Research Journal of Maaref University of Applied Sciences
Research Journal of Maaref University of Applied Sciences (RJMU) / مجلة بحوث جامعة المعارف للعلوم التطبيقية is an open-access, peer-reviewed journal dedicated to promoting knowledge and innovation in applied sciences, engineering, technology, mathematics, social sciences, and humanities, with a commitment to excellence and integrity. The journal provides a platform for publishing high-quality research that addresses pressing challenges and contributes to the advancement of theoretical and applied research in diverse fields. 1. Vision: Research Journal of Maaref University of Applied Sciences (RJMU) aspires to be a leading center for scholarly publishing, innovation, and knowledge dissemination, promoting scientific research, excellence, and impact, and contributing to shaping the future of academic publishing and advancing the frontiers of knowledge across various disciplines and fields of study. 2. Mission: The mission of Research Journal of Maaref University of Applied Sciences (RJMU) is to promote innovation and excellence in scholarly publishing, advance knowledge, foster interdisciplinary collaboration, provide innovative solutions to address pressing challenges in various fields and disciplines, foster a culture of scientific research among academia, students, and society, and make scientific knowledge accessible to all. 3. Journal Objectives: The Journal of Research at Research Journal of Maaref University of Applied Sciences (RJMU) aims to achieve all of the following: Publish high-quality research in various research fields, adhering to the highest standards of academic accuracy and integrity. Stimulate creativity and innovation, foster a culture of curiosity, exploration, and discovery, and contribute to finding comprehensive solutions to research challenges and issues and societal problems. Provide a dynamic platform for researchers, scholars, and academics to share their perspectives and achievements with the global academic community. Promote research and academic collaboration, dialogue, and the exchange of ideas, contributing to the advancement of knowledge and the betterment of humanity. Ensure that research is conducted with integrity and honesty, and encourage researchers to adhere to ethical guidelines. Build a broad network of academic relationships with highly qualified and experienced referees and consultants.
Literature Review: Determinants and Interventions for Optimizing Medication Adherence
This literature review synthesizes recent evidence on the determinants of medication adherence and the interventions most likely to improve it in chronic care. Using the initiation–implementation–persistence framework, it organizes barriers and facilitators across four levels: patient factors (health literacy, beliefs, motivation, mental health), therapy factors (polypharmacy, side effects, dosing complexity), provider factors (communication, shared decisions, follow-up), and system factors (cost, access, continuity, and fragmented services). The review compares intervention approaches, including tailored education, regimen simplification, motivational interviewing, pharmacist-led monitoring, multidisciplinary care pathways, and financial or logistical support. Particular attention is given to digital strategies—SMS reminders, mobile apps, telehealth, electronic refill prompts, and smart packaging—and the conditions under which they succeed or fail. Findings indicate that single, generic interventions rarely sustain adherence; combined, patient-centered and context-sensitive packages perform better, especially when aligned with local resources at Maaref University of Applied Sciences and similar settings, and evaluated with pragmatic outcomes and equity.
Copyright (c) 2026 Research Journal of Maaref University of Applied Sciences
The Views of EFL University Students on English Language Skills and How They Can Improve them
The views of EFL (English foreign language) students are often omitted while preparing the curricula to teach them the English language skills. This study aims to explore what students of English foreign language students think about their English language skills courses i.e., how they view what they are learning and how they can improve their comprehension and overall use. We also wanted to find out what made some students better than others at both learning and practicing these skills. Our methodology includes both qualitative and quantitative research methods in which we interviewed the lecturers and the dorm supervisors and made a questionnaire for the students at the university. We faced some problems that consisted of not being able to reach the female students’ answers and our university only having first- and second-year students. The findings of this study will help both lecturers and students of the English language improve on both ends of the spectrum of learning whether it is helping students know where, how, and what to practice, or helping lecturers and universities make a curriculum more suited to teaching English language skills. The results of our survey highlighted that speaking and listening are tied to being the skill that students find hardest, that listening is the skill they think they need more time with, and that they enjoy listening the most.
