International Journal of Engineering and Management Research
Not a member yet
1311 research outputs found
Sort by
Robage BOT
Get PDFOne of the biggest issues facing the entire globe today is waste management. Rapid population growth is a result of fast industrialisation, which also causes problems with waste management. It has been observed that there is a considerable likelihood that dumping light weight solid waste items may pollute public areas where the public congregates momentarily. There is no ideal method for keeping an eye on and maintaining these locations. It is possible to create a self-controlled robot application to solve these issues. Here machine can identify garbage and separate it into several categories, such as metallic and non-metallic waste.Implemented system uses IR sensors to detect garbage, metal proximity sensors to distinguish between metallic and non-metallic junk, and moisture sensors to further divide garbage into wet and dry waste. Here robot is controlled by an ESP32 microcontroller
Revolutionizing Divorce Case Prediction in India: A Machine Learning Approach to Save Marriages and Enhance Decision Accuracy
Get PDFThe rising number of divorce cases in India has raised concerns about the stability and well-being of marriages. Predicting divorce cases accurately can be critical in identifying potential risks and implementing timely interventions to save marriages. This study proposes a novel approach that uses machine learning algorithms to forecast divorce cases in India. The primary goal is to use advanced predictive models to improve decision accuracy and marriage preservation. To begin, the paper establishes the importance of accurate divorce case prediction by investigating the social, emotional, and economic consequences of divorce on individuals and society as a whole. An extensive review of existing literature is conducted, shedding light on the limitations of traditional divorce methods. The paper goes over the process of gathering detailed socio-demographic information, marriage history, and psychological factors from various sources. Preprocessing is performed on the collected dataset to address missing values, outliers, and ensure data integrity. To train predictive models, various machine learning algorithms such as logistic regression, support vector machines, random forests, and gradient boosting are investigated. To identify the most relevant predictors contributing to divorce cases, feature selection techniques are used. The accuracy, precision, recall, and F1-score of these models are used to evaluate their performance. In addition, the interpretability of machine learning models is investigated in order to gain insights into the underlying factors that lead to divorce [7]. This analysis contributes to a better understanding of the critical factors that influence marital outcomes and provides useful information for policymakers, counsellors, and individuals looking to strengthen their marriages. The proposed machine learning approach\u27s ethical considerations and potential implications in the legal and counselling domains are thoroughly discussed. Concerns about privacy, fairness, and transparency are addressed in order to ensure responsible and accountable predictive model deployment in the divorce case prediction process. The study demonstrates how machine learning has the potential to revolutionise divorce case prediction in India. This approach can facilitate timely interventions, counselling, and support systems to preserve marriages and foster marital harmony by accurately identifying marriages at risk. This study\u27s findings contribute to the burgeoning field of automatic court decision prediction and provide actionable insights for stakeholders involved in marriage counselling and family law in India [4]
Utilization of Manufactured Sand with Partially Replacement of Natural Sand in Concrete
Get PDFNatural Sand used in manufacturing concrete is sourced from natural river bed which if not replenished causes environmental concerns. Scarcity of good quality Natural River sand due to depletion of resources and restriction due to environmental consideration has made concrete manufactures to look for suitable alternative fine aggregate. This has prompted researchers to look for alternate material that could potentially replace natural river sand without adversely impacting properties of resulting concrete. A replacement of finer aggregates by a manufactured sand by varying proportions leads to the increase in both engineering & physical properties of concrete constituents which are to be considered in recent trends. In the present study manufactured sand with varying proportions from 0 to 60 % by its weight are mixed with concrete materials as a partial replacement with fine aggregates & analyzed for its physical and engineering properties, with the further analysis an introduction of manufactured sand in a proper proportion will lead to increase in the compressive strength by 15 to 20% for the concrete cubes which are being tested for 7 days, 14 days & 28 days strength
Design and Development of Experimental Test Rig for Fault Diagnosis of Ball Bearing Using Fuzzy Logic Concept
No full textRolling element bearings are frequently employed in industry. Many machine-related issues are linked to bearing failures. To minimize downtime and preserve product quality in a highly automated production, an online detection system is required. Condition-based monitoring for deep groove ball bearings is becoming more common. All rotating machinery uses these bearings extensively to accommodate both static and dynamic loads. Techniques for condition-based monitoring can be utilized to diagnose bearing defects to prevent this failure. So, it is important to study these faults present in the machines. The techniques for fault detection will be described in this paper. We are discussing Fast Fourier Transform (FFT) technique. In FFT, we obtain frequency-relationship graphs, and based on peak frequencies, we predict faults. A detailed analysis using the FFT Methodology is done to find out the possible faults, and finally validate with MATLAB software. For the aim of bearing diagnostics, the system performs vibration analysis. More advanced diagnostic systems use fuzzy logic and classification methods to identify the state of the machinery. These techniques enable the creation of more automatic and trustworthy diagnostic systems
Intelligent Assistance for Smart Shopping
Get PDFOver the past few years there has been vast development in Android Application technology. This development made people\u27s lifestyle much easier and interesting through various innovations by finding solutions to day-to-day problems. Even though many things became easier, still shopping is tough. For customers finding the required product in the supermarket is the most challenging task and moreover it is exhausting to stand in long queues at the billing counters. Shopping is a day-to-day activity. Many people visit supermarket for shopping on regular basis and during weekends, holidays and festive season supermarkets witness huge crowds. The development of online shopping websites has attracted people to purchase products online without visiting any supermarket. Mostly all the products are available on websites like Amazon, Flipkart, etc. But people cannot verify the quality of the product physically and can only verify after the product’s delivery. If the product is not up to the customer’s expectations, then it becomes a hefty task of returning and reordering the product
Thermal Stress Analysis of Composite Laminates using Trigonometric Shear Deformation Theory and Finite Element Method
Get PDFLaminated composite materials offer a versatile design approach for achieving the desired levels of stiffness and strength by selecting specific lamination schemes. The Trigonometric Shear Deformation Theory (TrSDT) effectively addresses the appropriate distribution of transverse shear strains throughout the plate thickness while maintaining stress-free boundary conditions on the plate\u27s top surfaces. Consequently, there is no need for a shear correction factor.
