Volume 07 Issue 01

Abstract: The term “stock market” describes the exchanges and markets were buyers and sellers trade equities. Without understanding and knowledge of how the stock market operates, one risks suffering significant financial losses. The market is unpredictable; recent instances include COVID-19 and Russia’s invasion of Ukraine, both of which caused significant losses for the market. Without awareness, people suffer more losses, which strains relationships within families. People are becoming victims of scams and other types of fraud more frequently these days due to the increasing market dangers. We must gain a thorough understanding of the stocks and the market’s operation if we are to prevent those losses [15]. In the stock market, stock exchange prediction is quite significant. Forecasting stock exchange rates is an essential financial topic that is getting more attention since it makes it easier to design profitable trading techniques [9]. It is thought that one of the most intriguing concepts and crucial tasks for the investigation of financial time series is the- forecasting of stock price movement in general. The Least Absolute Shrinkage and Selection Operator (LASSO) method is suggested in this paper as a special way for predicting the behavior of financial markets. A linear regression model is the foundation of LASSO. When there are fewer features than observations, the LASSO approach excels at producing sparse solutions.

Abstract: Safe drinking water has always been one of the primary essential requirements for healthy and sustainable human life. Due to the scarcity of water in some places, reusable water cans play a major role in many parts of the world. Reusable water cans not only save money for the user in the long run, but it is also more environmentally friendly than disposable materials. However, there is a risk of microbial growth in reusable drinking water cans and its associated health risks even if it is normally used daily or for many months by users. In the long run of the usage of cans, sediments and algae get deposited in the water cans, and this deposition contaminates the water and makes it unfit for use. Awareness associated with safe drinking water is tremendously important and should be given good thought to the people. With that social cause, this work focuses on the design and fabrication of a semi-automatic water can cleaning system for effective cleaning. Further, the system is not just only to clean the slag but also to reduce human efforts. The mechanism used in the system is more effective and safer than conventional methods and thus ensures clean and safe drinking water.

Abstract: Inverters are widely used in Switch Mode Power Supply (SMPS), Flexible AC Transmission System, Variable Frequency Drives (VFD), Active High Power Filters High Voltage Direct Current (HVDC) Systems, Renewable Power Conversion Systems as well as in different industrial and domestic processes. Power electronic inverters are very popular for fast response and precise control. In this paper conventional modes of conduction such as 180° and 120° are compared with different modes of conduction such as 80°, 90°, 110°, 130°, 140°, 150°, 160° and 170° of Three-Phase IGBT based Voltage Source Inverter (VSI) on MATLAB Simulink. A detailed comparative harmonics analysis is carried out explaining the reduction in Total Harmonic Distortion (THD) when Voltage Source Inverter (VSI) is operated at different conduction modes. The effect of filters on harmonics is also studied in this paper. Simulation results for 3 Phase inverters with and without filters and impact on harmonics have been presented. The line to Line and Line to Ground voltage waveform results are evaluated. The design is tested on resistive and inductive loads, proving 150° as the best suitable mode of operation of VSI for different loads. The objective of the research is to design an efficient inverter for domestic and industrial purposes. The simulation is done at higher voltages so that practical implementation becomes easier.

Abstract: Traditional cryptography techniques have been used for many years to protect data from malicious attacks. However, these methods have become increasingly vulnerable to attack over time due to advances in computing technology. This paper proposes Hybrid Multiple Cryptography (HMC), a novel data encryption scheme. This scheme implements an approach that seeks to incorporate both Hybrid cryptography and Multiple cryptography as a way to provide an enhanced layer of security by combining both of their strengths while also mitigating the drawbacks that are present in each individual approach. The process begins with the creation of a symmetric key as well as an asymmetric key pair consisting of a public and a private key. Initially, the message is encrypted using the symmetric key encryption technique with the symmetric key that can encrypt the message for n number of times. The resulting encrypted text and symmetric key are encrypted with the asymmetric public key using the asymmetric key encryption algorithm. The decryption process, on the other hand, is a reversal of the encryption process. Thus, the scheme is a reliable and effective data encryption system that can offer greater data protection than conventional encryption approaches.

