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)

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)

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)

Irfan Ahmad makes the far-reaching argument that potent systems and modes for self-critique as well as critique of others are inherent in Islam--indeed, critique is integral to its fundamental tenets and practices. Challenging common views of Islam as hostile to critical thinking, Ahmad delineates thriving traditions of critique in Islamic culture, focusing in large part on South Asian traditions. Ahmad contemplates and interrogates Greek and Enlightenment notions of reason and critique, and he notes how they are (...) invoked in relation to "others," including Muslims. Drafting an alternative genealogy of critique in Islam, Ahmad reads religious teachings and texts, drawing on sources in Hindi, Urdu, Farsi, and English, and demonstrates how they serve as expressions of critique. Throughout, he depicts Islam as an agent, not an object, of critique. (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)

Context. Social media platforms such as Facebook and Twitter carry a big load of people’s opinions about politics and leaders, which makes them a good source of information for researchers to exploit different tasks that include election predictions. Objective. Identify, categorize, and present a comprehensive overview of the approaches, techniques, and tools used in election predictions on Twitter. Method. Conducted a systematic mapping study on election predictions on Twitter and provided empirical evidence for the work published between January 2010 and (...) January 2021. Results. This research identified 787 studies related to election predictions on Twitter. 98 primary studies were selected after defining and implementing several inclusion/exclusion criteria. The results show that most of the studies implemented sentiment analysis followed by volume-based and social network analysis approaches. The majority of the studies employed supervised learning techniques, subsequently, lexicon-based approach SA, volume-based, and unsupervised learning. Besides this, 18 types of dictionaries were identified. Elections of 28 countries were analyzed, mainly USA and Indian elections. Furthermore, the results revealed that 50% of the primary studies used English tweets. The demographic data showed that academic organizations and conference venues are the most active. Conclusion. The evolution of the work published in the past 11 years shows that most of the studies employed SA. The implementation of SNA techniques is lower as compared to SA. Appropriate political labelled datasets are not available, especially in languages other than English. Deep learning needs to be employed in this domain to get better predictions. (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)

For the safe and economical construction of embankment dams, the mechanical behaviour of the rockfill materials used in the dam’s shell must be analyzed. The characterization of rockfill materials with specified shear strength is difficult and expensive due to the presence of particles greater than 500 mm in diameter. This work investigates the feasibility of using an extreme gradient boosting computing paradigm to estimate the shear strength of rockfill materials. To train and validate the proposed XGBoost model, a total of (...) 165 databases obtained from the literature are chosen. The XGBoost model was compared against support vector machine, adaptive boosting, random forest, and K-nearest neighbor models described in the literature. XGBoost beats SVM, RF, AdaBoost, and KNN models in terms of performance evaluation metrics such as coefficient of determination, Nash–Sutcliffe coefficient, and error in the root mean square ratio to the standard deviation of the measured data. The results demonstrated that the XGBoost model has the highest prediction performance with, followed by the SVM model with, RF, the AdaBoost model with and the KNN model with. A sensitivity analysis has been conducted to ascertain the impact of each investigated input parameter. This study demonstrates that the established XGBoost model for estimating the shear strength of rockfill materials is reliable. (shrink)

Given that personal source of information is preferred by the customers over company-generated marketing communications, promoting advocacy behavior among customers is of much importance for every organization. Literature suggests that an organization's corporate social responsibility (CSR) activities significantly influence individual behavior. However, the advocacy behavior of customers (ADB), from a CSR perspective, did not receive due attention. To address this literature gap, the current study attempts to explore the relationship among CSR and ADB with the intervening role of brand admiration (...) (BA). To collect the data, customers of a large fast-food service organization in Pakistan were approached. The proposed relationships were tested through the structural equation modeling (SEM) technique. The statistical evidence verifies a positive link between CSR and ADB, while BA mediated this relationship. These findings will be supportive to the fast-food business to realize the critical role of CSR for a meaningful customer-company relationship in the face of competition. (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)

