An Empirical Investigation of Using ANN Based N-State Sequential Machine and Chaotic Neural Network in the Field of Cryptography

Cryptography is the exchange of information among the users without leakage of information to others. Many public key cryptography are available which are based on number theory but it has the drawback of requirement of large computational power, complexity and time consumption during generation of key [1]. To overcome these drawbacks, we analyzed neural network is the best way to generate secret key. In this paper we proposed a very new approach in the field of cryptography. We are using two artificial neural networks in the field of cryptography. First One is ANN based n-state sequential machine and Other One is chaotic neural network. For simulation MATLAB software is used. This paper also includes an experimental results and complete demonstration that ANN based n-state sequential machine and chaotic neural network is successfully perform the cryptography

Hybrid Data Storage Framework for the Biometrics Domain

Biometric based authentication is one of the most popular techniques adopted in large-scale identity matching systems due to its robustness in access control. In recent years, the number of enrolments has increased significantly posing serious issues towards the performance and scalability of these systems. In addition, the use of multiple modalities (such as face, iris and fingerprint) is further increasing the issues related to scalability. This research work focuses on the development of a new Hybrid Data Storage Framework (HDSF) that would improve scalability and performance of biometric authentication systems (BAS). In this framework, the scalability issue is addressed by integrating relational database and NoSQL data store, which combines the strengths of both. The proposed framework improves the performance of BAS in three areas (i) by proposing a new biographic match score based key filtering process, to identify any duplicate records in the storage (de-duplication search); (ii) by proposing a multi-modal biometric index based key filtering process for identification and de-duplication search operations; (iii) by adopting parallel biometric matching approach for identification, enrolment and verification processes. The efficacy of the proposed framework is compared with that of the traditional BAS and on several values of False Rejection Rate (FRR). Using our dataset and algorithms it is observed that when compared to traditional BAS, the HDSF is able to show an overall efficiency improvement of more than 54% for zero FRR and above 60% for FRR values between 1-3.5% during identification search operations

Urban Growth in Himalaya: Understanding the Process and Options for Sustainable Development <Article>

During recent years, urbanization has emerged as one of the important drivers of global environmental change transforming mountain regions, particularly in developing countries where the process of urban-growth has been fast but mostly unsystematic, unplanned and unregulated. Himalaya representing tectonically alive, densely populated, and one of the most marginalized mountain regions of the world has experienced rapid urban growth during last three decades. More recently, comparatively less accessible areas have also come under the process of rapid urbanization mainly owing to improved road connectivity, publicity and marketing of new tourist sites and the resultant growth of domestic as well as international tourism; development of horticulture; economic globalization and gradual shift from primary resource development practices to secondary and tertiary sectors; and due to absence of urban land use policy. Consequently, there has been tremendous increase in size, area, number and complexity of urban settlements in the Himalaya resulting into the expansion of urban processes (i.e., expansion of urban land use in surrounding agricultural zone, forests and rural environments) as well as increase in the intensity of urban land use (i.e., increase in the density of covered area, density of building, and increase in the density of population) within the towns. On the one hand, the growing urban areas in high mountain are now serving as the centres of growth by creating opportunities of employment, variety of socio-economic services and expansion of infrastructure; and contributing towards the development of their vast hinterland through trickledown effect; while on the other, the sprawling urban growth in fragile mountains has disrupted the critical ecosystem services. The speedy and unplanned urbanization has perturbed the hydrological regimes of Himalayan watersheds and reduced ground water recharge, and decreased the availability of water for drinking, sanitation and crop production; depleted forests and biodiversity; increased risks of natural hazards and disasters both in urban areas as well as in their peri-urban zones; and increased vulnerability of mountain inhabitants to water, food, livelihood and health insecurity. Moreover, climate change has stressed urban ecosystems by increasing the frequency, severity and intensity of extreme weather events. As in other parts of the world, urban growth cannot be stopped or reduced in Himalaya, but it can be steered in a more sustainable manner through an integrated urban-rural land use planning. Effective land use policies need to be evolved and implemented for the protection and conservation of forests, biodiversity, water resources and agricultural land

Coupling between feedback loops in autoregulatory networks affects bistability range, open-loop gain and switching times

