A Random Walk Perspective on Hide-and-Seek Games

We investigate hide-and-seek games on complex networks using a random walk framework. Specifically, we investigate the efficiency of various degree-biased random walk search strategies to locate items that are randomly hidden on a subset of vertices of a random graph. Vertices at which items are hidden in the network are chosen at random as well, though with probabilities that may depend on degree. We pitch various hide and seek strategies against each other, and determine the efficiency of search strategies by computing the average number of hidden items that a searcher will uncover in a random walk of $n$ steps. Our analysis is based on the cavity method for finite single instances of the problem, and generalises previous work of De Bacco et al. [1] so as to cover degree-biased random walks. We also extend the analysis to deal with the thermodynamic limit of infinite system size. We study a broad spectrum of functional forms for the degree bias of both the hiding and the search strategy and investigate the efficiency of families of search strategies for cases where their functional form is either matched or unmatched to that of the hiding strategy. Our results are in excellent agreement with those of numerical simulations. We propose two simple approximations for predicting efficient search strategies. One is based on an equilibrium analysis of the random walk search strategy. While not exact, it produces correct orders of magnitude for parameters characterising optimal search strategies. The second exploits the existence of an effective drift in random walks on networks, and is expected to be efficient in systems with low concentration of small degree nodes.Comment: 31 pages, 10 (multi-part) figure

Smart Assisted Vehicle for Disabled/Elderly using Raspberry Pi

Independent mobility is a key component in maintaining the physical and psychosocial health of an individual. Further, for people e having disabled/elderly, independent mobility increases vocational and educational opportunities, reduces dependence on caregivers and family members, and promotes feelings of self-reliance. Psychologically, a decrease in mobility can lead to feelings of emotional loss, anxiety, depression, educed self-esteem, social isolation, stress, and fear of abandonment. Even though the benefits of powered mobility are well documented, the safety issues associated with operation of powered vehicles often prevent clinicians and rehabilitation practitioners from prescribing powered mobility. So we are introducing an intelligent vehicle for disables/elderly people which uses an array of sensors to help with the movement of the vehicle with minimal human interaction. Functionalities of the proposed system are further enhanced using android interface connect to the vehicle via Bluetooth

Experimental demonstration of 25 GHz wideband chaos in symmetric dual port EDFRL

We study dynamics of chaos in dual port erbium-doped fiber ring laser (EDFRL). The laser consists of two erbium-doped fibers, intracavity filters at 1549.30 nm, isolators, and couplers. At both ports, the laser transitions into the chaotic regime for pump currents greater than 100 mA via period doubling route. We calculate the Lyapunov exponents using Rosenstein’s algorithm. We obtain positive values for the largest Lyapunov exponent (≈0.2) for embedding dimensions 5, 7, 9 and 11 indicating chaos. We compute the power spectrum of the photocurrents at the output ports of the laser. We observe a bandwidth of ≈ 25 GHz at both ports. This ultra wideband nature of chaos obtained has potential applications in high speed random number generation and communication

Polynomial approach modeling among diabetic patients associated with age in rural hilly population of Dehradun district, Uttarakhand

Background: Diabetes mellitus is a form of infections that includes issues with the hormone insulin. It is described by constant rise of blood glucose level surprising ordinary esteem. In this paper, an exertion has been made to fit scientific model to diabetic patients and additionally its total dispersion for both genders related with time of rural population from Dehradun district, Uttarakhand.Methods: For this reason, the information have been taken from field overview in rural hilly population of Dehradun district. In this investigation, an endeavor has been given to demonstrate that the polynomial model is attempted to fit to the conveyance of diabetic patients related with age and also its cumulative distribution.Results: The fitted model provides statistically significant values with R2=0.9997 and ρcv2= 0.994857. This is the polynomial of degree four, i.e. bi-quadratic polynomial model. The polynomial model is assumed for the cumulative distribution of diabetic patients associated with age and the fitted model provides statistically significant values providing R2= 0.99998 and ρcv2= 0.999983 and shrink-age coefficient=0.00001414. This is the polynomial of degree three, i.e. cubic polynomial model. From this statistic we see that the fitted models are highly cross-validated, and their shrinkages are 0.004842857 and 0.00001414 for the models (1) and (2) respectively.Conclusions: It is discovered that the distribution of diabetic patients for both genders related with age takes after bi-quadratic polynomial model. In addition, it is found that cumulative distribution of diabetic patients takes as cubic polynomial model. Cross validity prediction power is utilized to the fitted model to verify the stability of the model in this study

