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The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech. It proposes a convolutional neural network-based capsule network (CNN-CapsNet) model and outlining the performance of the system in recognition of gait and speech variations. The proposed intelligent system mainly focuses on relative spatial hierarchies between gait features in the entities of the image due to translational invariances in sub-sampling and speech variations.

This proposed work CNN-CapsNet is mainly used for automatic learning of feature representations based on CNN and used capsule vectors as neurons to encode all the spatial information of an image by adapting equal variances to change in viewpoint. The proposed study will resolve the discrepancies caused by cofactors and gait recognition between opinions based on a model of CNN-CapsNet.

This research work provides recognition of signal, biometric-based gait recognition and sound/speech analysis. Empirical evaluations are conducted on three aspects of scenarios, namely fixed-view, cross-view and multi-view conditions. The main parameters for recognition of gait are speed, change in clothes, subjects walking with carrying object and intensity of light.

The proposed CNN-CapsNet has some limitations when considering for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.

This research work includes for detecting the walking targets from surveillance videos considering multimodal fusion approaches using hardware sensor devices. It can also act as a pre-requisite tool to analyze, identify, detect and verify the malware practices.

This proposed research work proves to be performing better for the recognition of gait and speech when compared with other techniques.

In wireless sensor networks, improving the network lifetime is considered as the prime objective that needs to be significantly addressed during data aggregation. Among the traditional data aggregation techniques, cluster-based dominating set algorithms are identified as more effective in aggregating data through cluster heads. But, the existing cluster-based dominating set algorithms suffer from a major drawback of energy deficiency when a large number of communicating nodes need to collaborate for transferring the aggregated data. Further, due to this reason, the energy of each communicating node is gradually decreased and the network lifetime is also decreased. To increase the lifetime of the network, the proposed algorithm uses two sets: Dominating set and hit set.

The proposed algorithm uses two sets: Dominating set and hit set. The dominating set constructs an unequal clustering, and the hit set minimizes the number of communicating nodes by selecting the optimized cluster head for transferring the aggregated data to the base station. The simulation results also infer that the proposed optimized unequal clustering algorithm (OUCA) is greater in improving the network lifetime to a maximum amount of 22% than the existing cluster head selection approach considered for examination.

In this paper, lifetime of the network is prolonged by constructing an unequal cluster using the dominating set and electing an optimized cluster head using hit set. The dominator set chooses the dominator based on the remaining energy and its node degree of each node. The optimized cluster head is chosen by the hit set to minimize the number of communicating nodes in the network. The proposed algorithm effectively constructs the clusters with a minimum number of communicating nodes using the dominating and hit set. The simulation result confirms that the proposed algorithm prolonging the lifetime of the network efficiently when compared with the existing algorithms.

The proposed algorithm effectively constructs the clusters with a minimum number of communicating nodes using the dominating and hit sets. The simulation result confirms that the proposed algorithm is prolonging the lifetime of the network efficiently when compared with the existing algorithms.

The case study aims to provide students with an understanding of the challenges businesses face expanding into the home market after having an international presence through exports. It also throws light on operations in an emerging market economy – both rural and urban. The key objectives are to understand the leather footwear business operation in India, understand the challenges of expanding business in India, analyse strategies adopted to sustain and compete in India and identify the possible distribution strategies for the leather footwear business in India.

The case study focuses on Tata International Limited’s (TIL) leather and leather products business in India. The leather and leather products division was present in India since 1973 (Anand, 2020) and exported to more than 35 countries across the world (Anand, 2020). TIL did not want to miss the opportunity available in India and planned to expand its leather footwear business in the country. The company opened retail outlets in major Indian cities and an experience store in Dewas (Madhya Pradesh) in 2019. It aimed for a domestic presence along with the existing export business. However, the biggest challenge that was in front of V. Muthukumaran, head of leather products division at TIL, was how to go ahead with the idea of domestic expansion (Anand, 2020). Should the company expand the market through sister companies (Westside and Tata CliQ) in India? How and in what way should TIL plan for going through Westside and Tata CLiQ? Should Muthukumaran think of either the brick-and-mortar route or the online route or both?

This case study is designed for use in undergraduate and graduate early-stage programmes. This case study is primarily designed for use in Master of Business Administration and/or Bachelor of Business Administration programmes. The case study is ideal for courses on understanding the expansion in the domestic market, strategy, retail and international marketing. The teaching note discusses theoretical frameworks such as external environment analysis and SWOT analysis to devise distribution strategies. The case study mapped the distribution channel and decision alternatives for the company.

