Reliable Fault Tolerance System for Service Composition in Mobile Ad Hoc Network

A Due to the rapid development of smart processing mobile devices, Mobile applications are exploring the use of web services in MANETs to satisfy the user needs. Complex user needs are satisfied by the service composition where a complex service is created by combining one or more atomic services. Service composition has a significant challenge in MANETs due to its limited bandwidth, constrained energy sources, dynamic node movement and often suffers from node failures. These constraints increase the failure rate of service composition. To overcome these, we propose Reliable Fault Tolerant System for Service Composition in MANETs (RFTSC) which makes use of the checkpointing technique for service composition in MANETs. We propose fault policies for each fault in service composition when the faults occur. Failure of services in the service composition process is recovered locally by making use of Checkpointing system and by using discovered services which satisfies the QoS constraints. A Multi-Service Tree (MST) is proposed to recover failed services with O(1) time complexity. Simulation result shows that the proposed approach is efficient when compared to existing approaches

Fuzzy Based Optimal QoS Constraint Services Composition in Mobile Ad Hoc Networks

In recent years, computational capability of mobile devices such as Laptops, mobile phones, PDAs, etc., are greatly improved. Implementation of SOA ("Service Oriented Architectures") in mobile ad hoc networks increases the flexibility of using mobile devices. On composing different available services to satisfy end user requirement is a critical challenge in MANETs ("Mobile Ad Hoc Network") due to dynamic topology, Resource heterogeneity, Band width constraint and highly distributed service providers. Existing composition services approaches are not suitable for MANETs due to lack of constraints consideration while choosing services. In this paper, we proposed Fuzzy based optimal QoS constrained Service Composition in MANETs. We consider Energy constraint, hop count, Response time & service throughput as QoS Constraints composing optimal services. We proposed fuzzy logic based system to provide rating to the services for optimal selection of services. We also considered that each node can provide one or more services. The service composition failure rate will be reduced by selecting optimal services in available services. The simulation result demonstrates that the proposed method outperformed than the traditional AODV in terms of average packet delay, energy constraint, throughput and turnaround time

Social media use by community-based organizations conducting health promotion: a content analysis

Background: Community-based organizations (CBOs) are critical channels for the delivery of health promotion programs. Much of their influence comes from the relationships they have with community members and other key stakeholders and they may be able to harness the power of social media tools to develop and maintain these relationships. There are limited data describing if and how CBOs are using social media. This study assesses the extent to which CBOs engaged in health promotion use popular social media channels, the types of content typically shared, and the extent to which the interactive aspects of social media tools are utilized. Methods: We assessed the social media presence and patterns of usage of CBOs engaged in health promotion in Boston, Lawrence, and Worcester, Massachusetts. We coded content on three popular channels: Facebook, Twitter, and YouTube. We used content analysis techniques to quantitatively summarize posts, tweets, and videos on these channels, respectively. For each organization, we coded all content put forth by the CBO on the three channels in a 30-day window. Two coders were trained and conducted the coding. Data were collected between November 2011 and January 2012. Results: A total of 166 organizations were included in our census. We found that 42% of organizations used at least one of the channels of interest. Across the three channels, organization promotion was the most common theme for content (66% of posts, 63% of tweets, and 93% of videos included this content). Most organizations updated Facebook and Twitter content at rates close to recommended frequencies. We found limited interaction/engagement with audience members. Conclusions: Much of the use of social media tools appeared to be uni-directional, a flow of information from the organization to the audience. By better leveraging opportunities for interaction and user engagement, these organizations can reap greater benefits from the non-trivial investment required to use social media well. Future research should assess links between use patterns and organizational characteristics, staff perspectives, and audience engagement

Traditional knowledge among fishers of coastal Tamil Nadu with special reference to climate change

Traditional knowledge is an excellent tool for understanding extreme events related to climate change. The Tamil Nadu fishers have extensive Traditional knowledge related to climate change

Segmentation of Optic Disc in Fundus Images using Convolutional Neural Networks for Detection of Glaucoma

