Breast cancer represents the highest percentage of cancers and the second most common cancer overall that affect women with 87,090 deaths approximately as reported by ICMR, 2018 in India (1). Breast tumours are classified into two types as a) benign, which is not very harmful and would not cause breast cancer and b) malignant, the tumours are extremely dangerous and would form an abnormal cell that may cause cancer. One transfer learning model called VGG16 (Visual Geometry Group (16) has been implemented with a focus on breast cancer classification using mammography images taken from the MIAS dataset. Moreover, at the preprocessing step, all the breast images are enhanced by using CLAHE (Contrast Limited Adaptive Histogram Equalization) technique that specifically maintains adaptive techniques to remove the lines, letters, and other boxes irrelevant to the Breast Image. As the name suggests, this VGG16 has taken 13 convolutional layers and 3 fully connected layers to train the dataset. In the training period, this model could predict whether the breast images contain any type of cancerous cells or not. And finally, the model has successfully implemented and produced Network’s test score of 87.999 percent.

The development of Intelligent Transportation System (ITS) will transition into a next level development of variously new requirements coupled with the new generation wireless communication technology. In this paper, the process-oriented structured system analysis is extended on the existing intelligent transportation architecture to establish an intelligent transportation system based on the new generation wireless communication technology, and further in-depth analysis will be performed to discuss the required additional capabilities of network, services and application support in the view of user, function, information, connection and communication. In order to comprehensively understand the technical characteristics and development of the new generation intelligent transportation system, it lays a foundation for implementation of the new generation ITS technology.

As the world continues to shift towards clean and renewable energy sources, wind energy has emerged as a promising alternative to traditional fossil fuels

Part of Speech (POS) Tagging is a challenging task to identify the meaning of each word in a sentence. This paper shows the task of identifying each word in an odia sentence using the technique of Support Vector Machine. The POS Tagger is developed using a very small tagset of five tags. Various features sets are taken for different contextual information is helpful in predicting the POS classes. An Odia corpus of 10,000 words has taken and tested it very carefully. The previous POS Tagger was done using Artificial Neural Network (ANN) had given the accuracy of 81%. But this SVM based POS Tagger for Odia gives the result with an accuracy of 82%. It is very helpful to use in many field of natural language process. The result of this system compares with POS tagger using ANN which was previously done

In the Internet of Medical Things (IoMT), medical devices are connected to the Internet of Things (IoT), allowing better tailored healthcare, faster hospital treatments, more affordable medical solutions, and more patient comfort. The most serious threat to the safety and confidentiality of patient’s medical records is the possibility of attacks on the IoMT environment. In order to address these problems, researchers have proposed several approaches and methodologies. None of these protocols presents a low-computing-overhead method that combines authentication with privacy preservation. This research proposes a protocol for secure authentication of IoMT devices while protecting user privacy. The proposed approach ensures the confidentiality of the IoMT devices connected to the patient’s body while communicating. In addition, the proposed protocol is validated using the widely recognized formal validation tool Automated Validation of Internet Security Protocols and Applications (AVISPA). The suggested protocol resolves existing protocols’ vulnerabilities and is resistant to many well-known security issues. Compared with existing protocols that use public cryptosystems, such ElGamal and RSA, the suggested protocol stands out due to its smaller key size and reduced computational overhead. A comparison with the well-known protocols revealed that the combined method for “lightweight authentication and privacy preservation” is computationally 5 to 6 times more efficient. However, this research has significant real-world implications from various social, economic, and business viewpoints, both locally and globally.