Teaching notes are available for educators only.

CSS 8: Marketing.

The purpose of the paper is to study effect of the implantation of oxygen and helium ions on the corrosion performance of the AISI3l6L stainless steel. It presents useful new results which allows one to draw conclusions as to the suitability of the helium and oxygen ion implanted AISI 316L stainless steel for biomedical use in the body.

The implantation of oxygen and helium ions was done on AISI 316L SS at an energy level of 100 keV at a dose of 1×10¹⁷ ions/cm², at room temperature. In order to simulate the natural tissue environment, an electrochemical test using cyclic polarization was done in a 0.9 percent sodium chloride solution at a pH value of 6.3 at 37°C. This was carried out on both the virgin and implanted AISI 316L stainless steel for the purpose of comparing performance. In addition to this, the hardness of the virgin and implanted samples was also studied using Vickers microhardness tester with varying loads. Besides, the surface morphologies of the implanted samples and the corroded samples were studied with XRD and SEM.

From the study the following findings are made. First, the XRD and SEM results were found to be in accordance with the corrosion test results. Second, the general corrosion behavior showed a significant improvement in the case of both helium implanted (icorr=0.0689 mA/cm²) and oxygen implanted (icorr=1.104 mA/cm²), when compared to the virgin AISI 316L SS (icorr=1.2187 mA/cm²). The pitting corrosion showed a significant improvement for helium implanted (Epit=230 mV) when compared to virgin material (Epit=92 mV). The oxygen implanted has not shown any improvement (Epit=92 mV). The surface hardness is found to be 1202 HV for helium implanted and 1020 HV for oxygen implanted, while it is found to be 195 HV for the virgin material. The hardness of the helium and oxygen implanted samples is found to be increased by about 600 percent and 500 percent, respectively, when compared to the virgin samples. Helium implanted samples show better performance in terms of corrosion resistance and hardness when compared to those of the oxygen implanted samples.

Although a number of authors have conducted many research on AISI 316L stainless steel, this work has original experimental results in terms of the oxygen and helium ion implantation parameters used and the specific tests: microhardness, electrochemical corrosion test, SEM and XRD that were used. It thus presents useful new results which allows one to draw conclusions as to the suitability of the Helium and Oxygen ion implanted AISI 316L stainless steel for biomedical use.

With the growing pressure to gain optimum level of quality and speed, Lean Six Sigma (LSS) practices have drawn considerable attention as a viable alternative for process improvement. However, previous studies revealed that there is very little systematic and rigorous research to validate the claims. In this regard, this paper aims to empirically examine the effect of LSS practices on quality performance in the medical device manufacturing industry.

For this study, partial least square–based structural equation modeling (PLS-SEM) was used to empirically examine the effect of LSS practices on quality performance in Malaysian medical device manufacturing industry.

The findings of this paper revealed that LSS practices have a significant and positive effect on quality performance in the medical device manufacturing industry.

This paper will serve as a valuable implication for industry practitioners in providing them with a clearer managerial direction to exploit the strength of LSS practices to achieve company’s quality goals. Moreover, this study will serve as a basis for future LSS scholars, providing them with valuable insights and directions for future research.

This paper develops a conceptual LSS framework that captures the integrated nature of two methodologies and provides empirical evidence that supports the positive influence of LSS practices on quality performance; hence, it contributes to the growing body of LSS literature in both theoretical and empirical sense.

This study aims to investigate the effect of Lean Six Sigma elements on the Jordanian Pharmaceutical Manufacturing organizations’ business performance.

Data were collected from 120 managers out of about 300 managers by means of questionnaire. After confirming normality, validity and reliability of the study tool, correlation analysis was carried out, and then multiple regressions were used to test the hypotheses.

The results show that there is an agreement on high implementation of Lean Six Sigma variables among Jordanian Pharmaceutical Manufacturing organizations; there are strong relationships among Lean Six Sigma variables, except between non-utilized talent and transportation; there are strong relationships between Lean Six Sigma variables and business performance. All Lean Six Sigma variables have effect on business performance, except extra processing and waiting time.

This study was carried out on the pharmaceutical industry in Jordan, generalizing results of one industry and/or one country to other industries and/or countries may be questionable. Extending the analyses to other industries and countries represents future research opportunities.

