Search results
1 – 10 of 191Sara El-Ateif, Ali Idri and José Luis Fernández-Alemán
COVID-19 continues to spread, and cause increasing deaths. Physicians diagnose COVID-19 using not only real-time polymerase chain reaction but also the computed tomography (CT…
Abstract
Purpose
COVID-19 continues to spread, and cause increasing deaths. Physicians diagnose COVID-19 using not only real-time polymerase chain reaction but also the computed tomography (CT) and chest x-ray (CXR) modalities, depending on the stage of infection. However, with so many patients and so few doctors, it has become difficult to keep abreast of the disease. Deep learning models have been developed in order to assist in this respect, and vision transformers are currently state-of-the-art methods, but most techniques currently focus only on one modality (CXR).
Design/methodology/approach
This work aims to leverage the benefits of both CT and CXR to improve COVID-19 diagnosis. This paper studies the differences between using convolutional MobileNetV2, ViT DeiT and Swin Transformer models when training from scratch and pretraining on the MedNIST medical dataset rather than the ImageNet dataset of natural images. The comparison is made by reporting six performance metrics, the Scott–Knott Effect Size Difference, Wilcoxon statistical test and the Borda Count method. We also use the Grad-CAM algorithm to study the model's interpretability. Finally, the model's robustness is tested by evaluating it on Gaussian noised images.
Findings
Although pretrained MobileNetV2 was the best model in terms of performance, the best model in terms of performance, interpretability, and robustness to noise is the trained from scratch Swin Transformer using the CXR (accuracy = 93.21 per cent) and CT (accuracy = 94.14 per cent) modalities.
Originality/value
Models compared are pretrained on MedNIST and leverage both the CT and CXR modalities.
Details
Keywords
Wang Zhang, Lizhe Fan, Yanbin Guo, Weihua Liu and Chao Ding
The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection…
Abstract
Purpose
The purpose of this study is to establish a method for accurately extracting torch and seam features. This will improve the quality of narrow gap welding. An adaptive deflection correction system based on passive light vision sensors was designed using the Halcon software from MVtec Germany as a platform.
Design/methodology/approach
This paper proposes an adaptive correction system for welding guns and seams divided into image calibration and feature extraction. In the image calibration method, the field of view distortion because of the position of the camera is resolved using image calibration techniques. In the feature extraction method, clear features of the weld gun and weld seam are accurately extracted after processing using algorithms such as impact filtering, subpixel (XLD), Gaussian Laplacian and sense region for the weld gun and weld seam. The gun and weld seam centers are accurately fitted using least squares. After calculating the deviation values, the error values are monitored, and error correction is achieved by programmable logic controller (PLC) control. Finally, experimental verification and analysis of the tracking errors are carried out.
Findings
The results show that the system achieves great results in dealing with camera aberrations. Weld gun features can be effectively and accurately identified. The difference between a scratch and a weld is effectively distinguished. The system accurately detects the center features of the torch and weld and controls the correction error to within 0.3mm.
Originality/value
An adaptive correction system based on a passive light vision sensor is designed which corrects the field-of-view distortion caused by the camera’s position deviation. Differences in features between scratches and welds are distinguished, and image features are effectively extracted. The final system weld error is controlled to 0.3 mm.
Details
Keywords
Iling Aema Wonnie Ma, Sachin Sharma Ashok Kumar, Ramesh Kasi, Ammar Shafaamri and Ramesh Subramaniam
This study aims to propose that the corrosion resistance of the neat epoxy coating can be further enhanced by incorporating reinforcing agents.
Abstract
Purpose
This study aims to propose that the corrosion resistance of the neat epoxy coating can be further enhanced by incorporating reinforcing agents.
Design/methodology/approach
Chitosan, silica and their hybrid compound were used to study the subject of corrosion resistance of epoxy coating systems. This work used 3.5 Wt.% NaCl solution as the electrolyte, and electrochemical impedance spectroscopy (EIS) was used to investigate the electrochemical behaviour of the studied coating systems. Standard and accelerated states were used without and with scratch on the coating layer.
