This study aims to explore a demoethical model for sustainable development in modern society. It proposes an approach that focuses on organizing activities to improve sustainable development. Specifically, it presents a demoethical model relevant to Society 5.0 and Industry 5.0 organizations. The objective is to identify demoethical values that can drive sustainable development in the era of digitalization. Through a literature review and analysis, this study identifies key components of the demoethical model and provides practical recommendations for stakeholders involved in (...) digital transformation. The analysis of demoethical norms and phenomena, such as education, nurturing, mind, knowledge, science, and honest work, has enabled the identification of values that align with sustainable development in society. The results of the study demonstrate that the notion of a demoethical foundation for sustainability is rooted in the concept of spirituality as the basis for a new societal development scenario and its relationship with nature. The study shows that ideas about the demoethical basis of sustainability are based on the priority of spirituality as the basis of a new scenario for the development of society, as well as the integration of demographic, socio-economical, and ecological components in system-wide modeling. (shrink)

This study aims to examine how the relationship between intellectual capital and bank profitability changed during COVID-19. Based on the data of 34 Chinese banks and 39 Pakistani banks, this study uses ordinary least squares to examine this relationship during the COVID-19 era. Profitability is measured by return on assets and return on equity, and IC is measured by the value added intellectual coefficient model. The findings show that, even during the COVID-19 pandemic, IC has managed to sustain its positive (...) influence on bank profitability in China and Pakistan. Among IC components, our study reports that human capital is the only IC resource that continues to enhance ROA and ROE of Chinese and Pakistani banks during the pandemic period. Our study suggests that policymakers should pay more attention to IC resources, which has the potential to improve banks’ profitability even during crisis times. (shrink)

Since their introduction in the early 2000s, the use of social networking websites has exploded. Many businesses are seeing increased revenue due to their social commerce strategy. Despite the popularity of social commerce websites, some consumers are still hesitate to use them. This study aims to evaluate the factors that influence the adoption of social commerce. A sample of 721 Chinese We Chat users took part in the research. The findings reveal that social capital mediates the positive effect of social (...) commerce adoption and perceived ease of use on techno-stress and online impulse purchasing. Likewise, information overloading mediates the positive effect of social commerce adoption and PERU on techno-stress and online impulse purchasing. The findings have implications for both practice and research in understanding social commerce adoption in emerging economies. (shrink)

This article has explored the impact of coronavirus disease 2019 -induced decline in consumer durables and mobility on nitrogen dioxide emission in Europe by providing empirical and graphical justifications based on consumer price index and gross domestic product deflator indexes. The empirical estimations show that carbon dioxide and NOx emission along with other greenhouse gases drastically decreased in the wake of COVID-19-induced lockdowns and decrease in the demand of consumer goods in Europe. This means that COVID-19 improved environment in the (...) European region. However, high cost makes COVID-19 an unstable solution to environmental woes where positive impact of COVID-19 on environment achieved in short run cannot be guaranteed in the long run. Besides environment, COVID-19 drastically curtailed economic activities and exposed them to the risk of economic crisis particularly in case of Europe. (shrink)

Nowadays, online product reviews have been at the heart of the product assessment process for a company and its customers. They give feedback to a company on improving product quality, planning, and monitoring its business schemes in order to increase sale and gain more profit. They are also helpful for customers to select the right products in less effort and time. Most companies make spam reviews of products in order to increase the products sales and gain more profit. Detecting spam (...) product reviews is a challenging issue in NLP. Numerous machine learning approaches have attempted to detect and classify the product reviews as spam or nonspam. However, in order to improve the classification accuracy, this study has introduced an ensemble machine learning model that combines predictions from multilayer perceptron, K-Nearest Neighbour, and Random Forest and predicts the outcome of the review as spam or real, based on the majority vote of the contributing models. In order to accomplish the task of spam review classification, the proposed ensemble and other benchmark boosting approaches are tested with 25 statistical features extracted from mobile application reviews of Yelp Dataset. Then, three different selection techniques are exploited to diminish the feature space and filter out the top 10 optimal features. The effectiveness of the proposed ensemble, the individual models, and other benchmark boosting approaches is again evaluated with 10 optimal features in terms of classification accuracy. Experimental outcomes illustrate that the proposed ensemble model outperformed the individual classifiers and state-of-the-art boosting approaches like Generalized Boost Regression Model, Extreme Gradient Boost, and AdaBoost Regression Model in terms of classification accuracy. (shrink)

