Analysis of Mental Health Problems Among Higher Education Students using Machine Learning

Currently, mental health concerns pose a significant issue in Odisha. Generally, mental health problems affect a person\u27s thoughts, feelings, actions, and communication. As per the 2017 National Health and Morbidity Survey (NHMS), one in five individuals in Odisha suffer from depression, two have anxiety, and one out of ten experiences stress. Additionally, students in higher education are at an elevated risk of developing mental health problems. However, helping a person with mental health concerns can be challenging due to difficulties in identifying the root causes of their condition. The main objectives of this study are to: 1. Explore mental health issues among higher education students. 2. Investigate the factors that contribute to these issues. 3. Assess the effectiveness of machine learning techniques in analyzing and predicting mental health problems among higher education students. Using computational modeling, this paper\u27s findings will contribute to the ongoing discussion on mental health concerns in future research

Nonlinear Spectral Unmixing using Semi-Supervised Standard Fuzzy Clustering

Coarse resolution captured in remote sensing causes the combination of different materials in one pixel, called the mixed pixel. Spectral unmixing estimates the combination of endmembers in mixed pixels and their corresponding abundance maps in the Hyper/Multi spectral image. In this paper, a nonlinear spectral unmixing based on semi-supervised fuzzy clustering is proposed. First, pure pixels (endmembers) using Vertex Component Analysis (VCA) are extracted and those pixels are the labelled pixels where the membership value of each is 1 for the corresponding endmember and 0 for the others. Second, the semi-supervised fuzzy clustering is applied to find the membership matrix defining the fraction of the endmember in each mixed pixel and hence extract the abundance maps. The experiments were conducted on both synthetic data such as the Legendre data and real data such as Jasper Ridge data. The non-linearity of the Legendre data was performed by the Fan model on different signal-tonoise ratio values. The results of the new unmixing model show its significant performance when compared with four state-of the art unmixing algorithm

Cloud Computing for Supply Chain Management and Warehouse Automation: A Case Study of Azure Cloud

In recent times, organizations are examining the art training situation to improve the operation efficiency and the cost of warehouse retail distribution and supply chain management. Microsoft Azure emerges as an expressive technology that leads optimization by giving infrastructure, software, and platform resolutions for the whole warehouse retail distribution and supply chain management. Using Microsoft Azure as a cloud computing tool in retail warehouse distribution and supply manacle management contributes to active and monetary benefits. At the same time, potential limitations and risks should be considered by the retail warehouse distribution and the supply chain administration investors. In this research summary of the cloud figuring tool, both public and hybrid in supply chain administration and retail, warehouse distribution is addressed. A brief introduction to the use of Microsoft Azure technology is provided. This is followed by the application of cloud computing to warehouse retail distribution and supply chain management activities. At the same time, the negative and positive aspects of familiarizing this Microsoft Azure technology in the modern supply chain and retail distribution are debated. Also, the circumstance for the third-party logistics services suppliers has indicated respect for automation and cybersecurity solutions in a cloud environment. Lastly, the upcoming research practices and following technological trends are offered as the conclusion

AN EXPERIMENTAL INVESTIGATION OF MULTI-CYLINDER CONVENTIONAL CI ENGINE USING MADHUCA INDICA OIL AS FUEL

The present work is mainly discussed with a qualitative study of engine’s significant characteristics fuelled with mahua bio-diesel & its different types of mixtures with neat diesel. The significant technical properties of various mixtures are tabulated. A 4-S multi-cylinder (6-Cylinder) DI conventional CI engine is used for the study under different speed modes. All types of characteristics for various mixtures are estimated in running the engine. Pure diesel is indicated by B-0 and pure mahua bio-diesel is represented by B-100. From the test results, it is found that B-25 gives almost the same BTE as B-0 at maximum load, compared to all the blends. The blend B-0 and B-25 give the least SFC of 0.332 and 0.268 kg/kWh at minimum speed (1200 rpm) and maximum speed (2400 rpm) at maximum load as contrasted to all mixtures. The B-100 gave 3.01% of NOx while related to B-0 @ lower speed

Forecasting Stock Market Indices Using Gated Recurrent Unit (GRU) Based Ensemble Models: LSTM-GRU

A time sequence analysis is a particular method for looking at a group of data points gathered over a long period of time. Instead of merely randomly or infrequently, time series analyzers gather information from data points over a predetermined length of time at scheduled times. But this kind of research requires more than just accumulating data over time. Data in time series may be analyzed to illustrate how variables change over time, which makes them different from other types of data. To put it another way, time is a crucial element since it demonstrates how the data changes over the period of the information and the outcomes. It offers a predetermined architecture of data dependencies as well as an extra data source. Time Series forecasting is a crucial field in deep learning because many forecasting issues have a temporal component. A time series is a collection of observations that are made sequentially across time. In this study, we examine distinct machine learning, deep learning and ensemble model algorithms to predict Nike stock price. We are going to use the Nike stock price data from January 2006 to January 2018 and make predictions accordingly. The outcome demonstrates that the hybrid LSTM-GRU model outperformed the other models in terms of performance

