Namal University

In recent years, there has been a massive increase in the amount of Internet of Things (IoT) devices as well as the data generated by such devices. The participating devices in IoT networks can be problematic due to their resource-constrained nature, and integrating security on these devices is often overlooked. This has resulted in attackers having an increased incentive to target IoT devices. As the number of attacks possible on a network increases, it becomes more difficult for traditional intrusion detection systems (IDS) to cope with these attacks efficiently. In this paper, we highlight several machine learning (ML) methods such as k-nearest neighbour (KNN), support vector machine (SVM), decision tree (DT), naive Bayes (NB), random forest (RF), artificial neural network (ANN), and logistic regression (LR) that can be used in IDS. In this work, ML algorithms are compared for both binary and multi-class classification on Bot-IoT dataset. Based on several parameters such as accuracy, precision, recall, F1 score, and log loss, we experimentally compared the aforementioned ML algorithms. In the case of HTTP distributed denial-of-service (DDoS) attack, the accuracy of RF is 99%. Furthermore, other simulation results-based precision, recall, F1 score, and log loss metric reveal that RF outperforms on all types of attacks in binary classification. However, in multi-class classification, KNN outperforms other ML algorithms with an accuracy of 99%, which is 4% higher than RF.

The good quality of life, growth, nutrition and development of all living beings directly or indirectly depends upon natural surroundings. Urbanization, agriculture, industrial work and greenhouse effects are the leading causes of the climatic changes all over the world. These climatic changes are responsible to increase Carbon dioxide (CO2) and temperature on surface of the earth every year. All components of environment i.e. air, water and soil are altering mainly due to anthropogenic activities especially with changing life styles. The objective of this mini review is to elaborate the different climate changes, their causes and effects. Generally, climate change refers to any disturbance in climate which can cause negative impacts on living organisms which include humans, plants, and animals, which will be adverse for environment. With increase in population on the earth and industrialization the environment of the world is being disturbed every day. Human is destroying natural resources continuously for his own pleasure and convenience. Due to Carbon dioxide and other dangerous gases expelling from automobiles and industries are continuously poisoning air. Factories are releasing their wastes directly in water bodies without proper treatment and making them unfit for aquatic life. Plants act as filters which trap all pollutants to make environment cool, clean and green. Increase in population multiplication without increasing the plantation would completely damage the quality of life and our society in future. Plants are natural purifier of environment. Due to increasing concentration of carbon dioxide and global warming, temperature of earth is increasing day by day which cause various disorders in environment. The purpose of this review is to highlight climate change which is mostly occurring when there is rise in temperature and CO2 concentration and its impacts on environment. This change in climate is not beneficial rather it causes the damage of an ecosystem. So, human activities are changing the environment adversely. Increasing climate changes have affected life in different aspects. It is concluded that if we don’t plan the strategies to overcome these changes, in coming few years life on the earth will not be an easy task, and situation will be out of hand.

In this paper we examine the impact of the breakout of the conflict between Russia and Ukraine on the G20 and other selected stock markets using the event study approach. The analysis of the abnormal returns (AR) before and after the launch of the ‘special military operation’ by Russian military forces on the 24th of February 2022 revealed a strong negative impact of this military action on a majority of the stock markets, especially on the Russian market. The aggregate stock market analysis indicates a significant and negative impact of the Russia–Ukraine conflict on the event day and post event days. The country-wise analysis demonstrated that the stock markets of Hungary, Russia, Poland, and Slovakia were first to react in anticipation of the military actions in Ukraine, showing negative returns in pre- event days already, whereas the stock markets of Australia, France, Germany, India, Italy, Japan, Romania, South Africa, Spain, and Turkey were adversely affected in the post-invasion days. Finally, the regional analysis indicates that the European and Asian regions are significantly and adversely affected by this event.

The Boussinesq equation simulates weakly nonlinear and long wave approximation that can be used in water waves, coastal engineering, and numerical models for water wave simulation in harbors and shallow seas. In this article, the sine-Gordon expansion (SGE) approach and the generalized Kudryashov (GK) scheme are used to establish broad-spectral solutions including unknown parameters and typical analytical solutions are recovered as a special case. The well-known bell-shape soliton, kink, singular kink, compacton, contracted bell-shape soliton, periodic soliton, anti-bell shape soliton, and other shape solitons are retrieved for the definite value of these constraints. The 3D and contour plots of some of the results obtained are sketched by assigning individual values of the parameter and analyzed the dynamical behavior of the waves. Furthermore, the compatibility of the two approaches has been compared and examined the efficiency to ascertain soliton solutions.