Assessment of Knowledge and Awareness of Antibiotic Resistance Among University Students and Academics in Syria
Antibiotic Resistance (AR) has recently attracted the attention of academics and researchers in the field of medicine to be a significant clinical concern and one of the top global public health and development threats. The purpose of this study is to investigate Syrian students’ and academics’ knowledge and awareness of antibiotic resistance. A quantitative research design was employed by administering a questionnaire to obtain the data. The data were analyzed using descriptive statistical methods. The respondents of this study were 210 university students and academics in Syria. This study highlights significant differences in knowledge and awareness of antibiotic resistance between university students and academic staff in Syria. Findings reveal a notable prevalence of misconceptions, including the erroneous belief that the human body, rather than bacteria, develops immunity to antibiotics, underscoring widespread inappropriate antibiotic use. The findings will help attain valuable insights regarding the level of knowledge and awareness of antibiotic resistance.
Reimagining Legal Education: Preparing for an AI-Driven Future
Artificial intelligence is not merely automating legal tasks—it is reshaping the very foundations of how legal knowledge is discovered, structured, and understood. This chapter explores how AI technologies are transforming legal research from a traditionally interpretive and text-driven discipline into a data-rich, algorithm-informed field. We examine the implications of this shift for knowledge creation, focusing on both its promise and its perils. As legal scholars and educators grapple with tools that accelerate analysis but may obscure reasoning, the balance between human judgment and machine logic becomes more urgent than ever. Through critical reflection and real-world examples, the chapter interrogates the evolving epistemology of law in the AI era and considers how legal education must adapt to foster ethically grounded, critically aware, and technologically fluent legal thinkers.
Sustainable Sourcing: How E-Commerce Can Embrace Responsible Procurement
In the rapidly evolving world of e-commerce, procurement decisions shape more than just profit margins—they influence labor conditions, environmental footprints, and societal values. This chapter explores how e-commerce platforms can move from transactional procurement to purposeful sourcing, guided by sustainability principles. It unpacks the complexities of embedding ethical considerations into globalized, tech-driven supply chains and highlights how data transparency, supplier accountability, and stakeholder collaboration are reshaping procurement models. Drawing on emerging best practices and industry examples, it outlines a pragmatic yet aspirational framework for responsible sourcing that aligns with environmental, social, and governance (ESG) goals. By reframing procurement as a lever for positive impact, this chapter calls for a mindset shift—one that sees sustainability not as a constraint, but as a competitive advantage and moral imperative.
Laboratory-Based Investigation of Calcium Hypochlorite as an Antibacterial Agent Against Escherichia Coli and Staphylococcus Aureus
Antibiotic resistance is one of the greatest global public health challenges, driving the need to develop effective alternatives for disinfection and pathogen control. This study aims to evaluate the biological activity of calcium hypochlorite—one of the most widely used disinfectants in medical and food-related fields—against two common pathogenic bacteria: Escherichia coli and Staphylococcus aureus. A purely experimental approach was adopted by exposing both strains to graded concentrations of calcium hypochlorite and assessing the effects through turbidity testing, spectrophotometric absorbance measurements, and colony counts. The results showed a significant reduction in bacterial density with increasing concentration, and high effectiveness of the compound in eliminating both Gram-negative and Gram-positive bacteria, though at varying levels. The study recommends the use of this compound in health and environmental applications within specific concentration ranges, and calls for future research on its effectiveness in complex biological environments.
Evaluation of the Antibacterial Effectiveness of Calcium Hypochlorite Against Escherichia Coli and Staphylococcus Aureus Under Laboratory Conditions
Oxidizing disinfectants are increasingly important in infection-control systems as antibiotic resistance continues to rise and pathogenic bacteria persist in clinical and public environments. This study evaluates the antibacterial effectiveness of calcium hypochlorite against two clinically significant models: Escherichia coli (Gram-negative) and Staphylococcus aureus (Gram-positive), under controlled laboratory conditions. Building on inorganic chemistry, biochemistry, and microbiology, the paper explains how calcium hypochlorite acts through rapid oxidative damage, emphasizing the role of hypochlorite ion chemistry and the formation of hypochlorous acid as a highly reactive antimicrobial species. The analysis links disinfectant performance to bacterial cell-envelope structure, clarifying why Gram-negative and Gram-positive organisms may show different susceptibility to oxidative stress. By integrating mechanistic discussion with laboratory-focused evaluation, the study supports more rational disinfectant selection and dosage decisions for healthcare sanitation, water treatment, and laboratory sterilization, while highlighting areas where molecular-level evidence remains limited and warrants further investigation.
