Multimodal Fusion of Face and Palm Using Local Color Binary Patterns and Haralick Features

Face recognizable proof has drawn in numerous scientists because of its novel benefit, for example, non-contact measure for include obtaining. Varieties in brightening, posture and appearance are significant difficulties of face acknowledgment particularly when pictures are taken as dim scale. To mitigate these difficulties partially many exploration works have been completed by considering shading pictures and they have yielded better face acknowledgment rate. A strategy for perceiving face utilizing shading nearby surface highlights is depicted. Test results show that Face ID approaches utilizing shading neighborhood surface highlights astonishingly yield preferred acknowledgment rates over Face acknowledgment approaches utilizing just shading or surface data. Especially, contrasted and grayscale surface highlights, the proposed shading neighborhood surface highlights can give great coordinating with rates to confront pictures taken under extreme varieties in enlightenment and furthermore for low goal face pictures. The other biometric framework utilizes palmprint as quality for the recognizable proof and validation of people. The principal point is to extract Haralick highlights and utilization of probabilistic neural organizations for confirmation utilizing palmprint biometric quality. PolyUdatabase tests are taken from around 200 clients every client's 2 examples are gained. This palm print biometric recognizes the phony (fake) palmprint made of POP (Plaster of paris) and separates among living and non-living dependent on the entropy highlight. Test results portray that the eleven Haralick feature values are acquired in execution stage and productive precision is accomplished.

Comparative Study of Various Nuclear Medicine Imaging Technique - A Review

Nuclear Medicine is a medical specialty that allows modern diagnostics and treatments using radiopharmaceuticals original radiotracers (drugs linked to a radioactive isotope). The radiopharmaceuticals are considered a special group of drugs and thus their preparation and use are regulated by a set of policies that have been adopted by individual member countries. The radiopharmaceuticals used in diagnostic examinations are administered in very small doses. So, in general, they have no pharmacological action, side effects or serious adverse reactions. The most serious issue with their use is the potential for diagnostic mistakes due to changes in their biodistribution. The appearance and development of new radiopharmaceuticals in both the diagnostic and therapeutic domains, as well as the impact of new multimodality imaging techniques, are all having a significant impact on nuclear medicine (SPECT-CT, PET-CT, PET-MRI, etc.). It is crucial to understand the techniques limitations, radiopharmaceutical distribution and potential physiological changes, radiological contrast contraindications and bad responses, and the possibility of both interfering. The process of generating radiopharmaceuticals is introduced and relevant interactions of radiation with matter are discussed. Diagnostic nuclear medicine instrumentation is explained, and future trends in nuclear medicine imaging technology are forecasted.

Review of Data Mining for Twitter Data Analysis

In today’s life Twitter, Facebook, Google are well known social sites that many uses for different purposes. Social sites are the fastest medium which delivers news to user as compared to the new paper and television. One among the online social networks like Twitter, has quickly gained fame as it provides people with the opportunity to communicate and share messages known as “tweets”. Tremendous value lies in automated analysis and data mining of such vast and diverse data to derive meaningful insights, which carries potential opportunities for businesses, consumers, product survey and political survey. In the proposed system of analysis of the tweets, a search query for topic is provided to extract required data using ‘clustering algorithm’ in machine learning. The unique advantage of using machine learning is that once an algorithm knows what to do with the information, it can do its job automatically. To deduce for a search query, the proposed system extracts feature from the tweets like keywords in tweets, number of words in tweets. The output tweet list can further be used for analysis for business improvement or for surveys.

Evaluation of Women Protection using Machine Learning

In this era, as we know there are various preceding cases in the world regarding women harassment which is starting from stalking leading to abusive harassments such as acid attacks, rape cases, obscenity, pornography etc. With such issues, an analysis of women safety in Indian cities has been proposed using Machine Learning on Tweets. The Sentimental Analysis is taken as the main idea and is performed through machine learning, taking an input from tweets to ensure safety. This sentimental analysis on tweets helps in creating awareness among people. As we know Twitter and Instagram are responsible to spread information far and wide among the people across the globe, this helps the women in expressing her feelings to the world. We have taken Twitter as an important resource because it provides text, audio, video message and are easy to handle. This can help our research to overcome the sentiments of people around us.