Abstract In this article, we explored the relationship between inclusive leadership and innovative work behavior with the mediating role of psychological empowerment. We collected data from employees in the information technology and cargo sectors within the United Kingdom and Canada. The results revealed that inclusive leadership was positively related to innovative work behavior both directly and indirectly through psychological empowerment. Cognitive evaluation theory was used to support the findings. Implications of the study were discussed.

The degradation of dyes is a difficult task due to their persistent and stable nature; therefore, developing materials with desirable properties to degrade dyes is an important area of research. In the present study, we propose a simple, one-pot mechanochemical approach to synthesize CuO nanoparticles (NPs) using the leaf extract of Seriphidium oliverianum, as a reducing and stabilizing agent. The CuO NPs were characterized via X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence (PL) and Fourier-transform infrared spectroscopy (FTIR). The photocatalytic activity of CuO NPs was monitored using ultraviolet-visible (UV-Vis) spectroscopy. The CuO NPs exhibited high potential for the degradation of water-soluble industrial dyes. The degradation rates for methyl green (MG) and methyl orange (MO) were 65.231% ± 0.242 and 65.078% ± 0.392, respectively. Bio-mechanochemically synthesized CuO NPs proved to be good candidates for efficiently removing dyes from water.

Abstract Medical images possess significant importance in diagnostics when it comes to healthcare systems. These images contain confidential and sensitive information such as patients’ X-rays, ultrasounds, computed tomography scans, brain images, and magnetic resonance imaging. However, the low security of communication channels and the loopholes in storage systems of hospitals or medical centres put these images at risk of being accessed by unauthorized users who illegally exploit them for non-diagnostic purposes. In addition to improving the security of communication channels and storage systems, image encryption is a popular strategy adopted to ensure the safety of medical images against unauthorized access. In this work, we propose a lightweight cryptosystem based on Henon chaotic map, Brownian motion, and Chen’s chaotic system to encrypt medical images with elevated security. The efficiency of the proposed system is proved in terms of histogram analysis, adjacent pixels correlation analysis, contrast analysis, homogeneity analysis, energy analysis, NIST analysis, mean square error, information entropy, number of pixels changing rate, unified average changing intensity, peak to signal noise ratio and time complexity. The experimental results show that the proposed cryptosystem is a lightweight approach that can achieve the desired security level for encrypting confidential image-based patients’ information.

Electrocardiogram (ECG) signals play a vital role in diagnosing and monitoring patients suffering from various cardiovascular diseases (CVDs). This research aims to develop a robust algorithm that can accurately classify the electrocardiogram signal even in the presence of environmental noise. A one-dimensional convolutional neural network (CNN) with two convolutional layers, two down-sampling layers, and a fully connected layer is proposed in this work. The same 1D data was transformed into two-dimensional (2D) images to improve the model's classification accuracy. Then, we applied the 2D CNN model consisting of input and output layers, three 2D-convolutional layers, three down-sampling layers, and a fully connected layer. The classification accuracy of 97.38% and 99.02% is achieved with the proposed 1D and 2D model when tested on the publicly available Massachusetts Institute of Technology-Beth Israel Hospital (MIT-BIH) arrhythmia database. Both proposed 1D and 2D CNN models outperformed the corresponding state-of-the-art classification algorithms for the same data, which validates the proposed models' effectiveness.

In this paper, a novel and miniaturized band-stop frequency selective surface (FSS) is presented. This FSS provides effective shielding in X-band, with attenuation of at least 56 dB. The proposed FSS provides 3-dB fractional bandwidth of 48% which is necessary to cover X-band. Moreover, the proposed design is polarization independent as it provides a stable frequency response at normal and oblique angles of incidences for both perpendicular TE and parallel TM wave modes. The copolarized and cross-polarized scattering parameter S <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">21</sub> is analyzed at the selected band-stop/notch frequencies. More importantly, the proposed FSS is suitable for conformal applications and hence finds wider employability. A prototype of the proposed FSS is fabricated and tested. The measured results are in good agreement with the simulated results.

