Metallurgical and Materials Engineering (E-Journal)
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Numerical and Experimental Investigation of Phase Change Material-Based Thermal Management for Mitigating Aging in Lithium-Ion Battery Packs
Get PDFThe paradigm shift from internal combustion engines to electric vehicles is driven primarily by advancements in lithium-ion cells (LICs) technology. As the advancement of the LICs in terms of long-life, high-energy density, high power density, high charge/discharge rate and cost-effective shows potential for future. This research examines a 3-series x 3-parallel (3s3p) based 21700-NMC lithium-ion battery pack module utilizing phase change material (PCM) as its thermal management solution. The module is evaluated for capacity degradation through a cycling test consisting of 600 continuous charge-discharge cycles. After 600 cycles at 1.5C charge and 2.5C discharge at room temperature, the SOH dropped by 24% without PCM and 19% with PCM. During operation, cell temperature rises, and PCM absorbs heat to keep it within the optimal range. PCM enhances battery performance and extends its lifespan. A deviation of ±5% is observed between the experimental and simulation results. This research emphasizes the effectiveness of PCMs in managing thermal challenges, enhancing the safety, reliability, and suitability of lithium-ion batteries for electric vehicles and other high-power applications
Hybrid Metaheuristic Adaptive QoS Routing Using Dual-Layer Deep Reinforced Swarm Learning in 5G-Enabled Materials with Secure Packet Clustering
Get PDFQoS routing in MANETs continues to present significant challenges in the era of emerging wireless technologies, particularly with the integration of 5G networks, silicon-based antenna systems, and advanced material-based communication devices. The dynamic nature of node mobility, energy limitations, and vulnerability to security attacks requires robust and intelligent routing frameworks for modern MANET environments. Conventional swarm intelligence-based routing models, although effective, often lack adaptivity to dynamic topologies and fail to ensure secure packet transmission in heterogeneous material-driven wireless environments.
To overcome these limitations, this paper proposes a novel Hybrid Metaheuristic Adaptive QoS Routing Framework that seamlessly integrates Ant Colony Optimization (ACO), Red Deer Algorithm (RDA), and Butterfly Optimization Algorithm (BOA), reinforced by a Deep Q-Learning (DQL) controller. The hybrid architecture intelligently adapts its optimization strategies based on real-time network parameters such as energy, link stability, and packet loss, leveraging DQL for parameter tuning. Furthermore, the proposed model incorporates a dual-layer secure packet scheduling system comprising modified TDMA scheduling and secure fuzzy-based packet clustering, ensuring encrypted data transmission even in complex 5G-enabled silicon antenna-based MANET nodes.
The proposed framework was extensively validated through simulations and exhibited superior performance across multiple QoS metrics. It achieved a 15.3% increase in throughput, 13.8% improvement in packet delivery ratio, 22.5% reduction in delay, and 18.1% energy savings compared to existing approaches like MACOPM, RDA-EQRP, and ISMBOQAR-PS. The study establishes this hybrid approach as a highly adaptive and secure solution for next-generation MANETs integrated with advanced materials, 5G technologies, and silicon-based antenna infrastructures
Analysis Grid Search Optimization of Machine Learning Models for Slope Stability Prediction Supports the Design Construction of Geotechnical Structures and Environmental Development
Get PDFThe accurate prediction of slope stability is crucial for the design and construction of geotechnical structures, as well as for environmental development and risk mitigation. This study explores the application of machine learning (ML) models optimized using the Grid Search method to enhance slope stability predictions. In this study, an in-depth analysis of seven prediction models Logistic Regression (LR), K-Nearest Neighbor (KNN), Support Vector Classifier (SVC), CatBoost, and RUSBoost is provided. These models were evaluated using a grid search approach to find the optimal hyperparameters. The model takes several input features, including pore water ratio (ru), height (H), unit weight (Ƴ), cohesion (c), slope angle (β), and angle of internal friction (ɸ). The output is the slope status, either stable (1) or unstable (0). The generalization ability of classification models is improved by using a 5-fold cross-validation (CV). Evaluation indicators such as AUC, accuracy, and kappa were analyzed, and CatBoost outperformed other machine learning models with the highest AUC of 0.823, accuracy of 0.874, and kappa of 0.642. The results indicate that CatBoost is a highly effective tool for predicting slope stability, surpassing other models in classification accuracy. The capacity and efficiency of RF in deformation prediction models make it the most accurate tool available for forecasting slope stability. Additionally, a comprehensive analysis of feature sensitivity was conducted to determine the most significant characteristics for predicting slope stability. These findings not only enhance geotechnical safety but also contribute to sustainable environmental development by preventing landslides, reducing soil erosion, and supporting responsible land-use planning. The integration of machine learning into slope stability analysis promotes ecological preservation and long-term resilience in infrastructure projects