Findings
It was found that the impedance value of composite coating incorporated with the hybrid compound was significantly higher at 1010 Ω after 14 days of exposure in both testing states. The breakpoint frequency (fb) determination also proves with large capacitive region at low-to-high frequency of impedance plots corresponding to the high corrosion resistance.
Originality/value
The hybrid compound consisting of chitosan as organic biopolymer and silica as inorganic material, respectively, served as a promising reinforcing agent for composite coating as a promising corrosion inhibitor. Different states of EIS measurement were used which are standard (without scratch) and accelerated (with scratch) states associated with the fb values.
Details
Keywords
Yuanhao Yang, Guangyu Chen, Zhuo Luo, Liuqing Huang, Chentong Zhang, Xuetao Luo, Haixiang Luo and Weiwei Yu
The purpose of this study is to prepare thermal transfer ribbons with good alcohol resistance.
Abstract
Purpose
The purpose of this study is to prepare thermal transfer ribbons with good alcohol resistance.
Design/methodology/approach
A variety of alcohol-resistant thermal transfer inks were prepared using different polyester resins. The printing temperature, printing effect, adhesion and alcohol resistance of the inks on the label were studied to determine the feasibility of using the ink for manufacturing thermal transfer ribbons. The ink formulations were prepared by a simple and stable grinding technology, and then use mature coating technology to make the ink into a thermal transfer ribbon.
Findings
The results show that the thermal transfer ink has good scratch resistance, good alcohol resistance and low printing temperature when the three resins coexist. Notably, the performance of the ribbon produced by 500 mesh anilox roller was better than that of other meshes. Specifically, the ink on the matte silver polyethylene terephthalate (PET) label surface was wiped with a cotton cloth soaked in isopropyl alcohol under 500 g of pressure. After 50 wiping cycles, the ink remained intact.
Originality/value
The proposed method not only ensures good alcohol resistance but also has lower printing temperature and wider label applicability. Therefore, it can effectively reduce the loss of printhead and reduce production costs, because of the low printing temperature.
Details
Keywords
Shuliu Wang, Qianqian Liu, Jin Wang, Nana Chen, JunHang Chen, Jialiang Song, Xin Zhang and Kui Xiao
This study aims to investigate the role of aluminium (Al) in marine environment and the corrosion mechanism of galvalume coatings by conducting accelerated experiments and data…
Abstract
Purpose
This study aims to investigate the role of aluminium (Al) in marine environment and the corrosion mechanism of galvalume coatings by conducting accelerated experiments and data analysis.
Design/methodology/approach
Samples were subjected to accelerated corrosion for 136 days via salt spray tests to simulate the natural conditions of marine environment and consequently accelerate the experiments. Subsequently, the samples were examined using various test methods, such as EDS, scanning electron microscopy (SEM), X-ray diffraction (XRD) and electrochemical impedance spectroscopy (EIS), and the obtained data were analysed.
Findings
Galvalume coatings comprised interdigitated zinc (Zn)-rich and dendritic Al-rich phases. Corrosion was observed to begin with a Zn-rich phase. The primary components of the corrosion product film were Al2O3 and Zn5(OH)8Cl2·H2O. It was confirmed that the role of Al was to form a dense protective film, thereby successfully blocking the entry of corrosive media and protecting the iron substrate.
Originality/value
This study provides a clearer understanding of the corrosion mechanism and kinetics of galvalume coatings in a simulated marine environment. In addition, the role of Al, which is rarely mentioned in the literature, was investigated.
Details
Keywords
Gomaa Abdel-Maksoud, Hanaa Nasr, Sayed Hussein Samaha and Mahmoud Saad ELdeen Kassem
This study aims to evaluate the state of preservation of one of the most famous manuscripts dated back to the 15th century using some analytical techniques to identify the…
Abstract
Purpose
This study aims to evaluate the state of preservation of one of the most famous manuscripts dated back to the 15th century using some analytical techniques to identify the manuscript components, explain its deterioration mechanisms and produce some solutions for conservation processes in future studies.