Sonogashira coupling involves coupling of vinyl/aryl halides with terminal acetylenes catalyzed by transition metals, especially palladium and copper. This is a well known reaction in organic synthesis and plays a role in sp2-sp C-C bond formations. This cross coupling was used in synthesis of natural products, biologically active molecules, heterocycles, dendrimers, conjugated polymers and organic complexes. This review paper focuses on developments in the palladium and copper catalyzed Sonogashira cross coupling achieved in recent years concerning substrates, different catalyst systems and reaction conditions.

Adsorption is one of the promising techniques for the remediation of wastewater and it also offers advantages such as low cost, availability of the adsorbent and ease in operation. The wastewater treatment using smart materials gained much attention and the present investigation evaluated the adsorption efficiencies of ZnO, MgO and FeO for the removal of Direct Sky Blue (DSB) dye. The adsorption affecting parameters, i.e., effect of adsorbent dose, pH, concentration of dye, temperature and contact time were studied in association with dye adsorption. The effect of electrolytes and surfactants was also studied on dye adsorption. The dye adsorption data was analysed using various kinetics parameters, isotherms and thermodynamics models. The maximum adsorption capacities of MgO, FeO and ZnO were recorded to be 46.7, 42.9 and 40.9 mg/g, respectively at the pH 2, adsorbent dose 0.05 g, contact time 75 min, 40 °C and 70 mg/L initial concentration of the dye. The dye adsorption onto MgO followed a Langmuir isotherm, while ZnO followed Temkin isotherm. Langmuir and Temkin isotherms were satisfactory in the case of FeO. Pseudo second order best explained the dye adsorption kinetics. The thermodynamics studies revealed non-spontaneous adsorption of DSB dye onto ZnO, MgO and FeO. In view of promising efficiency, the ZnO, MgO and FeO have potential to apply for dyes adsorption from textile wastewater.

Purpose Through the lens of the leader–member exchange theory, this study assessed the relationship between inclusive leadership (IL) and project success by incorporating the mediating roles of psychological empowerment (PE) and psychological safety (PS). Design/methodology/approach Time-lagged data were collected from 328 employees working in project-based organisations across the information technology industry. Structural equation modelling (SEM) using AMOS 26 was employed for data analysis. Findings By using the SEM approach, the confirmatory factor analysis had verified the distinctiveness of the variables used in this study. The findings displayed that IL increased project success both directly and indirectly through the mediating roles of PE and PS. Originality/value This study addressed two research questions that have been left unanswered in the literature. The initial research question is “how IL enhances project success?”, and this study found that IL enhanced project success. The second research question is “what are the suggested mechanisms for IL to promote project success?” This study has proven that IL enhanced project success through two important mediating mechanisms, namely, PE and PS.

This paper studies the optical soliton solutions of a nonlinear Schrödinger equation (NLSE) involving parabolic law of nonlinearity with the presence of nonlinear dispersion by using the generalized auxiliary equation technique. As a result, new varieties of exact traveling wave solutions have been uncovered, comprising of the hyperbolic trigonometric, trigonometric, exponential, and rational. Interestingly, we obtain the bright, dark, periodic, singular, and other soliton solutions to the nonlinear model. Some of the achieved solutions are illustrated graphically in order to fully understand their physical behaviour. Furthermore, the findings discussed in this present investigation may be useful in explaining the propagation of optical solitons in a weakly nonlocal parabolic law medium.

This study develops a test model that can conceptually contribute to the formation of a green brand image for the hospitality market. A conceptual model highlighting the mediating role of green brand image based on two antecedent constructs (consumer’s perceived functional and emotional benefits of green hotels) and four outcome constructs (green brand preferences, trust, loyalty, and corporate image) was tested using 347 Malaysian lodging consumers. The findings indicate that the increase in consumer’s perceived functional and emotional benefits will initially increase their green brand image, and eventually increase their green brand preferences, trust, loyalty, and corporate image. Moreover, the role of green brand image as a mediator exists between consumers’ perceived benefits and their green brand preferences, trust, loyalty, and corporate image. Based on these findings, the managers can devise green branding strategies for their hotels, and show how green campaigns can highlight ecological concerns among green hotel consumers.

