International Journal of Machine Design and Manufacturing

ijmdm | Peer-Reviewed | Hybrid Open Access

Journal Metrics

Key performance indicators showcasing our journal’s impact and reach

36

Published Articles (2024)

34.24

Days Acceptance Time

37.58

Day Publication Time

Total Visits

About the Journal

Current Trends in Information Technology is a peer-reviewed hybrid open-access journal launched in 2011, focused on the rapid publication of fundamental research papers on all areas of Information Technology across multidisciplinary domains.

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Journal Information

Title:
Recent Trends in Fluid Mechanics
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English
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CC BY-NC-ND
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ICV Value: 2024 : 68.72,
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SJIF,
ICV Value: 2024 : 64.27,
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Editorial Board

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ijaip maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

Editor in Chief

Editor

Prof. Utpal Sharma, Director & Professor

Nirma Univesity, Gujarat, India,

Email :

Latest Articles

Relative Study on Design and Analysis of Iron Box using Different Materials

In this study, a steady-state thermal analysis of the soleplate is conducted using four different materials(Aluminium, Stainless Steel, Titanium and Ceramics) using ANSYS Workbench. 

Aluminum, Ceramics, Finite Element Analysis, Safety, Soleplate, Stainless Steel, Temperature, Titanium.

Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning

The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as a predictor of future performance in school by utilizing computer technology. Peer pressure is an influential factor and impacts academic achievement, and therefore this study will focus on the relationship between peer pressure and academics through machine learning methods, resulting in predictive assessments for students similar to this population. The present research gathered student data through two means: survey and record review.

Peer pressure; Academic achievement; Machine learning; Student performance; Social networks; Predictive modeling; Educational behavior

POLYMER AND COMPOSITE-BASED GEOSYNTHETIC REINFORCEMENTS FOR SEISMIC STABILITY OF SOIL RETAINING STRUCTURES: MATERIALS, MECHANICS, AND PERFORMANCE REVIEW

Geosynthetic materials based on polymer and composites have become important items for the structural performance and seismic resilience of the reinforced soil retaining systems.

Polymer composites; Geosynthetics; Fiber-reinforced polymers (FRP); Soil–reinforcement interaction; Seismic stability; Mechanically stabilized earth (MSE) walls; Creep behaviour; Pullout resistance; Smart geosynthetics; Sustainable polymers; Finite element analysis; Time-history analysis

Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification

The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate.

neuro-symbolic AI, drug target identification, deep reinforcement learning, quantum simulation, explainable AI, LLM hypothesis generation, knowledge graph, protein conformational dynamics, SHAP attribution, autonomous scientific discovery.

Artificial Intelligence-Assisted Multi-Objective Optimization of Agricultural Biomass-Reinforced Polymer Composites

Agricultural biomass can reduce the environmental burden of polymer composites, yet its heterogeneous structure creates competing effects on strength, moisture resistance, density, and process ability.

Agricultural biomass, Polymer composites, Artificial intelligence, Multi-objective optimization, Explainable machine learning

Psychological Drivers of ESG Investment in the Polymer Sector

This research will delve into the mentalities of investors concerning investments in polymer ESG projects.

ESG Investment, Psychological Drivers, Polymer Sector, Structural Equation Modeling (SEM), Investor Behaviour, Sustainable Finance

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