Recycling Polysulfone by Electrospinning and Testing Its Nanofibers in Water Desalination
A polysulfone filter used in a kidney dialysis machine was used. The polysulfone fibers were mechanically, chemically, and thermally treated. Then mixed with an appropriate concentration of PVP. The as mixed dissolved in DMF, taking into account the appropriate viscosity. The solution was electrospinning. The distance between the collector and the spinning needle tip was kept to 15cm, and the applied voltage was 24Kv. The structural and optical properties of the spun mat were studied, and the nanostructure of the mat was confirmed. The mat's effectiveness in absorbing NaCl ions was tested, and it was found that a 0.057mm thick mat removed 22% of the salinity, confirming its potential as a seawater desalination filter when used with other polymers such as polyamides.
World Englishes and Lingua Franca: Rethinking English Language Teaching in the Classroom
This paper examines English as a lingua franca (ELF) within the framework of World Englishes. It reviews Kachru’s model and highlights its contribution to the recognition of English in its global use. The paper also highlights the limitations of the model in representing the complex realities of global English use. It focuses on English language teaching and critiques the native versus non-native dichotomy. The paper explores which variety of English should be taught in classrooms, emphasizing that learner needs and communicative effectiveness should guide the contemporary ELT (English Language Teaching) practices and that they are more important than adhering to the native-speaker norm.
“The Will to Power” as a Source of Transformation: A Psychological and Philosophical Assessment
This paper examines Friedrich Nietzsche’s concept of the will to power as a fundamental source of psychological and philosophical transformation. Rather than treating the will to power solely as a metaphysical doctrine or a theory of domination, the study advances an interpretation that emphasizes its role as a dynamic principle of self-overcoming and life-affirmation. Through close engagement with Nietzsche’s major texts and contemporary scholarship, the paper explores the diverse interpretations of the will to power, metaphysical, psychological, ethical, and cultural. The study also highlights how the will to power functions as an organizing structure of drives that enables self-mastery and the creative revaluation of values. Special attention has been given to Nietzsche’s response to nihilism, showing how the will to power operates as a generative force that transforms despair into affirmation and passivity into creativity. The paper also addresses major criticisms of the concept concerning egoism, elitism, and domination. Ultimately, the study argues that Nietzsche’s will to power offers a compelling framework for understanding transformation as an ongoing process of self-creation and existential affirmation, rather than as a fixed moral or metaphysical principle.
Struggle Between Accuracy and Fluency in Teaching Online
This study examines the academic tension between language precision and verbal proficiency within synchronous virtual language instruction. The digital sphere initiates unique restrictions, such as audio delay and limited non-verbal signals, which confuse the slight balance between immediate error feedback and continuous verbal output. This research highlights the particular obstacles learners face in developing fluency without paying attention to grammatical precision, a struggle frequently aggravated by the technological constraints of online engagement through virtual sessions. It further examines adaptive methods, such as employing text dialogue, for instance, gentle feedback, and influencing independent tools for comprehensive precision work. The results show that efficient digital learning necessitates an adjusted technique to the correction process, supporting multimodal assessment methods that enhance learners’ confidence and communicative implementation while efficiently tackling linguistic proficiency.