_One of the enduring queries in the development of human intellectual thought is, "What is human nature?" What does it mean to be a human tends to be defined by all disciplines, including religion? We all need theories about what makes people tick in order to predict how they will respond to their environment in various situations. Indeed, how we view human nature affects a number of things. People utilize it in their private lives to govern their daily routines, manage (...) their relationships, raise their children, and influence others. Additionally, our policies in areas of collective social life like politics, law, and education are influenced by how we view human nature. Steven Pinker critically explains the modern view of human nature and its theoretical presuppositions in his widely read book The Blank Slate: The Modern Denial of Human Nature. Pinker contends that this contemporary account of human nature faces significant challenges in light of recent developments in the fields of biology, genetics, evolution, and the brain sciences. Because it is built on axioms that we cannot accept in light of the advancements in science over the past few decades, the current theory of human nature is conceptually unsound. This research performs a comparative analysis between Pinker’s View of Human Nature and Dupré’s Critique of Evolutionary Psychology on the principles which serve as the foundation for the influential idea of human nature, and contributes significantly in our contemporary intellectual life._. (shrink)

The number of scientific publications is growing exponentially. Research articles cite other work for various reasons and, therefore, have been studied extensively to associate documents. It is argued that not all references carry the same level of importance. It is essential to understand the reason for citation, called citation intent or function. Text information can contribute well if new natural language processing techniques are applied to capture the context of text data. In this paper, we have used contextualized word embedding (...) to find the numerical representation of text features. We further investigated the performance of various machine-learning techniques on the numerical representation of text. The performance of each of the classifiers was evaluated on two state-of-the-art datasets containing the text features. In the case of the unbalanced dataset, we observed that the linear Support Vector Machine achieved 86% accuracy for the “background” class, where the training was extensive. For the rest of the classes, including “motivation,” “extension,” and “future,” the machine was trained on less than 100 records; therefore, the accuracy was only 57 to 64%. In the case of a balanced dataset, each of the classes has the same accuracy as trained on the same size of training data. Overall, SVM performed best on both of the datasets, followed by the stochastic gradient descent classifier; therefore, SVM can produce good results as text classification on top of contextual word embedding. (shrink)

The possibility of accomplishing sustainable objectives is largely connected to the management and flourishing of an organizational system which keeps human capital engaged and committed. Our study investigated the association of inspirational leadership and innovative communication with employee engagement and commitment under the lens of leader member exchange theory. Specifically, we emphasized the mediating role of mutual trust in connection to social sustainability facets. A survey of data from employees in the manufacturing sector of Yunnan, China was utilized to test (...) the hypothesized model. The study findings reported a significant association and came to the conclusion that a leader’s inspirational behavior coupled with innovative communication is a significant predictor of engagement and commitment in socially sustainable organizations. Moreover, mutual trust significantly mediated the relationship of innovative communication and inspirational leadership with employee engagement and commitment reaching the social perspective of sustainability. The current study added to the literature of sustainable organization by pointing out the social dimensions of sustainability. (shrink)

Unmanned aerial vehicles, particularly quadcopters, have several medical, agriculture, surveillance, and security applications. However, the use of this innovative technology for civilian applications is still very limited in low-income countries due to the high cost, whereas low-cost controllers available in the market are often tuned using the hit and trial approach and are limited for specific applications. This paper addresses this issue and presents a novel proof of concept low-cost quadcopter UAV design approach using a systematic Model-Based Design method for (...) mathematical modeling, simulation, real-time testing, and prototyping. The quadcopter dynamic model is developed, and controllers are designed using Proportional Integral, and Derivative, Pole Placement, and Linear Quadratic Regulator control strategies. The stability of the controllers is also checked using Lyapunov stability analysis. For verification and validation of the design, Software-in-the-Loop, Processor-in-the-Loop, Hardware-in-the-loop testing, and Rapid Control Prototyping have been performed. The V&V methods of the MBD approach showed practically valid results with a stable flight of the quadcopter prototype. The proposed low-cost POC quadcopter design approach can be easily modified to have enhanced features, and quadcopters with different design parameters can be assembled using this approach for a diverse range of applications. (shrink)

Caricatures can help to understand the perception of a face. The prominent facial feature of a subject can be exaggerated, so the subject can be easily identified by humans. Recently, significant progress has been made to face detection and recognition from images. However, the matching of caricature with photographs is a difficult task. This is due to exaggerated features, representation of modalities, and different styles adopted by artists. This study proposed a cross-domain qualitative feature-based approach to match caricature with a (...) mugshot. The proposed approach uses Haar-like features for the detection of the face and other facial attributes. A point distribution measure is used to locate the exaggerated features. Furthermore, the ratio between different facial features was computed using different vertical and horizontal distances. These ratios were used to calculate the difference vector which is used as input to different machine and deep learning models. In order to attain better performance, stratified k-fold cross-validation with hyperparameter tuning is used. Convolution neural network-based implementation outperformed the machine learning-based models. (shrink)

