153 research outputs found

    Indian and British Influences in the Identities of Mark Tully’s Travel Writings

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    As the title of the article ‘Indian and British Influences in the Identities of Mark Tully’s Travel Writings’ the central aims of the research is to study the unending journey in Indian and British Literature through Postcolonial aspect. Though the writer belongs to different culture, he shares some common problem in a colonized nation. The research will focus upon the similar and dissimilar problems of the writer and will study how he has presented the problems during his staying both country, and also focuses how he has influences by Indian people as a travel writer. In the research work, language will a key weapon for the study, so this research will try to bring out how the writer tries to fit in meaning in the respective use of language. The research will also study the structure of these literary forms. The novel is one of the major forms of literature to comprehend the literature of the modern era especially post-colonial literature, has witnessed major upheavals in all its forms and indifferent genres. To understand the cultural identity of a certain nation, the selected novels of Mark Tully have been chosen for the present research paper. The methodology of this article is adopted as interpretative and sociological in nature. MLA 2009 and the web sources would also be utilized

    Parallel Computing in Java

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    The Java programming language and environment is inspiring new research activities in many areas of computing, of which parallel computing is one of the major interests. Parallel techniques are themselves finding new uses in cluster computing systems. Although there are excellent software tools for scheduling, monitoring and message-based programming on parallel clusters, these systems are not yet well integrated and do not provide very high-level parallel programming support. This research presents a number of issues which are considered to be key to the suitability of Java for HPC (High Performance Computing) applications and then explore the support for concurrency in the current Java 1.8 specification. We further present various relatively recent parallel Java models which support HPC for both shared and distributed memory programming paradigms. Finally, we attempt to evaluate the performance of discussed Java HPC models by comparing the same with the relative traditional native C implementations, where appropriate. The analysis of the results suggest that Java can achieve near similar performance to natively compiled languages, both for sequential and parallel applications, thus making it a viable alternative for HPC programming

    Marketing of Agricultural Crops in Rural Indian Economy: A Case Study

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    The marketing of agricultural crops plays an important role not only in stimulating production and consumption, but also in accelerating the pace of economic development. It is not only an economic link between the producers and consumers; it maintains a balance between demand and supply. Study examined the transaction of agricultural crops through rural markets and the price structure of different crops in rural markets of Ambedkarnagar District. It also highlighted the composition and structure of sellers and traders engaged in the marketing process. Local rural markets are the best option for the marginal and small farmers to dispose off their perishable surplus to get quick returns. Due to the lack of good infrastructural facilities in the study area, most of the farmers prefer local rural markets instead of going to the specialised markets or near-by town area. The variation in the transaction of agricultural produce is mainly due to a number of factors like higher market demand, accessibility, nature of produce, transportation facility, market-size, fair price, and so on. The average price of individual crop also varies from market to market due to the various socio-spatial factors. Keywords: Marketing, Agricultural crops, Rural economy, Rural market

    Towards a Theory to Explain Prosocial Data Disclosure - An Explorative Investigation of the Antecedents of Infection Disclosure

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    The voluntary infection disclosure in contact-tracing applications is a prominent context where individuals disclose their data for the benefit of others, thereby demonstrating a form of prosocial behavior. Defining such distinct types of data disclosures as prosocial data disclosures, we propose that the often-implicit assumption in privacy research that individuals consider benefits and costs solely from a “self-focused” perspective, should be reassessed to develop a new theory to explain prosocial data disclosures. To advance our understanding of the antecedents of prosocial data disclosure, our explorative research consists of a structured literature review and two qualitative surveys among 318 users of a European contact-tracing application. Our results indicate that the antecedents of prosocial data disclosures are generally evaluated from both a “self-focused” and an “other-focused” perspective. Within the specific context of infection disclosures, the main drivers are other-focused benefits while self-focused benefits have almost no relevance

    Framing as an App-Design Measure to Nudge Users Toward Infection Disclosure in Contact-Tracing Applications