Teaching Languages Online: Targeting the Four Skills Efficiently
The digital technology has transformed language education, necessitating a reassessment of pedagogical perspectives to efficiently teach the four skills of language: listening, speaking, reading, and writing. This research paper emphasizes that online language instruction can be enhanced by integrating interactive tools, encouraging the independence of the learner, and fostering authentic communication. A comprehensive literature review underscores the challenges and opportunities presented by online platforms, focusing on the need for a balanced approach that tackles all four skills. The methodology used includes a qualitative analysis of current online language programs and interviews with educators to recognize best practices. Results show that effective online language teaching methods include multimedia resources, synchronous and asynchronous activities, and collaborative projects that engage learners in meaningful communications. This study highlights the value of flexibility in instructional design, promoting a customized approach that reflects individual learner needs and inclinations. The conclusion claims that while online language teaching introduces distinctive challenges, it also provides unique opportunities for skill development when approached with intentionality and innovation. Future research should concentrate on progressive studies to evaluate the long-term efficiency of online language instruction in developing competence across all four skills.
The Conversational AI Revolution: A Personal Perspective on Multilingual Education
The landscape of modern education is undergoing a revolutionary shift, driven by the rapid evolution of artificial intelligence. As someone observing the intersection of technology and linguistics, I believe we are currently witnessing a Conversational AI Revolution that fundamentally redefines how we approach multilingualism in the classroom. The traditional hurdles of linguistic diversity—once seen as complex logistical challenges—are now being reframed as opportunities for hyper-personalized growth.
Educational Linguistics: A Problem-Oriented Discipline Bridging Language, Education, and Policy
Educational linguistics is a specialized subfield of applied linguistics that examines the role of language in educational contexts and seeks to improve teaching, learning, and policy through linguistically informed practices. Emerging in response to the limitations of traditional language education, the field integrates insights from linguistics, education, sociology, psychology, and language policy studies. This paper explores the theoretical foundations, historical emergence, and defining characteristics of educational linguistics, emphasizing its problem-oriented, practice-focused, and policy-driven nature. Particular attention is given to the role of language inspectors as key stakeholders who operationalize educational linguistics through classroom observation, instructional coaching, assessment support, and professional development. The paper argues that educational linguistics provides a critical framework for addressing linguistic diversity and effectiveness in contemporary education systems.
The Influence of AI Tools and Gamification in Teaching Online: An Analysis of Pros and Cons
This paper tackles the positive impact of Artificial Intelligence (AI) and gamification on the effectiveness of online education. The integration of AI-driven tools, such as dynamic algorithms and intelligent instructional platforms, improves personalization by adjusting the material to suit students’ requirements while automating executive tasks. Nowadays, gamification approaches, employing mechanics like badges, points, and leaderboards, efficiently increase essential motivation, involvement, and cognitive recall by creating collaborative experiences instead of a passive educational approach. These methods build flexible, evolving environments that enhance the learning flow when incorporated. Nonetheless, the paper also tackles fundamental challenges, such as algorithmic prejudice, data privacy issues, and the risk of memorization-focused learning through over- dependence on external incentives. The results of this paper advocate that since AI and gamification support the ability of innovation for virtual classrooms, a well- adjusted, morally-based implementation setting is crucial to maximize educational consequences and confirm fair opportunities.
Discourse Analysis and Language Teaching
This paper examines how discourse analysis can strengthen language teaching by moving beyond sentence-level grammar toward language as purposeful social action. In English Language Teaching, teachers are expected to keep pace with expanding methods and research, and discourse analysis offers a practical lens for connecting form, meaning, and context in both spoken and written communication. By working with authentic texts and interaction, teachers can help learners notice how cohesion, turn-taking, stance, and politeness shape interpretation and relationships. The paper outlines key concepts, contrasts discourse-based and sentence-based approaches, and proposes classroom applications such as guided text exploration, interactional tasks, and reflective feedback. Emphasis is placed on developing learners’ communicative repertoire and appropriacy across settings. The discussion concludes that discourse-informed pedagogy supports fluency, motivation, and transfer of classroom learning to real-world communication. It gives teachers a principled basis for task-based work.
