Muhammad Khan

This article aims to improve the understanding of corporate governance and environmental reporting literature by analyzing the impact of board gender diversity (BGD) on environmental performance, environmental disclosure, and greenwashing behavior. The panel regression estimation technique with fixed effects was applied to Chinese firm data. As a result, it was found that more women who served on corporate boards enhanced the company's environmental performance and disclosures while limiting greenwashing behavior. The result indicated that women in top management play a constructive role in establishing firms' active environmental initiatives. Furthermore, this relationship was nonlinear and exponentially increased when women's representation reached the threshold of 33.5% representation on board or higher. Based on the findings, no internal bias was found even after other governance and firm-level control factors and probable endogenies were considered and variable biases were omitted. Notably, the results present important implications for regulators and policymakers by highlighting the influential role of BGD in promoting environmentally responsible practices and reducing greenwashing.

This study aims to elaborate on how work-life balance practices influence organizational cynicism through the mediation effects of person-job fit. We collected data from 331 nurses through a self-administered survey, and we tested our hypothesized model through partial least square structural equation modeling techniques using SmartPLS software. The findings revealed that WLB practices influenced OC negatively and PJF positively. We further found that PJF negatively influenced OC and mediated WLB practices’ effect on OC. These findings imply that nurses should be provided WLB practices to meet their job and home responsibilities and thus have a less cynical attitude toward the organization.

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%.

Current development in a deep neural network has given an opportunity to a novel framework for the reconstruction of a holographic image and a phase recovery method with real-time performance. There are many deep learning-based techniques that have been proposed for the holographic image reconstruction, but these deep learning-based methods can still lack in performance, time complexity, accuracy, and real-time performance. Due to iterative calculation, the generation of a CGH requires a long computation time. A novel deep generative adversarial network holography framework is proposed for hologram reconstruction. This novel framework consists of two phases. In phase one, we used the Fresnel-based method to make the dataset. In the second phase, we trained the raw input image and holographic label image data from phase one acquired images. Our method has the capability of the noniterative process of computer-generated holograms. The experimental results have demonstrated that the proposed method outperforms the existing methods.

Given the dearth of research examining the distinctions across various facets of employee knowledge-hiding (KH) behaviors, there is little known about why and when leadership negatively influences playing dumb and evasive hiding but positively influences rationalized hiding. The present study fills this void by hypothesizing that employee justice orientation (JO) acts as a mediator of the associations of ethical leadership (EL) with different facets of employee KH behaviors. We also propose employee conscientiousness moderates the relationship of EL with JO and the indirect relationships of ethical leadership with distinct variants of employee KH behaviors. The results based on time-lagged data from 387 employees provide support for the hypothesized relationships. Together, our research provides a more nuanced account of the influence of leadership on employee KH behaviors that can facilitate the development of more appropriate interventions to deal with the intricate problems related to employee KH behaviors.

In this study, we examined the impact of energies of 2.54 keV and 5 keV displacement cascades in molybdenum (Mo) using an atomistic simulation at 300 K. The simulation was carried out using machines learning developed spectral neighbor analysis potential (SNAP). We computed displacement threshold energy (E_d), vacancy formation energy (E_v^f), interstitial formation energy (E_i^f), interstitial cluster formation energy (E_cf^i), activation energy barrier of interstitial〖 (E〗_ai), activation energy barrier of vacancy (E_aV), elastic properties, i.e., shear, bulk, young's modulus, poison ratio. The simulations for primary displacement cascades were performed over a statistical average of 20 independent molecular dynamics simulations such that peak time and the surviving number of defects are inversely proportional to the incident energy of primary knock-on atoms (EPKA). Additionally, it is established that the number of clusters (Nclusters) during displacement cascades is directly proportional to EPKA. Furthermore, it was revealed that the number of interstitial clusters is higher than the number of vacancy clusters. This research will provide atomic insight into the interactions of defects in Mo for the development of structural materials for high temperature applications.

This study explores the impact of CEO ability on corporate environmental sustainability information disclosure. We take samples from Chinese A-share listed companies from 2010 to 2019 and use the ordinary least squares as a baseline regression model to check the relationship between CEO ability and corporate environmental sustainability information disclosure. Our findings are robust to different corporate environmental sustainability information disclosure measures and CEO ability. We found a positive association between CEO ability and corporate environmental sustainability information disclosure; thus, firms with a more able CEO are more likely to disclose more corporate environmental sustainability information. Our results also found a significant negative interaction coefficient between CEO ability and CEO career concerns. As the CEO grows older, his/her ability decreases; therefore, corporate environmental sustainability information disclosure reduces. Furthermore, we document that a female CEO strengthens the relationship between CEO ability and corporate environmental sustainability information disclosure. The study results are important for understanding corporate environmental responsibility development and implementation, particularly in China.

