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This paper analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The computed results are more supportable for repairable system performability analysis.

In this paper, the authors have analyzed a complex system consisting n-identical units under a k-out-of-n: G; configuration via a new method which has not been studied by previous researchers. The supplementary variable technique has employed for analyzing the performance of the system.

Reliability measures have been computed for different types of configuration. It generalized the results for purely series and purely parallel configurations.

This research may be beneficial for industrial system performances whereas a k-out-of-n-type configuration exists.

Not sure as it is a theoretical assessment.

This research may not have social implications.

This work is the sole work of authors that have not been communicated to any other journal before.

The purpose of this study is to develop a cost-effective autonomous wheelchair robot navigation method that assists the aging population.

Navigation in outdoor environments is still a challenging task for an autonomous mobile robot because of the highly unstructured and different characteristics of outdoor environments. This study examines a complete vision guided real-time approach for robot navigation in urban roads based on drivable road area detection by using deep learning. During navigation, the camera takes a snapshot of the road, and the captured image is then converted into an illuminant invariant image. Subsequently, a deep belief neural network considers this image as an input. It extracts additional discriminative abstract features by using general purpose learning procedure for detection. During obstacle avoidance, the robot measures the distance from the obstacle position by using estimated parameters of the calibrated camera, and it performs navigation by avoiding obstacles.

The developed method is implemented on a wheelchair robot, and it is verified by navigating the wheelchair robot on different types of urban curve roads. Navigation in real environments indicates that the wheelchair robot can move safely from one place to another. The navigation performance of the developed method and a comparison with laser range finder (LRF)-based methods were demonstrated through experiments.

This study develops a cost-effective navigation method by using a single camera. Additionally, it utilizes the advantages of deep learning techniques for robust classification of the drivable road area. It performs better in terms of navigation when compared to LRF-based methods in LRF-denied environments.

This chapter investigated tendering in stealth construction, emphasising innovative approaches and methodologies that prioritise environmental protection, safety, efficiency, and aesthetics. It began with an overview of the construction industry’s tendering processes, followed by an in-depth examination of various tendering types, including competitive and negotiated methods. The study highlighted contemporary trends such as electronic tendering, Building Information Modelling (BIM), green and sustainable procurement, risk management, data analytics, artificial intelligence, lean construction practices, and blockchain technology. Moreover, with a specific focus on stealth construction, the chapter further analysed certain criteria, including building cross-section development, visibility, radio frequency emission, and countermeasures. It explored integrating functional construction systems, including environmental, safety, health, and quality management. Additionally, it discussed methods like green building, modular construction, and low-impact techniques. Lastly, the chapter emphasised the strategies to achieve environmental protection, safety, speed, economy, and aesthetics in tendering for stealth construction.

Wheelchair robot navigation in different weather conditions using single camera is still a challenging task. The purpose of this study is to develop an autonomous wheelchair robot navigation method in different weather conditions, with single camera vision to assist physically disabled people.

A road detection method, called dimensionality reduction deep belief neural network (DRDBNN), is proposed for drivable road detection. Due to the dimensionality reduction ability of the DRDBNN, it detects the drivable road area in a short time for controlling the robot in real-time. A feed-forward neural network is used to control the robot for the boundary following navigation using evolved neural controller (ENC). The robot detects road junction area and navigates throughout the road, except in road junction, using calibrated camera and ENC. In road junction, it takes turning decision using Google Maps data, thus reaching the final destination.

The developed method is tested on a wheelchair robot in real environments. Navigation in real environments indicates that the wheelchair robot moves safely from source to destination by following road boundary. The navigation performance in different weather conditions of the developed method has been demonstrated by the experiments.

The wheelchair robot can navigate in different weather conditions. The detection process is faster than that of the previous DBNN method. The proposed ENC uses only distance information from the detected road area and controls the robot for boundary following navigation. In addition, it uses Google Maps data for taking turning decision and navigation in road junctions.

Banks play a vital role in the economy. Investigating their competitive environment is crucial to ensuring economic stability and development. The FinTech disruption has risks and opportunities for incumbent banks, and it can be valuable to investigate its effects on banking performance. Therefore, the aim of this study is to assess whether investment in FinTech is associated with better performance of Indian banks during 2012–2018.

To do this, a sample of Indian banks was investigated between 2012 and 2018 using k-means and hierarchical cluster analysis, ANOVA, and pairwise comparison tests.

Results of the analysis strongly suggest that investment in FinTech is associated with better banking performance. Higher FinTech investments, represented by mobile transaction volume, are associated with higher efficiency scores and accounting-based performance. In particular, banks that invest in FinTech and have relatively low non-performing loans have a 7.7% higher Return on Employment (ROE) than banks with exceptionally low FinTech use and no significant investment in smart branches.

Therefore, it can be recommended that Indian banks adopt a forward-looking strategic approach when making investment decisions regarding new technologies. Failing to adapt to the FinTech disruption may result in poor value creation prospects in the long run.