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 research study aims to determine the impact of secularism on religious practices and beliefs. Enforcing secular-based laws and principles is the main agenda of secular societies. These societies try hard to make every illegal act legal by declaring it under the Secular Law Act. European higher authorities must ensure that no illegal act is reinforced in the country under secular acts. European lawmakers have taken various legal measures to stop the prevalence of illegal acts in the country. One significant (...) advantage of secular society is that it provides people with the best medical and healthcare facilities despite religious differences. All the people, whether they belong to Christianity or Muslim, are provided with just and equal medical facilities in secular European society. The research study was based on primary data analysis, and SPSS software was used to measure the research. It generated informative results, including descriptive statistics, correlation, ANOVA test analysis, and the linear regression analysis between secularism and religious practices and beliefs in modern Europe. The health care services are the same for all genders in European countries. In public schools and other educational institutes of secular society, all the standards are fulfilled with equal educational facilities without discrimination.in governmental and private institutes, fair public services are provided to people of all ages regardless of religious faiths and norms. All these features of secular European society make it a transparent society with no flaws or faults. Overall, the research found a direct and significant impact of secularism on religious practices and beliefs. (shrink)

Data center technology changes the mode of computing. Traditional DCs consist of a single layer and only have Ethernet connections among switches. Those old-fashioned DCs cannot fulfill the high resource demand compared with today’s DCs. The architectural design of the DCs is getting substantial importance and acting as the backbone of the network because of its essential feature of supporting and maintaining the rapidly increasing Internet-based applications which include search engines and social networking applications. Every application has its parameters, like (...) latency and blocking in the DC network. Every data center network has its specialized architecture. It has a specific arrangement of layers and switches, which increase or decrease the DC network’s efficiency. We develop a simulation tool that comprises two different DC architectures: basic tree architecture and c-Through architecture. Using this simulation, we analyze the traffic behavior and the performance of the simulated DCN. Our main purpose is to focus on mean waiting time, load, and blocking with respect to the traffic within the DCN. (shrink)

This article documents the existence of a vibrant republic of letters stretching from Cairo to Karachi in the middle of the twentieth century. On the basis of private letters, memoirs, and modern editions of classical texts, this article recreates the scholarly and personal commitments of a new class of professional editors. These editors were responsible for the emergence of some of the most influential publishing houses in the Islamic world, and their contribution to the production and circulation of pre-modern texts (...) has had a profound impact on the intellectual development of Islam in the twentieth and twenty-first centuries. They believed that cultivating a republic of letters was necessary because it served the world of learning and scholarship. In this way was fashioned a virtual community, separated by national and political borders, but united by visions of history and a shared sense of moral and intellectual duty. (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)

We examined a largely ignored but imperative dimension of safety literature by testing the impact of ethical leadership style on organizational safety performance. We also tested dual mediating paths of safety culture and safety consciousness in the relationship between ethical leadership style and organizational safety consciousness. Data were collected from a large public sector telecom company in Pakistan. Confirmatory factor analysis was used to assess the reliability and validity of the study scales and model fit. Preacher and Hayes’s macro of (...) mediation was employed to test the direct and indirect paths proposed in the study. The findings suggest that ethical leadership has a positive impact on organizational safety performance. Partial mediating roles of safety culture and safety consciousness were also found between the dependent and independent variables. Theoretical and practical implications are discussed. (shrink)

Half a million species of plants could be existing in the world. Classification of plants based on leaf features is a critical job as feature extraction from binary images of leaves may result in duplicate identification. However, leaves are an effective means of differentiating plant species because of their unique characteristics like area, diameter, perimeter, circularity, aspect ratio, solidity, eccentricity, and narrow factor. This paper presents the extraction of plant leaf gas alongside other features from the camera images or a (...) dataset of images by applying a convolutional neural network. The extraction of leaf gas enables identification of the actual level of chlorophyll and nitrogen which may help to interpret future predictions. Our contribution includes the study of texture and geometric features, analyzing ratio of Ch and N in both healthy and dead leaves, and the study of color-based methods via CNN. Several steps are included to obtain the results: image preprocessing, testing, training, enhancement, segmentation, feature extraction, and aggregation of results. A vital contrast of the results can be seen by considering the kind of image, whether a healthy or dead leaf. (shrink)

