Model Selection Approach for Distributed Fault Detection in Wireless Sensor Networks

Sensor networks aim at monitoring their surroundings for event detection and object tracking. But, due to failure, or death of sensors, false signal can be transmitted. In this paper, we consider the problems of distributed fault detection in wireless sensor network (WSN). In particular, we consider how to take decision regarding fault detection in a noisy environment as a result of false detection or false response of event by some sensors, where the sensors are placed at the center of regular hexagons and the event can occur at only one hexagon. We propose fault detection schemes that explicitly introduce the error probabilities into the optimal event detection process. We introduce two types of detection probabilities, one for the center node, where the event occurs and the other one for the adjacent nodes. This second type of detection probability is new in sensor network literature. We develop schemes under the model selection procedure, multiple model selection procedure and use the concept of Bayesian model averaging to identify a set of likely fault sensors and obtain an average predictive error.Comment: 14 page

A Technique to Minimize Contention in Optical Burst Switching Networks

Optical burst switching (OBS) is the new switching technique for next generation optical networks. However, there are certain issues such as burst aggregation, scheduling, contention resolution and QoS that needs to be addressed in OBS. This thesis is an attempt to address the burst scheduling and burst contention in OBS networks. Several scheduling algorithms have been proposed in the literature, which can be categorized into Horizon and Void lling scheduling algorithm. Void lling algorithms perform better because they exploits void within a channel for scheduling. Reported void lling algorithms - Latest available unscheduled channel with void lling (LAUC-VF) and Minimum end void (Min-EV) - do not consider the void duration in scheduling. In this thesis we propose a new scheduling algorithm called Best Fit Void Filling (BFVF), which consider both void duration and incoming burst length to nd an optimal void channel. We simulate our proposed scheme using obs-ns simulator and compared with LAUC-VF and Min-EV algorithm. Result shows that the burst loss ratio is lower and channel utilization is higher in our proposed scheme

Packing Problem and Random Coverage in Continuous Domain

The packing problem is a well known-problem. There are several versions of this problem. In this paper we consider packing or covering of a disc of a given radius r by a number of discs of unit radius. We introduced two types of packing, hexagonal packing and square packing. We show that hexagonal packing is better in the sense that it needs less discs to cover a disc of higher radius. Coverage problem is similar to the packing problem in continuous domain. Coverage is essential in wireless sensor networks. In this paper we also discuss the coverage problem in random deployment scenario

Chemoselective O-methylation of phenols under non-aqueous condition

Chemoselective O-methylation of substituted phenols takes place in dry tetrahydrofuran (THF) in the presence of LiOH.H₂O and dimethylsulfate (DMS). Quantitative methyl transfer from DMS preserves the atom economy

Neonatal-onset hemophagocytic lymphohistiocytosis associated with primary dengue infection

A 40-day-old baby presented with prolonged fever, petechial spots, hepatosplenomegaly, generalized lymphadenopathy, and pancytopenia. Investigations revealed positive anti-dengue virus IgM antibody, and bone marrow examination demonstrated the presence of hemophagocytes. The diagnosis of hemophagocytic lymphohistiocytosis (HLH) was made according to HLH-2004 guidelines. HLH associated with primary dengue in an infant who was symptomatic from neonatal age has hitherto not been reported in the literature

Infectious mononucleosis due to epstein-barr virus infection in children: A profile from eastern India

Objective: The objective of this study is to delineate the clinical and laboratory profile of infectious mononucleosis due to Epstein-Barr virus (EBV) infection in children admitted to tertiary care teaching hospitals. Materials and Methods: Retrospective observational multicentric analysis of clinical and laboratory features of children between 1 month to 12 years with a diagnosis of infectious mononucleosis due to EBV infection confirmed by positive serology over a 12-month period after seeking approval from the Institutional Ethics Committee. Results: Out of 66 children screened, 53 were included in final analysis. The majority were aged between 5 and 8 years with male: female ratio of 1.2:1. Most presentations were during the monsoon months. The common clinical features were fever (100%), splenomegaly (86.7%), and cervical lymphadenopathy (73.5%) in contrast to the classical triad of fever, sore throat, and generalized lymphadenopathy described in the literature. There were no age differences in clinical findings except for generalized and cervical lymphadenopathy and hepatomegaly which were commoner in 9–12 years age band. Although the incidence of common findings matched with previously published studies, there were some notable differences. While frequencies of upper eyelid edema, epitrochlear lymphadenopathy, and splenomegaly were more, those of rash and sore throat were less. Lymphocytosis and presence of atypical lymphocytes were relatively less common in our series. All children recovered. Conclusions: This multicentric study on profiling childhood infectious mononucleosis, possibly first of its kind from Eastern India, has documented clinical and laboratory features associated with this condition. These data can serve as a reference for future studies

Programmatic assessment of electronic Vaccine Intelligence Network (eVIN).

eVIN is a technology system that digitizes vaccine stocks through a smartphone application and builds the capacity of program managers and cold chain handlers to integrate technology in their regular work. To effectively manage the vaccine logistics, in 2015, this technology was rolled-out in 12 states of India. This study assessed the programmatic usefulness of eVIN implementation in the areas of vaccine utilization, vaccine stock and distribution management and documentation across selected cold chain points. A pre-post study design was used, where cold chain points (CCPs) were selected using two-stage sampling technique in eVIN states. Pre-post comparative analysis was carried out on the identified indicators using both primary and secondary data sources. The vaccine utilization data reflects that the utilization had reduced from 305.3 million doses in pre-eVIN period to 215.0 million doses in post-eVIN period across 12 eVIN states, resulting into savings of approximately 90 million doses of vaccines. Number of facilities having stock-out of any vaccine showed a significant reduction by 30.4% in post-eVIN period (p<0.001). There was a 4.0% drop in facilities reporting minimum stock of any vaccine after implementation of eVIN. Facilities with maximum stock of any vaccine had increased from 37.4% in pre-eVIN to 39.2% in post-eVIN. During the pre-eVIN period, only 38.6% facilities updated vaccine stock on a daily basis, while in post-eVIN period, 53.5% facilities updated vaccine stock on daily basis. The completeness of records in the vaccine stock registers, indent form and temperature logbook have been substantially improved in the post-eVIN period (p<0.001). eVIN had helped in streamlining the vaccine flow network and ensured equity through better vaccine management practices. It is a powerful contribution to strengthen the vaccine supply chain and management. Upscaling eVIN in the remaining states of India will be crucial in improving the efficacy of vaccines and cold chain management