Volume 3 Issue 2
1. Emerging Trends in Cyber Crime and Safet
Author's Name: R.Shanthi Prabha

Abstract— Cyber Security plays an important role in the field of information technology. In the present day to securing the information is biggest issue. Whenever we think about the cyber security the first thing that comes to our mind is cyber crimes which are increasing immensely day by day. Various Governments and companies are taking many measures in order to prevent these cyber crimes. Besides various measures cyber security is still a very big concern to many. This paper mainly focuses on challenges faced by cyber security on the latest technologies .It also focuses on latest about the cyber security techniques, ethics and the trends changing the face of cyber security.

2. Human Interaction With Robots Through Verbal Communication
Author's Name: C.Vasuki

Abstract— In this paper is an overview of human–robot interaction (HRI) through verbal communication. Fundamentally, HRI problems represent breakdowns in communication, where poor information exchange between human and robots leads to faltering, wrong mental representation, poorly balanced trust, incomplete situational awareness, etc. Verbal communication in robotics is a significant increasing field in both the industrial and research side. The aim of verbal communication in robotics is to reach a natural human-like interaction with robots

3. Mobile Application to Detect Brain Tumor Using Transfer Learning
Author's: C.Bharath Balaji ,Dr.G.Charulatha, B.Lavnaya, B.Sree Devi,M.Dhivyabharathi

Abstract—In this paper, Classification of Brain Tumor (BT) is a vital obligation for assessing Tumors and making a suitable treatment. There exist numerous imaging modalities that are utilized to identify tumors in the brain. Magnetic Resonance Imaging (MRI) is generally utilized for such a task because of its unrivalled quality of the image and the reality that it does not depend on ionizing radiations. The relevance of Artificial Intelligence (AI) in the form of Deep Learning (DL) in the area of medical imaging has paved the path to extraordinary developments in categorizing and detecting intricate pathological conditions, like brain tumor, cancer etc. Deep learning has demonstrated an astounding appearance, particularly in segmenting and classifying brain tumors. In this work, the AI-based classification of BT using Deep Learning Algorithms is proposed for the classifying types of brain tumors utilizing openly accessible datasets. These datasets classify BTs into (malignant and benign). The datasets comprise 696 images on T1-weighted images for testing purposes. The projected arrangement accomplishes a noteworthy performance with the finest accuracy of 99.04%. The achieved outcome signifies the capacity of the proposed algorithm for the classification of brain tumors.

4. Analysis of Neuro-Imaging and Prediction of Alzheimer’s Syndrome and Brian Tumor using Machine Learning Techniques
Author's: Abirami K, M.Renuga, B.Lavanya, K.Lakshmi priya , K.Senthil Kumar

Abstract—This paper discusses about the analysis and detection of brain tumor and Alzheimer’s disease. A digital MRI scan is used for this purpose. Medical image processing and analysis tasks are complex and diverse at the technical level. There is an array of technologies including reconstruction, enhancement, restoration, classification, detection, segmentation and registration that are combined with multiple image modalities and numerous applications are formed and should be addressed. AI-based tools are developed to support the assessment of disease severity and recently there are tools for assessing treatment and predicting treatment success. Finally, numerous studies in fields like clinical neuroscience have shown that AI-based image evaluation can identify complex imaging patterns that are not perceptible with visual radiologic evaluation.