National University of Modern Languages

The Internet of Healthcare Things (IoHT) is an emerging technology that has attracted researchers’ interest due to its broad applicability in recent years. In IoHT platforms, sensors continually collect patient data, which most of the time contains normal readings, and send it to the cloud via intermediate devices. In an emergency, a large amount of data may rapidly fill network queues, causing congestion and data loss. It has significant consequences, particularly in time-sensitive healthcare applications. To solve this issue, the suggested approach minimizes data transfer by transmitting a Boolean value if no emergency is identified or the patient’s health parameters are normal. The aforementioned Boolean value is far less in size and takes much less time to process data, significantly decreasing the cache’s burden and freeing it up for unforeseen emergency data. This approach aims to improve the efficiency of packet data handling. This ensures that high-priority, critical data packets are processed immediately. Furthermore, after transferring 20 packets via Boolean values, the system then sends the entire data packet to keep track. This balanced strategy reduces unnecessary data traffic, alleviates network congestion, and ensures that vital information is processed on time. By reducing cache use and prioritizing emergency packets, the suggested solution improves the overall performance of the IoHT system and enhances patient safety by preventing the loss of critical data. A large number of simulations are performed on Ubuntu using NS-2.35. The results show that the proposed scheme outperforms in terms of communication cost, throughput, packet loss, and delay during an emergency.

This study examines how Pakistani youth use language on social media platforms to construct and express their identities. With the rapid growth of digital platforms like Instagram, TikTok, Facebook, and X (formerly Twitter), young people in Pakistan have found new spaces to communicate, interact, and present themselves to the world. This research uses a qualitative approach with discourse analysis to study approximately 50 public social media posts, captions, and comments created by Pakistani youth aged 18 to 30 years. The study is guided by Identity Construction Theory developed by Bucholtz and Hall (2005), which views identity as something people actively create through language rather than something fixed. The analysis looks at language features such as code-switching between English and Urdu, Roman Urdu writing, slang expressions, internet abbreviations, emojis, and memes. The findings reveal that Pakistani youth use these linguistic practices to balance global and local identities. They present themselves as modern and educated through English, while using Urdu and regional languages to show cultural belonging and emotional connection. The study also finds that different social media platforms influence language choices in different ways. This research contributes to understanding how digital communication shapes youth identity in multilingual societies like Pakistan and provides useful insights for educators, researchers, and policymakers.

Abstract The sustainability of public health systems relies heavily on the mental health and well-being of the healthcare workforce. In resource-constrained settings like South Punjab, Pakistan, excessive job demands pose a significant risk to both employee welfare and the quality of healthcare delivery. This study examines the impact of job demands on job performance, specifically investigating the mediating role of emotional exhaustion as a critical determinant of public health service effectiveness. Grounded in the Job Demands–Resources (JD-R) model and Effort–Reward Imbalance (ERI) theory, this research utilized a quantitative cross-sectional design. Data were collected through a structured questionnaire administered to a purposively selected sample of 249 healthcare professionals, including doctors, nurses, and paramedical staff, from public sector institutions. Structural Equation Modeling (SEM) using the Partial Least Squares (PLS) technique was employed to test the hypothesized relationships. The findings indicate that high job demands exert a significant positive effect on emotional exhaustion (β = 0.835), which subsequently degrades job performance. Emotional exhaustion was found to significantly mediate the relationship between job demands and performance (β = 0.426), suggesting that workforce burnout is a primary pathway through which systemic pressures undermine healthcare service quality.

