PROTECT: Proximity-based Trust-advisor using Encounters for Mobile Societies

Many interactions between network users rely on trust, which is becoming particularly important given the security breaches in the Internet today. These problems are further exacerbated by the dynamics in wireless mobile networks. In this paper we address the issue of trust advisory and establishment in mobile networks, with application to ad hoc networks, including DTNs. We utilize encounters in mobile societies in novel ways, noticing that mobility provides opportunities to build proximity, location and similarity based trust. Four new trust advisor filters are introduced - including encounter frequency, duration, behavior vectors and behavior matrices - and evaluated over an extensive set of real-world traces collected from a major university. Two sets of statistical analyses are performed; the first examines the underlying encounter relationships in mobile societies, and the second evaluates DTN routing in mobile peer-to-peer networks using trust and selfishness models. We find that for the analyzed trace, trust filters are stable in terms of growth with time (3 filters have close to 90% overlap of users over a period of 9 weeks) and the results produced by different filters are noticeably different. In our analysis for trust and selfishness model, our trust filters largely undo the effect of selfishness on the unreachability in a network. Thus improving the connectivity in a network with selfish nodes. We hope that our initial promising results open the door for further research on proximity-based trust

ANALYZING EPIDEMIOLOGICAL PATTERNS OF CONTACT DERMATITIS AMONG PATIENTS FROM BOTH RURAL AND URBAN AREAS: A CROSS-SECTIONAL STUDY.

Background  The number of dermatitis caused by contact cases is on the rise. There is few research on the occurrence and demographic traits of skin allergies in India. The purpose of this study was to determine how common dermatitis is caused by contact and assess the pattern of epidemiology of the condition in rural and urban communities.  Methods Each participant signed an informed agreement, and the study was carried out in a medical school in an eastern Indian semi-urban area. A cross-sectional study was conducted at Darbhanga Medical College & Hospital in Lehariasarai, Bihar, India for a period of 6 months. There were 134 patients in the study group who were seen in the outpatient department (OPD) of dermatology and had lesions that were clinically indicating that contact dermatitis exists. Depending on their address, patients visiting the OPD were separated into rural and urban groups. The statistical techniques used for data analysis were appropriate, standard, and suitable.  Results Participants in the dermatological OPD had a contact dermatitis rate of 4.38%. The prevalence in urban areas was substantially (P < 0.05) higher than that in rural areas. More number of patients were observed in the age group of 41-50. Women were more impacted in urban regions than in rural ones. In terms of occupation, there was a difference that was statistically significant (P < 0.05) between contact dermatitis patients in urban and rural areas. The urban group had a considerably higher cosmetic history (P < 0.05).  Conclusion There was a significant statistical variation in the prevalence of contact dermatitis and patient profiles for some characteristics, between individuals living in rural and urban areas.  Recommendation More study population would be needed at different intervals to validate the study findings and ascertain if these modifications are transient or permanent

A Software-equivalent SNN Hardware using RRAM-array for Asynchronous Real-time Learning

Spiking Neural Network (SNN) naturally inspires hardware implementation as it is based on biology. For learning, spike time dependent plasticity (STDP) may be implemented using an energy efficient waveform superposition on memristor based synapse. However, system level implementation has three challenges. First, a classic dilemma is that recognition requires current reading for short voltage$-$spikes which is disturbed by large voltage$-$waveforms that are simultaneously applied on the same memristor for real$-$time learning i.e. the simultaneous read$-$write dilemma. Second, the hardware needs to exactly replicate software implementation for easy adaptation of algorithm to hardware. Third, the devices used in hardware simulations must be realistic. In this paper, we present an approach to address the above concerns. First, the learning and recognition occurs in separate arrays simultaneously in real$-$time, asynchronously $-$ avoiding non$-$biomimetic clocking based complex signal management. Second, we show that the hardware emulates software at every stage by comparison of SPICE (circuit$-$simulator) with MATLAB (mathematical SNN algorithm implementation in software) implementations. As an example, the hardware shows 97.5 per cent accuracy in classification which is equivalent to software for a Fisher$-$Iris dataset. Third, the STDP is implemented using a model of synaptic device implemented using HfO2 memristor. We show that an increasingly realistic memristor model slightly reduces the hardware performance (85 per cent), which highlights the need to engineer RRAM characteristics specifically for SNN.Comment: Eight pages, ten figures and two table

