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 09
09 Oct 2020
Day
Hour
Min
Sec

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-23-07-2020-10923
Total View : 322

Title : Framework to Reduce Cost Scrapping and Cost of Assemble Test Capacity in Semiconductor Integrated Circuit Manufacturing

Abstract :

Semiconductor including integrated circuit (IC) is an expensive and complicated process. The trend of semiconductor packaging is going towards better performance with lower power consumption packages. Thus, the single-die packaging trend has evolved into multi-die packaging. The evolution of multi- die packaging requires more tools and processing steps in the assembly process. Furthermore, any die is tested at Class, and detected faulty will cause the whole package to be scrapped. These factors cause a bigger loss in production yield to compare to the single-die packaging. A new framework is suggested for model training and evaluation for the application of machine learning in the semiconductor test. The proposed new framework will be able to provide a range of possible recall rates from minimum to maximum to identify which machine learning algorithms specifically

Full article
Journal ID : TRKU-23-07-2020-10922
Total View : 212

Title : Order Fulfillment Application Testing for Small Medium Business Using ISO 25010

Abstract :

In small and medium-sized enterprises, the use of the information systems is now familiar. Information systems are widely used for different purposes, including the fulfillment of orders in a company. One system that can be used to fulfill orders in a small to medium business is Order Fulfillment Application. One small to medium business company in Jakarta has been using Order Fulfillment Application. A key process in chain management is the order fulfillment process. Supply is an order from customers that activates the supply chain, and it is the first step in providing customer service efficiently and effectively. Researchers are therefore interested in testing the software to assess application quality in the business. A field study and User Acceptance Test (UAT) with ISO 25010 standards are the tools used by researchers to run tests. Due to time and cost limitations, this work is restricted to functional suitability characteristics. Several inconsistencies between the expected results and real results have been identified from the test results, some of which have a significant level of severity. Although in its main functionality, the application used still meets the requirements of the company, it should be fixed as soon as possible. It is considered appropriate to use the UAT method because it can cover a wide range of functional suitability characteristics

Full article

Certificates