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1495 articles for “work”
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Evaluation of Coconut Coir Feasibility as Fluid Loss Control Material in Comparison with Commonly Used NUTPLUG
Abstract: This work centers on decreasing drilling fluid loss circulation by using coconut coir as a loss circulation material. Millions of dollars are invested yearly to counteract lost circulation and its consequences, including clogged pipes, blowouts, and abandoned wells. Drilling mud was formulated with varied percentages of coconut coir and nut plugs, which were utilized as loss circulation materials to minimize or decrease drilling fluid loss. The two materials being compared …
Published in International Journal of Chemical Engineering and Processing · Vol. 12, Issue 2, 2026 · pp. 20–36 Read article
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AI-Assisted Code Generation: Integrating Natural Language Models with Compiler Frameworks for Enhanced Software Development
Abstract: The rapid evolution of Artificial Intelligence (AI) has profoundly transformed contemporary software engineering practices, particularly through the emergence of AI-assisted code generation driven by large-scale natural language models (NLMs). These models, trained on extensive repositories of source code and technical documentation, enable developers to generate, modify, refactor, and optimize source code directly from natural language instructions, thereby significantly reducing manual coding effort and accelerating overall software development cycles. By allowing …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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AI-Based Deepfake Voice Detection Model for Hindi Language
Abstract: Most current research on deepfake voice detection focuses heavily on English or Mandarin, creating a significant security gap for Hindi speakers. To address this, we developed a detection framework specifically tailored for the Hindi language using a lightweight approach: Mel-Frequency Cepstral Coefficient (MFCC) feature extraction paired with an XGBoost classifier. We trained the system on a large dataset comprising over 99,000 real voice samples and roughly 3,800 synthetic samples, each …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article
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Getting Rid of Carbon: A New Direction for the Chemical Industry
Abstract: The chemical industry is a major contributor to global greenhouse gas emissions due to its reliance on fossil-based feedstocks, energy-intensive processing routes, and long-lived capital infrastructure. Achieving international climate targets therefore requires deep decarbonisation across the entire chemical value chain, a transition complicated by technological limitations, economic risks, and systemic operational barriers. This article critically evaluates key emission-reduction pathways, including electrification of process heat, substitution of fossil resources with bio-based …
Published in International Journal of Chemical Engineering and Processing · Vol. 12, Issue 1, 2026 · pp. 52–61 Read article
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Articulating Precarious Waters: A Critical Review of Pharmaceutical Contaminants, Their Pathways, and Ecological–Health Risks in the Aquatic Systems of Bihar, India
Abstract: The article examines the emerging yet under-documented issue of pharmaceutical contaminants in Bihar’s aquatic environment, focusing on their types, occurrence, sources, and implications for ecology and human health. Pharmaceuticals and personal care products-including antibiotics, non-steroidal anti-inflammatory drugs, analgesics, beta‑blockers, and hormones – are conceptualized as pseudo-persistent pollutants because continuous inputs from households, healthcare facilities, and diffuse anthropogenic activities sustain their presence in surface water and groundwater despite individual compounds having …
Published in International Journal of Chemical Engineering and Processing · Vol. 12, Issue 1, 2026 · pp. 28–51 Read article
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Intelligent Data Analytics on Cloud Infrastructure:Real-Time Insights and Managed Service Models
Abstract: This paper examines the integration of advanced data analytics and machine learning within modern cloud infrastructure, highlighting how organizations can transform large volumes of unstructured data into actionable business insights that drive competitive advantage. Cloud platforms leverage scalability and elasticity to efficiently process and analyze massive datasets in real time, allowing enterprises to identify hidden patterns, detect operational anomalies early, and generate accurate forecasts of future outcomes. A key factor …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 36–46 Read article
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Toward Sustainable Intelligence: A Framework for Green AI Adoption
Abstract: The rapid expansion of Artificial Intelligence has shattered the illusion of the cloud as an ethereal entity, revealing a massive physical infrastructure with a staggering environmental price tag. The traditional Red AI paradigm – where success is measured solely by accuracy through brute-force scaling – has created an unsustainable trajectory. Training a single large-scale model like GPT-3 requires 1,287 MWh of electricity, while the necessary cooling systems evaporate millions of …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 17–23 Read article
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Green Computing Strategies for Reducing Energy Consumption and E-Waste in Modern IT Ecosystems
Abstract: Green computing, also referred to as sustainable computing, addresses the urgent need to reduce the environmental impact associated with the design, operation, and end-of-life management of computing systems. As global reliance on digital technologies continues to expand rapidly, the demand for energy-intensive infrastructure such as data centers, cloud platforms, and network systems has increased significantly. This growth has led to rising energy consumption, higher carbon emissions, and an alarming accumulation …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 7–16 Read article
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An Overview on Metal Processing using Machine Learning
Abstract: Metalworking, which is an important part of modern industry, includes a wide range of steps, such as shaping and casting the metal, machining it, and riveting it. The industry has always relied on trial and error and other empirical methods, but machine learning (ML) is now causing a big change. It is expected that this change will lead to higher production, better product quality, and better use of resources. The …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 43–53 Read article
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Adaptive Production Scheduling in Multi-Machine Manufacturing Environments