Workplace productivity is badly affected by many negative factors such as narcissism, and sadism. In addition, paranoia and antagonism play an important role in increasing workplace incivility. Through emotional intelligence, such negative behaviors could be addressed by managers and their junior colleagues. The current study aims to investigate the parallel mediating role of paranoia, antagonism, and emotional intelligence on the relationship between narcissism, sadism, and workplace incivility. A survey approach was used. Primary data was collected in PLS-SEM. The population of (...) the study was all faculty members in higher education institutions in the Khyber Pakhtunkhwa region. A measurement model and structural model were developed. The measurement model demonstrated that convergent and discriminant validities were established. The structural model's findings revealed that narcissism, antagonism, and emotional intelligence were not mediated between narcissism and workplace incivility. Similarly, emotional intelligence did not play any mediating role between sadism and workplace incivility. This implied that emotional intelligence has no role in decreasing or reducing workplace uncivil behavior. (shrink)

The COVID-19 pandemic is an unprecedented time in history. Surrounding this pandemic are many enormous uncertainties across the globe. Severe consequences have assessed for the incomes of almost 84% of employers and 68% of self-employed who are working and living in countries that are or have went through a phase of closing workplaces. Similarly, the global rate of unemployment is also expected to be increased in the coming years as 54% of employers worldwide are running their businesses in the hardest-hit (...) sectors. All of these clearly show the uneven impact of the Coronavirus crisis which will remarkably compound already present inequalities, difficulties, and vulnerabilities. The economic ramifications for 186 countries under the crunch of the COVID-19 pandemic is also considered tremendous for Pakistan. The core aim of this research was to test a new conceptual framework depicting the ramifications of restructuring processes carried out by management for their organizations amidst the COVID-19 pandemic on an Institute’s reputation as an employer brand. It also investigates the impact of perceived restructuring on a corporate brand promise made by the university or institute from the viewpoints of other key stakeholders and potential job seekers. The current study had proposed four hypotheses and according to the results of Structural Equation Modeling, the direct hypothesis based upon the relationship between restructuring and employer branding has been rejected. This study shows that restructuring and employer branding has a negative and insignificant effect on each other. The second direct hypothesis of the study that measures the effect of restructuring on corporate branding has been accepted. A corporate brand is a kind of a hub and it considers how an institute treats and deals with all of its stakeholders. It is different from employer brand as the perceptions of employees were the main focus. So, according to the results restructuring did not cause massive damage to the overall outlook of the institute. Furthermore, for the purpose of mediation analysis, the maximum likelihood method by bootstrapping was adopted to test the indirect hypotheses of the study. Crowdsourcing was introduced as a mediator in this study with restructuring, employer, and corporate brand all together in one framework, which is the novel aspect of this study. There are two indirect hypotheses and according to the results both of them did not show any insignificant results. Firstly, the study analyzed mediation among crowdsourcing, restructuring, and employer branding which was fully accepted as the results showed full mediation between these constructs. Secondly, the study analyzed mediation among crowdsourcing, restructuring, and corporate branding which was partially accepted as results showed partial mediation between these constructs. (shrink)

Seasonal outbreaks have several different periods that occur primarily during winter in temperate regions, while influenza may occur throughout the year in tropical regions, triggering outbreaks more irregularly. Similarly, dengue occurs in the star of the rainy season in early May and reaches its peak in late June. Dengue and flu brought an impact on various countries in the years 2017–2019 and streaming Twitter data reveals the status of dengue and flu outbreaks in the most affected regions. This research work (...) presents that Social Media Analysis can be used as a detector of the epidemic outbreak and to understand the sentiment of social media users regarding various diseases. Providing awareness about seasonal outbreaks through SMA is an effective approach for researchers and healthcare responders to detect the early outbreaks. The proposed model aims to find the sentiment about the disease in tweets, and the seasonal outbreaks-related tweets are classified into two classes as disease positive and disease negative. This work proposes a machine-learning-based approach to detect dengue and flu outbreaks in social media platform Twitter, using four machine learning algorithms: Random Forest, K-Nearest Neighbor, Support Vector Machine, and Decision Tree, with the help of Term Frequency and Inverse Document Frequency. For experimental analysis, two datasets are analyzed individually. The experimental results show that the RF classifier has outperformed the comparison models in terms of improved accuracy, precision, recall, F1-measure, and Receiver Operating Characteristic curve. The proposed work offers favorable performance with total precision, accuracy, recall, and F1-measure ranging from 84% to 88% for conventional machine learning techniques. (shrink)

