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Optimizing Lean Manufacturing Efficiency with Novel Line Balancing in the Automotive Exhaust Manufacturing Sector
No full textThis study examined the application of Lean manufacturing tools and a novel approach called line balance loss analysis in optimizing production processes at a Malaysian automotive exhaust manufacturing company. The primary objective was to align production rates with customer demand. Data collection involved two key aspects: gathering production process data for catalytic converters, front pipes, and muffler subassemblies, and acquiring technical data on Lean tools, including the innovative line balance loss analysis method, from one muffler production line. The integration of Lean tools with the new line balance loss analysis approach was found to be crucial. The multi-process/multi-machine line balancing approach went beyond eliminating Non Value Added (NVA) activities and focused on determining manpower requirements and task allocation among operators. The integration of the new line balance loss analysis method improved task distribution across workstations, enhancing overall process efficiency. The study's analysis of Lean tool applications and the innovative line balance loss analysis provided insights into the cellular manufacturing system of the production line. These findings offered valuable information for management decision-making and process improvement, ultimately leading to increased productivity and cost savings for the company
Numerical Approach for Evaluation of Surface Integrals in Polygonal Domain by Gauss Legendre Quadrature and Generalized Gaussian Quadrature Method
Get PDFWe present a new approach for the numerical integration of arbitrary functions over polygonal region, by applying two kinds of quadrature method Gauss Legendre quadrature and Generalized Gaussian quadrature method, the polygonal region is divided into arbitrary triangles, the sides of each triangle is noted as equation of straight line by joining two end vertices, this approach is used to further reduces the integral equations, numerical integration of rational and irrational functions are approximated computationally, we illustrate several numerical examples to shows the accuracy of the present method 
"Optimizing Pharmaceutical Formulations: Advancements in Nanosuspension Pre-Formulation to Enhance Solubility and Bioavailability of Active Agents"
Get PDFThis study aimed to enhance the bioavailability of a poorly water soluble drug by developing a nanosuspension through an innovative formulation method. The nanosuspension was produced with meticulous attention to the materials reliability and excellent quality. Nepafenac was characterised in the pre-formulation study by establishing its melting point, solubility in different solvents, organoleptic properties, and creating a calibration curve. We utilised UV spectroscopy to determine the maximum wavelength (?max) of Nepafenac and construct a standard calibration curve in ethanol. To ensure the compatibility of the medicine with the polymers (Pluronic F127 and HPMC E 5), Fourier Transform Infrared Spectroscopy (FTIR) was utilised for drug interaction analysis. The nanosuspension was produced using the solvent diffusion approach. The effect of different concentrations of Poloxamer 407 and HPMC E 5 on the formulation's effectiveness was investigated experimentally using a 32 complete factorial design. We used Response Surface Methodology (RSM) and statistical analysis to enhance the formulation concerning in vitro release, particle size, and viscosity. The pre-formulation characteristics of Nepafenac met the standards outlined in the Pharmacopoeial regulations. The maximum absorption wavelength (?max) of Nepafenac was confirmed by UV spectroscopy, and a reliable calibration curve was created. The FTIR analysis showed no chemical interaction between the medicine and polymers. RSM and experimental design indicated that Poloxamer 407 and HPMC E 5 had a substantial impact on the performance of the nanosuspension. Analysis of variance (ANOVA) confirmed the model and parameters that influence controlled drug release percentage, particle size, and viscosity. Optimal conditions for enhancing drug delivery and reducing particle size were determined by the analysis of contour and response surface plots. The optimal parameter values, as indicated in the desirability plots, closely matched the anticipated values. The experimentation confirmed the viability and effectiveness of the nanosuspension formulation generated based on the RSM findings
Improving Kinnow Fruit Classification with Feature Weighting using Modified Levy Flight Distribution-Inspired Sunflower Optimization Technique
No full textIn this paper, Feature weighting is used to create an intelligent and effective classification method for Kinnow fruits. Feature weighting approach is used because it improves classification performance more than feature selection methods. The modified sunflower optimization algorithm (SFO) is proposed to search the optimal feature weights and parametric values of k-Nearest Neighbour (kNN).The levy flight distribution operator has been utilised to enhance the convergence speed of the sunflower optimization algorithm by improving the local and global search ability of the optimization algorithm. Also, the algorithmic parameter of the SFO algorithm has been adaptively selected using the linear time varying adaption method. In addition, tanh normalization technique is used for the data pre-processing to reduce the influence of outliers and dominating features before the feature weighting method. The findings suggest that the proposed wrapper based approach feature weighting technique is more capable of achieving higher accuracy than the existing strategies
Formulation And In Vitro, In Vivo Evaluation of Colon Targeted Drug Delivery System Of 5-Fluorouracil
No full textColon-targeted drug delivery systems can provide therapeutic benefits including better patient compliance and lower costs. The present investigation is aimed to design a colon specific microbially triggered system using biodegradable co-polymer mixtures. The calibration curves of 5-FU were measured in distilled water, 0.1N HCl and phosphate buffer of pH 6.8 and 7.4 which showed good linearity. Compatibility study of pure drugs, excipients and their physical mixtures were evaluated and passed as per standards. Solubility determination was carried out in different solvents. Satisfactory results were found from evaluation of micromeritic parameters such as flow property, in-vitro dissolution study and kinetic study. The prime focus of the study was to design and evaluate a swelling dependent delayed release system for a colonic delivery of anticancer agent 5-Fluorouracil (5-FU) and further to determine the effects of carboxy polymer (Carbopol 71G-NF) on release behavior of 5-FU from a matrix tablet system containing different amounts of inulin (a biodegradable oligofructose) aiding in enzymatic degradation by colonic microflora. Mixed film coating with a blend of Ethyl cellulose: Eudragit®S-100 (2:1) at coat weight levels of 2%w/w, 4%w/w and 6.0%w/w was carried out respectively, which further retarded the drug release in the initial hours of the in-vitro dissolution profile. Swelling studies were also carried out on uncoated matrix tablet batches. The releases studies with or without rat cecal contents were performed on optimized batches and the samples were analyzed by a validated RP-HPLC method. In-vitro rat cecal study results revealed that complete drug release would occur from the tablets in the human colonic microenvironment. The study revealed an effective site-specific delivery of a hydrophilic chemotherapeutic agent, 5-FU to the colon for the treatment of various local as well as systemic pathologies