Disability Transformation to Capability by Advancement of 3D Bioprinting prosthetics
Millions of people with disabilities suffer from the shortage of their daily life functions due to the lack of prosthetics that are related to their high costs and the short life of the traditional prosthetics; most of them lost their work opportunities and experienced many bad psychological effects. The traditional prosthetics are made from metals or composites and offer the users limited functions, whereas the printed prosthetics by the additive manufacturing process offer them highly durable and functional parts, especially when printed from bio materials, which made a real big forward step in the prosthetics manufacturing. Additive manufacturing is the technique of building the product layer by layer from the material filament with good stiffness and strength, which was a reason to shift from mechanical prosthetics to regenerative and intelligent systems.
Rehabilitation outcomes and accessibility
Coaxial Electrospinning of Tin Oxide to Improve Its Gas-Sensitive Properties
SnO2 porous nanofibers doped with Cu were prepared using coaxial electrospinning technology. A solution of SnCl4 with [(5%) Cu(ch3coo)2] was spun with a quantity of organic polymer PVA at a concentration of 15% (w/v), used as the core, and confined with a PVA solution at the same concentration to form the shell. The applied electric potential was 24KV. Core and shell were spooned on collector formed from glass slides on aluminum foil. The spun fibers were heat-treated at 350°C to obtain (SnO2/Carbon) porous nanofibers. The energy band gap was calculated from the UV-VIS absorption spectrum, and it was found to be 2.86 eV. Atomic force microscopy (AFM) images were acquired to study the morphology of the (SnO2/Cu/Carbon) porous nanofibers. and the nanofiber diameter and surface roughness were calculated. The operating temperature of the prepared sensor was measured. The sensor's sensitivity was tested for H2S and H2 gases.
From Error to Expression: A New Approach for ESL Learners
From Error to Expression reframes ESL writing development as bridge-building rather than error hunting. Instead of treating learners’ first languages as interference, it treats them as cognitive assets that carry logic, nuance, and rhetorical energy. Many apparent “errors” are systematic transfers: students apply L1 grammar, word order, or omission rules to English, so their ideas are often correct even when the form is not. The article proposes a teachable routine: validate the learner’s logic, then retrain the English habit through contrastive examples. It also addresses discourse rhythm, showing how inductive styles may sound “circular” to English readers, and offers a simple paragraph map to reorganize ideas without erasing cultural voice. Practical strategies include “think in L1, translate the core idea, then build the English structure,” and feedback that explains why a choice happened while modeling the target form. Ultimately, accuracy should serve meaning and voice for confident academic communication worldwide.
Geo-Economic Pathways to Peace: Innovative Domestic Business Functions for Resilient Economies with Zero Tariff
In the current global economic environment, rising tariff barriers and widening business gaps are creating significant inequalities between countries, reducing cooperation, and intensifying competition rather than shared progress. Against this backdrop, this research proposes a geo-economic strategy aimed at achieving the highest welfare point in international trade through a zero-tariff mechanism that avoids losses for any participating economy. The model establishes that an exporting economy may receive zero-tariff access only when it first preserves and supports the importer’s existing domestic manufacturing capacity. If the importer currently produces a certain volume of goods, the exporter must ensure that this same level is manufactured within the importer’s economy before supplying any additional volume from its own production. In addition, the exporter must provide direct assistance to the importer’s existing manufacturers to sustain their operations. The framework also allows multiple raw-pattern companies from the exporting economy to operate within the importer’s market, giving individuals a broader range of choices and enabling them to obtain the most affordable and efficient products. Furthermore, by hosting these collaborative activities and manufacturing extensions, the importer economy gains the opportunity to transform itself into a business hub, strengthening its internal capacity and attracting wider investment. Overall, this research presents a practical international zero-tariff model that reduces global economic gaps, protects domestic industries, expands consumer options, and builds a more stable and mutually beneficial geo-economic foundation.
