637 research outputs found

    Improved detection of Probe Request Attacks : Using Neural Networks and Genetic Algorithm

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    The Media Access Control (MAC) layer of the wireless protocol, Institute of Electrical and Electronics Engineers (IEEE) 802.11, is based on the exchange of request and response messages. Probe Request Flooding Attacks (PRFA) are devised based on this design flaw to reduce network performance or prevent legitimate users from accessing network resources. The vulnerability is amplified due to clear beacon, probe request and probe response frames. The research is to detect PRFA of Wireless Local Area Networks (WLAN) using a Supervised Feedforward Neural Network (NN). The NN converged outstandingly with train, valid, test sample percentages 70, 15, 15 and hidden neurons 20. The effectiveness of an Intruder Detection System depends on its prediction accuracy. This paper presents optimisation of the NN using Genetic Algorithms (GA). GAs sought to maximise the performance of the model based on Linear Regression (R) and generated R > 0.95. Novelty of this research lies in the fact that the NN accepts user and attacker training data captured separately. Hence, security administrators do not have to perform the painstaking task of manually identifying individual frames for labelling prior training. The GA provides a reliable NN model and recognises the behaviour of the NN for diverse configurations

    FoodNet: Recognizing Foods Using Ensemble of Deep Networks

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    In this work we propose a methodology for an automatic food classification system which recognizes the contents of the meal from the images of the food. We developed a multi-layered deep convolutional neural network (CNN) architecture that takes advantages of the features from other deep networks and improves the efficiency. Numerous classical handcrafted features and approaches are explored, among which CNNs are chosen as the best performing features. Networks are trained and fine-tuned using preprocessed images and the filter outputs are fused to achieve higher accuracy. Experimental results on the largest real-world food recognition database ETH Food-101 and newly contributed Indian food image database demonstrate the effectiveness of the proposed methodology as compared to many other benchmark deep learned CNN frameworks.Comment: 5 pages, 3 figures, 3 tables, IEEE Signal Processing Letter

    Challenges posed by non-standard neutrino interactions in the determination of δCP\delta_{CP} at DUNE

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    One of the primary objectives of Deep Underground Neutrino Experiment (DUNE) is to discover the leptonic CP violation and to identify it's source. In this context, we study the impact of non-standard neutrino interactions (NSIs) on observing the CP violation signal at DUNE. We explore the impact of various parameter degeneracies introduced by non-zero NSI and identify which of these can influence the CP violation sensitivity and CP precision of DUNE, by considering NSI both in data and in theory. In particular, we study how the CP sensitivity of DUNE is affected because of the intrinsic hierarchy degeneracy which occurs when the diagonal NSI parameter ϵee=1\epsilon_{ee}=-1 and δCP=±90\delta_{CP}= \pm 90^{\circ}

    The seed and agricultural biotechnology industries in India: An analysis of industry structure, competition, and policy options

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    Since the late 1980s, technological advances and policy reforms have opened up new opportunities for growth in India's seed and agricultural biotechnology industries. The impacts of such changes have been significant in India's cotton sector, but less so for the country's main cereal crops, where both yield and output growth rates have been relatively stagnant. Some public policymakers and corporate decisionmakers are confident that the private sector will help reverse these trends, arguing that the right combination of new technological solutions and progressive policy reforms will unleash a significant increase in private investment in productivity-enhancing products and services. The structure of India's seed and agbiotech industries, as well as the policies designed to support their growth, will be a significant determinant of this expected impact. This paper examines the structure of India's cereal seed and agbiotech industries, its potential effects on innovation and social welfare, and the policies that may improve both industry performance and the delivery of new technologies to resource-poor, small-scale farmers in India's cereal production systems. We focus our analysis on indicators and scenarios within India's agricultural innovation market for improved seed and agricultural biotechnology products. This market includes firms engaged in the development, commercialization, and marketing of new seed-based technologies; it is characterized by a high level of knowledge intensity, relatively high levels of R&D investment, significant barriers to entry, significant levels of regulation, and relatively few products in the market. And it is within this market that factors such as strategic corporate behavior and public policy can affect the balance between a socially desirable rate of innovation, on the one hand, and a socially desirable distribution of the gains from innovation among consumers, farmers, and innovators, on the other hand.Seed markets, Agricultural biotechnology, industrial organization, Cereal crops,

    സാമ്പിൾ ശേഖരണം ശാസ്ത്രീയ മണ്ണുപരിശോധനയ്ക്ക്

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    സാമ്പിൾ ശേഖരണം ശാസ്ത്രീയ മണ്ണുപരിശോധനയ്ക്ക് Sample collection for scientific soil analysi

    Impact of Self Help Groups in Gender Mainstreaming: A Case Study on Fish Amino Enterprise in Vypin, Kerala

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    A study for assessing the impact of SHGs in gender mainstreaming was undertaken on the fish amino acid producing units operating at Vypin located at Ernakulam District of Kerala. The analysis included specific aspects such as performance assessment of the SHGs, gender analysis, empowerment analysis and economic feasibility analysis which were carried out based on socio-economic surveys and personal interviews using pre-tested and structured data gathering protocols with standardized scales and indices involving the members of the SHGs. The male and female counterparts of the families were separately interviewed to assess the gender mainstreaming aspects in terms of equity and equality to access to resources, participation profile, decision making aspects, gender need analysis etc. Though majority of activities are female dominated, the male counterparts of the households also have definite role in decision making, purchase of accessories, sales, marketing etc. The indicative economics worked out for the economic feasibility analysis of the SHGs suggests that, the unit takes just one year to break even. A success case study was elucidated and documented as a documentary movie which can be used as a case model for promoting group action for mobilizing SHGs on a sustainable basis
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