Novel Schemes for Authentication

Authentication is one of the most basic process to provide security to any resource and application from unauthorized access. It covers two security goals confidentiality and integrity. Passwords are used as private identity for an individual. The password also has to be protected from several threats like stealing, shoulder surfing, eavesdropping and guessing. The most common method used for user Authentication is textual password using alphanumeric usernames and alphanumeric passwords. The issues which should be kept in mind while choosing a password is the how strong the password is and how good it is to memorize. Sometimes the stronger passwords are not easier to remember and easier passwords are not so secure. One more criteria for a good password, that should satisfy is, the password should be easy to type, such that any intruder, if any, is there beside you should not be able guess it or any camera behind you can’t capture the actual movements. To overcome the drawbacks of traditional textual schemes the new methods like graphical passwords are used. The easiness in remembering them and a strong resistance towards the brute force and dictionary attacks made them more popular. In this project, we have concentrated to protect our password from the above threats and to develop a system which has a strong resistant to above stated threats. We have implemented a varying password scheme which provides a better resistant to shoulder surfing, eavesdropping and guessing. This is an untraditional approach to use a not very complex and not very strong password in unsafe environments like public places. We have implemented the virtual keyboard and to make it more effective we are using multilingual keys. And also a hybrid system is designed by mixing three schemes: textual passwords, Recognition based passwords and Recall based password. All three are working together to remove the drawbacks of each scheme

Heat shock protein 70-2 (HSP70-2) overexpression in breast cancer

Supplementary Methods, Supplementary table, Supplementary Figure Legends. (DOCX 41 kb

Analysis of Bus Vulnerability Conducted Using a Synchronized Phasor Measurement Unit in Order to Achieve the Maximum Observability

Phasor measurement units (PMUs) have gained significant interest in recent decades. These instruments are used to measure synchronized phasor data. PMUs are gradually but definitely taking over power grids because of the significant phasor information that they generate for both regular and irregular conditions for the purpose of maintaining safety and control. PMUs may be used for a variety of purposes, including state estimation, which is a common task. In order to make state estimation more reliable, a variety of approaches have been looked into, and one of them is the positioning of PMUs. This paper provides a plan for the implementation of the PMUs, taking into account the potential for failure and vulnerability posed by PMU-equipped buses. Two separate studies were carried out and evaluated with the goal of solving the optimum PMU placement problem (OPPP), which pertains to the grids. The findings of the first study show that the maximum bus observability may be accomplished with the fewest possible number of PMUs, even while taking into consideration the fact that there is a risk that one or more PMUs would malfunction. This investigation was carried out with common measures such as zero injection bus (ZIB) and branch flow measurements, both with and without them, in order to assess the outcomes. The second research focused on selecting the PMU-equipped bus’s vulnerability analysis as its primary area of investigation. All of the tests were completed by using binary integer linear programming. Specifically, the described method is meant to be used with an existing PMU framework and in the case that new locations for new PMUs are necessary to be furnished with existing PMUs. This results confirm that the recommended strategy can be implemented successfully on the IEEE benchmark test systems

Ash Cooler Heat Recovery Under Energy Conservation Scheme

A healthy fluidization state in circulating fluidized-bed combustion (CFBC) combustor is attributed to proper quantity of hot bed material (ash), which acts as a thermal fly-wheel. It receives & stores thermal energy from the burning of fuel (lignite) & distributes uniformly throughout the combustor & helps in maintaining a sustained combustion. The quantity of bed ash inside the combustor or size of the bed, depends upon boiler load & subsequently upon combustor temperature, lignite feed rate and ash % in lignite. As these parameters varies during process continuously, sometimes it becomes necessary to drain out the ash from the combustor. As & when differential pressure across the bed is increased from a justified level, draining of hot bed ash starts into Ash Coolers. Bed ash is drained at very high temperature of 850 oC & it also contains burning particles of lignite. This paper describes the heat recovery from bed ash, unloaded from the combustor into ash cooler, by pre-heating the condensate water of turbine cycle in a 125 MW CFB boiler of Surat Lignite Power Plant in India. The thermal performance of ash cooler was derived by doing a heat balance calculation based on the measured temperature of ash and cooling water with different load. From the heat balance calculation influence of ash temperature and ash amount on heat transfer coefficient is determined. Simulation is carried out around main turbine cycle indicates improved thermal economy of the unit, higher plant thermal efficiency, lower plant heat rate and reduce fuel consumption rate. Also simulation result shows that the heat transfer coefficient increase with ash amount and decreases with increase in ash temperature

Imagerie du tenseur de diffusion du cerveau : vers des outils cliniques quantitatifs

