Mental health is the aggregation of emotional, social and psychological well-being of a person. These problems at workplace can lead to an increased amount of substance abuse, work errors, workplace accidents, poor decision-making, poor timekeeping and a general deterioration in planning and control of work, which all contribute to an overall reduction in work output. Mental Health Prediction application, a one stop solution for all the employees where they can check their mental health regularly Scope of mental health maintenance isn’t solely a requirement of seeing a mental health professional, but rather creating a routine of self-check ins, and proper maintenance of our mental states.
Internet has caused an extraordinary increase in the transfer and sharing of digital data like text, videos, images, audio, etc. over it. However, with the advent of modern access technology, multimedia data is more prone to security risks as data can be modified or redistributed without prior permission. Chaotic encryption-based blind digital image watermarking technique applicable to both grayscale and colour images. Discrete cosine transform (DCT) is used before embedding the watermark in the host image. Arnold transform is used in addition to chaotic encryption to add double-layer security to the watermark. Three different variants of the proposed algorithm have been tested and analysed. The simulation results show that the proposed scheme is robust to most of the image processing operations like joint picture expert group compression, sharpening, cropping, and median filtering. To validate the efficiency of the proposed technique, the simulation results are compared with certain state-of-art techniques.
At present world, Breast cancer is a second main cause of cancer death in women after lung cancer. Breast cancer occurs when some breast cells begin to raise abnormally. It can arise in any portion of the Breast and it can be prevented if the treatment is started at the early stage of the Breast cancer. Breast cancer is a malignant tumour i.e. a collection of cancer cells arising from the cells of the breast Treatment of breast cancer relies on the cancer type and its stage. Mainly this paper focused on diagnosing the Breast cancer disease using various classification algorithm with the help of data mining tools. Data mining of the intelligent accumulated from previously disease detected patients opened up a new aspect of medical progression In this paper, the focus has been prediction of breast cancer using various machine learning algorithms and visualizing the performances of each algorithm. This paper makes use of a dataset that contains numerical values about the clump thickness, uniformity of the cell for prediction using Multi Layer Perceptron, K-NN, Random Forest, Logistic Regression. Moreover, this also uses a dataset of tissue images for the prediction using Convolution Neural Network. Later, the accuracies of each algorithm is calculated along with the precision, recall, f-score, ROC for each algorithm.
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