Electroactive Biomaterials: Orchestrating Electrical Cues for Enhanced Osseointegration and Bone Regeneration- A Narrative Review
Get PDFElectroactive biomaterials are emerging as a transformative approach to enhance osseointegration and bone regeneration by mimicking the intrinsic electrical microenvironment of native bone. This review synthesizes recent advancements in piezoelectric, conductive, and composite electroactive materials, highlighting their capacity to modulate cellular behavior, promote osteogenesis, and combat implant-associated infections. Studies demonstrate that optimized 3D topographies and nanoarrays on piezoelectric substrates, coupled with conductive polymer coatings and antimicrobial surface modifications, significantly improve bone-implant integration and regeneration. Furthermore, the development of self-powered systems and multifunctional coatings exemplifies the pursuit of autonomous, biomimetic implants. Future directions should focus on integrating smart sensors for real-time feedback, developing biodegradable and self-healing materials, elucidating cellular mechanotransduction mechanisms, and establishing robust clinical translation pathways. By harmonizing electrical stimulation, antibacterial properties, and advanced material design, electroactive biomaterials hold immense promise for revolutionizing orthopedic and dental therapies
Exploring Cinematic Space, Mobility, and Identity in Malayalam Road Cinema: A Case Study of Neelakasham Pachakadal Chuvanna Bhoomi
Get PDFThis study investigates the use of cinematic space in Sameer Thahir's 2013 malayalam road film Neelakasham Pachakadal Chuvanna Bhoomi. The study examines how the protagonists' travels across various locations—from the lush landscapes of Kerala to the harsh deserts of Rajasthan and the rocky terrain of Ladakh—contribute to the main themes of freedom, mobility, and self-discovery. In order to examine how the route and the physical surroundings mirror the characters' emotional and psychological journeys, the article employs theories of cinematic space. This study examines how the film employs landscapes as active elements that shape the story arc and character development, rather than just as backdrops, through the prism of space. The study makes the case that traveling through these many locations represents personal development both literally and figuratively, which deepens our comprehension of the role that space plays in road films
Agricultural Crop Recommendations Based on Productivity and Season
Get PDFIn Indian economy and employment agriculture plays major role. The most common problem faced by the Indian farmers is they do not opt crop based on the necessity of soil, as a result they face serious setback in productivity. This problem can be addressed through precision agriculture. This method takes three parameters into consideration, viz: soil characteristics, soil types and crop yield data collection based on these parameters suggesting the farmer suitable crop to be cultivated. Precision agriculture helps in reduction of non-suitable crop which indeed increases productivity, apart from the following advantages like efficacy in input as well as output and better decision making for farming. Crop yield prediction incorporates forecasting the yield of the crop from past historical data which includes factors such as temperature, relative humidity, ph., rainfall and area (Hectares). This method gives solutions like proposing a recommendation system through an ensemble model with majority voting techniques using Random Forest and K Nearest Neighbor as learner to recommend suitable crop based on soil parameters with high specific accuracy and efficiency.
 
Health Status and Morbidity Trends among Student Youth: Insights from Southern Kyrgyzstan
Get PDFStudents' health situation significantly influences their academic performance and general well-being, particularly since higher education can lead to major lifestyle changes that could lead to chronic health disorders. This study evaluated students' health using epidemiological, analytical, and statistical research techniques. The results showed a general decrease in health markers over their academic careers; almost half of the students examined had chronic diseases—69% in the main group and 56% in the control group (p > 0.05). The study revealed notable increases in the frequency of gastrointestinal ailments, ophthalmic conditions, and dental cavities. From 239.6 ± 6.0 per 1,000 persons in 2021 to 280.4 ± 8.3 per 1,000 in 2023, primary morbidity rates increased by 17.2% (p < 0.05). Six main nosological categories—that of illnesses of the digestive and respiratory systems, ophthalmic problems, viral and parasitic diseases, and disorders of the ear and mastoid process—also showed increases in morbidity. These results emphasize the great importance of early diagnosis and treatment of chronic illnesses and related risk factors as well as of preventative actions aimed at encouraging good lifestyle choices. Given the alarming health trends, higher education institutions must provide ideal settings that promote student health and slow down the development of chronic diseases.  