Efficient community detection in a complex network is considered an interesting issue due to its vast applications in many prevailing areas such as biology, chemistry, linguistics, social sciences, and others. There are several algorithms available for network community detection. This study proposed the Sigmoid Fish Swarm Optimization algorithm to discover efficient network communities. Our proposed algorithm uses the sigmoid function for various fish moves in a swarm, including Prey, Follow, Swarm, and Free Move, for better movement and community detection. The (...) proposed SiFSO algorithm’s performance is tested against state-of-the-art particle swarm optimization algorithms in Q-modularity and normalized mutual information. The results showed that the proposed SiFSO algorithm is 0.0014% better in terms of Q-modularity and 0.1187% better in terms of NMI than the other selected algorithms. (shrink)

: The modern era may be deemed as that of scientific and technologicaldevelopment but peace and harmony among the people remain elusive. Thetwo world wars, Palestinian problem, bombing of world twin towers, invasionof Muslim countries by Americans and allied forces, and the continuous bloodshedding of humanity in one form or another in different parts of the world, allthese horrifying phenomena prove lack of political will on the part of UnitedNations. Had religions in the strife-torn regions played their crucial role, therewould (...) never have occurred bloodshed of the humanity. Judaism, Christianity,and Islam account for the big majority in the world today and have so manythings in common, especially essential human values guided by two universalprinciples, unity of God and unity of man. The Ten Commandments in theTorah, confirmation of the Mosaic Law in the Bible, and reconfirmation of theMosaic and Biblical instructions in the Qur’an still hold the significance forcreating peace and harmony among people of the three creeds. (shrink)

Ethical and quality concerns are important concerns in doctoral research programs and often draw the attention of governments, universities governing bodies, academics, and research students. Addressing these concerns is key to maintaining and improving the quality of doctoral research. This study used generic qualitative research design. The sample of the study consisting of seventeen doctoral students and ten doctoral supervisors was selected from social science doctoral programs using purposive sampling technique. Interviews were used as data collection tools. The study aimed (...) at contributing to the areas of quality and ethical processes and outcomes in social science research in the Pakistani context where ethical and quality dimensions in educational research have been relatively less explored. The study indicated several ethical and quality issues in the doctoral research programs including inadequate research supervision and evaluation processes, inadequate course work, low teaching quality, and a focus on getting degrees rather than on obtaining genuine scholarship. Policy makers and higher education institutions may need to deal with issues that lead to a compromise on doctoral research studies in ethical and quality terms. The findings of this study may prove helpful to remedy some of the existing causes of ethical and quality issues in research at the PhD level and may help to produce value added research for social and economic progress. Further research may be conducted to explore possible ethical and quality concerns in natural sciences doctoral programs and to explore possible intervention-mechanisms for ensuring ethical and quality concerns in such programs. (shrink)

Most of the IoT-based smart systems require low latency and crisp response time for their applications. Achieving the demand of this high Quality of Service becomes quite challenging when computationally intensive tasks are offloaded to the cloud for execution. Edge computing therein plays an important role by introducing low network latency, quick response, and high bandwidth. However, offloading computations at a large scale overwhelms the edge server with many requests and the scalability issue originates. To address the above issues, an (...) efficient resource management technique is required to maintain the workload over the edge and ensure the reduction of response time for IoT applications. Therefore, in this paper, we introduce a metaheuristic and nature-inspired Artificial Bee Colony optimization technique that effectively manages the workload over the edge server under the strict constraints of low network latency and quick response time. The numerical results show that the proposed ABC algorithm has outperformed Particle Swarm Optimization, Ant Colony Optimization, and Round-Robin Scheduling algorithms by producing low response time and effectively managing the workload over the edge server. Furthermore, the proposed technique scales the edge server to meet the demand of high QoS for IoT applications. (shrink)

In this paper, we utilized triangular conorms. The essence of using S-norm is that the similarity order does not change using different norms. In fact, we are investigating for a new conception for calculating the similarity of two Fermatean fuzzy sets. For this purpose, utilizing an S-norm, we first present a formula for calculating the similarity of two Fermatean fuzzy values, so that they are truthful in similarity properties. Following that, we generalize a formula for calculating the similarity of the (...) two Fermatean fuzzy sets which prove truthful in similarity conditions. Finally, various numerical examples have been presented to elaborate this method. (shrink)