With the development of wireless technology, two basic wireless network models that are commonly used, known as infrastructure and wireless ad hoc networks, have been developed. In the literature, it has been observed that channel contention is one of the main reasons for packet drop in WANETs. To handle this problem, this paper presents a routing protocol named CCBR. CCBR tries to determine a least contended path between the endpoints to increase packet delivery ratio and to reduce packet delay and (...) normalized routing overhead. Moreover, throughout the active data section, each intermediate node computes its channel contention value. If an intermediate node detects an increase in channel contention, it notifies the source node. Then the source node determines another least contended route for transmission. The advantages of CCBR are verified in our NS2-based performance study, and the results show that CCBR outperforms ad hoc on-demand distance vector in terms of packet delivery ratio, end-to-end delay, and routing overhead by 4% to 9%. (shrink)

Crop cultivation is one of the oldest activities of civilization. For a long time, crop production was carried out based on knowledge passed from generation to generation. However, due to the rapid growth in the human population of the world, human knowledge-based cultivation is not enough to meet the demanding need. To address this issue, the usage of machine learning-based tools has been studied in this paper. An experiment has been carried out over 0.3 million data. This dataset identifies 46 (...) prominent parameters for cultivation, which is collected from the Department of Agriculture Extension, Bangladesh. Comparison between neural networks and numbers of machine learning algorithms has been carried out in this research. It is observed that the neural network outperforms the other methods by maintaining an average prediction accuracy of 96.06% for six different crops. Other contemporary machine learning algorithms, namely, support vector machine, random forest, and logistic regression, have average prediction accuracy of around 68.9%, 91.2%, and 62.39%, respectively. (shrink)

Online forums have become the main source of knowledge over the Internet as data are constantly flooded into them. In most cases, a question in a web forum receives several responses, making it impossible for the question poster to obtain the most suitable answer. Thus, an important problem is how to automatically extract the most appropriate and high-quality answers in a thread. Prior studies have used different combinations of both lexical and nonlexical features to retrieve the most relevant answers from (...) discussion forums, and hence, there is no standard/general set of features that could be effectively used for relevant answer/reply post classification. However, this study proposed an answer detection model that is exclusively relying on lexical features and employs a random forest classifier for classification of answers in discussion boards. Experimental results showed that the proposed answer detection model outperformed the baseline technique and other state-of-the-art machine learning algorithms in terms of classification accuracy on benchmark forum datasets. (shrink)

The fourth industrial revolution will be ushered in by future high technology, and as a result, the world will face new difficulties relating to people, the environment, and profitability. Accordingly, the competitive edge and long-term viability of businesses would depend on the knowledge workers who could overcome these excruciatingly difficult obstacles and have the knowledge and competency to influence the overall performance of any type of company. But managing knowledge workers falls under the purview of human resources, and only effective (...) human resources tools, plans, and procedures can ensure the success of this task. One such tool, which has the capacity and capability to change the whole scenario in an organization's favor, is the human resource information system. The purpose of this structured review is to provide insight into a field of HRM that has largely been neglected by other reviews of the literature and has only been briefly discussed by a small number of publications published in reputable, top-tier journals. A customized HRIS framework is the result of this structured literature review for managing knowledge and competence. The study presents the content analysis of 48 articles, systematically and purposefully selected for this literature review, published during the past three decades. The study has several implications for policymakers and HR practitioners. (shrink)

With the advancement of scientific collaboration in the 20th century, researchers started collaborating in many research areas. Researchers and scientists no longer remain solitary individuals; instead, they collaborate to advance fundamental understandings of research topics. Various bibliometric methods are used to quantify the scientific collaboration among researchers and scientific communities. Among these different bibliometric methods, the co-authorship method is one of the most verifiable methods to quantify or analyze scientific collaboration. In this research, the initial study has been conducted to (...) analyze interdisciplinary research activities in the computer science domain. The ACM has classified the computer science fields. We selected the Journal of Universal Computer Science for experimentation purposes. The J.UCS is the first Journal of Computer Science that addresses a complete ACM topic. Using J.UCS data, the co-authorship network of the researcher up to the 2nd level was developed. Then the co-authorship network was analyzed to find interdisciplinary among scientific communities. Additionally, the results are also visualized to comprehend the interdisciplinary among the ACM categories. A whole working web-based system has been developed, and a forced directed graph technique has been implemented to understand IDR trends in ACM categories. Finally, the IDR values between the categories are computed to quantify the collaboration trends among the ACM categories. It was found that “Artificial Intelligence” and “Information Storage and Retrieval”, “Natural Language Processing and Information Storage and Retrieval”, and “Human-Computer Interface” and “Database Applications” were found the most overlapping areas by acquiring an IDR score of 0.879, 0.711, and 0.663, respectively. (shrink)

