The COVID‐19 pandemic is a global, national, and local public health concern which has caused a significant outbreak in all countries and regions for both males and females around the world. Automated detection of lung infections and their boundaries from medical images offers a great potential to augment the patient treatment healthcare strategies for tackling COVID‐19 and its impacts. Detecting this disease from lung CT scan images is perhaps one of the fastest ways to diagnose patients. However, finding the presence of infected tissues and segment them from CT slices faces numerous challenges, including similar adjacent tissues, vague boundary, and erratic infections. To eliminate these obstacles, we propose a two‐route convolutional neural network (CNN) by extracting global and local features for detecting and classifying COVID‐19 infection from CT images. Each pixel from the image is classified into the normal and infected tissues. For improving the classification accuracy, we used two different strategies including fuzzy c‐means clustering and local directional pattern (LDN) encoding methods to represent the input image differently. This allows us to find more complex pattern from the image. To overcome the overfitting problems due to small samples, an augmentation approach is utilized. The results demonstrated that the proposed framework achieved precision 96%, recall 97%, F score, average surface distance (ASD) of 2.8 ± 0.3 mm, and volume overlap error (VOE) of 5.6 ± 1.2%.

Purpose: The purpose of this paper is to investigate the influence of halal concern as well as emotional and epistemic values on consumer behaviour in the choice and purchase of halal-certified food supplies.Design/methodology/approach: This study used a quantitative methodology of convenience sampling to collect survey data from 1,550 Muslim respondents in Malaysia. It also employed multiple regressions by covariance-based structural equation modelling in the data analysis as well as in the validation of the proposed model.Findings: The empirical results showed that the importance of halal certification had the highest impact on consumer choice behaviour, particularly in the purchase of halal-certified food supplies. Also, epistemic and emotional values were both statistically significant in terms of their influence on the consumer decision-making process.Research limitations/implications: The results emphasize the importance of enhancing the hedonic (halal concern and emotional value) aspect as a way for the halal food industries to obtain an added value advantage for their products and services.Originality/value: This paper is the first to employ an empirical approach to consider the halal sentiment as a determinant of consumer purchasing behaviour in the context of halal-certified food supplies.

Major businesses around the world have been trying to reduce the total cost and wastes across their supply chain to remain competitive in the expanding global market. Hence, a collection of reliable tools and techniques are vital for decreasing costs and wastes and for providing effective services for customer demands. Given that lean concept attempts to decrease costs and wastes, this study aims to identify the effective lean tools required for eliminating wastes in the supply chain. Because of the large number of consumers and the global market of Halal products, this study focuses on Halal food supply chains. Out of the questionnaires distributed to 300 Halal food firms in Malaysia, only 61 usable replies were obtained. The results showed that demand collaboration, continuous improvement, and inventory management practices are the most important tools in Lean Supply Chain (LSC) implementation. In addition, the results indicated that only a small percentage of Halal food companies are implementing LSC. Malaysia is an important Halal food producer in the word, but has low level of LSC implementation among its Halal food producers. LSC is a new concept that needs more effort to be understood and implemented.

Purpose: – This study aims to assess the possibility of implementing lean practices in the Halal food supply chain, and the barriers to their implementation. Design/methodology/approach: – A survey was used to identify the perceived issues and attitudes towards implementing lean practices in the supply chain. The questionnaire was distributed to 300 Halal food firms in Malaysia. A total of 61 usable replies were received. Findings: – More than 70 percent of the firms reported that lean supply chain (LSC) has not yet been implemented in their firm. Data analysis shows that 14 percent of non-lean firms urgently need to implement lean manufacturing. Market competition and uncertainty was highlighted as an important barrier in implementing LSC among lean firms. In contrast, lack of customer awareness of LSCM practices was recognised as a major barrier in non-lean firms. Originality/value: – There is little documentation regarding the status of LSC implementation in the Halal food industries, and therefore identifying the necessity of its implementation and the important impediments was identified as a gap in the existing literature. This paper provides insightful information on the necessity of implementing lean manufacturing practices in Halal food supply chains.

Lean manufacturing system has been widely applied in manufacturing companies worldwide. However, the low success rate of lean transformations in many countries has given a cause for concern. Much of the literature had pointed out that the main reason is due to the failure in managing the change process during a lean manufacturing transformation. This paper presents a thorough literature review for lean manufacturing approach in the context of organisational change management. Finally, the authors have proposed an organisational change framework for lean manufacturing implementation that would serve as the basis for further empirical research and validation. The framework will further expand the body of knowledge by linking organisational change management with the transition to implementing a lean manufacturing system.