Impact Of Personality Traits On Employee's Job Satisfaction: A Study On Msmes Of Vadodara
Get PDFThis study investigates how various factors influence employee personality traits and job satisfaction within the manufacturing sector. Understanding these dynamics is crucial for enhancing workplace productivity and employee retention. Research Question - What is the relationship between factors (such as workplace environment, management styles, and peer relationships) and employee personality traits and job satisfaction in the manufacturing industry? Research Methodology This study employs a descriptive analysis research design to explore the impact of various factors on employee personality traits and job satisfaction within the manufacturing sector. The sampling method utilized is non-probability convenience sampling, allowing for selecting participants who are readily accessible and willing to participate. The target population comprises middle-level employees within manufacturing companies, and data is collected through an online survey, ensuring efficient reach and response. The survey instrument consists of a structured questionnaire designed to measure relevant personality traits and levels of job satisfaction. A sample size of 100 respondents is targeted to provide a robust analysis. Statistical analysis is conducted using SPSS software, which facilitates the evaluation of the collected data and the identification of significant patterns and correlations. This methodology is designed to yield insightful findings that can inform practices aimed at enhancing employee well-being and productivity in the manufacturing sector. Finding The findings of this study indicate a positive relationship between a supportive workplace environment, effective management practices, and enhanced employee personality traits, which in turn contribute to higher job satisfaction among middle-level employees in the manufacturing sector. Results - The results suggest that fostering a collaborative and encouraging atmosphere and sound management strategies can significantly improve employee morale and satisfaction
Influence Of Employee Perception, Attitude, And Behavior Towards Organizational Change In Commercial Banking Sectors Of Tamil Nadu."
Get PDFThe Indian banking institute has been long considered as the backbone of economic growth and constancy. However, in recent years the sector has seen fast shifts, owing to technological advancement and shifting client expectations. Tradition banking system has been replaced by creating dynamic and competitive environment .whereas this advancement provide enormous opportunities for potential innovation and progress as well as pose some distinct challenges for those employees who must adjust to the new system. The research paper aims to investigate the multiple behavior of employees experience in the banking industry and also study their perspectives of Organizational culture, attitude towards changing practices in the industry. Considering these aspects the research study the insights on developing a resilient, motivated and flexible workforce for those capable of thriving in a changing work atmosphere. The methodology used in this paper is partially quantitative analysis and the data are collected from commercial banks of Tamil Nadu (India). The result states that employee perception; attitude has greater influence towards organizational changes in private’s banks than the public banks
Partial Replacement Of Coarse Aggregate With Utilization Of Coal Wash Rejectors: A Sustainable Approach To Concrete Production
Get PDFThis study investigates the feasibility of partially replacing coarse aggregate with coal wash rejects in concrete production. Coal wash rejects are a waste material generated during coal washing processes, and their disposal poses environmental concerns. The results show that partial replacement of coarse aggregate with coal wash rejects up to 20% can produce concrete with satisfactory mechanical properties, reduced density, and lower environmental impact. This research explores the feasibility of using coal wash rejectors as a partial replacement for coarse aggregate in concrete. Coal wash rejectors, a by-product of the coal mining industry, pose significant environmental challenges due to their disposal. This study evaluates the impact of incorporating coal wash rejectors on the mechanical properties of concrete, including compressive strength, tensile strength, and workability. The results indicate that coal wash rejectors can be used effectively as a partial substitute for coarse aggregates without significantly compromising the structural integrity of the concrete.[1] The interest of regular totals is quickly turning out to be high step by step in the development industry. Different endeavors are being made to track down substitutes for normal totals.
The combustion of high-quality coal accounts for approximately 70% of the electricity produced in India. During the time spent coal washing, huge amounts of debased coal are being dismissed and causing removal issues. These dismissed debased coals are called as Coal Washery Rejects (CWR). The current study attempts to use the novel material CWR as a partial replacement for coarse aggregate in concrete in order to preserve environmental sustainability. This examination concentrated on the compressive strength of cement containing CWR at various substitution levels (0% - half). The compressive strength values were contrasted with M 25grade of customary cement (CC). From the outcomes, it is seen that the expansion in CWR substitution level diminished the compressive strength. At replacement levels of 20 percent and 30 percent, this decrease was only marginal, but after 30 percent, it was extremely significant. Consequently, it is uncovered that 30% CWR substitution can be viewed as ideal level in the development industry