Web search engines usually keep users’ profiles for multiple purposes, such as result ranking and relevancy, market research, and targeted advertisements. However, user web search history may contain sensitive and private information about the user, such as health condition, personal interests, and affiliations that may infringe users’ privacy since a user’s identity may be exposed and misused by third parties. Numerous techniques are available to address privacy infringement, including Private Information Retrieval protocols that use peer nodes to preserve privacy. Previously, (...) we have proved that PIR protocols are vulnerable to the QuPiD Attack. In this research, we proposed NN-QuPiD Attack, an improved version of QuPiD Attack that uses an Artificial Neural Network based model to associate queries with their original users. The results show that the NN-QuPiD Attack gave 0.512 Recall with the Precision of 0.923, whereas simple QuPiD Attack gave 0.49 Recall with the Precision of 0.934 with the same data. (shrink)

Landslide is a critical natural geological hazard that causes severe damage to property, infrastructure, and humans. In general, some location-specific factors trigger a landslide. Wireless sensor network is an enabling technology to monitor most of the parameters associated with these factors. A challenge in landslide monitoring through WSN is that each sensed data item might be critical whereas the underlying wireless communication is often unreliable. In case of landslides, the terrains have irregular shapes, providing harsh conditions for wireless communication thereby (...) more data loss may be expected. This study focuses on the effect of lossy communication in WSN on the efficiency and accuracy of landslide monitoring systems. To this end, collaborative local data analysis is used to enable each node to decide locally whether its sensed data corresponds to a potential event-of-interest. Through extensive simulations, the performance of various landslide prediction and detection models has been evaluated. By and large, the study lets a significant insight into landslide monitoring before implementing a parameterized application for real-world deployment. (shrink)

Research suggests that ethical leadership influences employees’ behavior and organizational functioning. Thus, the purpose of this study is to investigate the role of ethical leadership in the improvement of employees’ innovative performance. Specifically, this research developed and tested a framework about the intermediating mechanism of social capital in the relationship between ethical leadership and employees’ innovative performance. The current study integrated assumptions of social learning and social exchange theories, which postulate that the leadership has a direct effect on the employees’ (...) conduct, principally through role modeling and the reciprocal landscape. Data were collected through in-person administered questionnaire-based survey from 297 employees working in the manufacturing sectors of Pakistan. The conceptual model of our research was analyzed applying Structural Equation Modeling (SEM). The results exhibited that the ethical leadership plays an important role in fostering employees’ innovative performance. The present study also found that social capital plays an intermediating role between the ethical leadership and employees’ innovative performance relationship. The current study contributed to the leadership and innovation literature and provided insights in examining the ethical leadership-employees’ innovative performance relationship through the intermediating mechanism of social capital. (shrink)

The idea of the subject as a construct, of various external influences, was not new to the cultural and literary circles in the 1980s when DeLillo published White Noise. In the second half of the twentieth century, post-structuralist and postmodern theories unsettled the established ideas of the humanist tradition like the concept of the subject. The idea that the subject is constituted by external factors posed a challenge to the modernist notion of the subject as authentic and independent consciousness. Influenced (...) by post-structuralist and postmodern theories, novelists in post-war America, especially during and after the 1980s, portrayed their protagonists (the subjects) as textual constructs rather than authentic heroic figures we often find in modernists’ works of art. DeLillo engages with technological developments and sociocultural changes in post-war America and explores how such developments/changes influence an individual’s subjectivity. Critics have described Jack Gladney, the protagonist of White Noise, as a late-modernist displaced to negotiate the postmodern landscape. This study, which is purely of scholarly interest, attempts to show how Gladney vacillates between the notions of modernist authentic subject and the de-centred postmodern subject created textually. This article also attempts to explore how DeLillo’s fiction engages with the idea of the subject during the 1980s. (shrink)

We examined the direct and indirect (via relational social capital) relationship between ethical leadership and knowledge hiding. We also tested the moderating role of instrumental thinking in the relationship between ethical leadership and knowledge hiding and the relationship between ethical leadership and relational social capital. Data were collected from 245 employees in different firms spanning different manufacturing and service sectors. The results showed that ethical leadership was negatively related to knowledge hiding, both directly and via relational social capital. The results (...) revealed that instrumental thinking moderated the positive relationship between ethical leadership and relational social capital, such that the relationship was weak when instrumental thinking was high. The results also showed that instrumental thinking moderated both direct and indirect relationships between ethical leadership and knowledge hiding, such that the relationships were weak when instrumental thinking was high. The study carries important practical implications for managers concerned about the destructive consequences of knowledge hiding. (shrink)