Safe Human Robot-Interaction using Switched Model Reference Admittance Control

Physical Human-Robot Interaction (pHRI) task involves tight coupling between safety constraints and compliance with human intentions. In this paper, a novel switched model reference admittance controller is developed to maintain compliance with the external force while upholding safety constraints in the workspace for an n-link manipulator involved in pHRI. A switched reference model is designed for the admittance controller to generate the reference trajectory within the safe workspace. The stability analysis of the switched reference model is carried out by an appropriate selection of the Common Quadratic Lyapunov Function (CQLF) so that asymptotic convergence of the trajectory tracking error is ensured. The efficacy of the proposed controller is validated in simulation on a two-link robot manipulator

Dielectric response of makrofol-KG polycarbonate irradiated with 145 MeV Ne6+ and 100 MeV Si8+ ions

The passage of heavy ions in a track detector polymeric material produces lattice deformations. These deformations may be in the form of latent tracks or may vanish by self annealing in time. Heavy ion irradiation produces modifications in polymers in their relevant electrical, chemical and optical properties in the form of rearrangement of bonding, cross-linking, chain scission, formation of carbon rich clusters and changes in dielectric properties etc. Modification depends on the ion, its energy and fluence and the polymeric material. In the present work, a study of the dielectric response of pristine and heavy ion irradiated Makrofol-KG polycarbonate is carried out. 40 μm thick Makrofol-KG polycarbonate films were irradiated to various fluences with Si8+ ions of 100 MeV energy from Pelletron at Inter University Accelerator Centre (IUAC), New Delhi and Ne6+ ions of 145 MeV from Variable Energy Cyclotron Centre, Kolkata. On irradiation with heavy ions dielectric constant ( ) decreases with frequency where increases with fluence for both the ions. Variation of loss factor (tan ) with frequency for pristine and irradiated with Si ions reveals that tan increases as the frequency increases. Tan also increases with fluence. While Ne irradiated samples tan shows slight variation with frequency as well as with fluence. Tan has positive values indicating the dominance of inductive behavior.Author Affiliation: Rajesh Kumar, S Asad Ali, Udayan De, D K Avasthi and Rajendra Prasad 1.Department of Applied Physics, Z H College of Engineering & Technology, Aligarh Muslim University, Aligarh-202 002, Uttar Pradesh, India 2.Variable Energy Cyclotron Centre, 1/AF, Bidhan Nagar, Kolkata-700 064, India 3.Inter-University Accelerator Centre, Aruna Asaf Ali Marg, New Delhi-110 067, India E-mail : [email protected] of Applied Physics, Z H College of Engineering & Technology, Aligarh Muslim University, Aligarh-202 002, Uttar Pradesh, India Variable Energy Cyclotron Centre, 1/AF, Bidhan Nagar, Kolkata-700 064, India Inter-University Accelerator Centre, Aruna Asaf Ali Marg, New Delhi-110 067, Indi

Schottky Barrier MOSFET Enabled Ultra-Low Power Real-Time Neuron for Neuromorphic Computing

Energy-efficient real-time synapses and neurons are essential to enable large-scale neuromorphic computing. In this paper, we propose and demonstrate the Schottky-Barrier MOSFET-based ultra-low power voltage-controlled current source to enable real-time neurons for neuromorphic computing. Schottky-Barrier MOSFET is fabricated on a Silicon-on-insulator platform with polycrystalline Silicon as the channel and Nickel/Platinum as the source/drain. The Poly-Si and Nickel make the back-to-back Schottky junction enabling ultra-low ON current required for energy-efficient neurons

Treatment of Subject Descriptors on Children in Twenty Three DDC Editions

The study explores the treatment of subject descriptors on children and its correlated subjects in the 23 DDC editions by adopting an assessment and evaluation study. Authors found that the Home and family management (640) class holds the maximum subject descriptors on children