Suleiman Ibrahim Shelash Mohammad’s research while affiliated with INTI International University and other places

The study aimed to elucidate the impact of strategic planning on enhancing organizational effectiveness through the investment in human resources as a mediating variable. This empirical research was conducted among employees of the National Investment Authority in Iraq. A descriptive analytical methodology was employed, with the study population comprising 3,022 employees in senior and middle management positions. Among these, 490 held senior roles, while 2,532 occupied middle management positions. A stratified sampling technique was utilized, resulting in a final sample of 352 respondents, representing 11.46% of the valid questionnaires for statistical analysis. A questionnaire was developed as a data collection tool, and the study utilized the Statistical Package for the Social Sciences (SPSS V.24) and the AMOS program for path analysis. Various descriptive and inferential statistical methods were applied. The findings indicated that the respondents' perceptions of the application of strategic planning—encompassing dimensions such as strategic vision, strategic mission, strategic objectives, strategic analysis, and strategic options—alongside the level of organizational effectiveness, were rated as moderate. In contrast, the level of investment in human resources was found to be high.

Hypoxia, characterized by reduced oxygen levels, plays a pivotal role in cancer progression, profoundly influencing tumor behavior and therapeutic responses. A hallmark of solid tumors, hypoxia drives significant metabolic adaptations in cancer cells, primarily mediated by hypoxia-inducible factor-1α (HIF-1α), a key transcription factor activated in low-oxygen conditions. This hypoxic environment promotes epithelial-mesenchymal transition (EMT), enhancing cancer cell migration, metastasis, and the development of cancer stem cell-like properties, which contribute to therapy resistance. Moreover, hypoxia modulates the expression of circular RNAs (circRNAs), leading to their accumulation in the tumor microenvironment. These hypoxia-responsive circRNAs regulate gene expression and cellular processes critical for cancer progression, making them promising candidates for diagnostic and prognostic biomarkers in various cancers. This review delves into the intricate interplay between hypoxic circRNAs, microRNAs, and RNA-binding proteins, emphasizing their role as molecular sponges that modulate gene expression and signaling pathways involved in cell proliferation, apoptosis, and metastasis. It also explores the relationship between circRNAs and the tumor microenvironment, particularly how hypoxia influences their expression and functional dynamics. Additionally, the review highlights the potential of circRNAs as diagnostic and prognostic tools, as well as their therapeutic applications in innovative cancer treatments. By consolidating current knowledge, this review underscores the critical role of circRNAs in cancer biology and paves the way for future research aimed at harnessing their unique properties for clinical advancements. Specifically, this review examines the biogenesis, expression patterns, and mechanistic actions of hypoxic circRNAs, focusing on their ability to act as molecular sponges for microRNAs and their interactions with RNA-binding proteins. These interactions impact key signaling pathways related to tumor growth, metastasis, and drug resistance, offering new insights into the complex regulatory networks governed by circRNAs under hypoxic stress.

Introduction: This study examines the impact of e-learning, digital leadership, and digital innovation on educational performance in high schools, focusing on Jordan's transition to 5G technology. It explores how these factors enhance educational outcomes in a developing country facing technological and infrastructural challenges.Methods: A quantitative approach was used, collecting data from 385 high school teachers in Jordan through a cross-sectional survey. The study employed Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the relationships between e-learning, digital leadership, digital innovation, and educational performance.Results: The findings indicate that e-learning significantly improves educational performance by offering flexible and interactive learning environments. Digital leadership is crucial for guiding digital transformation and fostering innovation, while digital innovation, including AI, VR, and AR, enhances teaching methods and student engagement, leading to better educational outcomes.Conclusions: The study concludes that integrating e-learning platforms, effective digital leadership, and digital innovation is essential for improving high school performance. Policymakers and school administrators should invest in digital infrastructure, provide teacher training, and promote a culture of innovation to prepare students for a technology-driven future. This research offers valuable insights for enhancing educational practices in developing countries like Jordan.

