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 - 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. Shenyang Jianzhu Daxue Xuebao (Ziran Kexue Ban)/Journal of Shenyang Jianzhu University (Natural Science) General Medicine (ISSN:1311-1817) Chinese Journal of Evidence-Based Medicine Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation Lizi Jiaohuan Yu Xifu/Ion Exchange and Adsorption Kexue Tongbao/Chinese Science Bulletin Dalian Haishi Daxue Xuebao/Journal of Dalian Maritime University

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-17-04-2020-10695
Total View : 233

Title : An Integrated Auto-encoder Bottleneck Feature Representation and Optimized LSSVM Classification Model in Gear Fault Monitoring

Abstract :

This study proposes a new diagnosis method for identifying the vibration data of the multi-level fault of gear. The diagnosis method is based on the feature representation of the vibration signal and optimized machine learning model. Firstly, a deep Auto-Encoder (AE) bottleneck network is constructed with the two hidden layers to extract the fault features of gear vibration data, named AE-BtF. In which, the AE-BtF use the basic unsupervised learning algorithm to reveal the significant characteristics in the complex data with the nonlinear, non-station properties. The obtained features can provide good discriminability for fault diagnosis task. Secondly, an optimal classifier model is formed to perform supervised fine-tuning and classification. This model is based on the least square support vector machine (LSSVM) classifier and chemical reaction optimization algorithm (CRO), named CRO-LSSVM. The meta-heuristics CRO algorithm is used to exploit the appropriate parameters for the LSSVM. Based on the vibration data of gear fault status, the proposed AE-BtF-CRO-LSSVM technique shows a good ability for identifying the gear fault accuracy. The diagnosis results have demonstrated that the AE-BtF based feature extraction in conjunction with the CRO-LSSVM classifier model can achieve higher accuracies than the other popular classifier models to 60%

Full article
Journal ID : TRKU-16-04-2020-10694
Total View : 215


Abstract :

Restricting the amount of air mass induced into the engine is the most convenient way, and is commonly used to limit engine performance in racing competitions. Student Formula Japan uses this method in its competition. Another regulation is that the engine capacity cannot exceed 710 cc, but the engine must still use a 20 mm restrictor in the air intake system. With the restrictor, it is necessary to adjust various engine geometry parameters to maximize the performance of the engine. In this study, these adjustments were made to the camshaft phasing configuration, and it increases engine power and torque of up to 3%. The peak power and torque are delivered at lower engine speeds of 5,000 - 8,800 RPM. It provides progressive torque delivery and makes the engine much more suitable for FSAE and Formula Student applications. Modification of advance timing causes the power and torque curve at low speed to be wider, but its peak power and torque to be lower. Modify the valve timing configuration is the easiest way to adjust the engine performance characteristics on the track. These findings contribute to adjusting the valve timing configuration into advanced timing

Full article