The web is being loaded daily with a huge volume of data, mainly unstructured textual data, which increases the need for information extraction and NLP systems significantly. Named-entity recognition task is a key step towards efficiently understanding text data and saving time and effort. Being a widely used language globally, English is taking over most of the research conducted in this field, especially in the biomedical domain. Unlike other languages, Arabic suffers from lack of resources. This work presents a BERT-based (...) model to identify biomedical named entities in the Arabic text data that investigates the effectiveness of pretraining a monolingual BERT model with a small-scale biomedical dataset on enhancing the model understanding of Arabic biomedical text. The model performance was compared with two state-of-the-art models, and it outperformed both models with 85% F1-score. (shrink)

Pervasive usage and the development of social media networks have provided the platform for the fake news to spread fast among people. Fake news often misleads people and creates wrong society perceptions. The spread of low-quality news in social media has negatively affected individuals and society. In this study, we proposed an ensemble-based deep learning model to classify news as fake or real using LIAR dataset. Due to the nature of the dataset attributes, two deep learning models were used. For (...) the textual attribute “statement,” Bi-LSTM-GRU-dense deep learning model was used, while for the remaining attributes, dense deep learning model was used. Experimental results showed that the proposed study achieved an accuracy of 0.898, recall of 0.916, precision of 0.913, and F-score of 0.914, respectively, using only statement attribute. Moreover, the outcome of the proposed models is remarkable when compared with that of the previous studies for fake news detection using LIAR dataset. (shrink)

The relevance of transcreation skills goes beyond mere translation strategy to a more sought-after service, that help equip translators with relevant employability skills. Nevertheless, the concern for the high demands of translators who possess these skills calls for a thorough training of future translators to acquire these skills. On the other hand, this will be possible if translator educators are already equipped with these skills. As such, this study aims to explore how translation educators, specifically, university lecturers can be prepared (...) to effectively address the growing need for transcreation skills. The research further explores practical techniques and approaches aimed at teaching instructors to successfully impart transcreation abilities and adequately equip students for employment in creative translation. In order to achieve the objective of this research, a quantitative research methodology was adopted, and an online research questionnaire was also utilized. Moreover, a total of ninety-seven (97) study participants were included in the online survey to express their perspectives on how the university lecturers can be trained to address demands for creative translation. The participants' replies, which constitute the primary dataset for this study, were presented and subjected to thorough analysis. Additionally, these replies provided additional clarification on the two fundamental study hypotheses. The study results highlighted several fundamental elements connected with transcreation skills, including bilingual proficiency, creative writing, cultural sensitivity, and multimedia proficiency. Based on the analyzed data, the research revealed that adoption of practical strategies and methodologies such as professional development, inclusion of transcreation projects in translation training module, collaboration with industry experts, and technology integration helps to train translation educators to effectively teach transcreation skills. The study, however, recommends combination of these identified strategies for effective training of university lecturers. (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)

Software defects prediction at the initial period of the software development life cycle remains a critical and important assignment. Defect prediction and correctness leads to the assurance of the quality of software systems and has remained integral to study in the previous years. The quick forecast of imperfect or defective modules in software development can serve the development squad to use the existing assets competently and effectively to provide remarkable software products in a given short timeline. Hitherto, several researchers have (...) industrialized defect prediction models by utilizing statistical and machine learning techniques that are operative and effective approaches to pinpoint the defective modules. Tree family machine learning techniques are well-thought-out to be one of the finest and ordinarily used supervised learning methods. In this study, different tree family machine learning techniques are employed for software defect prediction using ten benchmark datasets. These techniques include Credal Decision Tree, Cost-Sensitive Decision Forest, Decision Stump, Forest by Penalizing Attributes, Hoeffding Tree, Decision Tree, Logistic Model Tree, Random Forest, Random Tree, and REP-Tree. Performance of each technique is evaluated using different measures, i.e., mean absolute error, relative absolute error, root mean squared error, root relative squared error, specificity, precision, recall, F-measure, G-measure, Matthew’s correlation coefficient, and accuracy. The overall outcomes of this paper suggested RF technique by producing best results in terms of reducing error rates as well as increasing accuracy on five datasets, i.e., AR3, PC1, PC2, PC3, and PC4. The average accuracy achieved by RF is 90.2238%. The comprehensive outcomes of this study can be used as a reference point for other researchers. Any assertion concerning the enhancement in prediction through any new model, technique, or framework can be benchmarked and verified. (shrink)