The regression model is generally utilized in several fields of study because of its applications. Regression is an extremely incredible approach; it builds up a connection between dependent and independent variables. We have addressed a powerful computational model by utilizing dengue information joined with fuzzy multiple linear regression. Information is accumulated on dengue fever through the survey. This paper is centered on the comparison of the crisp method with fuzzy multiple linear regression, and then, the utilization of a fuzzy multiple regression method is explained after the comparison. We have used multiple regression and then converted the said technique into three fuzzy cases. The effectiveness of the fuzzy multiple regression model is measured by numerical computation and comparison of both techniques. 2020 Mathematics Subject Classification. Primary 30C45; 30C50; 30C80; Secondary 11B65, 47B38.

The purpose of this study is to examine the link between English foreign language teacher’s professional identity and employee success via mediating role of critical thinking. Further, we examined the moderating role of leader motivational language between employee professional identity and critical thing and also indirect effect on employee success via critical thinking. We collected data from Chinese MNC’s school by using time lagged study design. We used hierarchical linear regression for direct hypotheses and Hayes PROCESS model’s for mediation, moderation, and mediation moderation analysis. The results show that there is positive relation between employee’s professional identity and teacher’s success. Further, critical thinking mediates the link between professional identity and employee success. The results of the moderated mediation analysis show that critical thinking mediated the interaction of employee’s professional identity and leader’s motivational language on teacher’s success.

The COVID-19 pandemic has caused a global crisis that particularly hit employment globally. Due to the economic crisis, many small businesses attempted to minimise their expenses by either closing or downsizing. During such organisational situations, the employees face negative workplace attitudes that lead to knowledge hiding and affect team performance. This study examines negative attitudes and their effect on team performance. Further, this study examines the mediating effect of knowledge hiding and moderating the role of servant leadership. Through a multi-time data collection approach, the authors obtained 363 responses from the education sector in China during the COVID-19 pandemic. PROCESS Hayes model 1 and 4 were used for mediation and moderation analysis. Results show that job insecurity, cynicism, and role stress are significant forces behind knowledge-hiding behaviour. Furthermore, the knowledge hiding behaviour adversely affects task performance. Servant leadership shows a buffering effect on knowledge hiding behaviour caused by negative workplace attitudes. This is one of the first studies in the South Asian environment to examine the association between employees’ negative attitudes and task performance using knowledge hiding as a mediator and servant leadership as a moderator in the COVID-19 scenario. Lastly, the paper concludes with a consideration of its theoretical, practical implication and future direction.

BackgroundIn recent years, technological advancements have increased the importance of innovation activities. Therefore, firms invest millions of dollars in innovation activities to ensure long-term business sustainability. Similarly, consumer concerns have increased dramatically over the past years. Thus, brand loyalty has become a top priority for firms and consumers. In this background, this research examines how firms’ innovation activities translate into consumer brand loyalty to assure business sustainability in Asian markets, particularly China, Pakistan, and Indonesia.ObjectivesThis study’s specific objectives are to comprehend the concept of firms’ innovation activities and their effect on the brand prototype. Examine the effect of the brand prototype on global brand preference, recommendation, and loyalty among Asian consumers. Find out the impact of brand preference on brand recommendations and the influence of brand recommendations on brand loyalty among Asian consumers.Materials and methodsA total of 814 consumers from Asian countries participated in this study, and structural equation modeling was used to analyze the data.ResultsThe findings indicate that firms’ innovation activities, such as processes, products, and store environment, positively influenced the brand prototype, thereby increasing consumer brand knowledge. Likewise, brand prototype contributes to developing brand preference, brand recommendation, and brand loyalty among Asian consumers. Lastly, consumer brand preference significantly influenced brand recommendation, which positively improves consumer brand loyalty in Asia.ConclusionThis study concluded that Asian consumers have favorable perceptions of firms’ innovation activities, which influences their ability to develop brand prototypes to increase consumer brand knowledge. Similarly, brand prototype fosters brand preference, recommendation, and loyalty. Likewise, favorable brand preference encourages consumers to recommend the brand to others, strengthening brand loyalty. Thus, firms should invest in innovation activities to strengthen consumer brand loyalty in Asian markets. Consequently, this study may assist multinational corporations in increasing their business volumes and market shares in Asia.Managerial recommendationsThis study provides important managerial recommendations. The findings revealed that global managers can develop and implement several branding strategies for sustaining their businesses in the Asian environment.

