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 55 , Issue 02 )
10 Feb 2023
Day
Hour
Min
Sec
Publish On
( Vol 55 , Issue 02 )
28 Feb 2023
Scopus Indexed (2022)

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. Azerbaijan Medical Journal Zhonghua er bi yan hou tou jing wai ke za zhi = Chinese journal of otorhinolaryngology head and neck surgery Interventional Pulmonology Zhenkong Kexue yu Jishu Xuebao/Journal of Vacuum Science and Technology Wuhan Ligong Daxue Xuebao (Jiaotong Kexue Yu Gongcheng Ban)/Journal of Wuhan University of Technology (Transportation Science and Engineering) Zhonghua yi shi za zhi (Beijing, China : 1980) Zhongguo Shiyou Daxue Xuebao (Ziran Kexue Ban)/Journal of China University of Petroleum (Edition of Natural Science) Tobacco Science and Technology Teikyo Medical Journal Connected Health

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 :

Physics Section:

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-17-11-2022-420

Abstract : Quality of osmotically dehydrated pineapples is very important to consumers. A reliable non-destructive method for assessing quality of osmotically dehydrated pineapples is required for factories in order to ensure the quality of products be-fore sending to consumers. Near infrared hyperspectral imaging (NIR-HSI) has the potential to be used for this purpose and was therefore tested for predicting qualities including hardness, total soluble solids (TSS), sulfur dioxide content (SO2) and moisture content (MC) of osmotically dehydrated pineapples. Spectra of samples were acquired in the range of 935-1720 nm and were used for estab-lishing calibration models for the quality indices by partial least squares regres-sion (PLSR). The chemometrics was investigated in order to acquire the best models. The prediction of the models for hardness, TSS, SO2 and MC had a cor-relation coefficient of prediction (Rp) of 0.86, 0.80, 0.76 and 0.84 respectively and root mean squares error of prediction (RMSEP) of 0.82 N, 1.86%, 25.53 mg/kg and 0.73% respectively. These models were also applied to samples to ob-tain predictive images that showed spatial distributions of samples quality on a color-based scale. Results showed that NIR-HSI can be applied to use as a non-destructive quality prediction method in the on-line system of factories for sorting and guaranteeing the quality of osmotically dehydrated pineapples..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-14-11-2022-419

Abstract : Now a day’s millions of people use social networks like Facebook and Twitter to communicate, showing present status, achievements, and daily activities. Like two sides for a coin, here also two different paths that affect human life negatively and positively by the usage of social networks in the present world, like a genuine users some fake users spread fake contents by using fake user identities that may lead to several problems in the society like law and order problems, riots, protests, etc… to avoid these type of actions nowadays researchers focuses on spam detection techniques in twitter by which results are getting positively. Researchers employed spam-detection methods that relied on phoney users, spam-based URLs, spamming of popular topics, and fake material. All these techniques work based on features available on social networks like user information, content sharing, graphical data, time and structural data. Present literature work in this paper gives deep information about different techniques used by researchers to detect spam contents in various social networks that may be useful for researchers to have information gathered in a spot..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-14-11-2022-418

Abstract : Speaking is the most common and practical form of communication. Automated voice recognition allows for natural communication between machines and people. It has developed into an interesting and challenging field. It enhances the computer’s capacity to react precisely to spoken words. A method for locating individual pronounced words in voice signals is called keyword spotting. Markov Chain Models without discrimination are commonly utilized in algorithm-finding keywords. This study presented a keyword identification method that used neural networks and iterative data to estimate keyword probabilities over time. This work aims to properly identify keywords in a recently constructed multilingual speech dataset. This dataset includes data in Hindi, English, and Assamese for 7-day, 10-digit, and 12-month periods. According to test findings, the suggested framework can correctly predict word samples in English, Assamese, and Hindi with 83.34 percent, 86.96 percent, and 81.36 percent accuracy during training. Applications for finding keywords in spoken text utilize isolated word recognition. This is useful for embedded and mobile devices..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-14-11-2022-417

Abstract : Lung cancer is the cancer that spreads the fastest and is typically detected at an advanced stage. It may cause death with late diagnosing and improper treatment. A computer-aided detection method is required to categorise the lung nodule with the greatest degree of accuracy in order to avoid delays in diagnosis due to advancements in medical imaging methods like computed tomography (CT) scans. This study proposed a novel architecture D3DR_MKCA based on Deep Residual network incorporating convolutional block attention module (CBAM) which applied on different scale feature maps to classify lung nodules. CBAM improves the representation power of Residual Network. Initially lung nodules are efficiently segmented with the help of Location Aware Encoding Network and those segmented nodules are further classified into Adenocarcinoma, Small Cell Carcinoma, Large Cell Carcinoma, and Squamous Cell Carcinoma cancerous tissues with the help of proposed D3DR_MKCA deep architecture. A Large-Scale CT and PET/CT Dataset for Lung Cancer Diagnosis (Lung-PET-CT-Dx)are used for performance analysis and the D3DR_MKCA model archives F1-score up to 90.96%..
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Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-13-11-2022-416

Abstract :

In order to effectively solve the defects of boundary distortion, artifacts and training instability when repairing complex backgrounds and high-resolution images, an image repair algorithm based on dual generative adversarial networks and multi-scale discriminators is proposed. First, the image to be repaired is input into the content prediction network based on the dilated convolution layer, and the reconstruction loss and the global decision device based on the generative adversarial loss are used as the standard, and the rough repair is performed to obtain a clear and reasonable overall semantic consistency. structure. Then, the rough inpainting result is input into the detail inpainting network, and after being decoded and deconvoluted by the dilated convolution path and the perceptual convolution path, it is sent to three different-scale decision devices for optimization to improve the fine-grained texture of the inpainting result. Finally, 3 different scales of adversarial losses are used to optimize network parameters to capture multi-scale edge information of damaged regions and generate reasonable and realistic texture details. On the recognized image dataset, the algorithm of this paper is used for inpainting experiment, dual network inpainting comparison, high-resolution inpainting comparison, target removal experiment, ablation experiment and objective experiment. , can generate reasonable structure and clear texture details; the double network structure is better than the single network structure; the fine-grained texture obtained when repairing high-resolution images is better than the comparison algorithm; the algorithm proposed in this paper is used for high-resolution target removal , can get results with clear and reasonable structure and fine texture; ablation experiments verify the effectiveness of the proposed module; the peak signal-to-noise ratio, structural similarity, and average l1 error and average l2 The errors are all better than the compared classical inpainting algorithms. In short, the algorithm proposed in this paper can well combine the overall semantics of the image, enhance the restoration accuracy of image details, and effectively avoid problems such as structural texture disorder, pixel overlapping, and boundary distortion

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