Acute Myeloid Leukemia is a kind of fatal blood cancer with a high death rate caused by abnormal cells’ rapid growth in the human body. The usual method to detect AML is the manual microscopic examination of the blood sample, which is tedious and time-consuming and requires a skilled medical operator for accurate detection. In this work, we proposed an AlexNet-based classification model to detect Acute Myeloid Leukemia in microscopic blood images and compared its performance with LeNet-5-based model in Precision, (...) Recall, Accuracy, and Quadratic Loss. The experiments are conducted on a dataset of four thousand blood smear samples. The results show that AlexNet was able to identify 88.9% of images correctly with 87.4% precision and 98.58% accuracy, whereas LeNet-5 correctly identified 85.3% of images with 83.6% precision and 96.25% accuracy. (shrink)

To determine the knowledge, attitudes and practices regarding organ donation in a selected adult population in Pakistan.

For efficient energy distribution, microgrids provide significant assistance to main grids and act as a bridge between the power generation and consumption. Renewable energy generation resources, particularly photovoltaics, are considered as a clean source of energy but are highly complex, volatile, and intermittent in nature making their forecasting challenging. Thus, a reliable, optimized, and a robust forecasting method deployed at MG objectifies these challenges by providing accurate renewable energy production forecasting and establishing a precise power generation and consumption matching at (...) MG. Furthermore, it ensures effective planning, operation, and acquisition from the main grid in the case of superior or inferior amounts of energy, respectively. Therefore, in this work, we develop an end-to-end hybrid network for automatic PV power forecasting, comprising three basic steps. Firstly, data preprocessing is performed to normalize, remove the outliers, and deal with the missing values prominently. Next, the temporal features are extracted using deep sequential modelling schemes, followed by the extraction of spatial features via convolutional neural networks. These features are then fed to fully connected layers for optimal PV power forecasting. In the third step, the proposed model is evaluated on publicly available PV power generation datasets, where its performance reveals lower error rates when compared to state-of-the-art methods. (shrink)

In the historical process, the importance of doing interdisciplinary work has been accepted in all social sciences and has become an undeniable phenomenon. The history of Islamic thought can undoubtedly be seen as a very fertile field for such a study. It is because many different disciplines start the historical formation process from the same point. In other words, they are historically constructed on a common narrative. In this respect, interdisciplinary reading can be most functional in the context of usûl-ı (...) fiqh, kalam, philosophy and mysticism, which can be expressed as the pillars of Islamic thought. In this framework, we have identified Ahmed Mahmûd Subhi, the Egyptian thinker and academician, as a prototype in our study. As a matter of fact, Subhi has an approach that stands out with a holistic perception of Islamic thought and has produced texts that can build the idea in question. We can build Subhî's way of thinking with a tradition he abides by or in a teacher-student relationship. What is needed for this is to take an in-depth look at his life and works. Such a study will serve as the key to our understanding of Subhi's scientific method. The ultimate aim of this study is to emphasize the importance of taking different disciplines as a basis in order to make healthy and correct interpretations of Islamic thought. This issue, which we have expressed as a claim, will be embodied by Subhî's ideas in his texts and turned into a concrete structure. (shrink)

The influential stage of Internet of Things has reformed all fields of life in general but specifically with the emergence of artificial intelligence has drawn the attention of researchers into a new paradigm of life standard. This revolution has been accepted around the globe for making life easier with the use of intelligent devices such as smart sensors, actuators, and many other devices. AI-enabled devices are more intelligent and capable of doing a specific task which saves a lot of resources (...) and time. Different approaches are available in the existing literature to tackle diverse issues of real life based on AI and IoT systems. The role of decision-making has its own importance in the AI-enabled and IoT systems. In-depth knowledge of the existing literature is dire need of the research community to summarize the literature in effective way by which practitioners and researchers can benefit from the prevailing proofs and suggest new solutions for solving a particular problem of AI-enabled sensing and decision-making for the IoT system. To facilitate research community, the proposed study presents a systematic literature review of the existing literature, organizes the evidences in a systematic way, and then analyzes it for future research. The study reported the literature of the last 5 years based on the research questions, inclusion and exclusion criteria, and quality assessment of the selected study. Finally, derivations are drawn from the included paper for future research. (shrink)