A Novel Approach for Speech Recognition of Malayalam Using Enhanced MFCC Features
Get PDFThe study Investigates into the realm of speech recognition, particularly focusing on the evaluation of Hidden Markov Models (HMM), leveraging the MalayalamVoice dataset. The research scrutinizes the performance of HMM concerning word error rate (WER) and accuracy across varied word lengths, revealing a consistent trend of increased WER and decreased accuracy with longer utterances. This underscores the challenges inherent in accurately transcribing extended speech segments, accentuating the necessity for algorithmic enhancements. Moreover, analyses across diverse datasets and noisy environments underscore the criticality of comprehending dataset characteristics for refining recognition algorithms. Additionally, comparisons of different feature extraction methods elucidate the efficacy of Enhanced MFCC, particularly for shorter word lengths. However, as the word length extends, the distinctions between extraction methods diminish, highlighting the multifaceted nature of speech recognition. Overall, this study underscores the intricacies involved in speech recognition and the imperative of algorithmic refinements for augmenting accuracy, especially in practical scenarios
An Observational Study On Pharmaceutical Care Based On The Place Of Practice Of Pharmacists.
No full textBackground: Clinical pharmacists are crucial in enhancing patient care and medication effectiveness, focusing on safety and effectiveness, as they founded pharmaceutical care to improve patient quality of life. Methodology: An observational study was conducted on 869 patients in the southern state of India, examining prescription drugs received from various pharmacies, including community pharmacies, pharmacies connected to private hospitals, government medical college hospitals, and government Primary Health Centres. A self-administered, standardized, closed-ended questionnaire was employed. The data was sorted and summarized. Results: The study examined the impact of pharmacists' pharmaceutical care on workplaces, finding that patients appreciated the pharmacy's location, amenities, cleanliness, and hygiene. However, their educational background was not impressive. While most of them were unaware of the quality of the prescriptions they received, there wasn't much discontent with the medications' availability. The pharmacists' counselling attitude and knowledge were impressive. Conclusion: The study highlights the importance of pharmacists in pharmaceutical treatment, revealing that patients consider factors such as location, amenities, staff education, and attitude when choosing a pharmacy. Despite doubts about the quality of pharmaceuticals, adequate drug availability was found. The study also highlights the significance of pharmacists' knowledge and demeanor in responsible drug use, highlighting the need for both physical and professional aspects in pharmacy operations.
 
Prisoner’s Dilemma in Strategic Preventing of Covid -19: A Mathematical Exercise
No full textThe Prisoner’s dilemma is the best-known game of strategy in social science. It helps us understand what governs the balance between cooperation and competition in business, in politics, and in social settings [18]. The Prisoner's Dilemma model is being used for social problems as well as development work, thus this tool of game theory is multidimensional, it is using its important role in the topics of politics, biology, economics and logics etc. In this paper, we will discuss the success of the vaccine on the human being made to diagnose the current Covid-19 epidemic. MSC2010: 35Q91, 91A3
From Data to Decisions: The AI Revolution in Diabetes Care
No full textDiabetes Mellitus (DM) is a prevalent chronic disease that significantly increases the risk of developing other conditions such as ischemic heart disease, diabetic nephropathy, and atherosclerosis. This literature review investigates the application of artificial intelligence (AI) and machine learning (ML) in predicting and managing diabetes. The objective of the review is to explain how Artificial Intelligence and Machine Learning are currently employed in the provision of healthcare services with a specific focus on their application in diagnosing, predicting, countering diabetes through therapy. This paper presents a detailed stepwise systematic analysis based on PRISMA guidelines that sought to identify, choose, and assimilate select research works. For this review, 122 studies were reviewed out of 1235 articles first pulled from databases like PubMed, Google Scholar, Scopus, and IEEE Xplore. The results indicate that AI-driven predictive models significantly enhance risk assessment accuracy for diabetes management, achieving an area under the curve (AUC) of 0.85 for predicting the onset of type 2 diabetes. These models integrate genetic and environmental factors to improve prediction precision. Additionally, AI-based diagnostic tools, including image recognition for diabetic retinopathy, show high sensitivity (90.3%) and specificity (98.1%). The review highlights the need for thorough ethical and policy frameworks to ensure the safe and responsible implementation of AI in diabetes care. The findings suggest that audits of AI algorithms and the promotion of interoperability among AI systems are crucial for advancing AI-driven diabetes management. These insights contribute to policy development, clinical practice, and future research in the field. The conclusions emphasize the need for robust ethical frameworks and interdisciplinary collaboration to facilitate the effective implementation of AI and ML in healthcare systems
MSME In India: Recent Trends of MSME Which Reframed Its Definitional Characteristics
No full textSmall-scale enterprises have been around for a long time—over 4,000 years. They began in ancient cultures where trade was buzzing. Many societies, like the Indians, Egyptians, Arabs, Babylonians, Jews, Greeks, & Romans played a part. In those early days, skilled artisans made goods at home. They took care of everything—producing and selling right in the marketplac