In this research paper, we use the Trigonometric Shear Deformation Theory (TrSDT) that takes into account the influence of transverse shear deformation. The in-plane displacement field incorporates a sinusoidal function with respect to the thickness coordinate to accommodate the effects of shear deformation. Theories that involve trigonometric functions based on the thickness coordinate in the displacement fields are collectively referred to as Trigonometric Shear Deformation Theories (TrSDTs).
In the present study, we conduct a thermal stress analysis of Laminated Composite Plates using the TrSDT. This theory eliminates the need for shear correction factors and provides a more accurate distribution of interlaminar stresses compared to other methods like CPT and FOST. We assess deflection and stress at various locations and for different aspect ratios under thermal loads using TrSDT. Stress evaluations are carried out analytically, and the results are validated by comparing them with existing findings from the literature.
To further verify our findings, we model a composite laminate under thermal loads using the commercial Finite Element Method tool ABAQUS, and our results are validated against those obtained with the TrSDT for plates with simply supported boundary conditions
A Study of the Significance of Mini Cement Plants in Building A Self-Reliant Economy
Get PDFNowadays, usage of cement is recognized as the most influential yardstick of urbanization vis-à-vis development of the economy. With the increasing demand for this wonder material, the mini cement plants are emerging as the counterpart of large plants in making the material available in the remotest of locality. In this process, they are remarkably fostering self-reliance while giving due consideration to environmental protection too. In this paper, attempts have been made to highlight the significance of mini cement plants in encouraging local entrepreneurship along with shaping a concrete economy for the region. The study will also try to analyze the performance, problems, and prospects of the mini cement plants along with the extent to which various factors influence their existence in the region of study
Agile-Omoluabi Leadership, Technology-Transfer, Government Willingness to Change, Engagement and Organizational Citizenship Behavior: Examining the Moderating-Mediating Role of Workplace Happiness in Nigeria’s Healthcare System
Get PDFOn the backdrop of the aggressive move by the healthcare workers in Nigeria to foreign countries to ply their expertise, the country has suffered her worst brain-drain episode leading to been labelled among the 55 countries experiencing healthcare short in Africa. This is right and it call for an array of contextual issues including; leadership, technology transfer, government willingness to change, engagement, organisation citizen behaviour and workplace happiness to tackle this rather unfortunate incidence. A validated questionnaire was employed to gather data from 408 health-care practitioners including doctors, nurses, pharmacists, technologists and administrators in public-owned hospitals in Nigeria. A path analysis was used to examine the six-way direct, mediation, and moderation hypotheses. Results showed that agile-Omoluabi leadership, government willingness to change and technology transfer had positive and significant effect on engagement (Adj R2 =0.685, p=0.000, Q2 =0.484), workplace happiness stood as a positive and significant intervening variable mediating the interaction between agile-Omoluabi leadership and organisation citizen behaviour (β=0.257, t= 2.033, p= 0.043) as well as serving a moderator for the linkage between engagement and organisation citizen behaviour (β =0.300; p< 0.000, Q2 =0.365). The findings of this study as practical implication for the ministry of health in Nigeria because it offers strategic information which confirms the twofold relevance of workplace happiness as critical to sustaining health-care practitioners’ engagement and guaranty exhibiting citizen behaviour. Also reinforce the need for government at all levels to show readiness to transform, plan and implement a systematic process of technology transfer and show a leadership that care about the health-care practitioners and one that is dynamic. This if done, should address the brain drain and improve the lost glory of the health-care system in Nigeria
Green Attributes & Customer Loyalty towards ABC Supermarket in Colombo District, Sri Lanka
Get PDFAt present, people are more concerned with the environment because of growing environmental consequences. According to that shift, retail businesses are converting from traditional marketing practices to green marketing practices. In the Sri Lankan context. Most of the retail businesses are shifting to green practices. But customers\u27 actual green purchase behaviors are very low level. This study was conducted to examine green attributes impact on customer loyalty towards ABC supermarket in the Colombo district. This study observes six independent variables such as green products, eco branding, eco-labeling, eco advertising, environment awareness, and green price and customer loyalty as the dependent variable. This study was conducted using a quantitative research approach and explanatory design. Therefore, the researcher used self-administered questionnaires to collect primary data. The questionnaire was disseminated among 384 ABC supermarket users under the convenience sampling method. In this study, Correlation and multiple linear regression analysis were employed to analyze the hypotheses. According to the result of this study, there is no significant influence of eco-labeling and eco-advertising on customer loyalty. The other five independent variables such as green products, eco branding, environment awareness, and green price are a significant influence on customer loyalty. Furthermore, the analysis identified some limitations in the research and gave recommendations to future researchers to generate a successful and accurate result of the study
The Impact of AI-Enhanced Social Media Strategies on Entrepreneurial Performance
Get PDFThis research aims to explore the influence of AI-enhanced social media strategies on entrepreneurial performance. The study incorporates a bibliometric analysis in the research methodology to provide a comprehensive understanding of existing literature, identify key themes, and contribute to the current knowledge base. Both China and the United States emerge as frontrunners in contributing to the scholarly discourse. The suggested insights offer promising avenues for future research, encouraging scholars to delve deeper into the strategic, human-centric, precision-oriented, collaborative, ethical, and methodological dimensions of AI-enhanced social media strategies in the entrepreneurial context