Implementing Lean Six Sigma variables in all Jordanian Pharmaceutical Manufacturing organizations can improve their business performance; also, it can be applied to other manufacturing industry.

The aim of all organizations is to reduce waste, which leads to reserve the natural resources, which is considered as a corporate social responsibility.

Only few studies related to Lean or Six Sigma have been carried out in pharmaceutical industry in Jordan. Therefore, this study might be considered as an initiative study, which studies the effect of both Lean and Six Sigma on pharmaceutical industry in Jordan.

In recent years, the emergence of Industry 4.0 technologies as a way of increasing productivity has attracted the attention of the manufacturing industry. This study aims to investigate the relationship between Industry 4.0 technologies and lean tools (LTs) by measuring how the internalisation of LTs influences the adoption of Industry 4.0 technologies and how the synergy between them helps improve productivity in European manufacturing firms.

Results from 1,298 responses were used to analyse linear regression and study the correlation between the use of LTs and Industry 4.0 technologies.

Results show that the companies analysed tend to implement more Industry 4.0 technologies when their level of lean internalisation is high.

This study provides useful information for managers of manufacturing firms by showing the correlation between LT internalisation and Industry 4.0 technologies, corroborating that optimal implementation of these technologies is preceded by a high level of LT internalisation. Furthermore, although there are studies showing the relationship between LTs and Industry 4.0 technologies, none consider the intensity of their implementation.

The Internet of Things (IoT) is a cloud system that saves energy by being involved in the decision-making process of machines. By this means, machines create an environment of direct interaction without the need for explicit instructions. In this chapter, answers have been sought to the questions of what kind of research has been done on IoT-based technological devices, and how IoT-based technologies are effective in sustainable food production. The systematic literature review examined the scientific research on IoT and Food in the range of 2010–2022 in Scopus. The general framework of the research has been carried out in the context of 6Ws (who, when, where, what, why, and how), which is one of the systematic literature reviews. The results obtained have been analyzed and interpreted in the MAXQDA 2020 qualitative data analysis program. In the findings obtained, it has been determined that IoT and food have gained importance worldwide, especially in England, India, and China. Furthermore, it has been determined that most of the studies on IoT are based on case studies, and all the articles examined are collected in three main focus points. Subcodes have been created under the main codes ‘Food Supply Chain, Smart and Sustainable Agriculture ve Waste Management’, and problem points have been tried to be customized.

Lean management is a suitable methodology for companies that want to improve their productive performance and competitiveness. This study aims to research levels of implementation and internalisation of Lean production tools in Spanish manufacturing companies, and explores differences in behaviour between SMEs and large companies based on data gathered over three time periods. The correlation between Lean adoption and company performance is also analysed.

Company survey data for the years 2012, 2015 and 2018 collected from 354 respondents were used to conduct a longitudinal study on the level of lean tool adoption and internalisation in manufacturing companies.

Over the years, the use of Lean tools has increased, whereas levels of internalisation have remained stable. Lean tool use in SMEs and large companies show significant differences in 2012 and 2015, but this is no longer the case 2018. Results also show that higher Lean tool use helps increase return on sales (ROS), and higher levels of internalisation of tools helps reduce the number of products rejected.

To date, there are no known studies on the use and internalisation of Lean tools or their correlations with business performance indicators in Spanish manufacturing companies.

Firms have been adopting lean manufacturing to improve their business performances. However, they are facing failures or less success in implementation, mainly due to lack of understanding in relating the lean practices (LPs) from the required performance measures perspective. In view of the lack of research and the importance of understanding them, the purpose of this paper is to prioritize LPs.

As LPs are scattered in the literature and a variety of performance measures are used, an extensive literature review is first carried out to identify the LPs and performance measures. The blend of interpretive structural modeling and interpretive ranking process interpretive tools is adopted in establishing the contextual relationship among LPs and then ranking them based on the performance measures. A three-dimensional priority matrix is proposed for better explanation of the results.

The proposed framework can help firms better understand LPs and their levels of importance in lean implementation.

The involvement of lean experts may produce some bias in evaluating the LPs.

The proposed framework can help practitioners to develop an industry-specific road-map for the result-oriented LP implementation. Based on the area of performance to be improved, practitioners can prioritize LPs for implementation.

This is the first study that provides a comprehensive review of LPs available in the literature and prioritizes them in accordance with performance with interpretive tools.