Biochemical regulatory networks governing diverse cellular processes such as stress-response, differentiation and cell cycle often contain coupled feedback loops. We aim at understanding how features of feedback architecture, such as the number of loops, the sign of the loops and the type of their coupling, affect network dynamical performance. Specifically, we investigate how bistability range, maximum open-loop gain and switching times of a network with transcriptional positive feedback are affected by additive or multiplicative coupling with another positive- or negative-feedback loop. We show that a network's bistability range is positively correlated with its maximum open-loop gain and that both quantities depend on the sign of the feedback loops and the type of feedback coupling. Moreover, we find that the addition of positive feedback could decrease the bistability range if we control the basal level in the signal-response curves of the two systems. Furthermore, the addition of negative feedback has the capacity to increase the bistability range if its dissociation constant is much lower than that of the positive feedback. We also find that the addition of a positive feedback to a bistable network increases the robustness of its bistability range, whereas the addition of a negative feedback decreases it. Finally, we show that the switching time for a transition from a high to a low steady state increases with the effective fold change in gene regulation. In summary, we show that the effect of coupled feedback loops on the bistability range and switching times depends on the underlying mechanistic details

Data management in cloud environments: NoSQL and NewSQL data stores

: Advances in Web technology and the proliferation of mobile devices and sensors connected to the Internet have resulted in immense processing and storage requirements. Cloud computing has emerged as a paradigm that promises to meet these requirements. This work focuses on the storage aspect of cloud computing, specifically on data management in cloud environments. Traditional relational databases were designed in a different hardware and software era and are facing challenges in meeting the performance and scale requirements of Big Data. NoSQL and NewSQL data stores present themselves as alternatives that can handle huge volume of data. Because of the large number and diversity of existing NoSQL and NewSQL solutions, it is difficult to comprehend the domain and even more challenging to choose an appropriate solution for a specific task. Therefore, this paper reviews NoSQL and NewSQL solutions with the objective of: (1) providing a perspective in the field, (2) providing guidance to practitioners and researchers to choose the appropriate data store, and (3) identifying challenges and opportunities in the field. Specifically, the most prominent solutions are compared focusing on data models, querying, scaling, and security related capabilities. Features driving the ability to scale read requests and write requests, or scaling data storage are investigated, in particular partitioning, replication, consistency, and concurrency control. Furthermore, use cases and scenarios in which NoSQL and NewSQL data stores have been used are discussed and the suitability of various solutions for different sets of applications is examined. Consequently, this study has identified challenges in the field, including the immense diversity and inconsistency of terminologies, limited documentation, sparse comparison and benchmarking criteria, and nonexistence of standardized query languages

Impact of personal alcohol consumption on aspects of medical student alcohol-related competencies

AimAs part of the prevention and management of alcohol-related harms, health professionals need to be competent to assess the level of alcohol use in patients. In this study, we explored how medical students’ own alcohol consumption impacts on their familiarity with alcohol brands, strengths and alcohol-related harms.MethodsAs part of a wider study investigating the concept of ‘alcohol health literacy’, this study combined an anonymous online survey, linked to an electronic alcohol ‘brand’ recognition game. Participants were medical students in their first clinical year. The survey recorded demographics, self-reported alcohol consumption (using the AUDIT-C), a visual test of relative alcohol concentrations of wine, beer and spirits, and a free-text response asking them to list alcohol-related harms. Participants then completed the brand recognition game recording accuracy and reaction time for identifying alcohol drink brands.ResultsOne hundred and fifty students participated. There was a significant effect of ethnicity on drinking status, with 48% of non-white participants scoring zero on the AUDIT-C. Students who reported any alcohol consumption were more likely to correctly assess relative alcohol concentrations and were faster and more accurate at recognizing alcohol brands, which was dose dependent. Overall, only 45% correctly recognized relative alcohol strengths of drinks presented.ConclusionsAmong third-year medical students, ability to correctly identify relative strengths of alcoholic drinks is low. As might be expected, students who drink alcohol tend to identify brands and strengths more accurately. This has implications for how best to tailor the delivery of teaching and training about alcohol to ensure similar levels of clinical confidence in dealing with future patients regardless of personal experience