Design/methodology/approach
The analytical techniques used were visual assessment, digital microscope, scanning electron microscope (SEM) with EDX, pH measurement, attenuated total reflection – Fourier transform infrared spectroscopy (ATR/FTIR) and cellulose crystallinity.
Findings
Stains, missed parts and scratching were the most common aspects of deterioration. Some insects were observed by digital microscope. The SEM showed that linen fibers and goat skin were used to manufacture paper sheets and leather binding. Energy dispersive X-ray analysis proved that niobium and tantalum were added during the manufacture of paper sheets. Carbon black ink was the main writing material. The other pigments used were cinnabar in red ink, gold color from brass and blue color from lapis lazuli. FTIR analysis proved that some chemical changes were noticed. Low crystallinity of the historical paper was obtained. There was a reduction in the pH value of the historical bookbinding.
Originality/value
The importance of the analytical techniques used to detect the main components, forms and mechanism of deterioration of the studied manuscript. The elements of niobium and tantalum were added to paper sheets, which protected them from deterioration. The insects such as house flies and Sitophilus granarius were found in the manuscripts.
Details
Keywords
Xiao Wang, Xuan Liang, Bo Wang, Chang-qing Guo, Shan-gui Zhang, Kai Yang, Shi-ya Shao, Yan Sun, Zheng Guo, Xue-yan Yu, Donghai Zhang, Tai-jiang Gui, Wei Lu, Ming-liang Sun and Rui Ding
The purpose of this study is to evaluate the effect of graphene, basalt flakes and their synergy on the corrosion resistance of zinc-rich coatings. As the important heavy-duty…
Abstract
Purpose
The purpose of this study is to evaluate the effect of graphene, basalt flakes and their synergy on the corrosion resistance of zinc-rich coatings. As the important heavy-duty anticorrosion coatings, zinc-rich coatings provided cathodic protection for the substrate. However, to ensure cathodic protection, a large number of zinc powder made the penetration resistance known as the weakness of zinc-rich coatings. Therefore, graphene and basalt flakes were introduced into zinc-rich coatings to coordinate its cathodic protection and shielding performance.
Design/methodology/approach
Three kinds of coatings were prepared; they were graphene modified zinc-rich coatings, basalt flakes modified zinc-rich coatings and graphene-basalt flakes modified zinc-rich coatings. The anticorrosion behavior of painted steel was studied by using the electrochemical impedance spectroscopy (EIS) technique in chloride solutions. The equivalent circuit methods were used for EIS analysis to obtain the electrode process structure of the coated steel system. Simultaneously, the corrosion resistance of the three coatings was evaluated by water resistance test, salt water resistance test and salt spray test.
Findings
The study found that the addition of a small amount of graphene and basalt flakes significantly improved the anticorrosion performance of coatings by enhancing their shielding ability against corrosive media and increasing the resistance of the electrochemical reaction. The modified coatings exhibited higher water resistance, salt water resistance and salt spray resistance. The graphene-basalt flakes modified zinc-rich coatings demonstrated the best anticorrosion effect. The presence of basalt scales and graphene oxide in the coatings significantly reduced the water content and slowed down the water penetration rate in the coatings, thus prolonging the coating life and improving anticorrosion effects. The modification of zinc-rich coatings with graphene and basalt flakes improved the utilization rate of zinc powder and the shielding property of coatings against corrosive media, thus strengthening the protective effect on steel structures and prolonging the service life of anticorrosion coatings.
Originality/value
The significance of developing graphene-basalt flakes modified zinc-rich coatings lies in their potential to offer superior performance in corrosive environments, leading to prolonged service life of metallic structures, reduced maintenance costs and a safer working environment. Furthermore, such coatings can be used in various industrial applications, including bridges, pipelines and offshore structures, among others.
Details
Keywords
Michael Shick, Nathan Johnson and Yang Fan
The purpose of this viewpoint article is to serve as a discussion starting point regarding organizational leadership’s increasing reliance on AI – in particular, how the…
Abstract
Purpose
The purpose of this viewpoint article is to serve as a discussion starting point regarding organizational leadership’s increasing reliance on AI – in particular, how the technology is used as a supplemental tool for supporting rational decision-making. Practical implications and directions for further research are presented.
