Search results

The study adopts an intersectional approach to identify the key dimension(s) that reproduce inequalities in women's subsistence entrepreneurship within urban-poor settings in the global south.

The in-depth case study is based on 44 semi-structured interviews and four focus-group discussions with women entrepreneurs based within urban-poor dwellings in the twin cities of Islamabad and Rawalpindi in the Islamic Republic of Pakistan.

The authors contribute to the literature by identifying how intersecting socio-class and socioeconomic inequalities, and patriarchal norms of izzat (meaning: honour, respect) and purdah (or veil), perpetuate disadvantage for women entrepreneurs producing and/or selling business goods and services.

The findings challenge the view of entrepreneurship as a meritocratic and neutral activity for social emancipation. The authors argue that multiple social hierarchies and inequalities operate simultaneously, but how these are understood, exercised and reproduce disadvantage for women entrepreneurs, depends on their social class. The authors propose a triple bind of domestic, market and societal inequalities as a heuristic framework for understanding intersecting inequalities, patriarchy and subsistence entrepreneurship in Pakistan, specifically the global south.

The key teaching objectives of the case are the following:▪ to develop an awareness of a megaproject’s external environment (through PESTLE) in terms of challenges from each source;▪ to introduce theory that allows students to identify, characterise and describe factors that can lead to inter-organisational conflict during construction projects;▪ to develop the ability to apply the typology of causal factors (identified in Objective 2) to a given context, answering why each factor may have contributed to the given contractual dispute;▪ to develop an understanding of the procurement and contract management process wherein contracts are not only the logical outcome of the procurement process but also the primary vehicles for clarifying responsibilities (for task completion) and risk transfer; and▪ to understand specific dynamics of construction projects that make disputes inevitable and ways to overcome these.

Priced at US$1.63bn (in 2015), the Orange Line Metro Train (OLMT) project in Lahore was one of Pakistan’s earliest (and costliest!) transport infrastructure megaprojects ever undertaken. Devised to ease congestion in Lahore, promote ecofriendly, efficient, modern and affordable transport systems and lead to improved mobility across Lahore, the OLMT was a socially, politically and economically important project.The case is seen through the eyes of the protagonist, Uzair Shah, a seasoned public servant and an experienced Transport Engineer. At the time of the decision, Shah was General Manager – Operations at the newly established Punjab Metrobus Authority (PMA – the project sponsor) and was also the project lead of OLMT’s Project Management Unit (PMU). Through Shah’s eyes, students approach the project at a juncture when the most serious contractual dispute in the project’s history has erupted. The parties at the interface were Lahore Development Authority (LDA), PMU’s technical interface with contractors and consultants and Maqbool-Colson Joint Venture (MCJV), one of the two civil work contractors hired for OLMT’s civil works.While quality issues had been emerging with MCJV for a few months, LDA had maintained unilateral communications and remained considerably adversarial in their dealings with MCJV. Eventually, in October 2016, this relationship had soured to such an extent that it appeared irreconcilable. It was only then that LDA had recommended Shah to take the contractor to court for non-performance.The decision that Uzair faced was whether to take LDA’s advice and take the contractor to court (terminate the contract, claim performance guarantee and appoint a new contractor) or negotiate and continue with the current contract. The decision had huge financial, legal, reputational, political and schedule-related implications. The decision needed to be taken by the protagonist in the context of all these factors.

The case was initially developed for use within a Procurement and Contracts Management course for a (business) executive audience. The case is intended for the business school audience or students enrolled in courses related to the construction management discipline.Courses where the case can be used include Construction Project Management, Public Sector Projects, Contracts and Procurement and Strategic Projects and Practice (or similar). The case can also be used within an MBA setting.

Teaching notes are available for educators only.

CSS: 9: Operations and Logistics.

Image Processing is an emerging field that is used to extract information from images. In recent years, this field has received immense attention from researchers, especially in the research domains of object detection, Biomedical Imaging and Semantic segmentation. In this study, a bibliometric analysis of publications related to image processing in the Science Expanded Index Extended (SCI-Expanded) has been performed. Several parameters have been analyzed such as annual scientific production, citations per article, most cited documents, top 20 articles, most relevant authors, authors evaluation using y-index, top and most relevant sources (journals) and hot topics.