The thesis explores three major methodological questions in clinical brain DTI, in the context of a clinical study on HIV. The first question is how to improve the DTI resolution. The second problem addressed in the thesis is how to create a multimodal population specific atlas. The third question is on the computation of statistics to compare white matter (WM) regions among controls and HIV patients. Clinical DTIs have low spatial resolution and signal-to-noise ratio making it difficult to compute meaningful statistics. We propose a super-resolution (SRR) algorithm for improving DTI resolution. The SRR is achieved using anisotropic regularization prior. This method demonstrates improved fractional anisotropy and tractography. In order to spatially normalize all images in a consistent coordinate system, we create a multimodal population specific brain atlas using the T1 and DTI images from a HIV dataset. We also transfer WM labels from an existing white matter parcellation map to create probabilistic WM atlas. This atlas can be used for region of interest based statistics and refining manual segmentation. On the statistical analysis side, we improve the existing tract based spatial statistics (TBSS) by using DTI based registration for spatial normalization. Contrary to traditional TBSS routines, we use multivariate statistics for detecting changes in WM tracts. With the improved method it is possible to detect differences in WM regions and correlate it with the neuropschylogical test scores of the subjects.La thèse explore trois questions méthodologiques en imagerie de diffusion (DTI) clinique du cerveau, dans le contexte d’une étude sur le VIH. La première question est comment améliorer la résolution du DTI. Le deuxième problème est comment créer un atlas multimodal spécifique à la population. La troisième question porte sur le calcul des statistiques pour comparer les zones de matière blanche entre les contrôles et patients. Les DTI cliniques ont une résolution spatiale et un rapport signal sur bruit faibles, ce qui rend difficile le calcul de statistiques significatives. Nous proposons un algorithme de super-résolution pour améliorer la résolution qui utilise un a priori spatial anisotrope. Cette méthode démontre une amélioration de l’anisotropie fractionnelle et de la tractographie. Pour normaliser spatialement les images du cerveau dans un système de coordonnées commun, nous proposons ensuite de construire un atlas multimodal spécifique á la population. Ceci permet de créer un atlas probabiliste de la matière blanche qui est consistant avec l’atlas anatomique. Cet atlas peut être utilisé pour des statistiques basées sur des régions d’intérêt ou pour le raffinement d’une segmentation. Enfin, nous améliorons les résultats de la méthode TBSS (Tract-Based Spatial Statistics) en utilisant le recalage des images DTI. Contrairement á la méthode TBSS traditionnelle, nous utilisons ici des statistiques multivariées. Nous montrons que ceci permet de détecter des différences dans les régions de matière blanche qui étaient non significatives auparavant, et de les corréler avec les scores des tests neuropsychologiques

Learning Dexterous Manipulation from Exemplar Object Trajectories and Pre-Grasps

Learning diverse dexterous manipulation behaviors with assorted objects remains an open grand challenge. While policy learning methods offer a powerful avenue to attack this problem, they require extensive per-task engineering and algorithmic tuning. This paper seeks to escape these constraints, by developing a Pre-Grasp informed Dexterous Manipulation (PGDM) framework that generates diverse dexterous manipulation behaviors, without any task-specific reasoning or hyper-parameter tuning. At the core of PGDM is a well known robotics construct, pre-grasps (i.e. the hand-pose preparing for object interaction). This simple primitive is enough to induce efficient exploration strategies for acquiring complex dexterous manipulation behaviors. To exhaustively verify these claims, we introduce TCDM, a benchmark of 50 diverse manipulation tasks defined over multiple objects and dexterous manipulators. Tasks for TCDM are defined automatically using exemplar object trajectories from various sources (animators, human behaviors, etc.), without any per-task engineering and/or supervision. Our experiments validate that PGDM's exploration strategy, induced by a surprisingly simple ingredient (single pre-grasp pose), matches the performance of prior methods, which require expensive per-task feature/reward engineering, expert supervision, and hyper-parameter tuning. For animated visualizations, trained policies, and project code, please refer to: https://pregrasps.github.io

PHYSIO-ANATOMICAL EXPLORATION OF ROLE OF MENTAL HEALTH IN ANNAVAHA SROTAS DISORDERS

The good health is defined not only on basis of physical well being but rather also on mental well being. As told in Ayurveda texts- “Prasanna Atmendriya Manah Swasth Ityabhidheeyate”. In era of globalization, the fast & modernized lifestyle has taken toll on one’s health. Now a day, majority of population is suffering from digestive problems such as acidity, reflux, bloating, stomach pain, constipation, and anorexia. These digestive problems are mainly due to bad dietary habits like junk foods, lack of balanced diet etc and also due lack of proper sleep, stress etc. Stress shows both long term and short term effect on gut functions like gastric secretions, gut motility, mucosal permeability etc. Our Acharas were well aware about this factor for digestive disorders, as they included Shoka, Bhaya, Krodha etc. as Nidana (cause) of digestive disorders. These various Nidana of digestive disorders causes Agnidushti which is cause of Annvaha srotodushti and Mandagni. It is very important to understand the relationship between gut and mental health to know aetio-pathogenesis of disorders, which will help to develop holistic approach for better treatment of Annavaha Srotas Disorders