Borrow or buy? cost-effective delivery of monographs

In an effort to reduce Interlibrary borrowing activity, while enhancing the Library collection, the Bertrand Library has initiated a program to purchase current monographs requested through ILL by Bucknell University students and faculty. The results have been a successful reduction in ILL workload, and a cost-effective means of document delivery as measured by average delivery time, cost-per-title, processing costs, and circulation statistics. This procedure reflects an overall change in our philosophy concerning document access and delivery, which led to the reorganization of ILL services and staff in the Bertrand Library.

The Role of Small and Medium-sized Centers for Territorial Development in Switzerland

This paper describes the role of small and medium-sized urban centers in Switzerland. Switzerland is a highly urbanized country where small and medium-sized urban centers play an important role in ensuring a balanced national urban system. Besides the four largest metropolitan regions （Zurich, Geneva, Basel and Bern）, small and medium-sized towns function as central places for a wider, often extensive hinterland. They provide opportunities for living and working and they connect rural and mountain regions to national and international networks. Using secondary statistics and a case study, the paper shows that small and medium-sized urban centers are home to significant concentrations of export-oriented industries. Firms in these value-adding secondary sectors are rooted in these places and benefit from strong local embeddedness while also being oriented towards global markets. Small and medium-sized urban centers also profit from their strong local identities. While these places face various challenges, they function as important pillars in creating a balanced regional development pattern. Swiss regional development policy follows the goal of polycentric spatial development and it employs various instruments that aim to ensure a balanced urban system.

Increasingly Rank: The Use and Misuse of Rankings in Economic Development

Debates over the merits of competing schemes for ranking metropolitan areas as hightech centers shed little light on the important policy questions that should be the core of economic development policy. There are no strong theoretical reasons for preferring one ranking system to others. Rankings often conflate different industries and ignore history, obscuring the varied and often idiosyncratic processes that drive growth in different regions. Although an occupational perspective is a useful one for examining economic activity, it is a supplement to, not a replacement for, a careful understanding of metropolitan industrial specialization. Practitioners should not put too much weight on any ranking system but instead should work to develop detailed knowledge of their region’s special economic niche and to develop relationships and strategies that build on established strengths.

Pressoes e oposiçoes contra pequenos criadores familiares de gado bovino leiteiro da zona periurbana do Município de Castanhal (Pará, Brasil - Amazônia Oriental)

It is analyzed, in this paper, the conflicts involving a family of small dairy cattle breeders, faced with the opposition of society and restrictions imposed by the local authorities, against the livestock grazing on public lands in peri-urban zone of a medium-sized Amazonian city. The case study employed participant observation, interviews and document research. Despite the subordinate position occupied by the focused group in the credibility hierarchy of versions issued on the conflict, the group maintains a resistance conduct, based both in the need for sustenance, and in an attempt to preserve a way of life cherished by its members

Key Factors to Successful Community Development: The Korean Experience

The Saemaul Undong of the Republic of Korea has been world-widely recognized as a successful model of rural community development. The Saemaul Undong was a pure Korean way of community development program which was initiated by the political will of the top national leadership in order to escape from poverty. There are several key factors to the success of the Saemaul Undong. First, the national government's guidance and support for the movement played a very important role in the whole period of the movement. Second, there was a wide range of people's participation in the implementation process. Third, the Saemaul Undong could make a big success by nurturing community leadership which was selected by rural residents themselves. Finally, as a movement for the spiritual reform, the Saemaul Undong imbued the people with the spirits of diligence, the self-reliance, and cooperation.

Theory of a Flowchart Approach to Industrial Cluster Policy

A flowchart approach to industrial cluster policy emphasizes the importance ofthe ordering of policy measures. The flow of policy implementation is to establish an industrial zone, to invite an anchor company, and to promote its related companies to invest in the industrial zone. This article delineated "a flowchart approach to industrial cluster policy" by proposing sufficient conditions for forming industrial clusters typical in the manufacturing industry in Asia to enhance regional economic growth. The typical industrial cluster policy was theorized by defining an industrial zone as "quasi-public goods", and it was shown that the policy enhances economic growth under a production function of "increasing returns to scale" of an anchor company. Critical amounts of the production of "scale economies" that are used by the related companies to decide whether or not to invest in clusters were also shown.

Factors Underlying the Formation of Industrial Clusters in Japan and Industrial Cluster Policy: A Quantitative Survey

The purpose of this report is to use information provided by a questionnaire survey to analyze the factors and processes underlying the formation of industrial clusters in Japan. The study, based on questionnaire surveys, forms part of an "Industrial Cluster Project". The Japanese government has implemented policies for industrial clusters so as to enable Japanese industries to maintain competitive power in global markets, and to aid the self-sufficient expansion of local industries. The government's project goes under the heading "Industry Agglomeration for the Recovery of Local Industries with respect to so-called "Industry Clusters." The authors aim to identify what expectations are held of government by the enterprises that make up industrial clusters. As part of our investigation, we used the results of a survey conducted by UNDP in 2004. Tsuji's study, published by the Osaka School of International Public Policy, surveyed 1198 small or medium sized manufacturing companies located in O ward, Tokyo and Higashi Osaka city, Osaka prefecture. The outcome of the present study, together with data from Tsuji's work on IT usage by SMEs in Japan, is meant to form the basis for policy design and implementation.

