B. Dinesh Reddy's research while affiliated with Vignan’s Institute of Information Technology and other places

Online social networking has caused profound changes within the manner folks communicate and move. These changes might have an effect on sure traditional aspects of human behavior and cause medical specialty disorders. Mental disease is quickly turning into one in every of the foremost current public unfitness around the world. Social media networks, wherever clients will categorical their emotions, feelings, and thoughts, area unit a worthy supply of knowledge for analyzing mental state, and procedures supported machine intelligence area unit more and more used for this purpose. It is difficult to sight social network mental disorder (SNMDs) as a result of the mental factors thought of in existing diagnostic criteria (questionnaire) cannot be determined from online group action logs. To mechanically sight SNMDs cases of OSN clients, taking out these constraints to evaluate user’s online psychological states is extremely difficult. As an instance, the range of isolation with the impact of less inhibition of OSN clients do not seem to be simply discernible. Abnormal activity connected keywords area unit generated and hold on server. Each user activity (tweets, post, comments, etc.) information area unit hold on in information that may be accustomed analyze folie. This can facilitate to observe user activities in social network. Projected work detects sever style of SNMDs with a binary SVM classification approach.

As the computation power of microcomputers increases over time, we need to put them to proper use. Green energy generation and consumption are evident problems that need to be prioritized. We know that green energy is not produced at a scale for us to rely on but if we know how electricity is consumed, we might be able to hack our way. In order to know that we are using light-dependant resistor (LDR) to count pulses from the electricity meter and update it in the database using a Raspberry Pi connected to the Internet which hits the server, the end user can see the utilization in real time.

The eyes are the most important feature of our bodies because they allow us to see and explore the world. Nowadays, technology is continually evolving, paving the way for greater development and increased use of gadgets by everyone. When people stare at digital screens for long periods of time, they develop eye strain and visual issues, which is known as computer vision syndrome (CVS). The best way to avoid visual problems caused by digital screens is to take appropriate preventive measures such as getting regular eye care. To protect users from eye disorders, we created a model that uses the Viola–Jones method and the SVM classifier to estimate the user's eye blinking ratio. As a result, the proposed approach calculates locations of significance and another scalar parameter is derived—ratio of the eyes (EAR)—that characterizes each frame's eye opening. Finally, in a limited temporal window, eye blinks are recognized as a pattern of EAR values using an SVM classifier. The user can be notified about his gadget usage based on the results of the eye blink ratio and gradually diminish his addiction to digital screens that affect his eyes.

Cloud computing is the most advanced and the most used technology for the never-ending IT and software technologies. Various large servers was used in cloud models for storing the vast amount of data. To store massive databases, various setoff servers with high-end hardware and with fast internet facilities were required and with a set of servers for providing services to the end users. In these servers, users store massive amount of data and also retrieve it from time to time, providing security to the data in these cloud computing models was very much essential and important. Hence, as the data storing in the various locations of the servers, the provision of adjusting the various amount of considerable data in the servers at various locations from time to time was essential and also the provision of security to these massive set of databases and also retrieving and storing the data is more critical. Hence, we need to provide more security to the data being stored in the huge number of the server. As we need to provide security to these servers, several factors are important to note. The detailed description of these points was presented in the current article.KeywordsSecurity techniquesSpace issues for securityArchitectureCloud computingFirewalls

Due to the exponential advancement of information technology, computer, storage systems and networking technology, medical devices and clinical diagnosis has acquired tremendous popularity in the last two decades. Mostly in medical field including biomedical science, the effect of such advances is becoming apparent, allowing the detection and diagnosis in a much more vivid way. The significant hurdle in the diagnostic imaging study is to select an image without any substantial details being lost. It is extremely likely that throughout the course of the retrieval organ in subsequent processing phases, the data captured can be distorted by noises or artifacts. Noise is defined as the initial pixel value being modified at random. Noise lowers the clarity of the image which is particularly important whenever the structures are scanned is smaller and even has comparatively poor intensity. Denoising of image data is thus important, and in medical diagnostics it has always been a necessary preprocessing level. An analysis of several significant researches in the field of image denoising is discussed in this article. Since images were quite essential in any area, image denoising is indeed a valuable preprocess prior toward more image analysis, such as segmentation, extraction of features, texture analysis, etc. This research intended to perform the comprehensive study of various denoising strategies for medical imaging that involves MRI, CT, and Retinal funding images. A comparison study with many existing methods approaches focused on resemblance tests, reveals that the proposed approach is superior in image consistency to them.KeywordsImage denoisingOn-local means filteringSpatial filteringCT scanMRI

Remote network incorporates a bigger favourable position in the present correspondence application like ecological, movement, military and well-being perception. To understand these applications, it is important to have a solid directing convention. The self-sorting out nature of MANETs makes them appropriate for some applications and henceforth, extensive exertion has been put into anchoring this kind of systems. Secure correspondence in a system is dictated by the unwavering quality of the key administration conspire, which is in charge of creating, circulating and looking after encryption/decoding keys among the hubs. In this paper, different key administration plans for MANETs are talked about. This examination work proposes a novel secure identity-based key management convention making utilization of cryptographic and information theoretic security.

Traffic problems in cities and developing cities are proliferating. Several methods are being followed to reduce the congestion on city roads. In the current article, an attempt has been made to identify the number of vehicles on city roads and based on the number of vehicles on city roads, the traffic lights are controlled automatically such that to reduce the congestion on city roads. Identifying vehicles on different lanes at traffic signals and trying to control the signals based on the number of vehicles. The current model was developed and implemented on the platform of Python, and the testing of the current model was done with four cases. The results observed for the four test cases are excellent and encouraging. The exact method and it's functioning and the results are displayed in the results and discussions sections in detail.