The current research examines the possible outcomes of cronyism like organizational deviance, organizational cynicism, and counterproductive work behavior and also investigates the mediating variable violation of psychological contract among cronyism and its possible outcomes. Many studies have investigated the presence of organizational cronyism at the workplace and its impacts on certain variables. However, the outcomes observed in this study, i.e., OD, OCy, and counter-productive work behavior were not empirically investigated previously as per researchers’ knowledge. The second gap this study fills is the mediating effect of VPC between the studied variables. Thirdly, the study was conducted in Azad Jammu and Kashmir, Pakistan, which is almost the first attempt to investigate this phenomenon in Azad Jammu and Kashmir. Data were collected from the employees working under different ministries of Azad Jammu and Kashmir, Pakistan like education, forest, sports, information, local government, finance, and tourism. The data from 350 employees were collected through convenience sampling. The data collection process was conducted at two distinct time lags. Results show that OC significantly and positively relates with OD, OCy, and counter-productive work behavior, whereas VPC mediates the relationship among OC and OD, OC, and counter-productive work behavior. Employees enjoying special favors from the leadership seem to be more dedicated toward the organization than the employees who do not have this favor, and the ultimate result is negative for the organization.

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.

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.

The current study investigates whether tournament incentives motivate chief executive officer to be socially responsible. Furthermore, it explores the role of sub-national institutional contingencies [i.e., state-owned enterprises vs. non-SOEs, foreign-owned entities vs. non-FOEs, cross-listed vs. non-cross-listed, developed region] in CEO tournament incentives and the corporate social responsibility performance relationship. Data were collected from all A-shared companies listed in the stock exchanges of China from 2014 to 2019. The study uses the baseline methodology of ordinary least squares and cluster OLS regression. Moreover, firm-fixed effects regression, two-stage least squares regression, and propensity score matching deal with the endogeneity problem and check the robustness of the results. The results provide reliable evidence that tournament incentives motivate CEOs to be more socially responsible. On the other hand, sub-national institutional contingencies positively affect the association between CEO tournament incentives and CSRP. The findings have important implications for companies and regulators who wish to enhance CSP by providing incentives to top managers.

During the COVID-19 outbreak, educational institutions were closed, and students worldwide were confined to their homes. In an educational environment, students depend on collaborative learning to improve their learning performance. This study aimed to increase the understanding of social media adoption among students during the COVID-19 pandemic for the purpose of CL. Social media provides a learning platform that enables students to easily communicate with their peers and subject specialists, and is conducive to students' CL. This study addresses the key concept of CL during the COVID-19 pandemic by assessing social media use among students in higher education. The relationship between social media use and students' performance is crucial to understanding the role of social media during a pandemic. This study is based on constructivism theory and the technology acceptance model. Structural equation modeling was used to analyze the conceptual model using SmartPLS. The research findings indicate that social media plays an important role during the pandemic because it provides opportunities for students to enhance CL under the aforementioned situations. This study makes noteworthy theoretical and practical contributions.

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.

A passive brain–computer interface based upon functional near-infrared spectroscopy brain signals is used for earlier detection of human drowsiness during driving tasks. This BCI modality acquired hemodynamic signals of 13 healthy subjects from the right dorsolateral prefrontal cortex of the brain. Drowsiness activity is recorded using a continuous-wave fNIRS system and eight channels over the right DPFC. During the experiment, sleep-deprived subjects drove a vehicle in a driving simulator while their cerebral oxygen regulation state was continuously measured. Vector phase analysis was used as a classifier to detect drowsiness state along with sleep stage-based threshold criteria. Extensive training and testing with various feature sets and classifiers are done to justify the adaptation of threshold criteria for any subject without requiring recalibration. Three statistical features along with six VPA features were used. The average accuracies for the five classifiers are 90.9% for discriminant analysis, 92.5% for support vector machines, 92.3% for nearest neighbors, 92.4% for both decision trees, and ensembles over all subjects’ data. Trajectory slopes of CORE vector magnitude and angle: m and m are the best-performing features, along with ensemble classifier with the highest accuracy of 95.3% and minimum computation time of 40 ms. The statistical significance of the results is validated with a p-value of less than 0.05. The proposed passive BCI scheme demonstrates a promising technique for online drowsiness detection using VPA along with sleep stage classification.

Serious study of terrorism requires a proper understanding of why individuals turn extremism md what motivates them to join terrorist organizations. This essay analyzes socio-economic, cultural, religious, and psychological dimensions in a comprehensive framework gauging the "root causes" of terrorism The analysis is based on data collected from Pakistan-based organtations serving as allies of Al-Qaeda. The results indicate that almost all sample resporuients involved in terrorism were unmarried males exposed to fundamentalist teachings of the Qur'an. All believed that if they sacrificed themselves for the sake of their religion, they would be blessed with paradise in life after death. The essay employs relevant models in order to identify empirically the effects of education, an individual's age, household income, and rural or urban residence. The resulting evidence on the individual level suggests that both higher standards of living and education are negatively associated with participation in terrorist activities.

