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Gongcheng Kexue Yu Jishu/Advanced Engineering Science

Gongcheng Kexue Yu Jishu/Advanced Engineering Science (ISSN: 2096-3246) is a bi-monthly peer-reviewed international Journal. Gongcheng Kexue Yu Jishu/Advanced Engineering Science was originally formed in 1969 and the journal came under scopus by 2017 to now. The journal is published by editorial department of Journal of Sichuan University. We publish every scope of engineering, Mathematics, physics.


Submission Deadline
( Vol 58 , Issue 01 )
26 Jan 2026
Day
Hour
Min
Sec
Publish On
( Vol 58 , Issue 01 )
31 Jan 2026
Scopus Indexed (2026)

Aim and Scope

Gongcheng Kexue Yu Jishu/Advanced Engineering Science (ISSN: 20963246) 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:

Agricultural science and engineering Section:

Horticulture, Agriculture, Soil Science, Agronomy, Biology, Economics, Biotechnology, Agricultural chemistry, Soil, development in plants, aromatic plants, subtropical fruits, Green house construction, Growth, Horticultural therapy, Entomology, Medicinal, Weed management in horticultural crops, plant Analysis, Tropical, Food Engineering, Venereal diseases, nutrient management, vegetables, Ophthalmology, Otorhinolaryngology, Internal Medicine, General Surgery, Soil fertility, Plant pathology, Temperate vegetables, Psychiatry, Radiology, Pulmonary Medicine, Dermatology, Organic farming, Production technology of fruits, Apiculture, Plant breeding, Molecular breeding, Recombinant technology, Plant tissue culture, Ornamental horticulture, Nursery techniques, Seed Technology, plantation crops, Food science and processing, cropping system, Agricultural Microbiology, environmental technology, Microbial, Soil and climatic factors, Crop physiology, Plant breeding,

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 Journals
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-17-04-2025-831

Abstract : Geo-polymer composites are emerging as sustainable replacement options of conventional cement concrete, for effective reduction in carbon footprint. Owing to the use of supplementary cementitious materials viz. fly ash, GGBS, metakaolin, brick husk ash and their combinations, the resulting concrete is different from the conventional concrete in terms of fineness, density, packing etc. Hence, the correlation equations used to derive compressive strength values from non- destructive test results, for conventional concrete, cannot be applied to the Geo-polymer concrete. In the recent experimental research program, six types of geo-polymer concrete specimen were prepared to evaluate their performance. Both nondestructive tests (Schmidt rebound hammer, Ultrasonic pulse velocity) and destructive tests were conducted to determine compressive strength using suitable regression equations. The collected data from tests were first imported into predefined models for analysis of polynomial regression technique (PRT) to derive the equations. To improvise the data structure performance and avoid issues such as over fitting and under fitting, the datasets were imported in machine learning algorithms, including ANN, ANFIS techniques. If we compare regression analysis, ANN and ANFIS, ANN the latter yields less error than the former..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-10-04-2025-829

Abstract : The paper addresses challenges in measuring sustainable development indicators in cities, highlighting the importance of considering variations in city categories and sizes. It emphasises that problems arise from measurement methods that do not account for differences in developmental capabilities and categories of cities. The study proposes a novel approach to reclassifying sustainable development indicators based on the developmental capabilities of each city, with a specific focus on the Al-Qassim region in Saudi Arabia. By studying the developmental capabilities of urban settlements in Al-Qassim and linking them to Sustainable Development Goals (SDGs), the research aims to establish a connection between these capabilities and relevant indicators. This process involves excluding certain indicators or adjusting calculation methods based on the developmental capacities of cities, ensuring a more accurate reflection of their sustainable development performance. The classification process involves assessing variables such as population size, service centrality, and spatial centrality to determine the minimum threshold for urban settlements. Cities that fall below this threshold are excluded from the analysis. The study highlights the need to reevaluate indicators related to population size and service levels, especially for cities with regional roles, to align measurement methods with the specific characteristics of each city. Ultimately, the research underscores the significance of aligning sustainable development indicators with the developmental capabilities of cities to enhance decision-making processes and promote more effective urban development strategies..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-19-03-2025-823

Abstract : Waste as a major global problem is increasing in both developed and developing countries. According to the World Bank, in the year 2050, it is estimated to be 3.4 tons per year in the year 2050, which is about 46% of the majority. Therefore, it is urgent to find a sustainable, efficient, and competitive way to deal with food waste. The purpose of this study are to improve bioconversion processes based on information systems. The bioconversion process includes the sorting of organic waste, cutting, and the bioconversion process through bioponds and screening. The bioconversion process produces maggots, liquid fertilizers, and cassava. Optimization of the bioconversion process is supported by a waste management information system. At this stage, laboratory testing of each bioconversion process will be carried out. The results of the laboratory test will be compared with similar products on the market and with the laboratory standards of the product..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-12-03-2025-821

Abstract : In DSP (Digital Signal Processing), the MAC unit, or Multiply-Accumulate Computation, plays a vital role in the processing chain. The multiplier distinguishes among its constituents as a crucial building piece. This paper describes the design of the multiply-accumulate unit with the Novel sleep Transistor technique and compares 8-bit MACs and their building blocks with relevant techniques. This MAC unit is designed with Cadence 45nm technology. These designs are analyzed and simulated with a virtuoso simulation tool..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-24-02-2025-818

Abstract : Executing Join-Aggregate queries on Big Data can incur enormous computational costs. Hence, the Approximate Aggregate Query Processing Techniques (AQPTs) are an attractive choice to execute such join-aggregate queries, because they incur limited computational costs. The AQPTs utilize random sampling to approximately execute a given join aggregate query. However, the effectiveness of random sampling is highly correlated with the number of qualifying tuples of the given query. If the given query has limited number of qualifying tuples, the approximate answer obtained by AQPT can suffer from poor approximation accuracy. Hence, it is extremely necessary to analyze the feasibility of a given join-aggregate query to be executed by AQPT. In the literature, such feasibility framework has not received any attention. Hence, in this paper, a feasibility framework for analyzing the feasibility of a given join-aggregate query to be executed by AQPT, is presented. This proposed feasibility framework is designed through the aid of a probabilistic model. An empirical analysis study of the proposed feasibility framework is presented. In this study, the proposed feasibility framework demonstrates appreciable performance in-terms of prediction accuracy and execution latency. The proposed feasibility framework presents a significant advancement in the field of Approximate Aggregate Query Processing AI Techniques. Its effective utilization of a probabilistic model for feasibility analysis provides a reliable and efficient solution for executing join-aggregate queries, paving the way for more optimized and cost-effective Big Data processing..
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