ABSTRACT This article proposes a theoretical framework for thinking systematically about Muslim males’ involvement in criminality, derived from the philosophy of critical realism. This theoretical framework is deployed to explore primary data from life story interviews with 17 Muslim male offenders in a way that explains the role of structural and cultural factors, as well as individual agency, in participants’ involvement in crime at a range of ‘emergent’ ontological levels. As well as factors in common with offending by young males (...) generally, such as absent role models at home, experiences of socio-economic marginalization, the presence of hypermasculine hegemonic masculinities on the street and an inadequate experience of school, ‘unserious’ religion and ‘religious’ justifications for involvement in crime are factored into the ontology of the male Muslim offender as rendering some young Muslim males particularly vulnerable to offending. (shrink)

Mankind is faced with a number of serious problems that demand an effective solution. The prevalence of injustice and the frequency of financial crises are two of the most serious of these problems. Consisting of an in-depth introduction along with a selection of eight of Muhammad Umer Chapra's essays--four on Islamic economics and four on Islamic finance--this timely book raises the question of what can be done to not only minimize the frequency and severity of the financial crises, but (...) also make the financial system more equitable. The author considers the origins of Islamic economics and outlines its development and underlying principles. He compares the approach taken to ethics and economics in Islam with that taken in the West, considering whether lessons can be applied to the global financial architecture in order to mitigate against financial crises. The book also examines the case against interest and looks at both innovation in Islamic finance, as well as challenges facing the industry. Written by a leading authority in the field, this book will be a stimulating resource for students and researchers in Islamic economics and finance, as well as providing valuable insight to all of those with an interest in financial systems and their interaction with society. (shrink)

Data analytics, machine intelligence, and other cognitive algorithms have been employed in predicting various types of diseases in health care. The revolution of artificial neural networks in the medical discipline emerged for data-driven applications, particularly in the healthcare domain. It ranges from diagnosis of various diseases, medical image processing, decision support system, and disease prediction. The intention of conducting the research is to ascertain the impact of parameters on diabetes data to predict whether a particular patient has a disease or (...) not. This paper develops an improved ANN model trained using an artificial backpropagation scaled conjugate gradient neural network algorithm to predict diabetes effectively. For validating the performance of the proposed model, we conduct a large set of experiments on a Pima Indian Diabetes dataset using accuracy and mean squared error as evaluation metrics. We use different number of neurons in the hidden layer, ranging from 5 to 50, to train the ANN models. The experimental results show that the ABP-SCGNN model, containing 20 neurons, attains 93% accuracy on the validation set, which is higher than using the other ANNs models. This result confirms the model’s effectiveness and efficiency in predicting diabetes disease from the required data attributes. (shrink)

In this research article, we presented the idea of intuitionistic fuzzy incidence graphs along with their certain properties. The number of operations including Cartesian product, composition, tensor product, and normal product in an IFIGs are also investigated. The method to compute the degree of IFIGs obtained by CP, composition, tensor product, and the normal product is discussed. Some important theorems to calculate the degree of the vertices of IFIGs acquired by CP, composition, tensor product, and normal product are elaborated. An (...) application of CP and composition of two IFIGs in the textile industry to find the best combinations of departments expressing the highest percentage of progress and the lowest percentage of nonprogress is provided. A comparative analysis of our study with the existing study is discussed. Our study will be beneficial to comprehend and understand the further characteristics of IFIGs in detail. Another advantage of our study is that it will be helpful to find the maximum percentage of progress and minimum percentage of nonprogress in different departments of universities, garment factories, and hospitals. (shrink)

This work situates the Qur’anic story of Moses’ meeting with Khiḍr in an ever-expanding network of intercultural and interreligious ideas about knowledge, humility, and spiritual excellence, where Moses and Khiḍr are seen as representing the ẓāhir and the bāṭin, respectively.