The use of slang, abusive, and offensive language has become common practice on social media. Even though social media companies have censorship polices for slang, abusive, vulgar, and offensive language, due to limited resources and research in the automatic detection of abusive language mechanisms other than English, this condemnable act is still practiced. This study proposes USAD, a lexicon-based intelligent framework to detect abusive and slang words in Perso-Arabic-scripted Urdu Tweets. Furthermore, due to the nonavailability of the standard dataset, we (...) also design and annotate a dataset of abusive, offensive, and slang word Perso-Arabic-scripted Urdu as our second significant contribution for future research. The results show that our proposed USAD model can identify 72.6% correctly as abusive or nonabusive Tweet. Additionally, we have also identified some key factors that can help the researchers improve their abusive language detection models. (shrink)

The earlier volume in this series dealt with two religions of Indian origin, namely, Buddhism and Jainism. The Indian religious scene, however, is characterized by not only religions which originated in India but also by religions which entered India from outside India and made their home here. Thus religious life in India has been enlivened throughout its history by the presence of religions of foreign origin on its soil almost from the very time they came into existence. This volume covers (...) three such religions—Zoraoastrianism, Judaism, and Islam. In the case of Zoraostianism, even its very beginnings are intertwined with India, as Zoroastrianism reformed a preexisting religion which had strong links to the Vedic heritage of India. This relationship took on a new dimension when a Zoroastrian community, fearing persecution in Persia after its Arab conquest, sought shelter in western India and ultimately went on to produce India’s pioneering nationalist in the figure of Dadabhai Naoroji ( 1825-1917), also known as the Grand Old Man of India. Jews found refuge in south India after the destruction of the Temple by the Romans in 70 C.E. and have remained a part of the Indian religious scene since then, some even returning to Israel after it was founded in 1948. Islam arrived in Kerala as soon as it was founded and one of the earliest mosques in the history of Islam is found in India. Islam differs from the previously mentioned religions inasmuch as it went on to gain political hegemony over parts of the country for considerable periods of time, which meant that its impact on the religious life of the subcontinent has been greater compared to the other religions. It has also meant that Islam has existed in a religiously plural environment in India for a longer period than elsewhere in the world so that not only has Islam left a mark on India, India has also left its mark on it. Indeed all the three religions covered in this volume share this dual feature, that they have profoundly influenced Indian religious life and have also in turn been profoundly influenced by their presence in India. (shrink)

Though the current research stream has provided some risk factors for envy at the workplace, little is still known about the drivers and consequences of envy. Based on Vecchio’s theory, this study investigates the ripple effect of the span of supervision on envy. Moreover, it sheds light on the moderating role of meaningful work in their relationship. The data comprising sample size 439 were collected from confrères of four fast food companies listed on the Stock Exchange of Pakistan. Partial Least (...) Square Structural Equation Modeling technique was implemented through SmartPLS 3.3.2 to analyze the measurement and structural relationships. The results demonstrate that a narrow span of supervision will increase work engagement, and reduce instigated incivility via decreasing envy and resource depletion in sequence. Moreover, meaningful work would help regulate the inimical stream of dénouement of envy. Theoretical and practical implications, along with the limitations and future directions, have also been discussed. (shrink)

Introduction As systems for communicating, moralities are languages of persuasion. They seek to convince persons to act in expected or desired manner by ...

Design problems in structural engineering are often modeled as differential equations. These problems are posed as initial or boundary value problems with several possible variations in structural designs. In this paper, we have derived a mathematical model that represents different structures of beam-columns by varying axial load with or without internal forces including bending rigidity. We have also developed a novel solver, the LeNN-NM algorithm, which consists of weighted Legendre polynomials, and a single path following optimizer, the Nelder–Mead algorithm. To (...) evaluate the performance of our solver, we have considered three design problems representing beam-columns. The values of performance indicators, MAD, TIC, NSE, and ENSE, are calculated for a hundred simulations. The outcome of our statistical analysis points to the superiority of the LeNN-NM algorithm. Graphical illustrations are presented to further elaborate on our claims. (shrink)