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
03
)
16 May 2026
Day
Hour
Min
Sec
Day
Hour
Min
Sec
Publish On
(
Vol
58
, Issue
03
)
31 May 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-13-06-2025-845
Abstract : Breast cancer continues to be among the major causes of cancer mortality among women worldwide, with more than 2 million cases and around 680,000 deaths recorded in 2020, as per the World Health Organization (WHO). Early diagnosis is very important, especially in low- and middle-income countries (LMICs) where diagnostic facilities are scarce. In this paper, a non-invasive breast cancer classification system based on thermal infrared imaging and deep learning is suggested. The DMR-IR dataset, which includes ground-truth thermal images, was utilized to train an ensemble model combining VGG16 and EfficientNet using transfer learning. Image enhancement methods and Grad-CAM visualizations were employed to enhance interpretability. The ensemble model had a classification accuracy of 99.8% and an AUC value of 1.00. These outcomes demonstrate high potential for precise early detection. The research shows how interpretable AI can aid radiologists during diagnosis with a decrease in reliance on intrusive procedures, particularly in healthcare settings with limited resources..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-13-06-2025-844
Abstract : Alzheimer’s disease (AD) is a progressive neurode- generative condition that features loss of brain volume, loss of neurons, and deposition of amyloid and tau proteins resulting in dementia and cognitive decline. Since AD evolves 8–15 years before the development of overt symptoms and is not treatable, timely diagnosis is imperative to slow down the progression of the disease and enhance patient outcomes. The objective of this research is to classify Alzheimer’s disease stages using deep learning on the OASIS dataset. The model categorizes subjects into four groups: Non-Demented, Very Mild Demented, Mild Demented, and Moderate Demented. Transfer learning is employed, and ResNet-50 as a feature extraction base model and a custom CNN as a classifier. The input has major neuroimaging biomarkers that include hippocampal volume, cortical thickness, and ventricle volume, which improve the model’s diagnostic capability. The use of pre-trained feature extraction with task- specific fine-tuning yields precise and efficient classification by the proposed method. The project assists in early diagnosis and accurate staging of Alzheimer’s disease, facilitating improved treatment and management practices..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-13-06-2025-843
Abstract : This paper explores the application of machine learning algorithms in predicting the compressive strength of high-performance concrete (HPC), a critical aspect of ensuring structural integrity in modern construction. Various machine learning models—such as XGBoost, K-nearest neighbors (KNN), Decision Tree, and Random Forest—were evaluated to predict HPC strength with high accuracy. The study compares the performance of these models using metrics like R², MAE, and RMSE to identify the most effective approach. Results indicate that XGBoost outperformed other models like decision Tree KNN and Random Forest. Feature importance analysis highlighted key factors influencing HPC strength, such as age, cement, and water-to-cement ratio. These findings emphasize the potential of machine learning in improving quality control for HPC and optimizing mix design processes. Future work will explore the integration of environmental factors and advanced hybrid models to further enhance prediction accuracy..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-16-05-2025-836
Abstract : Thirty-one cities from around the world were analyzed to identify the best practices and successful policies that promote sustainable urban development. this study proposes an advanced Biophilic City Index—a practical tool designed to help cities evaluate their efforts to improve well-being and ecological resilience. It assesses urban performance through 25 indicators across four dimensions: governance, infrastructure, engagement, and equity. Unlike city-level tools such as the City Biodiversity Index or ICLEI’s models, which often overlook multidimensional and equity-based aspects, this index applies a frequency-weighted method to ensure proportional representation of key indicators. Cities like Singapore, Fremantle, and Vitoria-Gasteiz stand out for their policy alignment, investment in nature, and inclusive access. However, challenges persist—particularly in ensuring equitable distribution of green space. This index offers planners and decision-makers a clearer path to advancing nature-based solutions and building resilient, inclusive urban environments..
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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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