The concept of corporate social responsibility (CSR) has been embedded across psychological and physical frontiers of organizations building up on philanthropy, ethics, regulation, and economy. However, there is a lack of empirical evidence that how CSR gears up various aspects of an organization. The major objective of the present study is to explain the multidimensional catalytic role of CSR in transforming brand equity from brand reputation in the fast-food industry. The study has been designed to get responses through a structured questionnaire to analyze the data through descriptive and inferential statistical techniques. Sample size of 420 consumers and employees of international fast-food chains, located in Pakistan, with diverse demographical profiles have been involved for the survey. Three models were developed to understand the aforementioned phenomenon; the first model examines the impact of brand reputation on brand equity, and the second model reassesses the same relationship with moderating role of CSR, while the third model evaluates the associations with each dimension of CSR. The results indicate that brand reputation is a significant predictor of brand equity, and its predictive power boosts up in the presence of CSR activities. It was also ascertained that CSR initiatives related to ethics, economy, and philanthropy expedite the process of conversion from brand reputation to brand equity. The legal aspect of CSR in developing economies could not prove to be fruitful in this particular context. The research would provide great insight to the managers of fast-food retail chains to evaluate investments for CSR activities in raising equity of their organizations.

Abstract This study examines the relationship between ethical leadership and employee creativity with mediating role of trust in leader and moderating role of openness to experience. Data were collected from 205 supervisor–subordinate small textile firms across Pakistan. Confirmatory factor analysis confirmed the distinctiveness of variables used in our study. The results confirmed that ethical leadership promotes creativity at workplace, while trust in leader mediates the effect of ethical leadership on creativity. Furthermore, the results did not confirm the moderation of openness to experience on the relationship between trust in leader and employee creativity. The implications are discussed.

is not only a new addition to crystallographic data but also possesses good optical and NLO properties for its potential use in lasers and frequency-converting applications.

Metal-organic frameworks (MOFs) are a fascinating class of porous crystalline materials constructed by organic ligands and inorganic connectors. Owing to their noteworthy catalytic chemistry, and matching or compatible coordination with numerous materials, MOFs offer potential applications in diverse fields such as catalysis, proton conduction, gas storage, drug delivery, sensing, separation and other related biotechnological and biomedical applications. Moreover, their designable structural topologies, high surface area, ultrahigh porosity, and tunable functionalities all make them excellent materials of interests for nanoscale applications. Herein, an effort has been to summarize the current advancement of MOF-based materials (i.e., pristine MOFs, MOF derivatives, or MOF composites) for electrocatalysis, photocatalysis, and biocatalysis. In the first part, we discussed the electrocatalytic behavior of various MOFs, such as oxidation and reduction candidates for different types of chemical reactions. The second section emphasizes on the photocatalytic performance of various MOFs as potential candidates for light-driven reactions, including photocatalytic degradation of various contaminants, CO2 reduction, and water splitting. Applications of MOFs-based porous materials in the biomedical sector, such as drug delivery, sensing and biosensing, antibacterial agents, and biomimetic systems for various biological species is discussed in the third part. Finally, the concluding points, challenges, and future prospects regarding MOFs or MOF-based materials for catalytic applications are also highlighted.

In this article, unmanned aerial vehicles (UAVs) are expected to play a key role in improving the safety and reliability of transportation systems, particularly where data traffic is nonhomogeneous and nonstationary. However, heterogeneous data sharing raises plenty of security and privacy concerns, which may keep UAVs out of future intelligent transportation systems (ITS). Some of the well-known security and privacy issues in the UAV-enabled ITS ecosystem include tracking UAVs and vehicle locations, unauthorized access to data, and message modification. Therefore, in this article, we contribute to the sum of knowledge by combining the hyperelliptic curve cryptography (HECC) techniques, digital signature, and hash function to present a privacy-preserving authentication scheme. The security features of the proposed scheme are assessed using formal security analysis methods, i.e., real-or- random (ROR) oracle model. To examine the performance of the proposed scheme, a comparison with other existing schemes has been carried out. The results reveal that the proposed scheme outperforms its counterpart schemes in terms of computation and communication costs.

The purpose of this paper is to explore the relationship between inclusive leadership, Leader-Member Exchange (LMX) and innovative work behavior (IWB) in employees of small capitalized textile firms of Pakistan. We hypothesized that LMX mediates the relationship between inclusive leadership and IWB. We collected data from 150 supervisors-subordinate dyads to test our hypotheses. We selected small capitalized firms because they are more innovative and change-oriented in order to enhance their innovativeness. Moreover, these firms enjoy the benefits of lack of bureaucracy and low resistance to change. Therefore, employees are better able to experience a close relationship with entrepreneurial leaders who tend to be inclusive, in order to facilitate the process of innovation. In line with these facts, our results also suggest that inclusive leadership is positively related with IWB and LMX partially mediates this relationship. The theoretical and practical implications of our findings are also discussed.