The condition of the vascular network of human eye is an important diagnostic factor in ophthalmology. Its segmentation in fundus imaging is a difficult task due to various anatomical structures like blood vessel, optic cup, optic disc, macula and fovea. Blood vessel segmentation can assist in the detection of pathological changes which are possible indicators for arteriosclerosis, retinopathy, microaneurysms and macular degeneration. The segmentation of optic disc and optic cup from retinal images is used to calculate an important indicator, cup-to disc ratio( CDR) accurately to help the professionals in the detection of Glaucoma in fundus images.In this proposed work, an automated segmentation of anatomical structures in fundus images such as blood vessel and optic disc is done using Convolutional Neural Networks (CNN) . A Convolutional Neural Network is a composite of multiple elementary processing units, each featuring several weighted inputs and one output, performing convolution of input signals with weights and transforming the outcome with some form of nonlinearity. The units are arranged in rectangular layers (grids), and their locations in a layer correspond to pixels in an input image. The spatial arrangement of units is the primary characteristics that makes CNNs suitable for processing visual information; the other features are local connectivity, parameter sharing and pooling of hidden units. The advantage of CNN is that it can be trained repeatedly so more features can be found. An average accuracy of 95.64% is determined in the classification of blood vessel or not. Optic cup is also segmented from the optic disc by Fuzzy C Means Clustering (FCM). This proposed algorithm is tested on a sample of hospital images and CDR value is determined. The obtained values of CDR is compared with the given values of the sample images and hence the performance of proposed system in which Convolutional Neural Networks for segmentation is employed, is excellent in automated detection of healthy and Glaucoma images

Climate change and vulnerability of Coastal Villages in Tamil Nadu

Climate change is mainly the effect of human activities such as burning of fossil fuels, land conversion, deforestation, infrastructure development, industrial processes and from agriculture processes

The bacteria profiles of wounds in diabetic patients hospitalized in northern Kwazulu-Natal, South Africa

Diabetic wound infections still remain a health concern such that correct identification of bacteria is essential in monitoring the spread of the infections as well as in the administration of the correct treatment. This study therefore focuses on isolating and identifying bacteria present in diabetic wounds of hospitalized patients in northern KwaZulu-Natal and assessing their distribution.The wound specimen were collected and swabbed onto selective and differential media. The bacteria identities were presumptively ascertained through biochemical characterization (Gram-stain, catalase test, oxidase test and API) and then confirmed through 16S rDNA sequencing.A total of 42 isolates were recovered from 83% of the patients sampled from the three participating hospitals (X, Y, and Z). Gram-negative bacilli from Enterobacteriaceaewere predominant followed by Staphylococci spp and Enterococcus faecaliswith 43% polymicrobial cases from hospital Z and 29% from hospital X. Distribution of some opportunistic pathogens and nosocomially-acquired pathogens were also observed across the patients with five bacterial identities distributed among hospital X and Z. The adverse effects associated with the recovered bacteria in diabetic wounds pose a serious health concern and preventive measure should be taken.Keywords: Diabetes mellitus, wounds, bacteria, infectio

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Effect Of Online Education On Elementary Education In India

The mishaps happening in online education can cost a lot to the students who are getting educated by it in many ways. Elementary students particularly suffer immensely in terms of health, safety due to the online mode of education. The education system for young kids is viewed as a sacred stage since it helps in imparting basic knowledge to a human being. Yet, there are many Initiatives to help the problem, but it is still not enough. The objective of this study is to find whether online education is fruitful for the elementary school, and to deduce how many hours is advisable for elementary class, also to find how much health is getting affected, likely also to see if gadgets is advised to provide to the elementary students, lastly to ascertain which mode of education is most preferable for elementary education. Unlike in the case of doctrinal research where the research is conducted on the basis of facts and data already collected in the library, archives and other databases, collecting or gathering information by a first-hand study into the universe, it helps the empirical research to be carried on. There are a total of 1005 samples collected with regard to this study. Hence, through these figures, we are able to understand that there is not much reception regarding online education for elementary students among the general public but truly they are at a confused level about which mode is truthfully the good one for elementary school students

Vulnerability index and climate change: An analysis in Cuddalore District of Tamil Nadu, India

Erratic monsoon and extreme climatic events cause considerable damage to life and property of the fishers in the country. Cuddalore District has been the worst affected of all districts in Tamil Nadu, in the recent past with the tsunami in 2004, cyclone Thane in 2011 and cyclone Neelam in 2012 creating a detrimental impact on coastal communities and their activities, particularly fishing. This in turn has affected their livelihood to a great extent. This coastal zone is largely low-lying with gentle slope, thus making it highly vulnerable to climate related changes. The vulnerability of this region to climate change and its devastating effects necessitates identifying vulnerability indices to assist in developing proactive policies by local government bodies in better disaster management. The vulnerability index of ten coastal villages of Cuddalore District was computed using Parameter, Attribute, Resilient indicator and Score (PARS) method. The study showed that the Cuddalore coast is highly vulnerable to climate change and related sea level rise. The villages of Pettodai, Reddiarpettai and Sothikuppam of Cuddalore District were identifified as most vulnerable. The outcome of this study will be of use in the protection of coastal livelihoods and planning better adaptation policies and mitigation plans