The Bibliographic data has been extracted from the Web of Science which is well known and the world's top database of bibliographic citations of multidisciplinary areas that covers the various journals of computer science, engineering, medical and social sciences.

The research work in image processing is meager in the past decade, however, from 2014 to 2019, it increases dramatically. Recently, the IEEE Access journal is the most relevant source with an average of 115 publications per year. The USA is most productive and its publications are highly cited while China comes in second place. Image Segmentation, Feature Extraction and Medical Image Processing are hot topics in recent years. The National Natural Science Foundation of China provides 8% of all funds for Image Processing. As Image Processing is now becoming one of the most critical fields, the research productivity has enhanced during the past five years and more work is done while the era of 2005–2013 was the area with the least amount of work in this area.

This research is novel in this regard that no previous research focuses on Bibliometric Analysis in the Image Processing domain, which is one of the hot research areas in computer science and engineering.

Islamic banking as a financial institution has always been proclaimed to be different from conventional banking systems. This is mainly due to the prohibition of interest and emphasis on achieving social economic responsibility in society. However, in practice, Islamic banking practices in the UK seem to be far away from its paradigm version. The main purpose of this study is to evaluate user perceptions of Islamic banking practices in the UK.

To explore the understandings and perceptions of customers about Islamic banking practices in the UK an online questionnaire survey is used as the research approach in this study. The survey was conducted through a closed‐ended structured questionnaire.

The overall findings of this study suggest that Islamic banking in the UK is not fully aligned with the paradigm version of Islamic finance. The respondents generally agree with the view that the principle of profit and loss sharing element represents the true spirit of Islamic banking practices, however, due to the complex nature of Islamic banking products, they are unsure about the full benefits of this system. There is a high expectation among the respondents about the commitment and strong welfare role of Islamic banks in society. It is therefore suggested that through research, effective marketing and generating more awareness in users about Islamic finance, it is possible to achieve more from the Islamic banking paradigm.

This study is not only relevant to Muslims, but also to the banking regulators in the UK, as many conventional banks are now offering Islamic products and services alongside their routine interest‐based transactions. Hence there is a need for the regulators to understand the real nature of such practices by both the Islamic and conventional banks and establish a uniform regulation so that users are not ill‐treated by banks in the UK.

The main issue is whether customers prefer convenience over Shariah compliance or the opposite when they decide their Islamic banking needs. The purpose of this paper is to explore why customers adopt Islamic banking products and services: Shariah compliance or convenience?

Using convenience sampling, 310 respondents’ data were collected through online survey. For testing the fit and hypotheses of the proposed model, AMOS 25 software and Smart-PLS 4.0 software have been used.

Attitude, Islamic value and convenience have significant determinants of Islamic banking products and services. Shariah compliance has no direct or indirect influence on neither intention nor actual behaviour to adopt Islamic banking services. Furthermore, gender has no such differential effect on the adoption.

Managers and marketers of Islamic banks may benefit from the findings of this study, which demonstrate fresh insights regarding the factors which help in strategy formulations to promote Islamic banking services.

The growth of Islamic banks, branches and windows is remarkable in both Muslim-majority and Muslim-minority countries in the world. This paper postulates the behavioural finance studies in Islamic banking and finance research stream by extending the theory of planned behaviour of Ajzen (1985) as all the three new constructs (Islamic value, convenienc and Shariah compliance) are statistically fit for further studies. However, only Islamic value and convenience are the two significant factors which drive customers to take decision in the proposed model. This study gives insights to the bankers and authority about the consumer behaviour.

The paper aims to investigate the feasibility of developing natural dyes from the barks of Araucaria columnaris and leaves of Macaranga peltata, Averrhoa bilimbi. The paper also deals with the application of natural dyes in textile coloration.

Dye extraction was carried out using the aqueous method. The dyeability of the aqueous extract was assessed on cotton, silk and polyester yarns using different mordants (alum, acetic acid, CuSO₄, lemon juice) and without mordant. UV–Visible spectral analysis and pH of different natural dyes were determined. Percent absorption, K/S values, CIELab values and fastness properties of the selected dyed yarns were also assessed.