Modern Problems and Prospects of Digital Accounting Transformations in Syria
This study analyzes the current state of accounting in Syria, with an emphasis on identifying the key challenges associated with the transition to a digital economy. It examines the features of the traditional accounting system, the impact of digital technologies on financial control and transparency, as well as the role of artificial intelligence, blockchain technology, and cloud platforms in modernizing accounting processes. Particular attention is paid to the need to update the regulatory framework, create a unified digital infrastructure, and train qualified personnel. The paper presents tables illustrating the advantages of blockchain technologies, as well as the stages of digital transformation.
This study investigates the impact of the internet era on the transmission of Noble Hadiths, focusing on the authenticity and reliability of digital platforms compared to traditional sources. Rooted in a long tradition of meticulous preservation, Hadith sciences emphasized accurate transmission through critical evaluation of narrators and texts. Today, however, social media and online databases facilitate widespread but often unchecked circulation of Hadiths, including fabricated or erroneous narrations. To assess this phenomenon, the research employed a structured questionnaire completed by 312 participants of diverse educational and geographic backgrounds, alongside a comparative analysis of two well-known Hadiths across printed editions and digital platforms. Results revealed that nearly half of the respondents lacked printed Hadith books, with most relying instead on online sources. While many participants exhibited caution by verifying Hadiths, trust in digital platforms was moderate, and discrepancies between online and printed texts were frequent, including typographical errors, altered wording, and omissions. Comparisons confirmed that printed sources largely maintained consistency, while online sources introduced notable variations. These findings underscore both the awareness among Muslims of the importance of accuracy and the risks posed by unregulated online transmission. The study concludes with a call for greater scholarly oversight and standardized mechanisms to safeguard Hadith sciences in the digital age.
Internet-era challenges in Hadith sciences
Integration of Artificial Intelligence and Big Data Analysis: Towards a Smarter Decision-making Policy
This study examines the relationship between artificial intelligence also it's checking the integration with other technologies. This research aims to explore the complementary relationship between artificial intelligence (AI) and big data analytics, analyzing how each can benefit from the other to enhance the accuracy of analyses, decision-making, and the extraction of broadly applicable insights. The research relied on a descriptive methodology through a review of previous literature and practical applications in sectors such as healthcare, finance, e-commerce, and smart cities. The current era is witnessing a massive surge in the volume of data generated from various sources, posing a significant challenge in extracting valuable insights from it. This research explores how artificial intelligence technologies, such as deep learning and machine learning, can be integrated with big data analytics systems to address these challenges. This study seeks to improve data processing efficiency, increase the accuracy of predictive models, and enable intelligent, real-time decision-making. Through a systematic analysis of the latest literature, the research highlights the anticipated benefits of this integration and discusses the associated technical, legal, and ethical challenges, such as privacy, transparency, and energy consumption
Hybrid Random Forest and XGBoost Approach for Android Malware Detection
Android malware continues to pose a serious threat to mobile security, frequently evading traditional signature-based detection techniques and compromising sensitive user data. While signature-based approaches are effective against known malware, they struggle to identify obfuscated and evolving threats. To address these limitations, this paper proposes a hybrid machine-learning framework for Android malware detection that integrates Random Forest and XGBoost classifiers. The model relies on static features, specifically API calls and application permissions, which are highly indicative of malicious behaviour. Experiments are conducted using the CIC-AndMal2017 dataset, consisting of labelled benign and malicious Android applications. A systematic feature-selection process is applied to retain the most informative API and permission features. Dimensionality reduction using t-Distributed Stochastic Neighbour Embedding (t-SNE) is employed to improve computational efficiency while preserving meaningful patterns in the data. Experimental results demonstrate that the proposed hybrid model achieves an accuracy of 91.20%, outperforming individual classifiers. The findings highlight the effectiveness of ensemble learning, optimised feature selection, and dimensionality reduction in building scalable and accurate Android malware detection systems.
