M. S. Ramaiah Institute of Technology

About: M. S. Ramaiah Institute of Technology is a based out in . It is known for research contribution in the topics: Feature extraction & Photoluminescence. The organization has 2853 authors who have published 2434 publications receiving 23507 citations.

Stress as a Cause of Recurrent Aphthous Stomatitis and Its Correlation with Salivary Stress Markers.

Abstract: Stress causes an increase in cortisol and amylase. Recurrent aphthous stomatitis (RAS) results due to a multitude of causes, amongst which stress is one of the most important. Aim of the study was to estimate the level of stress, serum cortisol, salivary cortisol, amylase and electrolytes in subjects with RAS. 34 subjects with RAS (cases) were compared with 34 controls. Stress was measured using state trait anxiety inventory (STAI). Serum cortisol (Radioimmunoassay), Salivary cortisol, amylase (ELISA) and electrolytes (Flame photometry) were measured. Statistical analysis was done using SPSS 18.0 version software. The mean STAI scores were 48.71 ± 4.6 in cases and 46.74 ± 6.4 in controls (P = 0.13). The mean salivary cortisol concentration was 3.35 ± 1.8 ng/dl in cases and 3.65 ± 2.5 ng/dl in controls (P = 0.78). The mean salivary amylase was 155.09 ± 116.1 U/ml in cases and 128.74 ± 86.3 U/ml in controls (P = 0.49). The salivary sodium (0.24 ± 0.4 in both groups) and potassium (0.65 ± 0.5 in cases and 0.82 ± 0.4 in controls; P = 0.07) was not different in the two groups (electrolytes in mEq/dl). No correlation was seen between the salivary stress markers and STAI scores. Though stress was higher in RAS group none of the measured parameters were different from the control group. Stress may cause RAS but, in this study, there was no change in the salivary homeostasis.

SentenceRank — A graph based approach to summarize text

Abstract: We introduce a graph and an intersection based technique which uses statistical and semantic analysis for computing relative importance of textual units in large data sets in order to summarize text. Current implementations consider only the mathematical/statistical approach to summarize text. (like frequency, TFIDF, etc.) But there are many cases where two completely different textual units might be semantically related. We hope to overcome this problem by exploiting the resources of WordNet and by the use of semantic graphs which represents the semantic dissimilarity between any pair of sentences. Ranking is usually performed on statistical information. The algorithm constructs semantic graphs using implicit links which are based on the semantic relatedness between text nodes and consequently ranks nodes using a ranking algorithm.

"Luminescent carbon nanodots: Current prospects on synthesis, properties and sensing applications".

Abstract: "Nanocarbon science" ignited interest owing to its substantial scope in biomedicine, energy and environment-beneficial applications. Carbon dots (C-dots), a multi-faceted nanocarbon material, emerged as a homologue to graphene and henceforth geared extensive investigation both on its properties and applications. Eximious properties like excitation-wavelength tunable fluorescence emission, up-converted photoluminescence, photon-induced electron transfer, low cytotoxicity, chiroptical behavior, high chemical and photostability set the ground for astounding applications of carbon dots. Abundant availability of raw "green" precursors complementary to other molecular/graphitic precursors make them environmentally benign, inexpensive and ultimately "nanomaterials of the current decade". This review focuses on the synthesis of carbon dots not only from natural sources but also from other carbonaceous precursors and contemplates the inherent but controversial properties. We also aim to garner the attention of readers to the recent progress achieved by C-dots in one of its prestantious area of applications as nanosensors.

Game theoretic resource allocation in cloud computing

Abstract: Considering the proliferation in the number of cloud users on an everyday basis, the task of resource provisioning in order to support all these users becomes a challenging problem. When resource allocation is non-optimal, users may face high costs or performance issues. So, in order to maximize profit and resource utilization while satisfying all client requests, it is essential for Cloud Service Providers to come up with ways to allocate resources adaptively for diverse conditions. This is a constrained optimization problem. Each client that submits a request to the cloud has its own best interests in mind. But each of these clients competes with other clients in the quest to obtain required quantum of resources. Hence, every client is a participant in this competition. So, a preliminary analysis of the problem reveals that it can be modelled as a game between clients. A game theoretic modelling of this problem provides us an ability to find an optimal resource allocation by employing game theoretic concepts. Resource allocation problems are NP-Hard, involving VM allocation and migration within and possibly, among data centres. Owing to the dynamic nature and number of requests, static methods fail to surmount race conditions. Using a Min-Max Game approach, we propose an algorithm that can overcome the problems mentioned. We propose to employ a utility maximization approach to solve the resource provisioning and allocation problem. We implement a new factor into the game called the utility factor which considers the time and budget constraints of every user. Resources are provisioned for tasks having the highest utility for the corresponding resource.