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    Contact-tracing applications are only effective in countering current and future pandemics when A) they are widely adopted, and B) users voluntarily disclose their infection to warn others. While much research has investigated how contact-tracing applications should be designed and promoted to motivate app-adoption, little is known about how to increase voluntary infection disclosures. To increase the voluntary infection disclosure among app-users, our joint research project with the core development team of a contact-tracing application, relied on the theory of message framing to investigate how to nudge users toward infection disclosure in contact-tracing applications. Based on a mixed method research design consisting of 15 workshops with the core development team of the contact-tracing application and a conjoint study among 139 users of a European contact-tracing application we show that message framing can be a useful approach to increase the voluntary infection disclosure in contact-tracing applications

    Fixation of Mandibular Fractures- A Comparative Study Between 2.0 mm Locking Plates snd Screws and 2.5 mm Conventional Miniplates and Screws

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    Introduction; Fixation stability and occlusion are of atmost importance in the management of mandibular fractures. Locking plates (2mm) were introduced as internal fixators for achieving stability by locking the screw to the plate. The advantage of using locking plates was decreased amount of inflammatory response and decrease in the infection rate. Our aim was to compare the efficacy of 2mm locking plate and screw with 2.5mm conventional mini plates and screws in the treatment of mandibular fractures in the inter foraminal region and also to evaluate the fixation stability provided by these plates. Methods; 20 patients with mandible fractures were selected who required open reduction and internal fixation under general anesthesia were included in the study. 2mm locking plates and screws were used for fixation of linear fractions in the interforaminal region in 10 patients and 2.5mm mini plates and screws in 10 patients. The various parameters that were compared were fixation stability which included gap alignment after reduction and fixation. Occlusion was checked on the second day and at six weeks post operatively. Patients had a follow up of six weeks and complications if any were recorded Results; In our study it was found that the gap between the fractured fragments after fixation was reduced in the 2mm locking plate and screw system with better fixation stability when compared to mini plate group. Conclusion; So we safely conclude that locking plates and screw showed better results in comparison to miniplate in relation to their fixation stability and complication

    Noise-Aware Quantum Software Testing

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    Quantum Computing (QC) promises computational speedup over classic computing for solving some complex problems. However, noise exists in current and near-term quantum computers. Quantum software testing (for gaining confidence in quantum software's correctness) is inevitably impacted by noise, to the extent that it is impossible to know if a test case failed due to noise or real faults. Existing testing techniques test quantum programs without considering noise, i.e., by executing tests on ideal quantum computer simulators. Consequently, they are not directly applicable to testing quantum software on real QC hardware or noisy simulators. To this end, we propose a noise-aware approach (named QOIN) to alleviate the noise effect on test results of quantum programs. QOIN employs machine learning techniques (e.g., transfer learning) to learn the noise effect of a quantum computer and filter it from a quantum program's outputs. Such filtered outputs are then used as the input to perform test case assessments (determining the passing or failing of a test case execution against a test oracle). We evaluated QOIN on IBM's 23 noise models with nine real-world quantum programs and 1000 artificial quantum programs. We also generated faulty versions of these programs to check if a failing test case execution can be determined under noise. Results show that QOIN can reduce the noise effect by more than 80%80\%. To check QOIN's effectiveness for quantum software testing, we used an existing test oracle for quantum software testing. The results showed that the F1-score of the test oracle was improved on average by 82%82\% for six real-world programs and by 75%75\% for 800 artificial programs, demonstrating that QOIN can effectively learn noise patterns and enable noise-aware quantum software testing

    Towards a Theory to Explain the Effect of Uncertainty on Prosocial Data Disclosure

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    Privacy research widely assumes that individuals are less likely to disclose their data if they are uncertain about the consequences of their disclosure decision. This negative effect has been confirmed in various contexts where individuals disclose their data primarily for their own benefit. However, recent studies in behavioral science provide evidence that uncertainty may have a different effect in prosocial contexts. Transferring this to the privacy and data disclosure context, our research study aims to better understand how uncertainty influences prosocial data disclosure, i.e., situations where individuals disclose their data to benefit others. In this short paper, we present the results of qualitative interviews conducted with 19 users of a COVID-19 contact-tracing application and develop hypotheses on how the relevant context-specific uncertainties affect prosocial data disclosure. We hypothesize that a specific type of uncertainty–other- focused impact uncertainty–is positively associated with prosocial data disclosure
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