Challenges and Strategies for Women Empowerment in India: Facts and Realities

In today’s world women empowerment is an important issue of discussion because in every sector we find women which constitute half of the total population in the world are lacking behind. If about half of the nation\u27s human resources are neglected, the overall progress of the country would obviously be hampered. Women empowerment has become one of the most central concerns and need of the hour but in reality, the situation is not good enough. In the traditional patriarchal society, women have been given a secondary status which is reflected in the economic, social and political spheres. However, women equality and empowerment has always remained a priority area and has been taken utmost care by stake holders. Gender mainstreaming propels progress towards the ultimate goal of attaining gender equality and women empowerment. In this direction policies and programmes at different levels to cover various proportions and strategies of gender development have been framed by the government of India. The paper critically examines women empowerment in India, various challenges and strategies. The paper discusses constitutional safe guards as well as plans and programmes by the government and their implementation, indicators of women empowerment in India. Finally, this paper is an attempt to examine the status of women in India and provides some policy suggestions for women empowerment

A Systematic Review of Hybrid Renewable Energy Systems About Their Optimization Techniques with Analytic Hierarchy Process

Hybrid renewable energy systems are the fastest growing power sector worldwide. The drawbacks of most hybrid energies were identified by the previous researchers such as space/sizes and costs of the system. This review article aims to find out the best optimization techniques for HRES by using the Analytic Hierarchy Process (AHP). More than 100 plus papers were taken to do this review. Among all the top energy journal publications considered for these reviews such as ELSEVIER -54.9%, SPRINGER-6.9%, MDPI-5.9%, TAYLOR AND FRANCIS-5%, IEEE ACCESS-13%, and others -15%. Thus, the expected result of this review is that the researchers acknowledge their decision-making to choose the best optimization techniques and hybrid renewable energies

An Experiment To Analyze The Impact of Steam On The Productivity of The RF STALAM 85 kW Yarn Dryer

Radio Frequency has been one of the most commonly used technologies in the processing industries like textile, rubber, paper and many other industries for drying purposes. The RF STALAM 85kW is a machine used to dry the yarn obtained after the dyeing and hydro extraction process. This machine uses radio frequency to remove the moisture content from the dyed yarn. In this research paper, I would like to share the findings of an experiment conducted on the RF STALAM 85kW yarn dryer machine. In this experiment, I have three trials each with and without the steam at variable conveyor belt speeds. At the end of the experiment, I calculated the per day production to conclude the optimum speed to run the RF STALAM 85kW yarn drier machine to obtain maximum production with and without steam

Minimise Cost Overrun Using Sustainable Construction Materials in Sri Lankan Construction Industry

A successful construction project is determined when it is completed within the expected budget and time, ensuring the required levels of quality and safety. For a project to be successful, it is essential to plan properly and have a reliable monitoring system in place. Furthermore, the building construction sector has a negative impact on the environment by generating waste, increasing carbon emissions, polluting the air and water, and accelerating climate change. This study intends to investigate cost overrun prevention strategies in Sri Lanka using sustainable building materials. Accordingly, a mixed-method research approach was selected, and an e-based closed-ended questionnaire survey and semi-structured expert interviews were carried out to collect data from construction industry professionals. In the questionnaire survey, a total of 80 construction industry experts were selected from different job categories as the respondents, and 53 responses were received with a response rate of 66.25%. On the other hand, 10 construction professionals participated in the semi-structured interview. The study has identified 15 factors that significantly impact cost overrun in the Sri Lankan building construction sector based on the mean weight ratings. The study found that using sustainable alternatives to natural resources at a lower cost is preferable. The most workable solutions to control the identified critical factors were determined to be new policies for sustainable construction, new financial frameworks for importing sustainable materials, new construction methods and technologies associated with sustainable materials and controlling the monopoly of sustainable material suppliers or manufacturers

FAILURE MODE EFFECTIVE ANALYSIS IN A BOILER USING COMBINATION OF EVENT TREE AND FAULT TREE ANALYSIS

Boilers are valued highly in many industrial industries and are expensive assets. In addition to their initial expense, they demand a large maintenance budget in order to guarantee output in respectable and safe working conditions. In order to avoid extreme repercussions, including the loss of lives, these assets must be carefully operated under experienced, well-trained supervision and subject to rigorous maintenance schedules and safety activities. However, this investigation is carried out with the help of the FMEA method, considering the previous literature\u27s studies of boiler accidents in Asia so far. Phase I has detailed information about boilers and Asian boiler accidents, and this research paper explains its nature. Subsequently, based on the data obtained in Phase I, an FMEA model will be developed in Phase II to highlight key boiler safety points. This research helps boiler manufacturers, boiler-related entrepreneurs, and boiler users to ensure maximum safety and identify any new things related to boiler safety