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-27-08-2020-11049
Total View : 452

Title : Forging The Pi-Chain Framework: A Backdrop Of The Block-Chain Smart Contracts With Chain Isomerism On Graph

Abstract :

The advent of the Internet, the increased processing power as well as increased memory allocation cum usage has continued to advance various frontiers with underlying technologies that seeks to secure and uphold data integrity. Also, with the rising trend of adversaries, new emerging paradigms and platforms seek to create safer means for disseminating data from one source to another. This birthed the emergence of block-chain alongside cryptocurrencies – that have today minimized the sole dependence on banking institutions and the adoption of fiat legacy tenders across borders. With its applications therein, cryptocurrencies have evolved as new transaction paradigm to buy/sell assets amongst other usages. However, the inherent challenges of the block-chain network has continued to call for a shift in focus as well as to address the issues therein. The study presents Pi-Chain network, a directed acyclic graph (DAG) network based on chemical isomerism of position, size and structure of a node. It adapts the many benefits of the block-chain – while evolving the weaknesses therein via reshuffled user model method, which allocates  that splits network into two halves via the MLLM (most, least, least, most) scheme.

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Journal ID : TRKU-27-08-2020-11047
Total View : 361

Title : Medium Resolution DEM-based Watershed Modelling Using QGIS for Flood Simulation in an Indonesian Catchment

Abstract :

Watershed modelling is one of the most important factors in the analysis of rainfall-runoff transformations. As an agent of transformation, the catchment plays an important role in determining flow characteristics, especially peak flow as one of flood hydrograph parameters. The main characteristic of this catchment is expressed in the form of surface topography as the basis for determining network channels and its boundaries. The accuracy of determining these two characteristics is largely determined by the type of baseline data used to model the watershed. This study aims to build a watershed model using medium resolution Digital Elevation Model (DEM) data as a flood simulation means. DEM data is derived from Shuttle Radar Topography Mission (SRTM) data with a resolution of 30 meters and is obtained from USGS Earth Explorer for the Bangga Catchment, as one of the flood-prone areas in Central Sulawesi, Indonesia. Channel network derivation and catchment delineation were performed using Raster (R. *), one of QGIS Processing Toolbox. The result of the catchment analysis using this data was also compared with the low-resolution DEM data of 90 meters to determine the effect of DEM resolution on stream network configuration and catchment boundary. Based on this watershed, flood prediction is carried out using the ITS-2 Model, one of the flood estimation models in the form of synthetic unit hydrographs based on river network configuration. The analysis results indicate that the utilization of DEM data with a higher resolution produces smoother catchment features and influences the accumulative length of drainage channels and the area of the catchment. The hydrology simulation using the watershed with the input of design rainfalls shows that the peak flood discharge in the study area for certain return periods is relatively very large for a catchment of fewer than 100 km2 in area

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