This study investigates the significance of understanding police perspectives on community policing as a means of addressing insecurity, particularly within the context of localised and asymmetrical conflicts. It highlights the pivotal role of the police in shaping community security and the substantial impact they can have (positive or negative) in fragile environments. The study contends that the localised nature of the community policing effectively addresses security and development issues and empowering citizens. Qualitative interviews were conducted with senior police in Islamabad, (...) to assess the implementation and potential impacts of community policing in Pakistan’s Federal Capital Territory. The findings reveal how the historical foundations of police structures and operations – which date back to the colonial period – have led to the promotion of fear, mistrust and manipulation under successive regimes. Despite these challenges, the findings are promising highlighting enhanced human security through context-specific community policing. Finally, the paper argues that the movement towards community-oriented policing marks a departure from the control of elites within state systems, and encourages values such as local ownership, social cohesion, mutual engagement, accountability and agency. These developments have profound implications for global security and justice. (shrink)

The dominant debate on Islam and democracy continues to operate in the realm of normativity. This article engages with key literature showing limits of such a line of inquiry. Through the case study of India’s Islamist organization, Jamaat-e-Islami, I aim at shifting the debate from textual normativity to demotic praxis. I demonstrate how Islam and democracy work in practice, and in so doing offer a fresh perspective to enhance our understandings of both Islam and democracy. A key proposition of this (...) article is that rather than discussing the cliché if Islam is compatible with democracy, or Islam should be democratized, we study the ‘hows’ of de-democratization in Muslim societies. (shrink)

The dominant debate on Islam and democracy continues to operate in the realm of normativity. This article engages with key literature showing limits of such a line of inquiry. Through the case study of India’s Islamist organization, Jamaat-e-Islami, I aim at shifting the debate from textual normativity to demotic praxis. I demonstrate how Islam and democracy work in practice, and in so doing offer a fresh perspective to enhance our understandings of both Islam and democracy. A key proposition of this (...) article is that rather than discussing the cliché if Islam is compatible with democracy, or Islam should be democratized, we study the ‘hows’ of de-democratization in Muslim societies. (shrink)

With the growing call for private sector actors to address global challenges, it is necessary to first assess whether regions with the greatest needs are accessing corporate philanthropy. In this paper, we ask whether corporate philanthropy is reaching those with the greatest health-care needs. Drawing on economic geography and corporate homophily, we argue that corporate philanthropy tends to exacerbate health inequality as grants are destined for counties with fewer health problems. We test and find support for this hypothesis using data (...) on health grants made by US corporate foundations and county-level health data. Our results that corporate health grants are less likely to go to counties which have a lower proportion of medical service providers and insured citizens suggest that corporate foundations are unwittingly complicit in worsening the resource gap between small, poor, rural counties and large, wealthy, urban counties. From an ethical perspective, we provide some guidance as to how this may be corrected. (shrink)

Muslim communities in the village facing the COVID-19 Pandemic attempts to find refuge from the plague and hope for survival. However, this led to more caution, which may lead to xenophobia. Via ethnography, this study unmasks the xenophobic attitude. This research discusses the root causes of panic in the community so that remedies can be implemented. The research attempts to explain, from a socio-anthropological viewpoint, how people and religious groups in the village perceive the pandemic of COVID-19 based on their (...) belief in their faith and in the science. The research takes place in Cigagak village, an area of approximately 7000 m2 on the outskirts of Bandung of West Java of Indonesia. This study examines the selected respondents from about 190 inhabitants who had close ties to managing places of worship and public places. This study utilises a collaborative self-ethnographic method and qualitative analysis. The influence of COVID-19 has moved to new exclusive and disintegrating practices from the inclusion-cohesive religious tradition. Therefore, this study tries to find out ways on how to reduce exclusive perception and religious practices to a minimum level and how to disappear xenophobia. Amid the COVID-19 Pandemic, inclusive awareness and actions were re-established, and even social cohesiveness was fostered. This study concludes that in its deep conviction nature, theology can change exclusive behaviour to be inclusive if it is based on the religious principles that are raised in response to human events. In this case, the Muslim community in a village can change the fear of COVID-19 pandemic to be a reducer of the panic based on the support of the religious doctrines.Contribution: This article used a collaborative self-ethnography with a religious socio-anthropological viewpoint. This study could help to solve social problems through theological convergence in Islamic milieu, especially that of the government’s formal Islamic organisation and organic Islamic leaders of the society. (shrink)

The effect of arousal safety has been analyzed on purchase intention, then attitude towards the advertisement and attitude towards the brand have been incorporated as intervening variables between the relationships. The interaction effect of self-monitoring and message arguments have also been taken in to consideration for better understanding of the consumer’s response. The data has been gathered from 206 respondents by using purposive sampling method. The research instrument was comprised of summated rating/additive scale and semantic differential scaling. Confirmatory Factor Analysis (...) has been applied after the application of preliminary tests on the data. Structure Equation Modeling and moderation and mediation analysis have also been applied to test the hypotheses. Arousal safety in the advertisements shape consumers response and it proved to be a fully mediated model. Self-monitoring also probes the relationship. Message arguments haven’t had any affect as moderator, hence can be used as a focal predictor. The study is a starting point for future research to provide a coherent methodology for capturing the necessary data, processing the underlying information and evaluating the effects of arousal safety in advertisements. The study extends the field of advertising in the direction of arousal safety effects. In comparison to previous research, empirical evidence on the arousal safety in television advertising and purchase intention in relation with moderating and mediating variables is provided. (shrink)

