Design of Distributed Control and Emergency Shutdown System for Urea and Ammonia Plant

In modern process industries, the need for automation has become necessary to improve the feasibility of production. Automation reduces the possibility of human error and also ensures accuracy of output. In automation and process industries, DCS is used to control several processes being carried out simultaneously with minimum scope for failure. In this project, we have proposed a design on Distributed Control System and Emergency Shutdown System which controls the processing of urea and ammonia. The software used for the Distributed Control System is Centum VP (Vigilant Plant) and the logic designer tool is used to design the control logics of the DCS and ESD

Energy Efficient Blood Transfusion System

RBCs stand for red blood cells (also known as erythrocytes), are the most common type of blood cells. They are the basic means of delivering oxygen, in the vertebrates to different cells and tissues. Hemoglobin is a protein in the RBCs, which carries oxygen and gives blood its red color. The normal range of RBCs in men is approximately 4.7 to 6.1 million cells per microliter and the normal range of RBCs in women is approximately 4.2 to 5.4 million cells per microliter. For a person to be eligible to donate blood, he/she should have the minimum number of RBCs in their blood for donation. This is only possible when the minimum duration between two donations is 3 months, be- cause it takes RBC about three months to develop completely. Many equipment have been developed or installed in hospitals for reducing energy consumption and increasing the efficiency. But even after installing these energy efficient devices in hospitals, it has been found out that these devices face a number of difficulties or obstacles. Thus, this paper focuses in developing an energy efficient software for blood transfusion that can function without interfering with any obstacles and thus giving accurate results

Identification of Autism in Children Using Static Facial Features and Deep Neural Networks

Autism spectrum disorder (ASD) is a complicated neurological developmental disorder that manifests itself in a variety of ways. The child diagnosed with ASD and their parents’ daily lives can be dramatically improved with early diagnosis and appropriate medical intervention. The applicability of static features extracted from autistic children’s face photographs as a biomarker to distinguish them from typically developing children is investigated in this study paper. We used five pre-trained CNN models: MobileNet, Xception, EfficientNetB0, EfficientNetB1, and EfficientNetB2 as feature extractors and a DNN model as a binary classifier to identify autism in children accurately. We used a publicly available dataset to train the suggested models, which consisted of face pictures of children diagnosed with autism and controls classed as autistic and non-autistic. The Xception model outperformed the others, with an AUC of 96.63%, a sensitivity of 88.46%, and an NPV of 88%. EfficientNetB0 produced a consistent prediction score of 59% for autistic and non-autistic groups with a 95% confidence level

Energy Efficient Blood Transfusion System

RBCs stand for red blood cells (also known as erythrocytes), are the most common type of blood cells. They are the basic means of delivering oxygen, in the vertebrates to different cells and tissues. Hemoglobin is a protein in the RBCs, which carries oxygen and gives blood its red color. The normal range of RBCs in men is approximately 4.7 to 6.1 million cells per microliter and the normal range of RBCs in women is approximately 4.2 to 5.4 million cells per microliter. For a person to be eligible to donate blood, he/she should have the minimum number of RBCs in their blood for donation. This is only possible when the minimum duration between two donations is 3 months, be- cause it takes RBC about three months to develop completely. Many equipment have been developed or installed in hospitals for reducing energy consumption and increasing the efficiency. But even after installing these energy efficient devices in hospitals, it has been found out that these devices face a number of difficulties or obstacles. Thus, this paper focuses in developing an energy efficient software for blood transfusion that can function without interfering with any obstacles and thus giving accurate results

Comparative Analysis of Clustering Techniques for Movie Recommendation

Movie recommendation is a subject with immense ambiguity. A person might like a movie but not a very similar movie. The present recommending systems focus more on just few parameters such as Director, cast and genre. A lot of Power intensive methods such as Deep Convolutional Neural Network (CNN) has been used which demands the use of Graphics processors that require more energy. We try to accomplish the same task using lesser Energy consuming algorithms such as clustering techniques. In this paper, we try to create a more generalized list of similar movies in order to provide the user with more variety of movies which he/she might like, using clustering algorithms. We will compare how choosing different parameters and number of features affect the cluster's content. Also, compare how different algorithms such as K-mean, Hierarchical, Birch and mean shift clustering algorithms give a varied result and conclude which method will suit for which scenarios of movie recommendations. We also conclude on which algorithm clusters stray data points more efficiently and how different algorithms provide different advantages and disadvantages

Comparative Analysis of Clustering Techniques for Movie Recommendation

Movie recommendation is a subject with immense ambiguity. A person might like a movie but not a very similar movie. The present recommending systems focus more on just few parameters such as Director, cast and genre. A lot of Power intensive methods such as Deep Convolutional Neural Network (CNN) has been used which demands the use of Graphics processors that require more energy. We try to accomplish the same task using lesser Energy consuming algorithms such as clustering techniques. In this paper, we try to create a more generalized list of similar movies in order to provide the user with more variety of movies which he/she might like, using clustering algorithms. We will compare how choosing different parameters and number of features affect the cluster's content. Also, compare how different algorithms such as K-mean, Hierarchical, Birch and mean shift clustering algorithms give a varied result and conclude which method will suit for which scenarios of movie recommendations. We also conclude on which algorithm clusters stray data points more efficiently and how different algorithms provide different advantages and disadvantages

Rheumatic Heart Disease Classification Using Adaptive Filters

An efficient and innovative method has been proposed in this paper to detect heart murmurs as a method to identify rheumatic fever with the use of adaptive filters, transform techniques and Neural Network Algorithms by considering various parameters such as number of peaks, Signal to Noise Ratio (SNR) and Power Spectral Density. Under optimum conditions the classification returned exact outputs even when the neural network was trained under false positive data thus showing its effectiveness