Effectiveness Extent of Internal Control System in Small and Medium-Sized Enterprises (An Empirical Study in Syria)
This research aims to study the effectiveness of the internal control system in small and medium-sized enterprises (SMEs) in Syria through An Empirical Study. To achieve the research objectives, a questionnaire consisting of 36 questions was designed to measure the perceptions and understanding of the research sample regarding the effectiveness of internal control systems in Syrian SMEs. The questionnaire was distributed to internal auditors, accountants, and senior management in the studied SMEs. Purposive sampling was used in distributing the questionnaire, resulting in the distribution of 62 questionnaires and the receipt of 53. Upon reviewing these questionnaires, 3 were found to be incomplete and unsuitable for analysis, and were therefore excluded. Consequently, 50 questionnaires, representing 80.6% of the total distributed questionnaires, were deemed suitable for statistical analysis.
Small and Medium-Sized Enterprises (SMEs)
Comparative Analysis of Objective Functions in PSO-PID Control for BLDC Motor Speed Regulation
Brushless DC (BLDC) motors are fundamental in applications such as electric vehicles and robotics, where precise speed regulation is crucial. This study presents a BLDC motor speed control system based on a PID controller optimized using Particle Swarm Optimization (PSO). The system was simulated in MATLAB/Simulink under three speed levels (low, medium, high) and three load conditions (no load, half load, full load), with a comparative evaluation of four objective functions: Integral of Time Absolute Error (ITAE), Integral of Time Squared Error (ITSE), Root Mean Squared Error (RMSE), and a hybrid ITAE+ITSE. A total of 720 experiments were conducted and assessed using five performance metrics: rise time (Tr), settling time (Ts), maximum overshoot (Mp), steady-state error (Ess), and mean value of speed after settling time. Results demonstrated that ITAE outperformed the other objective functions in minimizing rise time, settling time, and steady-state error, achieving a rise time of 0.00087 s at high speed, a settling time of 1.6992 s at medium speed, and a steady-state error of 0.6178% at medium speed. However, other objective functions showed superiority in certain cases for specific performance indices. Overall, RMSE exhibited weaker performance, particularly in settling time and steady-state error. These findings highlight the significance of selecting an appropriate objective function and its impact on the quality of BLDC motor speed control, providing valuable insights for designing efficient PSO-PID controllers for practical applications.
Design and Experimental Evaluation of EKF-LQR Navigation on Raspberry Pi for Autonomous Mobile Robots
Accurate and robust navigation is essential for autonomous mobile robots operating in dynamic, GPS-degraded environments. We propose and validate a low-cost navigation framework implemented on Raspberry Pi, combining an Extended Kalman Filter for sensor fusion with a Linear Quadratic Regulator for optimal control. Unlike previous implementations, our system achieves real-time performance on resource-constrained hardware through computational optimization, maintaining localization accuracy during extended GPS outages of up to 30 seconds. The EKF fuses measurements from GPS, IMU, optical flow, and wheel encoders to provide reliable localization, while the LQR minimizes trajectory tracking error and control effort. Field experiments demonstrate that the proposed EKF–LQR approach achieves a Mean Square Error of 2.9 m², outperforming GPS-only and dead reckoning methods by 66% and 81%, respectively.
The Communication Gap in Between Humans and Robots
The increasing integration of robots and AI systems into everyday life has made effective human-robot communication a crucial area of research. Despite the rapid advancement in AI technologies, a signif-icant gap persists between human expectations and the actual communicative capabilities of robots. This study explores the factors contributing to this communication gap by combining a systematic re-view of literature with expert perspectives. Ten empirical studies published between 2015 and 2025 were analyzed, focusing on the core dimensions of trust, empathy, contextual nuance, and interaction quality. Additionally, semi-structured interviews were conducted with five academic experts in artificial intelligence, robotics, and related fields to complement the literature findings. The results indicate that current AI systems face substantial limitations in emotional understanding, contextual interpretation, cultural and linguistic variations, and trust-development. Although robots can recognize patterns such as facial expressions and speech, they may lack human-like emotional understanding which limits the quality of interaction. Many experts have confirmed that misunderstandings or misinterpretations of-ten arise from the ambiguity in natural-language communication and an overreliance on language-only interaction. Overall, the findings suggest that technological advancements alone are insufficient to bridge the communication gap.
A New Beginning for Knowledge Without Borders
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