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67 articles for “Media optimization”
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Isolation and Identification of Novel Bacillus tequilensis TB5 from Vegetable Waste and Analyze the Effect of Rudiment Compounds on Bio-Catalytic α-Amylase Production
Abstract: AbstractAmylase is one of the basic components for leather, baking, textiles and paper industries. It hydrolyzes starch into simple productive sugar which reduces the cost of the final desired product. In this work, amylase producing novel Bacillus tequilensis TB5 was isolated from vegetable waste and different chemical compounds were added at different concentration in production medium to analyze its effect on amylase enzyme production. We observed that addition of weight/volume …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 9, Issue 2, 2019 · pp. 39–50 Read article
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Integrated Rock Typing and Rock Mechanics Studies for Median Line Principle Optimization
Abstract: Once a field has been identified, and a general method of reservoir exploitation decided, there are several methods to achieve the reservoir management goal, but some ways may cost twice as much as others. The most critical operations to developing a field are drilling of wells, and it overemphasizes which in the early stages of field development. Petroleum wells have changed character in recent decades, as compared to earlier times. …
Published in Journal of Petroleum Engineering & Technology · Vol. 10, Issue 1, 2020 · pp. 21–32 Read article
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APPLICATION OF AGRO BASED RESUIDALS FOR THE PRODUCTION OF SURACTANT ON IOR USING MICROBES
Abstract: Utilization of surfactants for IOR is an accepted technique with high potential. However, technology application is frequently limited by cost. Biosurfactants (surface-active molecules produced by microorganisms) are commonly used in specialty markets such as food and textiles and have potential for IOR application. Currently, biosurfactants are not widely utilized in the petroleum industry due to high production costs associated with use of expensive substrates and inefficient product recovery methods. The …
Published in Journal of Catalyst & Catalysis · Vol. 5, Issue 3, 2018 · pp. 1–4 Read article
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The Role of Social Media Analytics in Integrated Marketing Communication and Understanding Consumer Behaviour: The Pathway to Optimal Customer Relationship Management
Abstract: This study explores the role of social media analytics in understanding consumer behavior within the context of Integrated Marketing Communication (IMC). Businesses now have access to a lot of data thanks to the spread of social media platforms, which can give them important insights into consumer preferences, attitudes, and behaviors. This study discusses the methodologies and tools used in social media analytics and how they can be leveraged to enhance …
Published in International Journal of Electronics Automation · Vol. 1, Issue 1, 2023 · pp. 22–29 Read article
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Machine Learning Optimization for VARTM Carbon Polymer Laminates
Abstract: Vacuum-assisted resin transfer moulding (VARTM) is a key low-cost, out-of-autoclave process for manufacturing large-scale carbon-fibre reinforced polymer (CFRP) laminates crucial to aerospace wings, wind-turbine blades, marine hulls, and automotive structures. Unpredictable resin flow often leads to voids, dry spots, and race-tracking defects, resulting in 27.9% scrap rates and lengthy, costly trial-and-error design cycles. Although surrogate models provide rapid impregnation predictions for simple flat-plate geometries, vision-based monitoring is limited to idealized …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 229–245 Read article
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Role and Importance of Machine Learning in Social Media
Abstract: The widespread adoption of social media platforms has transformed the way individuals interact and communicate. Going beyond personal connections, social media has evolved into a potent tool for sharing information, shaping ideas, and fostering participation across various industries. Machine learning is pivotal in enhancing social media's impact. Social media generates vast data daily, and machine learning is essential for extracting insights. Sentiment analysis, a machine learning application, identifies emotions in …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 11, Issue 1, 2024 · pp. 23–30 Read article
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Sustainable Waste Management Using AI and Robotics
Abstract: The fast increment in squander era around the world has driven to noteworthy natural and open wellbeing concerns. Conventional squander administration strategies, which depend intensely on manual labor and obsolete forms, are battling to keep up with the developing volume, driving to wasteful aspects and environmental harm. AI and Mechanical autonomy give inventive arrangements by improving effectiveness in squander collection, sorting, reusing, and transfer. AI-driven squander sorting frameworks optimize exactness, …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 42–48 Read article
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Production and optimization of amylase enzyme using bacillus subtilis under solid state fermentation and its characterization
Abstract: This study employed solid state fermentation to maximize amylase production by Bacillus subtilis (OR578403). The research began by discovering and analyzing amylase-producing bacteria in soil samples followed with biochemical, molecular characterization. By using commercially available substrates like wheat bran, rice bran, and wheat rava were obtained from the local market and employed as solid substrates, which may influence amylase production and to be assessed. The identified organism was Bacillus subtilis, …
Published in International Journal of Biochemistry and Biomolecule Research · Vol. 4, Issue 1, 2026 · pp. 37–52 Read article
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Enhancing User Engagement and Content Relevance: A Novel Approach to Social Media Post Recommendation System
Abstract: The social media post recommendation system is an innovative solution aimed at optimizing content delivery for users in today's digital age. Its primary motive is to tailor online experiences, ensuring users receive posts most relevant to their preferences. Various machine learning algorithms are employed to suggest related posts. This system leverages advanced algorithms and analytics, producing key results that highlight user engagement metrics and content relevance. Preliminary findings of this …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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CRISPR, Recombinant DNA, and LAMP-Based Platforms for Monkeypox: Emerging Tools for Diagnosis and Therapeutic Development
