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An experimental investigation is carried out to study the behaviour of cement mortar using red soil partially replaced with p-sand (plastering sand). In this study, cement mortar of mix proportion 1:4 using red soil is partially replaced with p-sand as 5%, 10%, 15%, 20%, 25%. Compressive strength test, water absorption test, sorptivity test and acid immersion test are conducted to determine the properties of the cement mortar. The results show that the partial replacement of red soil with p-sand improves the compressive strength and reduces water absorption and sorptivity. Additionally, the acid immersion test revealed that the cement mortar with partial replacement of red soil with p-sand is more resistant to acidic conditions. This study provides insights into the potential use of p-sand as a partial replacement of red soil in cement mortar production, particularly for plastering purposes

Liver Tumour (LT) develops when healthy cells undergo abnormal DNA changes that cause them to grow and divide uncontrollably. In manual examination, evaluation might be changed by the unique perception of the observers, which depends on their expertise and subjectivity. Therefore, computer-aided intelligent tools are established to eliminate subjectivity and increase the performance. To overcome these challenges, a novel Two-fold Segmentation of Liver Tumour (TFSLT) model for accurately detecting the liver tumour using computed tomography (CT) images. Initially, the CT images are pre-processed using Normalized-Modified Anisotropic Diffusion Filtering (NMADF) Algorithm to reduce the noise artifacts. These pre-processed CT images are taken as input to the Canny Edge Detector (CED) for detecting the edges of the liver. Based on these edges, the first-fold segmentation process is performed using the Jaccard metric-based Watershed (JMWS) algorithm to accurately segment the liver region. Improved Deep Neural Network (IDNN) is utilized to classify the LT into normal, Hepatocellular carcinoma (HCC), Cholangio carcinoma (CC) and Metastatic tumour (MT). Modified Elephant Herd Optimization (MEHO) algorithm for the MEHO algorithm for selecting the features of the images. Finally, the Improved Expectation-Maximization (IEM) Algorithm as second-fold segmentation process to segment the different abnormal classes. The performance of the proposed TFSLT approach is assessed using the specific metrics like recall, precision, specificity, accuracy and F1 score. The experimental findings reveal that the proposed TFSLT approach achieves a better accuracy range of 99.57% for detecting LT in its early stages.

Many industries require a certain amount of electrical power. Prepaid metering, with its unique performance in the Internet of Things (IoT), tends to be an efficient power management system by providing cost-effective prepaid electricity services to the industrial sector. Errors can occur at any stage of the energy billing process, including errors in electromechanical meters, human errors during meter reading, and errors in processing paid and unpaid bills. A prepaid energy meter is the solution to these problems. In this work, prepaid energy meters were developed to reduce energy consumption in the industry. The introduction of this prepaid meter will contribute to improving energy management, saving energy, and eliminating fraudulent billing. Automated billing systems track consumption in real time, eliminating the possibility of fraudulent billing and consumption disputes. A prepaid energy meter was developed using current and voltage sensors, and the energy meter was tested with a load connected to a 220 V power supply. Energy meters are connected to the cloud to create a user alert system.

Aluminium metal matrix composites (AMCs)refer the class of light weight and it have been utilized in high-tech structural and functional applications including aerospace, defence, auto move, and thermal management area, as well as in sports and recreation on, Aluminium based metal matrix composites (MMCs) with add ion of SIC and Red Mud reinforcement was fabricated by using casting. Red mud emerges as the major waste material during production of alumina from bauxite by the Bayer's process. So composites using Red mud can be used to reduce the cost of the metal matrix and environmental related issues. The samples were produced by using the aluminium, silicon carbide and red mud. Two types of die 20mm used for compaction to obtain the specimen. The diameter of 20mm rod is used for the tensile, hardness and wear test. This present study evaluates the mechanical proper es of the composite and results were obtained.

The pure sense of automation is to reducing the human effort and increasing the reliability and accuracy of the process. The objective of the project is to design and implement a semi-automatic clutch system for automobiles, which provides a simplistic remedy for physically challenged. Applying clutch manually at every instant, while changing gear is comfortless. In synchronizing switch with clutch pedal differently-abled people realize more difficulty inCBA pedal system. During the rush hour of traffic, the driver should be able to shift the legs simultaneously to change the gears, but it is practically a hectic work for the driver to do so. Automationcan be achieved through computer, hydraulics, pneumatics, robotics, etc., of these sources’pneumatics form an attractive medium for low-cost automation. Automation plays an important role in automobile. Technical success of this project relies upon the work expected from the different sectionsof this project. The actuation of the clutch pedal depends upon the signal from the DCV and the link mechanism is used for engaging and disengaging the clutch. Hence this project can be used in either automatic mode or in the manual mode in which the link mechanism can be removed out when not necessary in the hill stations where to remain the vehicles in Half-clutch. The entire process is controlled by using the directional controlvalve in which the retraction speed of the systemis controlled by throttling valve or needlevalve