Abstract: For manufacturing processes to meet evolving market demands, they must be executed in the most efficient manner while maintaining flexibility against unanticipated disruptions. Often, traditional scheduling methods overlook dynamic variability and real-time interruptions. An inverse scheduling framework for a multi-machine flowshop system is proposed in this research with the primary objective of makespan minimisation. Several issue situations are analysed to validate the algorithmic efficacy, and metaheuristic techniques are used to …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article
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Design, Development, and Testing of 2-Phase Separator
Abstract: As the pressure vessel operates under high internal pressure, the choice of material and accuracy indesign play a vital role in ensuring its safety and reliability. Proper design is essential because anyfailure in a pressure vessel can lead to serious hazards, financial losses, and operational shutdowns.In compliance with the ASME Code (Section VIII, Division 1) and the process data sheet, this articledescribes how to design a pressure vessel. To guarantee …
Published in International Journal of Structural Mechanics and Finite Elements · Vol. 12, Issue 1, 2026 · pp. 29–37 Read article
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Development of an Automated Load-Controlled Thermopower Measurement Technique for Thermoelectric Materials
Abstract: The Seebeck coefficient, or thermoelectric power, is crucial. In order to deliver accurate readings over a wide temperature range, a load-based, high-precision thermoelectric power (TEP) measurement device has been designed, constructed, and experimentally validated in this study. The system is based on a differential DC approach and replaces conventional spring-based contact mechanisms with a shifting mechanical load to avoid errors caused by spring contraction, thermal cycling, and contact instability at …
Published in International Journal of Mechanics and Design · Vol. 12, Issue 1, 2026 · pp. 7–18 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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Process Optimization of Copper Phthalocyanine Pigment PB15:3: A Sustainable Solvent Reduction Strategy for Industrial Applications
Abstract: Copper phthalocyanine pigments, particularly PB15:3 (beta-phase), represent cornerstone materials in the global colorants industry with applications spanning automotive coatings, printing inks, and engineering plastics. Conventional synthesis routes for PB15:3 necessitate copious volumes of high-boiling organic solvents – predominantly dimethylaminoethanol (DMAE) and aromatic hydrocarbons – posing significant environmental burdens and economic constraints. This study presents a systematic investigation of solvent quantity optimization in the pigment finishing process of CI Pigment Blue …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 21–40 Read article
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Catalytic Methods to Produce 2,5-FurandicarboxylicAcid from Glucose
Abstract: The new avenue in the realm of catalysis and in chemical industry is the paradigm shift from fossil based to biobased inventory, including the feedstock. Biomass is found to be a promising substitute to petroleum- based feedstock. Almost all the chemicals that could be derived from the conventional petro-refinery can be obtained from the bio-refinery with the intelligent use of Catalysis for the conversion of biomass selectively to the target …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 12–20 Read article
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The Biomechanical Impact of Slipper Sole Compliance on Lumbar Spine Load: A Quantitative Analysis of Indoor Footwear Ergonomics
Abstract: Abstract The global shift toward remote work has significantly increased the duration of indoor footwear usage, yet the ergonomic standards for slippers remain critically under-researched compared to athletic or industrial footwear. While "high-compliance" or soft slippers are traditionally marketed for immediate comfort, excessive mechanical softness may lead to foot instability, altered gait kinetics, and subsequent compensatory stress on the lumbar spine. This study aims to quantify the correlation between varying …
Published in International Journal of Mechanics and Design · Vol. 12, Issue 1, 2026 · pp. 30–35 Read article
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Modern Technology Analog Circuits:Applications and Challenges - An Exploration
Abstract: An analog circuit is an electronic system that processes signals that vary continuously. The signals reflect physical quantities, such as sound, temperature or light, as proportionate levels of voltage or current. However, they are not digital circuits. They operate on a continuous spectrum. They use resistors, capacitors, and transistors, and can amplify, filter, or otherwise alter signals. Analog circuits are still a vital feature of electronic systems today, allowing continuous-time …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 1, 2026 · pp. 14–23 Read article
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Smart Battery Management System with Real-Time Estimation of SOC and SOH
Abstract: To make batteries in electric vehicles and energy storage systems last longer, work better, and be safer, they need a Smart Battery Management System (BMS). The main goal of this project is to find out the battery's State of Charge (SOC) and State of Health (SOH) right away. SOC reflects the remaining usable capacity of the battery, while SOH indicates the overall condition and degree of aging of the battery. …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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High-Tech Battery Management Systems with Integrated Battery Electronics
Abstract: “Sophisticated BMSs with onboard battery electronics are a paradigm shift in battery technology, sensitive enough to meet the increasing needs of contemporary applications like electric vehicles, renewable energy storage, and portable devices. This paper discusses the architecture and functional aspects of the integrated systems in optimizing performance, safety, and lifespan through real-time monitoring and control of individual cells. Integrating critical electronics directly onto the battery structure, such systems minimize complexity …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 1, 2026 · pp. 21–28 Read article
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A study AI-Driven IoT in Self-Healing Grid Power Systems
Abstract: Modern electricity infrastructure is undergoing a transformation thanks to the combination of artificial intelligence (AI) and the Internet of Things (IoT), especially in the development of self- healing grid systems. In the context of smart grid automation and resilience, this article provides a thorough review of AI-driven IoT infrastructures. By leveraging distributed sensor networks, real-time data acquisition, and advanced KSK Approach, and machine learning algorithms—includes ANN, DT and K-NN—the proposed …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 1, 2026 · pp. 15–24 Read article