929 resultados para Library and Information Sciences


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An administrative border might hinder the optimal allocation of a given set of resources by restricting the flow of goods, services, and people. In this paper we address the question: Do administrative borders lead to poor accessibility to public service such as hospitals? In answering the question, we have examined the case of Sweden and its regional borders. We have used detailed data on the Swedish road network, its hospitals, and its geo-coded population. We have assessed the population’s spatial accessibility to Swedish hospitals by computing the inhabitants’ distance to the nearest hospital. We have also elaborated several scenarios ranging from strongly confining regional borders to no confinements of borders and recomputed the accessibility. Our findings imply that administrative borders are only marginally worsening the accessibility.

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We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

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We develop a method for empirically measuring the difference in carbon footprint between traditional and online retailing (“e-tailing”) from entry point to a geographical area to consumer residence. The method only requires data on the locations of brick-and-mortar stores, online delivery points, and residences of the region’s population, and on the goods transportation networks in the studied region. Such data are readily available in most countries, so the method is not country or region specific. The method has been evaluated using data from the Dalecarlia region in Sweden, and is shown to be robust to all assumptions made. In our empirical example, the results indicate that the average distance from consumer residence to a brick-and-mortar retailer is 48.54 km in the studied region, while the average distance to an online delivery point is 6.7 km. The results also indicate that e-tailing increases the average distance traveled from the regional entry point to the delivery point from 47.15 km for a brick-and-mortar store to 122.75 km for the online delivery points. However, as professional carriers transport the products in bulk to stores or online delivery points, which is more efficient than consumers’ transporting the products to their residences, the results indicate that consumers switching from traditional to e-tailing on average reduce their CO2 footprints by 84% when buying standard consumer electronics products. 

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Data mining can be used in healthcare industry to “mine” clinical data to discover hidden information for intelligent and affective decision making. Discovery of hidden patterns and relationships often goes intact, yet advanced data mining techniques can be helpful as remedy to this scenario. This thesis mainly deals with Intelligent Prediction of Chronic Renal Disease (IPCRD). Data covers blood, urine test, and external symptoms applied to predict chronic renal disease. Data from the database is initially transformed to Weka (3.6) and Chi-Square method is used for features section. After normalizing data, three classifiers were applied and efficiency of output is evaluated. Mainly, three classifiers are analyzed: Decision Tree, Naïve Bayes, K-Nearest Neighbour algorithm. Results show that each technique has its unique strength in realizing the objectives of the defined mining goals. Efficiency of Decision Tree and KNN was almost same but Naïve Bayes proved a comparative edge over others. Further sensitivity and specificity tests are used as statistical measures to examine the performance of a binary classification. Sensitivity (also called recall rate in some fields) measures the proportion of actual positives which are correctly identified while Specificity measures the proportion of negatives which are correctly identified. CRISP-DM methodology is applied to build the mining models. It consists of six major phases: business understanding, data understanding, data preparation, modeling, evaluation, and deployment.

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This thesis focuses on the adaptation of formal education to people’s technology- use patterns, theirtechnology-in-practice, where the ubiquitous use of mobile technologies is central. The research question is: How can language learning practices occuring in informal learning environments be effectively integrated with formal education through the use of mobile technology? The study investigates the technical, pedagogical, social and cultural challenges involved in a design science approach. The thesis consists of four studies. The first study systematises MALL (mobile-assisted language learning) research. The second investigates Swedish and Chinese students’ attitudes towards the use of mobile technology in education. The third examines students’ use of technology in an online language course, with a specific focus on their learning practices in informal learning contexts and their understanding of how this use guides their learning. Based on the findings, a specifically designed MALL application was built and used in two courses. Study four analyses the app use in terms of students’ perceived level of self-regulation and structuration. The studies show that technology itself plays a very important role in reshaping peoples’ attitudes and that new learning methods are coconstructed in a sociotechnical system. Technology’s influence on student practices is equally strong across borders. Students’ established technologies-in-practice guide the ways they approach learning. Hence, designing effective online distance education involves three interrelated elements: technology, information, and social arrangements. This thesis contributes to mobile learning research by offering empirically and theoretically grounded insights that shift the focus from technology design to design of information systems.

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Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

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The goal of a research programme Evidence Algorithm is a development of an open system of automated proving that is able to accumulate mathematical knowledge and to prove theorems in a context of a self-contained mathematical text. By now, the first version of such a system called a System for Automated Deduction, SAD, is implemented in software. The system SAD possesses the following main features: mathematical texts are formalized using a specific formal language that is close to a natural language of mathematical publications; a proof search is based on special sequent-type calculi formalizing natural reasoning style, such as application of definitions and auxiliary propositions. These calculi also admit a separation of equality handling from deduction that gives an opportunity to integrate logical reasoning with symbolic calculation.

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The paper investigates which of Shannon’s measures (entropy, conditional entropy, mutual information) is the right one for the task of quantifying information flow in a programming language. We examine earlier relevant contributions from Denning, McLean and Gray and we propose and motivate a specific quantitative definition of information flow. We prove results relating equivalence relations, interference of program variables, independence of random variables and the flow of confidential information. Finally, we show how, in our setting, Shannon’s Perfect Secrecy theorem provides a sufficient condition to determine whether a program leaks confidential information.