Abstract: Background: Drusen are yellow deposits that are present in the retina. They are made up of proteins and lipids which are present as exudates. Drusen don’t particularly cause Age–Related Macular Degeneration (AMD), but the prolonged presence may cause the development of DRY AMD which can lead to WET AMD. Hence, it’s important to detect these deposits in the early stages. Deep learning-based artificial intelligence is currently creating an impact on healthcare. The application of Deep Learning in Ophthalmology speeds up the diagnosis process and gives accurate results in the early stages. Aim: To develop a deep learning-based algorithm for the diagnosis of drusen in Optical Coherence Tomography (OCT) and Colour Fundus Images. Method: In this study, we proposed a novel deep learning algorithm DrusNet for the diagnosis of drusen in OCT and Colour Fundus Images. DrusNet is an ensemble neural network developed from the pre-trained models EfficientNetB3 and VGG16 for accurate diagnosis. The proposed model DrusNet performed well in both OCT and fundus images. Result: For the classification of OCT images this model achieved an accuracy of 90.15%, an AUC of 0.95, a precision of 86.89%, and a recall of 91.38%. For the classification of Fundus images, this model achieved an accuracy of 95.9an 9%, AUC of 0.99 and, the precision of 98.91%, and recall of 91.00%. Conclusion: The proposed architecture may be used by ophthalmologists as a pre-screening tool to identify drusen deposits at an early stage to prevent AMD.

Abstract: The utilisation of renewable energy sources for sustainable energy utilisation activities is heavily promoted today. One example of a clean renewable energy source is photovoltaic (PV) energy. Here, we’re considering the amount of energy being consumed.Activities of the Holy Grace Academy of Engineering (HGAE), including a feasibility study for the installation of solar PV panels for the expected daily energy usage. The building’s daily energy needs and peak power demand can be calculated using the findings of an energy audit that identifies the energy-consuming activities. After identifying the energy consumption pattern, a technical and financial feasibility analysis of installing a solar panel is conducted.

Abstract: Ground effect is described as the phenomenon where an aircraft experiences an increase in lift and a reduction in drag when flying in very close proximity to the ground or water surfaces. This occurs due to the air pressure differential created between the lower surface of the aircraft’s wings and the ground, also known as ram pressure. As an aircraft approaches the ground, the air displaced by the wings is compressed between the compact portion of the wings and the ground, which increases air pressure, allowing the aircraft to fly more efficiently at lower altitudes. Ground effect is most significant when the wing of the aircraft is at an altitude less than one wingspan above the ground (20-80% of chord length). Certain airfoils like NACA 4412 is a common choice for the wings when it comes to designing a Wing-in- ground effect vehicle at an angle of attack ranging from 3° to 6°. The analysis of the NACA 4412 Airfoil is depicted in this paper at common cruise speeds experienced by Wing-in-Ground (WIG) vehicles at angles of attacks of 6° and 4°.
Factors such as velocity and pressure experienced by the airfoil in those conditions are analyzed. The lift coefficient and lift-to-drag ratios are studied as they are the indicators of the efficiency of airfoils.

Abstract: Uniconnect is a web application platform designed to provide a convenient way for university students to buy, sell, and exchange their used textbooks, stationeries, and other related materials. The platform enables students to connect and interact with each other to trade and exchange items based on their needs and preferences. This research paper focuses on the development and evaluation of the Uniconnect platform as a means of promoting sustainability and reducing waste in the university campuses. The study includes an analysis of user behavior, user satisfaction, and the platform’s impact on the environment. The findings suggest that Uniconnect has the potential to significantly reduce waste and increase the availability of affordable textbooks and stationeries for students. Overall, Uniconnect represents a novel approach to sustainable campus living, and its success can serve as a model for future sustainable initiatives.

Abstract: Sewage water contains toxic gases which may cause harmful effects on both humans and the ecosystem. Unfortunately, India lacks a proper monitoring system for detecting toxic gases in sewage. Exposure to sewage gases can cause serious health issues such as fatigue, loss of appetite, and even death. To address this issue, an IoT based monitoring system is proposed that detects the presence of toxic gases, their level, and flow of sewage water in real time. The system is equipped with various sensors such as gas detecting and flow detecting sensors to detect toxic gases. When the level of toxic gases increases beyond the normal range, the system sends an SMS alert to the main authority responsible for managing the sullage area. The proposed system uses Java for both frontend and backend. By implementing this monitoring system, the risk of disease-causing situations due to toxic gases can be greatly reduced.

Abstract: The increase in population and the growth of businesses has resulted in an increase in waste output. Leachate is a liquid that results from the movement of water through solid waste and can contain a variety of contaminants, including heavy metals, organic compounds etc. The objective of the project is to develop a long-term solution to leachate percolation into groundwater. Here, we consider the case of Brahmapuram waste dumping site at Kochi. As degradable and non degradable wastes are disposed there, leachate seeps into the ground and mixes with groundwater and the river that run along its boundary. As a result, the water from adjacent water bodies becomes unfit for drinking and other uses. Therefore, we are developing a solution for this problem. A landfill is firstly designed using data collected. After that,the leachate from waste is collected. The collected leachate is then handled sustainably and changed into a form that may be disposed into water bodies without endangering the aquatic life there. The project also seeks to suggest ways to utilize the waste generated by extracting fuels like biogas and plastic fuel. As a result, we are attempting to find a comprehensive solution for the Brahmapuram site, which has serious environmental implications.