To the best of the authors' knowledge, this is the first study that analyses. We are not aware of any similar study on whether investment in FinTech is associated with better performance of the Indian banks during 2012–2018.

This chapter investigates the effect of customer orientation and CRM organization on hotel financial performance. A model of enhancing hotel financial performance through customer satisfaction practices was tested. Customer satisfaction was hypothesized to be a mediator in the relationships between customer orientation and CRM organization and the result being financial performance. The sample consisted of 54 hotels that was made up of three 5-star, fifteen 4-star, and thirty-six 3-star hotels in Ghana. A quantitative deductive approach was employed to gather data using cross-sectional survey, which was analyzed using PLS-SEM to check the validity, reliability and factor loading of the data. The findings revealed that, CRM organization enhances customer satisfaction and financial performance of hotels. Also, customer orientation showed significant positively related to customer satisfaction in the hotels. Surprisingly, the effects of CRM organization and customer orientation on financial performance through customer satisfaction were insignificant. Thus, customer satisfaction failed to mediate the effect of CRM organization and customer orientation on the financial performance of hotels. This suggests that though an effective CRM organization enhances customer satisfaction, it directly affects the financial performance of hotels. The outcomes have useful implications for CRM implementation on hotel financial performance in Ghana.

The corrosion behaviour of iron in M HNO3 containing furfural hydrazone derivatives was studied by electro‐chemical, polarographic and scanning electron microscopy measurements. Polarization data indicates that all inhibitors tested were of a mixed type, affecting both the cathodic and anodic processes. The inhibition efficiency of the additives increases in the order I<II<III<IV<V. It was found that the compounds under consideration are adsorbed on the iron surface. The degree of surface coverage is influenced by the presence of functional groups and interaction between adsorbed molecules. Within the given homologous series the contribution of the functional group to adsorption increases with the length of the chain.

This study examines whether investors take into consideration the balance sheet numbers when determining the market value of companies. Specifically, an investigation is made of the association between the book value of equity and the value placed on the firm by the stock market. An equity valuation model first mentioned by Landsman (1986), based on the balance sheet identity, is used to permit assets and liabilities to have separate empirical coefficient values. In scope, the study covers Malaysian main board companies from years 1990 to 1997. Evidence is provided which is consistent with the notion that the market incorporates information on accounting numbers in the valuation of a firm. As a general conclusion, the results indicate that investors do use information in the balance sheet.

Although there have been extensive studies on the hydrological and erosional impacts of logging, relatively little is known about the impacts of conversion into agricultural plantation (namely rubber and oil palm). Furthermore, studies on morphological impacts, sediment-bound chemistry and forensic attribution of deposited sediment to their respective sources are scarcer. This chapter introduces the potential for using the multi-proxy sediment fingerprinting technique in this context. Featuring pilot projects in two major flood-prone river systems in Malaysia, the studies explore application of geochemistry-based sediment source ascription. The geochemical signatures of sediment mixtures on floodplains were compared to sediments from upstream source tributaries. The tributaries were hypothesised to have different geochemical signatures in response to dominant land management. The first case study took place in the Segama River system (4,023 km²) of Sabah, Malaysian Borneo where a mixture of primary forest, logged-forests and oil palm plantations were predominant. The second case study was in the Kelantan River Basin (13,100 km²) with two major tributaries (Galas River and Lebir River) where logged-forests and rubber and oil palm plantations are dominant land-uses. Both case studies demonstrated the applicability of this method in ascribing floodplain deposited sediment to their respective upstream sources. Preliminary results showed that trace elements associated with fertilisers (e.g. copper and vanadium) contribute to agricultural catchment signatures. Alkaline and alkaline-earth elements were linked to recently established oil palm plantations due to soil turnover. Mixing model outputs showed that contributions from smaller, more severely disturbed catchment are higher than those from larger but milder disturbed catchments. This method capitalises on flood events to counter its adverse impacts by identifying high-priority sediment source areas for efficient and effective management.

This chapter presents the outcome of an empirical study titled ‘Knowledge Sharing and Transfer (KST) that Really Works: An exploration of KST in Sub-Saharan South African Public Sector Institutions’. Enablers of KST were explored through the lens of lived experiences of managers working at Gautrain Management Agency (GMA), a rail transport public sector operator in South Africa. Qualitative data were collected from 15 managers and analysed using Thematic and Trans Positional Cognition Approach (TPCA) qualitative analytical tools. Four themes, essential originating antecedent factors, complementary people enabling factors, organisational enabling factors and effective KST implementing factors emerged. Rahman’s KST model was adopted as a theoretical framework and used to better understand the study findings. The current study affirms two elements within the theoretical framework, namely, complementary people enabling factors and organisational enabling factors, while the remaining two, essential originating antecedent factors and effective KST implementing factors, were not affirmed. This study contributes a new KST framework that helps business managers understand KST from the South African public sector practitioners’ perspectives, which represents this study’s contribution to the business performance measurement body of knowledge and practice.