This study aims to examine the shrinkage flaw in grey cast iron. The poor gating system design, improper composition management, and solid sections with a high modulus (Volume/ Surface area) in the casting are the root causes of the shrinkage fault. The gating mechanism can first be redesigned in order to lessen shrinkage. A new gating system with a different chemical makeup is suggested. Grey cast iron's composition changed due to an increase in carbon content. Thus, proCAST is used to develop and analyze the gating system. Implementing the planned gating system in the foundry served to validate the results. It is accomplished to increase the effective yield

Along with water and air, grub is a basic requirement for all living things. The grub issue occurs in the majority of developing countries, primarily as a result of unpreserved food. As a result, the solar drying system makes use of the solar energy is used to heat the air and dry any agricultural produce that is loaded, thereby lowering the cost. Agriculture reduces food waste while also preserving it. And dried produce (Ginger) is easily transported. And promotes the health and well-being of all living things. There are a lot of agricultural lands in India. Because of various factors Due to climate change, many agricultural products are thrown away. To reduce such waste, solar dryers are used to dry agricultural produce. Wood, glass, net, pipes, anemometer, blower, and basic carpentry work are used to build the solar dryer and drying chamber. The fabrication of dryer and drying chamber is construct with basic carpentry work. The blower forced the air inside the heater area the air will be heated with the solar radiation and the heat air forced with the drying chamber. The drying chamber has a surface area of (40*40) cm. The ginger (1/2 kg) drying three specific periods of time, and the reading will notice with specific time. After the moisture content will removed to compare the produces life with open sun drying and solar drying method

Introduction: In the context of the COVID-19 pandemic, studies on perinatal severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection play an essential role in the understanding of the disease which in turn is necessary for optimal management of affected neonates. Aim and Objective: To determine the clinical outcomes in neonates born to mothers with SARS-CoV-2 infection and to identify possible risk factors in perinatal transmission. Materials and Methods: This was a retrospective cohort study performed at level-3 teaching Neonatal Intensive Care Unit (NICU) in South India. Medical records of all mothers who delivered in the COVID-19 facility and neonates born to COVID-19 confirmed mothers from April 15, 2020, to September 15, 2021, were collected and analyzed. Results: Of 15,720 deliveries, 556 mothers who tested positive for COVID-19 delivered 563 babies (7 twins), of which 6.3% were positive for SARS-CoV-2. Out of 563 babies, 14.5% were preterm and 95% were asymptomatic. Among COVID-19 positive mothers, cesarean was the most common mode of delivery (73.5% and 88% in COVID-19 positive and negative neonates respectively; P value = .01) and most of the babies were roomed-in (85.2% in COVID-19 positive and 94.6% in COVID-19 negative neonates; P value = .02). COVID-19 positive neonates had significantly high probability of pneumonia ( P value = .003), sepsis ( P value = .03), septic shock ( P value = .01), and abnormal CXR ( P value = .01). There was no significant difference in the mortality rate. Conclusion: COVID-19 positive status of the mother is not associated with increased risk of preterm birth, neonatal admission, morbidity, or mortality. The risk of transmission was not found to be associated with direct breastfeeding or rooming-in.

Nowadays, Email spam is a major problem, with the increase usage of internet for product promotions, e-banking, e-loans, health related articles, movie news etc to users. Besides the people are practicing unwanted and unethical conduct as in phishing and mailing fraudulent information. Sending suspicious links through spam emails can harm our system and can also be sought after our system. Creating a fake user identity and email account is such easy for spammers. They pretend like a genuine entity in their spam emails and target those people who are not aware of these frauds. So, it is essential to identify those spam emails which are fraud. In this proposed work, we have applied machine learning algorithm to identify whether the incoming mail is spam or ham. This project will discuss how the Naive Bayes machine learning algorithm is applied on our data sets and how it has been selected for the email spam detection with the best precision and accuracy

This study deals with Drone based Aerial Survey in analyzing and identification of highly vulnerable mosquito breeding sites at Buckingham canal Chepauk, Chennai. It is small section of Buckingham canal studied using the drone for capturing the images and furtherly images were processed for identifying the sites prone to breeding of mosquitos. Approach used here of capturing images and classifying the vulnerable sites, using a machine learning approach in for extracting features using the algorithm and later generating a Support Vector Machine to train and classify the images. Tensorflow object detection algorithm was used to detect the object and also generate the probability level. Tensorflow based supervised classification involves stacking multiple layers of neural network for a classification. Methods like back propagation invoked in the neural networks ensures the classification accuracy are increased. In this algorithm Single shot multi box detector (SSD) has been used which provides fast detection. Single shot multi box detector (SSD) method is based on a feed-forward convolutional network, followed by a non-maximum suppression step to produce final detections. The accuracy constraint of 70% was kept for qualifying as a potential site to negate ambiguities arising due to processing errors.