Background: Academic stress remains a pervasive challenge in higher education, often leading to diminished mental health and poor pedagogical outcomes. While Emotional Intelligence (EI) is recognized as a protective resource, the underlying mechanisms specifically how EI translates into stress reduction through behavioral shifts and environmental buffers; remain under-explored. Methods: This study utilized a cross-sectional research design with a sample of 520 university students recruited via stratified sampling. Data were collected using validated instruments: the Wong and Law Emotional Intelligence Scale (WLEIS), the Perception of Academic Stress Scale (PASS), the Brief-COPE, and the Multidimensional Scale of Perceived Social Support (MSPSS). Data analysis was performed using IBM SPSS AMOS v.26 to conduct Confirmatory Factor Analysis (CFA) and path analysis with 5,000 bootstrap resamples. Results: The structural model demonstrated an excellent fit (X2/df = 2.14, CFI = .97, TLI = .96, RMSEA = .041). Findings revealed that EI exerted a significant negative direct effect on academic stress (p < .001). Furthermore, adaptive coping strategies partially mediated this relationship, explaining 24% of the variance in stress reduction. Multigroup analysis in AMOS indicated that Perceived Social Support significantly moderated the path between EI and stress, such that the stress-buffering effect of EI was significantly amplified in students reporting high levels of social support. Conclusions: These findings suggest that emotional literacy is not a standalone solution; its efficacy is contingent upon the deployment of specific coping behaviors and the presence of a supportive social environment. Implications for university counseling and policy are discussed.

The artificial intelligence (AI) chatbots are embraced prevalently in human lives in this digital era. Consequently, has restructured how emerging adults interdepend, pursue support, and undertake emotional needs. The study surveyed the relationship between perceived empathy of AI chatbots, social disconnection, and AI dependence among emerging adults in Pakistan. The study hypothesized that perceived AI empathy would positively predict AI dependence and negatively predict human connection; dependence on AI Chatbot mediate the relationship between perceived AI empathy and social disconnection. A correlational research design was used. A sample of emerging adults (N=242) concluded using uniform measures: the Interpersonal Reactivity Index–Empathic Concern Subscale (Davis, 1983); Generative AI Dependency Scale (Goh et al., 2025), and Social Connectedness Scale (Lee et al., 1995). The outcomes showed significant associations among Perceived Empathy of AI Chatbots, social disconnection and AI Dependency: with AI dependence somewhat mediating the link between perceived empathy and diminished human connection. Results highlighted that the artificial available of empathy has impacts among emerging adults in developing an increased social disconnection. The study suggested the implications for digital well-being and future policy making for safe use of digital space without staking social interactions.

This article discusses how power dynamics, national interests and security concerns determine the Palestine-Israel conflict, through the two sides’ actions. The study draws on principles of realist thought, including the sovereign voice of the state, the balance of power and self help in evaluating historical and contemporary motivating forces for the conflict. This examines the link between Israel’s efforts for territorial security and Palestinian pursuit of statehood as being predicated on opposite national interests. The article makes use of secondary sources and uses a qualitative analysis to show the importance of military strength, alliances and regional instability. The pragmatic lens of realist perspective helps explain the persistent deadlock because both parties care extremely about survival and self interest and not willing to cooperate. In the end, the article makes the argument that any lasting peace in the region cannot be addressed without resolving these core realist concerns.

Advanced Driver Assistance Systems (ADAS) and Collision Avoidance Systems (CAS) are the primary modules of modern human-centric and autonomous driving applications, such as forward and rear-end collision warnings. To enhance the performance of ADAS and CAS systems in foggy weather, an Efficient and Cost-Effective Vehicle Detection and Tracking with Driver Assistance (ECE-VDTDA) system is proposed. The proposed ECE-VDTDA system comprises vehicle detection, tracking, and driver assistance modules. An optimized SimYOLO-V5s_WIOU vehicle detection algorithm is proposed, based on the SimSPPF module, the baseline You Only Look Once (YOLO) algorithm (YOLO-V5s), and the Wise Intersection Over Union (WIOU) localization loss function. State-of-the-art Deep-SORT, Strong-SORT, and optimized Deep-SORT algorithms are utilized for vehicle tracking. The vehicle detection and tracking performance of the ECE-VDTDA system is rigorously evaluated on DAWN, foggy driving, foggy cityscapes, BDD100K, web-collected, and self-collected foggy weather datasets. Optimized SimYOLO-V5s_WIOU algorithm outperformed on the foggy driving dataset with a 17.45% increase in mAP50, and foggy cityscapes dataset with a 0.32%, 1.05%, 1.58%, 2%, 0.54% increase in the multiclass mAP50, mAP50-95, F1 score, precision, and recall scores, respectively, compared to the baseline YOLO-V5s. Furthermore, the SimYOLO-V5s_WIOU algorithm also outperformed the state-of-the-art methods and enables Deep-SORT, Strong-SORT, and optimized Deep-SORT vehicle tracking algorithms to track vehicles with high confidence. The driver assistance module of the ECE-VDTDA system helps prevent imminent road collisions in foggy weather by estimating distance, speed, and time-to-collision and by issuing timely collision warnings. The experimental results demonstrate the robustness and computational efficiency of the proposed ECE-VDTDA system.