Introduction: this study investigates the impact of 5G technologies, technological and environmental factors, and parental and community support on the educational performance of high school students in Jordan. Educational outcomes must be understood because modern technological systems alongside community involvement need assessment during this COVID-19 era of digital learning tool dependency. Researchers investigate here how educational variables enhance student academic achievements under present-day digital learning models. Method: a survey included 300 students across ten high schools throughout different Jordanian regions. The study relied on Partial Least Squares Structural Equation Modeling as its data analysis foundation through SmartPLS software implementation. A statistical analysis evaluated the link between 5G technologies, technological and environmental factors, and parental and community support which act as independent variables towards educational performance as the main dependent variable. Results: the study showed 5G technologies combined with both technological and environmental factors together with parental and community support have positive effects on educational performance measurement. The analysis through path coefficients and p-values showed that all variables lead to better student learning experiences with positive academic results. Specifically 5G technologies enabled interactive learning but additional student achievement came through digital resource access together with parental involvement. Conclusions: the study summarizes its findings by establishing that inserting 5G technologies together with improved environmental factors and enhanced technological factors plus support from parents and communities actually drives education success. Schools need to focus first on building strong digital infrastructure for learning purposes and secondly on building interconnections between parents and local communities to support student education. The evaluation of these elements' sustained influence on educational outcomes must occur through

Introduction: customer sentiment analysis is a vital tool for understanding consumer preferences and enhancing service quality in the food and beverage industry. Online reviews significantly influence customer decisions, making it essential for businesses to analyze sentiment trends and manage their digital reputation effectively. This study examines customer sentiment across different establishment types and digital platforms in Jordan, providing insights into sentiment patterns and their strategic implications.Method: a dataset of 384 customer reviews from various restaurants and hotels was analyzed using a rule-based sentiment classification approach. Sentiments were categorized as positive, neutral, or negative. To assess sentiment variations, an ANOVA test was conducted to compare establishment types, and a Chi-Square test was performed to examine differences across digital platforms.Results: findings indicate that luxury hotels and fine dining establishments receive more positive sentiment, while budget hotels and fast food chains experience higher negative sentiment. However, the ANOVA test showed no statistically significant sentiment differences across establishment types, suggesting that all businesses receive a mix of sentiment categories. The Chi-Square test confirmed significant sentiment differences across platforms, with TripAdvisor attracting the most positive reviews, Facebook and Google Reviews showing balanced sentiment, and Twitter experiencing the highest negative sentiment.Conclusion: these findings emphasize the importance of platform-specific digital reputation management. Businesses should strategically engage with customers on different platforms, address complaints proactively, and utilize AI-driven sentiment analysis tools to improve customer satisfaction. Future research should explore AI-based predictive analytics and sentiment monitoring for enhancing service quality in the hospitality industry.

This study explores how cybernetic principles—emphasizing feedback loops, self-regulation, and continuous adaptation—can drive shifts in organizational culture, and proposes a fuzzy analytics framework to measure and interpret these changes. Drawing on a mixed-methods case study of a medium-sized technology firm, the research integrates qualitative inputs (interviews, focus groups) with quantitative survey data to assess culture indicators such as Leadership Adaptability, Communication Openness, and Innovative Mindset. Fuzzy logic techniques capture the nuanced, in-between states of cultural phenomena by translating subjective perceptions into membership functions and applying rule-based inference to generate a Culture Shift Index (CSI). Results indicate that organizations with rapid information flow and efficient decision loop mechanisms exhibit more pronounced culture shifts, particularly in leadership responsiveness and communication patterns. However, developing a robust innovative mindset may require additional time and focused interventions. The findings illuminate the value of fuzzy analytics in handling the ambiguity and gradual nature of cultural transformations, offering a richer understanding of how cybernetic feedback loops facilitate or constrain organizational evolution. This study contributes to the theoretical discourse on adaptive organizational systems and provides a practical toolset for managers, HR professionals, and change agents seeking to foster agile and innovation-driven cultures in technologically dynamic settings. Limitations include the potential biases in qualitative responses and the context-specific membership function definitions, suggesting opportunities for future research in diverse and longitudinal scenarios.