This study aims to investigate the impact of stakeholders’ views on the practices of green innovation, consequent effect on environmental and organizational performance, and moderating influence of innovation orientation. A quantitative method was employed for the sample size of 515 responses. To accumulate the data from the respondents, convenient random sampling was used. Data were collected from manufacturing and services firms through a field survey by using a closed-ended questionnaire based in the Punjab province of Pakistan. The analysis was done using the structural equation model of the partial least square analysis method. Our findings proved a positive and significant link between stakeholders’ views on GI practices. A significant association has been found between GI practices and environmental and OP. The moderating effect was found to be negative but statistically significant. This research offers numerous contributions and provides decision-making insinuations.

Internet of Things-based environments pose various challenges due to their anytime/anywhere computing, and the efficient cryptographic based key management is one of the major challenges in Internet of Things. The key management life cycle consists of initialization, key generation, key registration, key backup, key update, key recovery, and key revocation. Our contribution in this paper is to summarize the state-of-the-art key management schemes and techniques in different scenarios, such as mobile ad hoc networks, wireless sensor networks, and the Internet of Things environments. Further different issues related specifically to the Internet of Things environment are discussed and the causes and effects pertaining to the security breach for Internet of Things are identified. Furthermore, in this research work, we develop a novel permutation of threshold and identity-based key management schemes for the Internet of Things environment and have proposed future directions to counteract the attacks on confidentiality, integrity, authentication, and availability of security services in the Internet of Things environment and identified the two key management schemes, that is, identity and threshold schemes for Internet of Things, to resolve Internet of Things key management issues and maximum possible security services effective implementation. We evaluate our scheme with the help of mathematical and statistical techniques.

Brain-computer interface multi-modal fusion has the potential to generate multiple commands in a highly reliable manner by alleviating the drawbacks associated with single modality. In the present work, a hybrid EEG-fNIRS BCI system—achieved through a fusion of concurrently recorded electroencephalography and functional near-infrared spectroscopy signals—is used to overcome the limitations of uni-modality and to achieve higher tasks classification. Although the hybrid approach enhances the performance of the system, the improvements are still modest due to the lack of availability of computational approaches to fuse the two modalities. To overcome this, a novel approach is proposed using Multi-resolution singular value decomposition to achieve system- and feature-based fusion. The two approaches based up different features set are compared using the KNN and Tree classifiers. The results obtained through multiple datasets show that the proposed approach can effectively fuse both modalities with improvement in the classification accuracy.

Jensen’s inequality is one of the fundamental inequalities which has several applications in almost every field of science. In 2003, Mercer gave a variant of Jensen’s inequality which is known as Jensen–Mercer’s inequality. The purpose of this article is to propose new bounds for Csiszár and related divergences by means of Jensen–Mercer’s inequality. Also, we investigate several new bounds for Zipf–Mandelbrot entropy. The idea of this article may further stimulate research on information theory with the help of Jensen–Mercer’s inequality.

Since the creation of Pakistan the foundation of the Idea of Pakistan has been a matter of academic and political debate. There is a difference between the two spheres. The academic debate allows a room to discuss popular and unpopular ideas and respect the contrary views. The ideology of Pakistan, political system of Pakistan and the constitution of Pakistan have always been discussed and debated amongst scholars. The purpose of this research is to explore the famous presidential address of Allama Iqbal at the annual session of Muslim League in 1930. There are many perceptions about the address delivered by Iqbal, such as he demanded a separate homeland for Muslims of India or not. This research will explore the facts of Iqbal’s speech of Allahabad and will attempt to do justice to his words which have been misinterpreted by some spheres.

Globalization and technological advancement has made market competitive. To survive in market every organization needs to maintain high performance. It can only be possible when the employees working in organization perform more efficiently than competitors. Increase in competition of market has made employee performance a big question to organization for its survival in global competition. Study reveals performance of employee is affected by various component of human resource management i.e. Job satisfaction, leadership, training &development and work stress. HRM is managing people effectively and efficiently to achieve strategic aims of organization. This study focuses on analyzing the impact of HR components on performance of employee. It also compares impact of HR component respect to public and private organizations. The study finds HR components have significant positive relationship with employee performance except work stress. Study also interprets findings irrespective of organization type.

Generally toxic employees are under performers, yet some get better salaries and excel at workplace, getting positioned at higher ranks. This research assesses the relationship between the dark triad (Narcissism, Machiavellianism, and Psychopathy) and perceived victimization with a focus on the mediating effect of abusive supervision and the moderating effect of mindfulness. The data were gathered in three waves. Both the structural equation model with partial least square and Process were used to analyze the data. The study findings suggest that abusive supervision plays a mediating role in the association between the dark triad and perceived victimization. However, the results did not support the mediating role of abusive supervision in the association between narcissism and perceived victimization. Moreover, the findings suggest that mindfulness weakens the effect of abusive supervision on perceived victimization. Furthermore, our findings support the mediated-moderation model. Theoretical and practical implications of the results are also discussed.