Saba Mahmood’s anthropological work studies the gain in skills, agency and capacity building by the women’s dawa movement in Egypt. These women increase their virtue toward the goal of piety by following dominant, often patriarchal norms. Mahmood argues that “teleological feminism” ignores this gain in agency because this kind of feminism only focuses on opposition or resistance to these norms. In this paper I defend Mahmood’s “anti-teleological” feminist work from criticisms that her project valorizes oppression and has no vision for (...) a nonoppressive feminist future. I argue the future envisioned by teleological feminists gets caught in “the Hegelian” trap of replicating past oppression in their feminist future. I find in Mahmood’s work the tools to escape this trap. I argue, rather than a movement of overcoming oppression, Mahmood’s work suggests an immanent and creative movement that emphasizes difference for a truly new future. I turn to a Bergsonian metaphor and argue that this movement can be seen as akin to the movement of biological evolution. I conclude using the work of Eve Sedgwick that the Egyptian women that Mahmood studies are being read in a “paranoid” fashion and demonstrate using Leila Ahmed a better “reparative” reading of these women. (shrink)

I begin the first part by showing how situationism should make us question traditional understandings of virtues as intrinsic dispositions. I concentrate specifically on situationist experiments related to mood. I then introduce Islamic virtue ethics and the dawa movement. In parts two and three I examine ethnography of the dawa movement to explore how they deal with worries about the influence of mood on their virtue. In part two I show how they train their habits in very traditional virtue ethics (...) ways in order to be more resilient when faced with virtue-diminishing affective situations. In part three I show how the situation, rather than hindering practitioners, is recruited into helping these women achieve piety. I conclude, in part four, by showing the dawa movement's creative use of the Islamic veil as a way to help these women deal with the objection that one cannot avoid all bad situations. Going beyond social psychological experiments, I examine two methodological sources not found in situationist debates. First, I argue for ethnography as an empirical method through which to study virtue. I draw on ethnography of the Islamic women's dawa movement. Secondly, the work in the philosophy of mind on ‘affective scaffolding’. (shrink)

In step with rapid advancements in computer vision, vehicle classification demonstrates a considerable potential to reshape intelligent transportation systems. In the last couple of decades, image processing and pattern recognition-based vehicle classification systems have been used to improve the effectiveness of automated highway toll collection and traffic monitoring systems. However, these methods are trained on limited handcrafted features extracted from small datasets, which do not cater the real-time road traffic conditions. Deep learning-based classification systems have been proposed to incorporate the (...) above-mentioned issues in traditional methods. However, convolutional neural networks require piles of data including noise, weather, and illumination factors to ensure robustness in real-time applications. Moreover, there is no generalized dataset available to validate the efficacy of vehicle classification systems. To overcome these issues, we propose a convolutional neural network-based vehicle classification system to improve robustness of vehicle classification in real-time applications. We present a vehicle dataset comprising of 10,000 images categorized into six-common vehicle classes considering adverse illuminous conditions to achieve robustness in real-time vehicle classification systems. Initially, pretrained AlexNet, GoogleNet, Inception-v3, VGG, and ResNet are fine-tuned on self-constructed vehicle dataset to evaluate their performance in terms of accuracy and convergence. Based on better performance, ResNet architecture is further improved by adding a new classification block in the network. To ensure generalization, we fine-tuned the network on the public VeRi dataset containing 50,000 images, which have been categorized into six vehicle classes. Finally, a comparison study has been carried out between the proposed and existing vehicle classification methods to evaluate the effectiveness of the proposed vehicle classification system. Consequently, our proposed system achieved 99.68%, 99.65%, and 99.56% accuracy, precision, and F1-score on our self-constructed dataset. (shrink)

This paper suggests philosophical foundations for mixed methods research based on the philosophy of critical realism. In particular, it suggests that the critical realist idea of the primacy of ontology helps bridge the apparent paradigmatic gap between qualitative and quantitative research. It illustrates this foundational idea by showing why and how a multi-disciplinary team used a mixed methods approach to understand the significance of religion in prison through a multi-site study of religious conversion to Islam in prison and how this (...) gives a better account than a single method approach. The mixed method research design used in the project sets out a new way of mapping and understanding religious conversion and differences within a faith group that draws on the emancipatory potential of critical realist thought. (shrink)