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In recent decades, library associations have advocated for the adoption of privacy and confidentiality policies as practical support to the Library Code of Ethics with a threefold purpose to (1) define and uphold privacy practices within the library, (2) convey privacy practices to patrons and, (3) protect against potential liability and public relations problems. The adoption of such policies has been instrumental in providing libraries with effective responses to surveillance initiatives such as warrantless requests and the USA PATRIOT ACT. Nevertheless, as reflected in recent news stories, the rapid emergence of data brokerage relationships and technologies and the increasing need for libraries to utilize third party vendor services have increased opportunities for data surveillers to access patrons’ personal information and reading habits, which are funneled and made available through multiple online library service platforms. Additionally, the advice that libraries should “contract for the same level of privacy reflected in their privacy policies” is no longer realistic given that the existence of multiple vendor contracts negotiated at arms length is likely to produce varying privacy terms and even varying definitions of what constitutes personal information (PII). These conditions sharply threaten the effectiveness and relevance of library privacy policies and privacy initiatives in that such policies increasingly offer false comfort by failing to reflect privacy weaknesses in the data sharing landscape and vendor contracts when library-vendor contracts fail to keep up with vendor data sharing capabilities. While some argue that library privacy ethics are antiquated and rendered obscure in the current online sharing economy PEW studies point to pronounced public discomfort with increasing privacy erosion. At the same time, new directions in FTC enforcement raise the possibility that public institutions’ privacy policies may serve as swords to unfair or deceptive commercial trade practices – offering the potential of renewed relevance for library privacy and confidentiality policies. This dual coin of public concern and the potential for enhanced FTC enforcement suggests that when crafting privacy polices libraries must now walk the knife’s edge by offering patrons both realistic notice about the limitations of protections the library can ensure while at the same time publicly holding vendors accountable to library privacy ethics and expectations. Potential solutions for how to walk this edge are developed and offered as a subject for further discussion to assist the modification of model policies for both public and academic libraries alike.

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Libraries are caught in the middle—between static or shrinking budgets on one hand and ever-expanding user needs on the other. How did we get here, and where do we go from here? This paper will offer two perspectives: Part I will present survey results about changing Library purchasing habits in light of changing formats, access, business models and user demands. Data from a previous survey on this topic will be compared and updated. Pricing trends and possible futures will be discussed. Part II will briefly trace the history of libraries’ roles in scholarly communication and connecting learners with knowledge. From there, we show an example of phasing in a patron-driven / demand-driven and short-term loan e-book program, complete with incorporating these tools in library instruction, research, and portable device loadability for field work.

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This article presents data-rich findings of a comprehensive follow-up study on the patron-driven/demand-driven ebook acquisitions (DDA) plan chronicled in two prior articles from the DDA ebook plan's October 2011 inception. Into the third fiscal year, print vs. ebook usage preferences have begun to emerge, and the results broken out by discipline are presented.

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Libraries seek active ways to innovate amidst macroeconomic shifts, growing online education to help alleviate ever-growing schedule conflicts as students juggle jobs and course schedules, as well as changing business models in publishing and evolving information technologies. Patron-driven acquisition (PDA), also known as demand-driven acquisition (DDA), offers numerous strengths in supporting university curricula in the context of these significant shifts. PDA is a business model centered on short-term loans and subsequent purchases of ebooks resulting directly from patrons' natural use stemming from their discovery of the ebooks in library catalogs where the ebooks' bibliographic records are loaded at regular intervals established between the library and ebook supplier. Winthrop University's PDA plan went live in October 2011, and this article chronicles the philosophical and operational considerations, the in-library collaboration, and technical preparations in concert with the library system vendor and ebook supplier. Short-term loan is invoked after a threshold is crossed, typically number of pages or time spent in the ebook. After a certain number of short-term loans negotiated between the library and ebook supplier, the next short-term loan becomes an automatic purchase after which the library owns the ebook in perpetuity. Purchasing options include single-user and multi-user licenses. Owing to high levels of need in college and university environments, Winthrop chose the multi-user license as the preferred default purchase. Only where multi-user licenses are unavailable does the automatic purchase occur with single-user title licenses. Data on initial use between October 2011 and February 2013 reveal that of all PDA ebooks viewed, only 30% crossed the threshold into short-term loans. Of all triggered short-term loans, Psychology was the highest-using. Of all ebook views too brief to trigger short-term loans, Business was the highest-using area. Although the data are still too young to draw conclusions after only a few months, thought-provoking usage differences between academic disciplines have begun to emerge. These differences should be considered in library plans for the best possible curricular support for each academic program. As higher education struggles with costs and course-delivery methods libraries have an enduring lead role.

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Contrary to divisive labels to describe generations, members of different age groups have much to teach each other: Younger workers bring fresh perspectives to old issues, while older workers' valuable organizational history help inform current contexts. All age groups in the workplace benefit in learning from each other's perspectives.