Abstract: Monkeypox, a zoonotic viral infection caused by the Monkeypox virus of the Orthopoxvirus genus, has recurred as a worldwide public health concern after recent outbreaks outside of its classical endemic areas in Central and West Africa. The resurgence has demanded a thorough reassessment of its epidemiology, mode of transmission, and clinical presentation. In light of these challenges, recombinant DNA technology (rDNA) has emerged as a candidate for developing vaccines, diagnostics, …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 7–28 Read article
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Pharmacodynamics and Drug–Receptor Interactions: Integrating PK/PD Modeling with Modern Drug Development
Abstract: Understanding drug action requires an integrated perspective of pharmacodynamics and pharmacokinetics, which together determine therapeutic efficacy and safety. This review provides a comprehensive overview of the mechanisms underlying drug action, with particular emphasis on drug–receptor interactions and their role in modulating physiological responses. Drugs exert their effects primarily through interactions with specific biological targets, including receptors, enzymes, ion channels, and transporters, resulting in a spectrum of desired and adverse outcomes. …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 · pp. 33–47 Read article
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Photochemical Studies of Photosensitive Compound in DSS Cell
Abstract: Solar energy is our earth’s primary source of renewable energy. It is one of the most resourceful sources of energy for the future. A technique for converting solar energy into electrical energy via formation of energy rich species that exhibit the photo-solar effect is known as DSS cell. Therefore, the present study of DSS cell of Carbol Fuchsin (PC) with efficiency enhancer chemicals such as TEA reductant in alkaline media …
Published in Journal of Semiconductor Devices and Circuits · Vol. 4, Issue 3, 2017 · pp. 21–29 Read article
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A Mathematical Perspective on Recent Cloud-Computing Trends for Scalable and Secure Social-Media Platforms
Abstract: Cloud computing underpins modern social-media platforms by providing elastic compute, storage, and data-processing pipelines capable of absorbing highly bursty workloads. This paper surveys recent cloud-native trends—serverless and event-driven design, container orchestration, edge/CDN offload, streaming analytics, and privacy-enhancing security controls—and formalizes their impact through a compact mathematical model. We express workload volatility using arrival-rate functions, use queueing-based capacity sizing to derive auto-scaling rules, and formulate an optimization objective that balances cost …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 35–40 Read article
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Performance Comparison of Plantain Stem Fibre, Palm Fruit Fibre and Banana Stem Fibre for Remediation
Abstract: This thesis goes on to show how each bioadsorbent works in a packed bed unit connected in series to remediate or treat contaminated fresh water medium using petroleum hydrocarbons, or crude oil. The purpose of this study was to determine the efficacy of plantain, banana, and palm bunch fibers with diameters of 50 µm, 150 µm, and 200 µm in treating contaminated water media. In each packed bed unit, the …
Published in Emerging Trends in Chemical Engineering · Vol. 10, Issue 3, 2023 · pp. 27–36 Read article
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Multifactorial Diseases Becoming the Epigenetic Factor for the Genz
Abstract: This comprehensive paper investigates the complex interplay between multifactorial diseases, particularly obesity and cardiovascular disease (CVD), and their relationship with epigenetic mechanisms, highlighting the transgenerational implications of these interactions. The multifaceted nature of obesity and CVD, involving genetic predisposition, environmental influences, and epigenetic modifications, underscores the intricate pathways contributing to disease susceptibility and progression. Drawing upon a synthesis of diverse research findings, the paper elucidates the critical role of genetic …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 1, 2024 · pp. 16–22 Read article
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A Comparison Study of Different Classification Algorithm on Brain Tumor Segmentation
Abstract: A brain tumor is a tissue mass caused by aberrant cell proliferation in the brain. It is a collection of tissues that causes hormonal alterations and eventually death. In order to save human lives, brain tumors prognosis and prevention is a difficult task. The use of modern medical image processing approaches has made the identification of brain tumors more flexible in recent years. Due to the absence of ionizing radiations, …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 1–7 Read article
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Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
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Data Mining for E-Commerce and Social Media: Insights and Future Research Directions
Abstract: The fast expansion of e-commerce and social media has heralded a new era of data-rich settings, with enormous quantities of user interactions, preferences, and transactions generated on a daily basis. Data mining has developed as a critical strategy for leveraging big datasets, allowing businesses to gain concrete knowledge and drive decision-making. Data mining in e-commerce improves operational efficiency and user pleasure by allowing for personalized recommendations, consumer segmentation, fraud detection, …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 1, 2025 · pp. 14–23 Read article
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Evolutionary Particle Swarm Optimization (EPSO) based technique considering Voltage Stability Margin for Reactive Power Reserve Optimization
Abstract: Reactive power reserve and voltage stability are one of the important parameters required for proper operation of the electrical power system. Voltage stability covers a broad span of phenomena in power systems and its applications. Voltage stability is defined as ability of power system to assist fixed bearable potential at every single bus of the system under standard operating conditions and when put through to a disturbance. At any instant …
Published in Journal of Power Electronics and Power Systems · Vol. 11, Issue 2, 2021 · pp. 36–41 Read article
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From Quantum Chemistry to Bioprocess Intensification: Advanced Computational Modeling and Enzyme-Based Catalytic Platforms for Green Chemical Transformations
Abstract: Green chemistry requires the development of sustainable catalytic systems that minimize waste generation, reduce energy consumption, and improve process efficiency. Computational chemistry and biocatalysis have emerged as complementary approaches for environmentally responsible chemical manufacturing. Computational techniques such as quantum chemistry, density functional theory (DFT), molecular dynamics, and machine learning provide mechanistic insights into catalytic reactions and support the rational design of efficient catalysts. These approaches enable the prediction of reaction …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 2, 2026 · pp. 45–52 Read article