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

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-24-03-2020-10593
Total View : 202

Title : Solving systems of Volterra integro-differential equations by using semi-analytical techniques

Abstract :

This paper mainly focuses on the recent advances in the semi-analytical approximated methods for solving a system of Volterra integro-differential equations of the second kind by using Adomian Decomposition Method (ADM), Variational Iteration Method (VIM) and Homotopy Perturbation Method (HPM). Convergence analysis of the exact solution of the proposed methods is established. To illustrate the methods, an example is presented

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Journal ID : TRKU-24-03-2020-10592
Total View : 175

Title : A Systematic Review of Speaker Recognition Using Deep Learning on Research Trends, Datasets and Methods

Abstract :

Speaker recognition is a research topic that is still interesting and challenging. Various problems such as noise problems, poor performance, short duration, spoofing and inconsistency are problems that need to be resolved immediately. The researchers conducted research with various models from traditional methods such as the Gaussian Mixture Model (GMM), Support Vector Machine (SVM) and Hidden Markov Model (HMM) to the Deep Learning methods using Deep Neural Network (DNN) and Convolutional Neural Network (CNN). In addition, various hybrid deep learning methods are also used. Various papers that use these methods are difficult to understand, especially when compared between one method with another to obtain novelty and direction of research on speaker recognition. Systematic Literature Review (SLR) is helpful in identifying and interpreting various findings in a field of research in answering the research questions that have determined. This paper uses SLR in identifying research trends,datasets, feature extraction ,classification methods and evaluation techniques used in speaker recognition using deep learning. Results of the SLR discussion are 82 major study journals from 2011 to 2019 show that 20% of research studies focus on speaker verification topics, 11.5% each at Speaker Recognition in Noisy Conditions, Speaker Emotion Recognition and Short and Mismatch Utterance Duration. Research in speaker recognition 90% used public datasets and 10% used private datasets. The MFCC method is a method often used in feature extraction although there are I-vector and X-Vector methods that are starting to be used in deep learning. Deep Neural Network is a classification method that is often used in speaker recognition. 31% of the evaluation techniques that are often used are Equal Error Rate, 29% used the Word Error Rate and 40% used others method such as Accuracy, Root Mean Square Error (RMSE), Signal to Noise Ratio (SNR), Character Error Rate (CER) , Phone Error Rate (PER) and Speech Separation Performance (SSP)

Full article