Search
997 articles for “Precision”
-
Role of Fluid Engineering in Biomedical and Healthcare Systems: A Comprehensive Review
Abstract: Fluid engineering — the study and application of fluid behavior, transport, and interaction — has become a cornerstone of modern biomedical and healthcare systems. This review synthesizes the multifaceted roles fluid engineering plays across diagnostics, therapeutics, biomedical devices, and physiological modeling. Micro-fluidics enables precise manipulation of microliter and nanoliter volumes, facilitating rapid point-of-care diagnostics, high-throughput screening, and the fabrication of uniform nano particles for targeted drug delivery. In cardiovascular medicine, …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–5 Read article
-
Firefly Algorithm–Based Optimization of Processing Parameters for Enhanced Performance of Polymer Composite Materials
Abstract: Polymer composite materials are extensively used in aerospace, automotive, and oil & gas applications due to their high strength-to-weight ratio and design flexibility. However, achieving optimal mechanical and thermal performance strongly depends on precise control of processing parameters such as curing temperature, energy consumption, and material utilization. Conventional trial-and-error approaches often lead to excessive energy usage, non-uniform curing, and sub-optimal composite properties. To address these challenges, this paper proposes an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 90–107 Read article
-
Intelligent Brain Tumor Diagnosis with AI-Based Classification* * Harnessing Deep and Machine Learning for Tumor Identification
Abstract: Brain tumors have become a leading cause of cancer- related deaths, posing significant health risks to many patients. This urgent medical challenge calls for rapid, automated, and reliable techniques to detect brain tumors accurately. Timely and precise tumor identification is crucial for devising effective medical plans that have the potential to save lives and improve patient outcomes. By leveraging advanced image processing methods, healthcare professionals can enhance their diagnostic capabilities …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
-
A Gamified Digital Platform for Sustainable Farming Practices: Simulation, Statistical Analysis, and Water Resource Management Implications
Abstract: Sustainable farming practices play a critical role in enhancing agricultural water use efficiency, conserving limited water resources, and ensuring long-term food security under increasing environmental and climatic pressures. Despite their importance, farmer participation in conventional agricultural extension and training programs remains limited due to low engagement and a lack of sustained motivation. To address this challenge, this study proposes a gamified digital decision-support platform aimed at promoting sustainable agricultural and …
Published in Journal of Water Resource Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 13–24 Read article
-
AI-Powered Drug Delivery: Revolutionizing Formulation Science
Abstract: Artificial Intelligence (AI) is emerging as a groundbreaking tool in revolutionizing Drug Delivery Systems (DDS), offering promising advancements in precision, efficiency, and personalized treatment strategies. The integration of AI technologies into pharmaceutical research and development is transforming how drugs are formulated, delivered, and monitored in real time. By leveraging machine learning algorithms and data analytics, researchers can design drug delivery models that are not only more effective but also tailored …
Published in Trends in Drug Delivery · Vol. 13, Issue 1, 2026 · pp. 48–61 Read article
-
ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
-
Exploring the Impact of Process Parameters on 3D Printing: A Comprehensive Review for Enhanced Product Quality
Abstract: Rapid developments in 3D printing technology have dramatically changed a wide range of industries, from consumer products and healthcare to automotive and aerospace. 3D printing is a process of manufacturing where material is deposited layer over layer which are previously deposited to provide the design shape to the desired products. This process has eliminated the numerous machining processes which were required to manufacture the products previously. The modification of process …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 975–996 Read article
-
A Quantitative Fuzzy MCDM Framework for Decision Support in Uncertain Environments
Abstract: Fuzzy mathematics play an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and it signs other possible solutions in addition to fuzzy mathematics. Fuzzy models offer a versatile and precise approach to assessing complex situations through the use of fuzzy sets, membership functions, and aggregation methods. Through time, cost and quality, the project management case study illustrates how fuzzy logic works for them. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 1–8 Read article
-
Elderly Healthcare Using Federated Learning Approach
Abstract: The healthcare system for elderly people faces several challenges, which can be addressed using advanced machine learning models. These models can help monitor chronic diseases, detect falls, and provide personalized health recommendations. The study uses comprehensive datasets like MIMIC-III/IV, WESAD, and UCIHAR to explore human movements, device limitations, and the differences in fall occurrences. A detailed review of existing literature discusses current technologies for activity monitoring and fall detection, focusing …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 13–23 Read article
-
Interfacial and Tribo-Mechanical Performance of a TiO₂–Castor Oil Polymeric Nanofluid During Sustainable Machining of AISI 316L Stainless Steel Under MQL Conditions
Abstract: This research examines the tribo-mechanical performance and interfacial film characteristics of a TiO₂-reinforced castor-oil polymeric nanofluid during the turning of AISI 316L stainless steel under minimum-quantity lubrication (MQL). A Taguchi L9 orthogonal array was utilized to assess the synergistic effects of cutting speed, depth of cut, and coolant composition on surface integrity, while machining experiments were performed under dry, conventional, and TiO₂-nanofluid lubrication techniques. ANOVA and multiple-regression modeling were used …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 901–914 Read article
