Volume 62, Issue 10 will be published on 02 December 2020

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 11
09 Dec 2020

Upcoming Publication

Volume - 62 , Issue 10
30 Nov 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. AMA, Agricultural Mechanization in Asia, Africa and Latin America Teikyo Medical Journal

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-23-09-2020-11141
Total View : 377

Title : Renewable energy projects in Latin America: Studying opportunities and barriers for green development

Abstract :

So as to consent to the COP 21 Paris Agreement, in the Latin American region, the implementation of green power projects should constitute a main pillar.  Consequently, the broadening of the power matrix must be inclined towards the consolidation of green energy and in this manner, the development of green power source ventures ought to be implemented. This article highlights the capability of the Clean Development Mechanism (CDM) to improve green energy projects and subsequently, to acquire profits by diminishing the effect of environmental changes thanks to green consumption. Additionally, this work studies key obstructions and open doors for promoting the constructing of clean power ventures prompting Latin America's green development. This study evidenced that, so as to progress in the development of green power ventures, new laws linked to clean developments ought to be established, proposing novel plans on sustainable viewpoints along with budgetary and administrative changes. Thus, new public policies, tax benefits, and administrative instruments ought to be set up. Financing components to create green power actions ought to be both sustainable and lucrative and, this is the reason the Clean Development Mechanism (CDM) should assume a fundamental part for expanding the proposal of sustainable projects as a way to survey the Kyoto Protocol's adequacy. Finally, advantages, for example, social framework ventures, through drinking water systems, emergency clinics, and schools can likewise be gotten from green projects

Full article
Journal ID : TRKU-23-09-2020-11140
Total View : 407

Title : Mixture Cure Rate Modelling Approach to Cure Rate Estimation: A Mini Review

Abstract :

Cure fraction models are used when some units in the population of survival data are thought to survive the event of interest. Besides, modelling survival data with cure fraction provides a better fit. In this study, Mixture Cure Rate Modelling approach was briefly reviewed with some highlights on Non- Mixture and Defective Modelling approaches. Mixture Cure Rate Modelling assumes the population under study to be a mixture of susceptible and unsusceptible to the event of interest. Estimating cure fraction in the presence of either unobserved heterogeneity or zero-adjusted units were discussed. Mandatory assumption of the presence of cure fraction is a risk associated with this approach, which if wrongly done leads to misleading conclusion. The non-mixture modelling of cure fraction has a natural biological interpretation due to the process of its development. It is mostly associated with Bayesian statistical context. Estimating cure fraction using defective modelling approach makes no assumption of the presence of cure fraction; the cure fraction is estimated when the estimated value of the distribution shape parameter is negative. One of the shortcomings associated with this type of methodology is that, only few distributions can become defective. Zero-adjusted Frailty Mixture Cure Model is proposed

Full article