Organizational burnout is a major psychological challenge that employees face in the workplace. This issue can lead to reduced performance, job satisfaction, and mental well-being. Various workplace scenarios, such as job stress, organizational culture, and interpersonal interactions, directly influence the occurrence of organizational burnout. In this context, organizational misconduct—including unfair practices, corruption, discrimination, and abuse of professional positions—can act as a mediating factor in this process.This study aims to examine the impact of workplace scenarios on organizational burnout, with organizational misconduct playing a mediating role. The research adopts a descriptive-survey methodology, and data were collected using standardized questionnaires distributed among 24 employees of Ibn Majid Company in Basra of Iraq. The findings indicate that organizational misconduct intensifies the negative effects of workplace scenarios on employee burnout. In other words, in environments with high levels of misconduct, job pressure and unfair interactions significantly contribute to increased burnout.The study suggests that organizations can mitigate burnout by fostering ethical practices, reducing misconduct, and creating a supportive work environment, ultimately enhancing employee mental health and performance.

Phishing attacks continue to pose a significant cybersecurity threat, with over 1.2 million unique phishing sites detected in 2023. Traditional detection methods struggle to keep pace with rapidly evolving phishing techniques, particularly given the short lifespan of modern phishing websites. This paper presents DaE2 (Diverse and Efficient Ensemble), a novel ensemble-based approach for real-time phishing URL detection. Our framework integrates four distinct ensemble methods—AdaBoost, Bagging, Stacking, and Voting—each chosen for their unique strengths in handling different aspects of URL classification. Using a comprehensive dataset of 11,055 URLs with 30 engineered features, we demonstrate that DaE2 achieves 98.7% accuracy while maintaining real-time processing capabilities. The framework shows particular strength in detecting newly created phishing URLs (99.1% accuracy) and handling sophisticated masquerading techniques (98.5% accuracy), while maintaining low false positive rates (1.6%). Performance analysis reveals that our approach outperforms traditional methods by 2.5% in accuracy while reducing processing time by 35% compared to deep learning approaches. The framework's adaptive weighting mechanisms and parallel processing implementation ensure robust performance across varying types of phishing attacks, making it suitable for real-world deployment.

The financial performance of tourism companies in Jordan is significantly influenced by their working capital practices. This study investigates how various working capital management strategies conservative, aggressive, and moderate impact the profitability of hotels and tourism corporations listed on the Amman Stock Exchange. Financial performance is assessed using return on assets (ROA), with company size considered as a control variable. By analyzing data from the financial statements of eight companies over the period 2010–2020 using SPSS, the findings indicate that a conservative strategy negatively affects financial performance, while aggressive and moderate strategies enhance ROA. The study also reveals notable differences in the application of working capital strategies across the sample. Offering empirical evidence from the hospitality sector in an emerging market context, the research underscores the critical role of efficient working capital management. It provides practical recommendations for managers to avoid overly conservative approaches while carefully balancing the risks of aggressive strategies to achieve sustainable profitability in the volatile tourism industry.

The most often occurring kind of cancer globally is skin cancer; melanoma is the deadliest kind. Good treatment results depend on early and correct diagnosis. Dermatologists visually inspect skin cancers as part of traditional diagnostic methods, which can be arbitrary and unreliable. However, recent advances in deep learning show that automated skin cancer identification has a lot of potential. This work presents a new hybrid model for dermoscopic image-based multi-class skin cancer classification. The five steps in our method are: using DeepLabV3+ with a ResNet50 backbone to separate skin lesions; extracting features using a triple-stream transformer-based architecture (Derm-ViT, Swin Transformer V2, and ConvNeXt V2); joining features together; choosing features using the ReliefF algorithm; and classifying with k-nearest neighbors (kNN). Each transformer branch collects a number of different but related parts of skin lesions, such as fine-grained texture information, multiscale characteristics, and patterns that are specific to dermatology. On the ISIC-2019 dataset, which has eight diagnostic categories, our suggested method has 94.42% accuracy, 94.13% precision, 92.99% sensitivity, and 98.96% specificity compared to individual transformer models and state-of-the-art approaches. This result shows how well our hybrid method addresses the difficulties of multi-class skin cancer classification and provides a consistent instrument to support dermatologists in daily clinical work.