessary etc. which are used to control the municipal solid waste. In this study Moving Average and linear regression method was used to forecast the municipal solid waste of mekelle city. Thus, the obtained equation used to forecast was, Y=0.757808*X+4.29 equation found used to forecast the proposed wastes. The Mean Average Percentage Error (MAPE), Root Mean Square Error (RMSE) was used as performance indicators for comparison between predicted and actual data Thus the result of the indicators showed acceptable error (very small error) and this indicated their good agreement between predicted and actual data.

Full article
Journal ID : TRKU-26-10-2020-11282
Total View : 394

Title : Sabo Dam Infrastructure System Performance Index Model in Mount Merapi

Abstract :

The volcanic area is blessed with a lot of resources and cursed with eruptive disaster at the same time. Fertile land, deep forest, mining deposit, and water reserve are examples of the potential within a volcanic environment. The more productive activity is taking place, the more it risks damaged by a disaster. In 2010, Merapi, an energetic volcano in Java – Indonesia, erupted on a massive scale equal to one event in one hundred and seventy years. It was estimated up to 140 million m3 lahars produced, overwhelming installed sabo dams with only 20 million m3 in capacity. It damaged these sabo dams severely. Meanwhile, damaged sabo dams urgently needs to be either rehabilitated or reconstructed to set preparation against the next incoming eruption. This paper would focus on the estimation of functional performance given by the sabo dam at present actual condition. The aim is to create modelling framework base on structural equation modelling (SEM) and Generalized Reduced Gradient (GRG) Method. It adopts water resources principles, recent developed model, regulations and factors that influencing this purpose.  All governing factors are grouped into three major classifications, i.e. physical aspect, regulative aspect and social aspect. These three aspect are consisted of eight dimension: sabo dam components performance, riparian vegetation condition, river course condition, sand mining performance, regulation conformity, socio-culture-economic, societal-private cooperation, and disaster loss then followed by thity nine indicators. The SEM result using SmartPLS from 89 sabo dam samples shows twenty six confirmed to be valid form thirty nine indicators, which the eight dimensions and three aspect remain intact. By the satisfactory statistical value of AVE (average variance extracted) > 0,5; CR (composite reliability) > 0,8; Cronbach Alpha > 0,8 and p ≤ α 0,1these twenty six indicators are: spillway, main dam, wing, drip hole, sub dam, apron, side wall, filling, parapet, parapet frame, and dyke under sabo dam components performance; vegetation species under riparian vegetation condition; roughness, depth, and slope under river course condition; legal mining, illegal mining and actual mining under sand mining performance; technical recommendation and sand mining license, under regulation conformity; local occupation, education and inhabitant economic, under socio-culture-economic; private corporate social responsibility (CSR) under societal-private cooperation; and public facilities damage, and husbandry loss under disaster loss.

Full article

Certificates