The percentage values for dye exhaustion differed with various mordants. The K/S values were found to be influenced by the addition of mordants. Different hues were obtained with the usage of different mordants. Fastness results exhibited good to very good grades.

The effective application of aqueous method of dye extraction in the study avoids solvent toxicity. The current results proved that the dyeing could be achieved at room temperature for different yarns (cotton, silk, polyester). At present, no report exists in the literature of research work on the extraction of natural dyes from the leaves of M. peltata, A. bilimbi and their dyeing potential on cotton, silk and polyester.

The present work offers new environment-friendly dye as well as simple dyeing method. Barks and leaves are promising sources of dye. Enormous availability of barks and leaves avoids the exploitation of the plant parts for the extraction of natural dyes.

The important feature of this study was the effective dyeing of natural and synthetic fibers at room temperature. The novel sources of natural dyes would contribute significantly to the existing knowledge of dyeing, and the natural dyes reduce the environmental impact of synthetic dyes.

The purpose of this paper is to provide a shorter time cost, high-accuracy fault diagnosis method for water pumps. Water pumps are widely used in industrial equipment and their fault diagnosis is gaining increasing attention. Considering the time-consuming empirical mode decomposition (EMD) method and the more efficient classification provided by the convolutional neural network (CNN) method, a novel classification method based on incomplete empirical mode decomposition (IEMD) and dual-input dual-channel convolutional neural network (DDCNN) composite data is proposed and applied to the fault diagnosis of water pumps.

This paper proposes a data preprocessing method using IEMD combined with mel-frequency cepstrum coefficient (MFCC) and a neural network model of DDCNN. First, the sound signal is decomposed by IEMD to get numerous intrinsic mode functions (IMFs) and a residual (RES). Several IMFs and one RES are then extracted by MFCC features. Ultimately, the obtained features are split into two channels (IMFs one channel; RES one channel) and input into DDCNN.

The Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection (MIMII dataset) is used to verify the practicability of the method. Experimental results show that decomposition into an IMF is optimal when taking into account the real-time and accuracy of the diagnosis. Compared with EMD, 51.52% of data preprocessing time, 67.25% of network training time and 63.7% of test time are saved and also improve accuracy.

This method can achieve higher accuracy in fault diagnosis with a shorter time cost. Therefore, the fault diagnosis of equipment based on the sound signal in the factory has certain feasibility and research importance.

This method provides a feasible method for mechanical fault diagnosis based on sound signals in industrial applications.

This paper aims to design an adaptive nonlinear strategy capable of timely detection and reconstruction of faults in the attitude’s sensors of an autonomous aerial vehicle with greater accuracy concerning other conventional approaches in the literature.

The proposed scheme integrates a baseline nonlinear controller with an improved radial basis function neural network (IRBFNN) to detect different kinds of anomalies and failures that may occur in the attitude’s sensors of an autonomous aerial vehicle. An integral sliding mode concept is used as auto-tune weight update law in the IRBFNN instead of conventional weight update laws to optimize its learning capability without computational complexities. The simulations results and stability analysis validate the promising contributions of the suggested methodology over the other conventional approaches.

The performance of the proposed control algorithm is compared with the conventional radial basis function neural network (RBFNN), multi-layer perceptron neural network (MLPNN) and high gain observer (HGO) for a quadrotor vehicle suffering from various kinds of faults, e.g. abrupt, incipient and intermittent. From the simulation results obtained, it is found that the proposed algorithm’s performance in faults detection and estimation is relatively better than the rest of the methodologies.

For the improvement in the stability and safety of an autonomous aerial vehicle during flight operations, quick identification and reconstruction of attitude’s sensor faults and failures always play a crucial role. Efficient fault detection and estimation scheme are considered indispensable for an error-free and safe flight mission of an autonomous aerial vehicle.

The proposed scheme introduces RBFNN techniques to detect and estimate the quadrotor attitude’s sensor faults and failures efficiently. An integral sliding mode effect is used as the network’s backpropagation law to automatically modify its learning parameters accordingly, thereby speeding up the learning capabilities as compared to the conventional neural network backpropagation laws. Compared with the other investigated techniques, the proposed strategy achieve remarkable results in the detection and estimation of various faults.