-
A study on Antibiotic Resistance: An Analysis of Molecular Mechanisms and Therapeutic Implications
Abstract: Antibiotic resistance (AR) represents one of the most critical existential threats to global public health, rapidly eroding the efficacy of established antimicrobial therapies and portending a return to the pre-antibiotic era. This analysis explores the intricate molecular landscape defining this crisis, focusing specifically on the primary mechanisms of action (MoA) utilized by major antibiotic classes—including cell wall inhibitors, protein synthesis inhibitors, and nucleic acid synthesis inhibitors—and the corresponding, diverse mechanisms …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 9–21 Read article
-
Prolonged Antibiotic Use and Reproductive Challenges in Dairy Cows: Implications for Ovarian, Uterine, and Overall Reproductive Health
Abstract: The widespread use of antibiotics in dairy farming has raised concerns regarding its potential impact on reproductive performance. Prolonged antibiotic administration can disrupt endocrine regulation, alter ovarian function, impair uterine health, and compromise overall fertility in dairy cows. This review explores the multifaceted consequences of antibiotic exposure on reproductive physiology, highlighting its effects on hormonal balance, follicular dynamics, uterine microbiota, and embryo viability. Antibiotics may induce hormonal imbalances that interfere …
Published in International Journal of Antibiotics · Vol. 3, Issue 1, 2026 · pp. 22–40 Read article
-
Drug Induced Immune Mediated Nephritis: Molecular Mechanism , Pathways and Clinical Implications
Abstract: Drug-induced immune-mediated nephritis (DI-IMN) has become a more widely known cause of acute kidney injury (AKI), with the potential for development to chronic kidney disease if not detected and treated promptly. T-cell hypersensitivity to pharmaceuticals, such as antibiotics, proton pump inhibitors, nonsteroidal anti-inflammatory drugs, and immunological drugs, are the major causes for it. Beyond clinical burden, DI-IMN reflectsintricate molecular interactions that sustain interstitial inflammation and tubular injury. These interactions include …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 13–29 Read article
-
Nanoformulation Strategies: Emerging Innovations in Drug Delivery Systems
Abstract: Nanotechnology is significantly advancing the pharmaceutical industry by introducing nanosystems that improve drug delivery, therapeutic efficacy, and patient outcomes. Various nanosystems-such as liposomes, dendrimers, polymeric nanoparticles, solid lipid nanoparticles, carbon nanotubes, and metallic nanoparticles-offer benefits like enhanced bioavailability, targeted delivery, improved stability, and reduced side effects. Innovative formulation strategies, including surface functionalization, particle size optimization, and use of biodegradable carriers, support controlled and sustained drug release. Additionally, production in non-aqueous …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 54–67 Read article
-
Nutrient-Mediated Activation of Cellular Signaling Pathways: Mechanistic Insights into Attenuation of Toxin Induced Inflammation in Food Animals
Abstract: Dietary and environmental toxins remain a persistent challenge in food animal production, where subclinical and clinical inflammation compromises health, productivity, and food safety. Toxin induced inflammation is driven by oxidative stress, mitochondrial dysfunction, and dysregulated immune signaling, resulting in impaired metabolic efficiency and increased disease susceptibility. Recent advances in nutritional science have revealed that nutrients act not only as substrates for growth but also as signaling molecules capable of modulating …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 1, 2026 · pp. 1–12 Read article
-
Personalized Therapy Using Drug Delivery Devices
Abstract: The persistent challenge in modern medicine lies in inter-patient heterogeneity, rendering standardized drug dosing protocols suboptimal for many chronic conditions. Traditional pharmacokinetics fail to account for real-time biological fluctuations, leading to cycles of ineffective treatment or dose-limiting toxicity. This paper explores the critical intersection of advanced drug delivery devices (DDDs) and personalized medicine, positioning these technologies as the vital link translating genomic and biological data into tangible, patient- specific interventions. …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 53–62 Read article
-
A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
-
Automation-Driven Composites: Pioneering the Next Generation of Lightweight and Sustainable Electric Vehicles
Abstract: Electric vehicle (EV) market is undergoing a dynamic change due to the changes in regulations, increasing demands of consumers, and a swift development of material science. Composite materials were one of these innovations which have become the key facilitators of lightweight, efficient and safe EV designs, with immense strength to weight ratios, corrosion resistance, and design flexibility unmatched before. The paper will discuss the growing use of composite materials in …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 513–525 Read article
-
Artificial Intelligence and IoT Integration for Real-Time Violence Monitoring
Abstract: The peace and tranquility of any place can be affected greatly by the insurgence of violence and violent attacks that are perpetrated by individuals with malicious and nefarious intentions. These individuals terrorize the areas and can cause a lot of harm and damage to people and public property. The incidences of violence are undesirable and can be problematic to handle by the law enforcement agencies, as these acts are committed …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 39–45 Read article
-
Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article