NALLI VINAYA KUMARI
@computer science engineering
Computer Science Engineering
RESEARCH, TEACHING, or OTHER INTERESTS
Artificial Intelligence, Multidisciplinary, Computer Engineering, Cancer Research
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Lokaiah Pullagura, Nalli. Vinaya Kumari, and Siva Kumar Gowda Katta
CRC Press
Lokaiah Pullagura, Dontha Madhusudhana Rao, Nalli Vinaya Kumari, Ravi Kumar Lanke, Siva Kumar Gowda Katta, and Ronald Chiwariro
IEEE
Electronic mail is a preferred way of written communication, especially in an official or corporate setting, and the influx of emails is ever-growing. While most emails are meant to communicate something useful or important, it is even more common to receive spam or phishing emails regularly. While some of the most used email service providers have filters in their inboxes to filter out unnecessary emails, it is easy for people with malicious intent to bypass the same, thus increasing the need for a more accurate and reliable system for filters. The study aims to survey and review existing work in the space of email classification and recognize the best practices and tools which can be used for analyzing and classifying emails.
V. Suresh Kumar, Lokaiah Pullagura, Nalli Vinaya Kumari, S. Pooja Nayak, B. Padmini Devi, Adnan Alharbi, and Simon Atuah Asakipaam
Hindawi Limited
It is becoming more popular because of the widespread availability of high-speed Internet and the widespread use of mobile phones, both of which are contributing to its rise in popularity. One such significant issue is the use of mobile phones by working parents to keep an eye on the behaviour of their children while they are babysitting for others, which is a significant concern. This study introduces the notion of a smart cradle, which enables for this kind of video monitoring to be carried out on an infant. An infant’s scream triggers the automated swinging of this cradle, which begins when the sensor detects it. In addition, if the baby’s cry persists for an extended period of time, the gadget triggers a buzzer and sends a text message to the phone, signalling that the cradle is no longer capable of handling the infant and that the baby needs human assistance if the cradle’s mattress is wet. This cradle is equipped with an automatic spinning toy for the baby’s entertainment, which reduces the likelihood of a newborn crying throughout the day. A notable rise in the number of working mothers has been seen in recent years. Consequently, the vast majority of parents place their children in the care of their grandparents or in the care of child-minding companies. In addition, we developed a new algorithm for our system, which is critical in delivering better newborn care when parents are not there to assist. Due to the fact that parents are unable to continuously monitor their children’s condition in ordinary or atypical situations while they are at work, this is the case. Node is the fundamental building unit of a microcontroller. Over the course of a single day, the controller board will collect data from the sensors and transmit it to the Adafruit MQTT server over Wi-Fi to be processed. In addition to monitoring the baby’s vital signs, sensors are also used to detect environmental conditions such as the temperature, humidity, and amount of crying in the surroundings. Using the NX Siemens software, a prototype for the cradle was created. Red meranti wood was utilized in its construction. Whenever the baby begins to scream, the system design automatically swings the infant cradle, which is powered by a motor that is built into the system. In addition, parents may use an external web camera to keep checks on the health of their children when they are away from home. Every aspect of this network has been tested to guarantee that it functions effectively and safely at all times.
G. S. Pradeep Ghantasala, Nalli Vinaya Kumari, and Rizwan Patan
Elsevier
G S Pradeep Ghantasala, B. Venkateswarlu naik, Suresh Kallam, Nalli Vinaya Kumari, and Rizwan Patan
IEEE
The second most important cause of death is breast cancer in the country. In the early stages of the disease, primary treatment is difficult as its mechanisms are virtually unknown. Nonetheless, some common signatures of this disease can be used to improve early diagnostics approaches that are important for female Life quality. Mammograms of X-ray are the primary diagnostic and early diagnosis method and are the key to improving the prognosis of breast cancer examination and recovery. Good contrast and sometimes very fluidity of mass and healthy glandular tissue have been described to assist in their treatment, radiologists and internists. Many computerized diagnostics programs have been developed. The method presented in this paper is an important study of visual texture-based mammography for early-stage tumor detection. A few pictures from the digital data base were taken to screen and diagnose cancer mammograms. The suggested algorithm could be used to differentiate mass and micro calcifications by morphological operators from the context fabric and then to separate them using machine learning.
N. Vinaya Kumari and A. Kumar
Union of Researchers of Macedonia