Sustainable Supply Chain Management (SSCM) has become one of the critical strategies in an organization whereby environmental, social, and operational responsibility have been incorporated in the supply chain processes. Although the importance of SSCM to enhance the efficiency and sustainability performance of an organization is not new, the role it has on the welfare of workers especially work-life balance continues to present an area of concern in research. This paper focuses on sustainable supply chain management and work-life balance in relation to bank employees in Pakistan. The quantitative research design was taken and data was gathered on 300 employees working in different commercial banks using a structured questionnaire. The relationship between the variables was studied using statistical methods such as descriptive analysis, correlation analysis and regression analysis. The results indicated that sustainable supply chain management positively influenced greatly the work-life balance of employees. The findings showed that good sustainable supply chain practices enhance the efficiency of operations, ease unnecessary workloads strains, as well as provide organized and supportive working conditions. The correlation analysis revealed the presence of a strong positive correlation between sustainable supply chain management and work-life balance whereas the regression analysis indicated that sustainable supply chain management is an important predictor of employee work-life balance. These results indicate that sustainability conscious organizational behaviors do not only emerge in the operational performance but also in the wellbeing of the employees. The paper finds that sustainable supply chain management is a critical component of enhancing employee work-life balance through enhancing the work processes in an organization and minimizing the work stress. The results are useful to the bank management and policymakers to incorporate sustainability in the organization strategies to improve the welfare of the employees and organizational performance. The strategic approach of developing efficient, responsible and people-oriented organizations, sustainable supply chain management may be used.

Although the robustness of optical flow field has been improved over the past few years, the problems of blurring motion boundaries and ill-defined edges have remained unsolved challenges in optical flow estimation. Variational optical flow estimation methods may not handle the abovementioned problems since the local filtering-based optimization may cause the problem of blurring motion boundaries. In this chapter, to address the issues of blurring motion boundaries and improve the robustness of optical flow, we propose a new nonlocal total variation (NLTV)- L 1 optical flow estimation method based on a weighted guided filter (named NLTV- L 1 +WGF). The WGF is based on a linear model, which is computationally efficient and edge-preserving under complex outdoor scenarios (i.e., haze, fog, etc.). The NLTV- L 1 optical flow estimation method is refined by employing the WGF in a nonlocal term and then optimized using the coarse-to-fine strategy. We evaluate the performance of the proposed NLTV- L 1 +WGF optical flow estimation method on two popular optical flow datasets (i.e., the Middlebury dataset and the MPI-Sintel dataset) and on several other outdoor complex datasets (i.e., the Foggy Zurich dataset and the Traffic dataset). Moreover, we evaluate the proposed method in a more complex scenario for the task of ant behavior study. It is challenging to perceive the motion and interactions of ants because the size of ants is small, they usually move quickly, and they may not move for a long period. Experimental results show that the proposed NLTV- L 1 +WGF method can preserve the edges of moving objects and improve the accuracy of optical flow estimation compared with several other state-of-the-art optical flow estimation methods.