Design/methodology/approach
With its inception in economics, the concept of rationality has a rich history across multiple research domains. Based on that literature, coupled with the recent advancements in AI, the paper asks: will AI afford organizational leadership the ability to move from making bounded rational decisions to making fully rational decisions? The paper only scratches the surface of such a large question; however, the goal is to start the discussion around the topic.
Findings
While bounded rationality supports efficient decision-making, a complete understanding of any given decision is typically limited, and as a result, neither accuracy nor effectiveness is guaranteed. As AI systems grow in speed and accuracy, they should provide positive support for organizational leaders to make fully rational decisions. AI’s ability to collect and organize data, analyze it, and offer decision alternatives may help close the gap between bounded and rational decision-making.
Originality/value
Although AI research is not new, the recent developments in natural language processing engines has rapidly brought about new possibilities for their use in rational decision-making in the business and organizational context. This is fertile ground for future research, particularly in the area of organizational decision-making.
Details
Keywords
Omprakash Ramalingam Rethnam and Albert Thomas
The building sector contributes one-third of the energy-related carbon dioxide globally. Therefore, framing appropriate energy-related policies for the next decades becomes…
Abstract
Purpose
The building sector contributes one-third of the energy-related carbon dioxide globally. Therefore, framing appropriate energy-related policies for the next decades becomes essential in this scenario to realize the global net-zero goals. The purpose of the proposed study is to evaluate the impact of the widespread adoption of such guidelines in a building community in the context of mixed-mode buildings.
Design/methodology/approach
This study decentralizes the theme of improving the energy efficiency of the national building stock in parcels by proposing a community-based hybrid bottom-up modelling approach using urban building energy modelling (UBEM) techniques to analyze the effectiveness of the community-wide implementation of energy conservation guidelines.
Findings
In this study, the UBEM is developed and validated for the 14-building residential community in Mumbai, India, adopting the framework. Employing Energy Conservation Building Code (ECBC) compliance on the UBEM shows an energy use reduction potential of up to 15%. The results also reveal that ECBC compliance is more advantageous considering the effects of climate change.
Originality/value
In developing countries where the availability of existing building stock information is minimal, the proposed study formulates a holistic framework for developing a detailed UBEM for the residential building stock from scratch. A unique method of assessing the actual cooling load of the developed UBEM is presented. A thorough sensitivity analysis approach to investigate the effect of cooling space fraction on the energy consumption of the building stock is presented, which would assist in choosing the appropriate retrofit strategies. The proposed study's outcomes can significantly transform the formulation and validation of appropriate energy policies.
Details
Keywords
Nehemia Sugianto, Dian Tjondronegoro and Golam Sorwar
This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video…
Abstract
Purpose
This study proposes a collaborative federated learning (CFL) framework to address personal data transmission and retention issues for artificial intelligence (AI)-enabled video surveillance in public spaces.
Design/methodology/approach
This study examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Based on the requirements, this study proposes a CFL framework to gradually adapt AI models’ knowledge while reducing personal data transmission and retention. The framework uses three different federated learning strategies to rapidly learn from different new data sources while minimizing personal data transmission and retention to a central machine.
Findings
The findings confirm that the proposed CFL framework can help minimize the use of personal data without compromising the AI model's performance. The gradual learning strategies help develop AI-enabled video surveillance that continuously adapts for long-term deployment in public spaces.
Originality/value
This study makes two specific contributions to advance the development of AI-enabled video surveillance in public spaces. First, it examines specific challenges for long-term people monitoring in public spaces and defines AI-enabled video surveillance requirements. Second, it proposes a CFL framework to minimize data transmission and retention for AI-enabled video surveillance. The study provides comprehensive experimental results to evaluate the effectiveness of the proposed framework in the context of facial expression recognition (FER) which involves large-scale datasets.
Details