Keyword extraction refers to the process of selecting most significant, relevant, and descriptive terms as keywords, which are present inside a single document. Keyword extraction has major applications in the information retrieval domain, such as analysis, summarization, indexing, and search, of documents. In this paper, we present a novel supervised technique for extraction of keywords from medium-sized documents, namely Corpus-based Contextual Semantic Smoothing. CCSS extends the concept of Contextual Semantic Smoothing, which considers term usage patterns in similar texts to improve (...) term relevance information. We introduce four more features beyond CSS as our novel contributions in this work. We systematically compare the performance of CCSS with other techniques, when implemented over INSPEC dataset, where CCSS outperforms all state-of-the-art keyphrase extraction techniques presented in the literature. (shrink)

In this paper, we draw on insights from theories in the management and corporate governance literature to develop a theoretical model that makes explicit the links between a firm’s corporate social responsibility related board attributes, its board CSR strategy, and its environmental and social performance. We then test the model using structural equation modeling approach. We find that the greater the CSR orientation of the board, the more proactive and comprehensive the firm’s CSR strategy, and the higher its environmental and (...) social performance. Moreover, we find this link to be endogenous and self-reinforcing, with superior CSR performers tending to further strengthen their board CSR orientation. This result while positive is also suggestive of the widening of the gap between the leads and laggards in CSR. Therefore, the question arises as to how ‘leaders’ are using their superior CSR competencies seen by many scholars as a source of corporate competitive advantage. Stakeholders of corporations therefore need to be cognizant of this aspect of CSR when evaluating a firm’s CSR activities. Policy makers also need to be cognizant of these concerns when designing regulation in this field. (shrink)

This study is based on the natural resource based view, which examines the impact of holistic marketing orientation on business performance by defining the role of enablers and mediators. The drivers, including corporate social responsibility and environmental culture influence, are tested by analyzing the role of sustainable competitive advantage as a mediator. The analysis is based on 298 samples collected from top and middle-level managers working in the pharmaceutical industry. Structural equation modeling was undertaken using Smart PLS 3.2.8. The research (...) outcomes reveal that corporate social responsibility and environmental culture have a substantial impact on green marketing orientation. The results show that GMO has a significant direct and indirect impact on business performance while a full mediation of sustainable competitive advantage exists between the green marketing orientation and business performance. The outcomes will facilitate managers in green marketing strategy and decision making in the long-term, with 3-fold benefits in addition to strengthening their competitiveness. (shrink)

The aim of the study is to reveal the underlying structure of issues of university students taking online classes during the COVID-19 pandemic period. The overall design of the study includes a review of contemporary literature and field survey for data collection and analysis. Discourse of literature coupled with expert opinion has been employed for identification of issues. Interpretive Structural Modeling is used for the determination of intra-issue relationships and analyzing the underlying structure. Cross impact matrix multiplication applied to classification (...) is used as a technique for classifying issues on the basis of driving–dependence power. Results of the literature show that there are 21 major issues faced by the students taking online classes. ISM shows that lack of institutional guidelines, lack of regulators’ guidelines, stress of pandemic situation, and abrupt start of online classes are the most critical issues. MICMAC analysis reveals that there is no autonomous issue, 4 are independent, 6 other issues are dependent, and the remaining 11 are linking. This is a valuable study having practical implications for regulators, students, parents, and society to understand the current problem. It is an original attempt that contributes toward literature in the form of a structural model and a diagram of classification of issues. (shrink)

We examine the link between a firm’s environmental and social disclosures and measures of its risk including total, systematic, and idiosyncratic risk. While we do not find any link between a firm’s E and S disclosures and its systematic risk, we find a negative and significant association between these disclosures and a firm’s total and idiosyncratic risk. These are novel findings and are consistent with the predictions of the stakeholder theory and the resource-based view of the firm suggesting that firms (...) which make extensive and objective E and S disclosures promote corporate transparency that can help them build a positive reputation and trust with their stakeholders. This in turn can help mitigate the firms' idiosyncratic/operational risk. These findings are important for all corporate stakeholders including managers, employees, and suppliers who have a significant economic interest in the survival and success of the firm. (shrink)

Megastable chaotic systems are somehow the newest in the family of special chaotic systems. In this paper, a new megastable two-dimensional system is proposed. In this system, coexisting attractors are in some islands, interestingly covered by megalimit cycles. The introduced two-dimensional system has no defined equilibrium point. However, it seems that the origin plays the role of an unstable equilibrium point. Therefore, the attractors are determined as hidden attractors. Adding a forcing term to the system, we can obtain chaotic solutions (...) and coexisting strange attractors. Moreover, the effect of three different values of the forcing term’s amplitude is studied. The dynamical properties of the designed system are investigated using attractor plots, bifurcation diagrams, and Lyapunov Exponents diagram. Phase portraits of the novel megastable oscillator are presented by FPGA design. Xilinx system generator block diagrams of the proposed system and trigonometric functions are also presented. (shrink)

A multifaceted, holistic approach to identifying potential predictors is needed to eradicate workplace bullying. The current study investigated the impact of an unfavourable organisational climate that plays a role in breeding workplace bullying. The present study also postulated that individual personality differences mediate between a caring climate and workplace bullying. Similarly, the interaction between workplace bullying and personality impacts PTSD. We also checked the role of workplace bullying as a mediator between a caring climate and PTSD. This research tested all (...) the proposed hypotheses, and the study was conducted in Pakistan. The data is analysed using the two-step partial least square structural equation modelling procedure. The first part assesses the measurement model, while in the second step, the structural model is evaluated. The results supported all the proposed hypotheses of this study. Type A behaviour moderated the caring climate—person-related bullying relationship, whereas it did not moderate the caring climate—work-related bullying in the suggested direction. Type A behaviour is moderated for both types of bullying and PTSD. Results also show significant indirect effects of a caring climate on PTSD through workplace bullying. This study will contribute theoretically to filling the literature gap on studies of climate-bullying and bullying-stress using contingency factors. (shrink)

With the increasing volume of data transmission through insecure communication channels, big data security has become one of the important concerns in the cybersecurity domain. To address these concerns and keep data safe, a robust privacy-preserving cryptosystem is necessary. Such a solution relies on chaos encryption algorithms over standard cryptographic methods that possess multistage encryption levels, including high speed, high security, low compute overheads, and procedural power, among other characteristics. In this work, a secure image encryption scheme is proposed using (...) linear feedback shift register and chaos-based quantum chaotic map. The focus of the scheme is mainly dependent on the secret keys from the input of the algorithm. The threat landscape, the statistical test analysis, along critical comparisons with other schemes indicate that the presented algorithm is significantly secure and is resistant to a wide range of different attacks such as differential and statistical attacks. The proposed method has sufficiently higher sensitivity and security when compared to existing encryption algorithms. Several security parameters validated the security of proposed work such as correlation coefficient analyses among the neighboring pixels, entropy, the number of pixels change rate, unified average change intensity, mean square error, brute force, key sensitivity, and peak signal to noise ratio analyses. The randomness of the ciphers produced by the proposed technique is also passed through NIST-800-22. The results of NIST indicate that the ciphers are highly random and do not produce any type of periodicity or pattern. (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)

al-qism 1. al-Fikr al-ʻArabī qabla "al-falsafah" wa-ḥattá tukhūmuhā -- [2. Without special title].