A Perspective to Adopt Continuous Dynamic Cognition for Malicious Node Detection in Heterogeneous Networks

The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.

Graph Modification Problems: A Modern Perspective

We give an overview of recent results and techniques in parameterized algorithms for graph modification problems.

A glucose-centric perspective of hyperglycemia

Digestion of food in the intestines converts the compacted storage carbohydrates, starch and glycogen, to glucose. After each meal, a flux of glucose (>200 g) passes through the blood pool (4-6 g) in a short period of 2 h, keeping its concentration ideally in the range of 80-120 mg/100 mL. Tissue-specific glucose transporters (GLUTs) aid in the distribution of glucose to all tissues. The balance glucose after meeting the immediate energy needs is converted into glycogen and stored in liver (up to 100 g) and skeletal muscle (up to 300 g) for later use. High blood glucose gives the signal for increased release of insulin from pancreas. Insulin binds to insulin receptor on the plasma membrane and activates its autophosphorylation. This initiates the post-insulin-receptor signal cascade that accelerates synthesis of glycogen and triglyceride. Parallel control by phos-dephos and redox regulation of proteins exists for some of these steps. A major action of insulin is to inhibit gluconeogensis in the liver decreasing glucose output into blood. Cases with failed control of blood glucose have alarmingly increased since 1960 coinciding with changed life-styles and large scale food processing. Many of these turned out to be resistant to insulin, usually accompanied by dysfunctional glycogen storage. Glucose has an extended stay in blood at 8 mM and above and then indiscriminately adds on to surface protein-amino groups. Fructose in common sugar is 10-fold more active. This random glycation process interferes with the functions of many proteins (e.g., hemoglobin, eye lens proteins) and causes progressive damage to heart, kidneys, eyes and nerves. Some compounds are known to act as insulin mimics. Vanadium-peroxide complexes act at post-receptor level but are toxic. The fungus-derived 2,5-dihydroxybenzoquinone derivative is the first one known to act on the insulin receptor. The safe herbal products in use for centuries for glucose control have multiple active principles and targets. Some are effective in slowing formation of glucose in intestines by inhibiting alpha-glucosidases (e.g., salacia/saptarangi). Knowledge gained from French lilac on active guanidine group helped developing Metformin (1,1-dimethylbiguanide) one of the popular drugs in use. One strategy of keeping sugar content in diets in check is to use artificial sweeteners with no calories, no glucose or fructose and no effect on blood glucose (e.g., steviol, erythrytol). However, the three commonly used non-caloric artificial sweetener's, saccharin, sucralose and aspartame later developed glucose intolerance, the very condition they are expected to evade. Ideal way of keeping blood glucose under 6 mM and HbAlc, the glycation marker of hemoglobin, under 7% in blood is to correct the defects in signals that allow glucose flow into glycogen, still a difficult task with drugs and diets.

A Perspective on Computer Assisted Assessment Techniques for Short Free-Text Answers

Computer Assisted Assessment (CAA) has been existing for several years now. While some forms of CAA do not require sophisticated text understanding (e.g., multiple choice questions), there are also student answers that consist of free text and require analysis of text in the answer. Research towards the latter till date has concentrated on two main sub-tasks: (i) grading of essays, which is done mainly by checking the style, correctness of grammar, and coherence of the essay and (ii) assessment of short free-text answers. In this paper, we present a structured view of relevant research in automated assessment techniques for short free-text answers. We review papers spanning the last 15 years of research with emphasis on recent papers. Our main objectives are two folds. First we present the survey in a structured way by segregating information on dataset, problem formulation, techniques, and evaluation measures. Second we present a discussion on some of the potential future directions in this domain which we hope would be helpful for researchers.