Evaluation of anti-psychotic effect of nimodipine using methylphenidate as a model to induce psychosis in albino mice

Background: Schizophrenia is a functional psychotic disorder currently treated by typical and atypical antipsychotic drugs. A large group of patients remain resistant to therapy. Nimodipine has been found effective for treating resistant bipolar mood disorder which is linked genetically with schizophrenia and has a high overlap of neurotransmitters in the etiopathology. Previous studies to evaluate nimodipine’s antipsychotic activity have shown inconsistent results. Methylphenidate, a CNS stimulant like amphetamine, has been shown to induce stereotypy in animals and can be proposed as an alternative model for psychosis.Methods: Methylphenidate 5 mg/kg was given intraperitoneally to induce psychosis in swiss albino mice (n=6). Nimodipine was given alone in doses of 2.5 and 5 mg/kg by i.p route and in combination with haloperidol 0.1 mg/kg and effects were compared with haloperidol 0.2mg/kg. Activity of nimodipine was also assessed on the haloperidol induced catalepsy test. Statistical analysis was done with ANOVA followed by Bonferroni’s test using SPSS v. 20.0.Results: Methylphenidate successfully induced characteristic stereotypy behaviour in mice similar to amphetamine. Both nimodipine 5 mg/kg and haloperidol 0.2 mg/kg showed significant reduction in stereotypy behaviour with no statistical difference between the two; result with nimodipine were only slightly inferior to haloperidol. Nimodipine 5 mg/kg with haloperidol 0.1 mg/kg showed significantly better activity than haloperidol in standard dose of 0.2 mg/kg. Nimodipine did not show significant activity on the haloperidol induced catalepsy test.Conclusions: Methylphenidate has potential to be used as an alternative model for inducing psychosis in animals and nimodipine shows promising results for use as adjuvant antipsychotic drug

Dissecting BFT Consensus: In Trusted Components we Trust!

The growing interest in reliable multi-party applications has fostered widespread adoption of Byzantine Fault-Tolerant (BFT) consensus protocols. Existing BFT protocols need f more replicas than Paxos-style protocols to prevent equivocation attacks. Trust-BFT protocols instead seek to minimize this cost by making use of trusted components at replicas. This paper makes two contributions. First, we analyze the design of existing Trust-BFT protocols and uncover three fundamental limitations that preclude most practical deployments. Some of these limitations are fundamental, while others are linked to the state of trusted components today. Second, we introduce a novel suite of consensus protocols, FlexiTrust, that attempts to sidestep these issues. We show that our FlexiTrust protocols achieve up to 185% more throughput than their Trust-BFT counterparts

Classification of Atrial Arrhythmias using Neural Networks

Electrocardiogram (ECG) is an important tool used by clinicians for successful diagnosis and detection of Arrhythmias, like Atrial Fibrillation (AF) and Atrial Flutter (AFL). In this manuscript, an efficient technique of classifying atrial arrhythmias from Normal Sinus Rhythm (NSR) has been presented. Autoregressive Modelling has been used to capture the features of the ECG signal, which are then fed as inputs to the neural network for classification. The standard database available at Physionet Bank repository has been used for training, validation and testing of the model. Exhaustive experimental study has been carried out by extracting ECG samples of duration of 5 seconds, 10 seconds and 20 seconds. It provides an accuracy of 99% and 94.3% on training and test set respectively for 5 sec recordings. In 10 sec and 20 sec samples it shows 100% accuracy. Thus, the proposed method can be used to detect the arrhythmias in a small duration recordings with a fairly high accuracy