Input-Output Based Economic Impact Evaluation System for Small City Development: A Case Study on Saemangeum's Flux City Design

The paper aims to develop a quasi-dynamic interregional input-output model for evaluating the macro-economic impacts of small city development. The features of the model are summarized as follows: (1) the consumption expenditure of households is regarded as an endogenous variable, (2) the technological change is determined by the change of industrial Location Quotient caused by firm's investment activities. (3) a strong feedback function between the city design and the economic analysis is provided. For checking the performance of the model, Saemangeum's Flux City Design Plan is used as the simulation target in our paper.

Detección de patrones y anomalías espectrales del terreno mediante espectrometría de imagen de alta resolución : reconocimiento, optimización y evaluación multiescenario

El objeto de esta Tesis doctoral es el desarrollo de una metodologia para la deteccion automatica de anomalias a partir de datos hiperespectrales o espectrometria de imagen, y su cartografiado bajo diferentes condiciones tipologicas de superficie y terreno. La tecnologia hiperespectral o espectrometria de imagen ofrece la posibilidad potencial de caracterizar con precision el estado de los materiales que conforman las diversas superficies en base a su respuesta espectral. Este estado suele ser variable, mientras que las observaciones se producen en un numero limitado y para determinadas condiciones de iluminacion. Al aumentar el numero de bandas espectrales aumenta tambien el numero de muestras necesarias para definir espectralmente las clases en lo que se conoce como Maldicion de la Dimensionalidad o Efecto Hughes (Bellman, 1957), muestras habitualmente no disponibles y costosas de obtener, no hay mas que pensar en lo que ello implica en la Exploracion Planetaria. Bajo la definicion de anomalia en su sentido espectral como la respuesta significativamente diferente de un pixel de imagen respecto de su entorno, el objeto central abordado en la Tesis estriba primero en como reducir la dimensionalidad de la informacion en los datos hiperespectrales, discriminando la mas significativa para la deteccion de respuestas anomalas, y segundo, en establecer la relacion entre anomalias espectrales detectadas y lo que hemos denominado anomalias informacionales, es decir, anomalias que aportan algun tipo de informacion real de las superficies o materiales que las producen. En la deteccion de respuestas anomalas se asume un no conocimiento previo de los objetivos, de tal manera que los pixeles se separan automaticamente en funcion de su informacion espectral significativamente diferenciada respecto de un fondo que se estima, bien de manera global para toda la escena, bien localmente por segmentacion de la imagen. La metodologia desarrollada se ha centrado en la implicacion de la definicion estadistica del fondo espectral, proponiendo un nuevo enfoque que permite discriminar anomalias respecto fondos segmentados en diferentes grupos de longitudes de onda del espectro, explotando la potencialidad de separacion entre el espectro electromagnetico reflectivo y emisivo. Se ha estudiado la eficiencia de los principales algoritmos de deteccion de anomalias, contrastando los resultados del algoritmo RX (Reed and Xiaoli, 1990) adoptado como estandar por la comunidad cientifica, con el metodo UTD (Uniform Targets Detector), su variante RXD-UTD, metodos basados en subespacios SSRX (Subspace RX) y metodo basados en proyecciones de subespacios de imagen, como OSPRX (Orthogonal Subspace Projection RX) y PP (Projection Pursuit). Se ha desarrollado un nuevo metodo, evaluado y contrastado por los anteriores, que supone una variacion de PP y describe el fondo espectral mediante el analisis discriminante de bandas del espectro electromagnetico, separando las anomalias con el algortimo denominado Detector de Anomalias de Fondo Termico o DAFT aplicable a sensores que registran datos en el espectro emisivo. Se han evaluado los diferentes metodos de deteccion de anomalias en rangos del espectro electromagnetico del visible e infrarrojo cercano (Visible and Near Infrared-VNIR), infrarrojo de onda corta (Short Wavelenght Infrared-SWIR), infrarrojo medio (Meadle Infrared-MIR) e infrarrojo termico (Thermal Infrared-TIR). La respuesta de las superficies en las distintas longitudes de onda del espectro electromagnetico junto con su entorno, influyen en el tipo y frecuencia de las anomalias espectrales que puedan provocar. Es por ello que se han utilizado en la investigacion cubos de datos hiperepectrales procedentes de los sensores aeroportados cuya estrategia y diseno en la construccion espectrometrica de la imagen difiere. Se han evaluado conjuntos de datos de test de los sensores AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) y MASTER (MODIS/ASTER Simulator). Se han disenado experimentos sobre ambitos naturales, urbanos y semiurbanos de diferente complejidad. Se ha evaluado el comportamiento de los diferentes detectores de anomalias a traves de 23 tests correspondientes a 15 areas de estudio agrupados en 6 espacios o escenarios: Urbano - E1, Semiurbano/Industrial/Periferia Urbana - E2, Forestal - E3, Agricola - E4, Geologico/Volcanico - E5 y Otros Espacios Agua, Nubes y Sombras - E6. El tipo de sensores evaluados se caracteriza por registrar imagenes en un amplio rango de bandas, estrechas y contiguas, del espectro electromagnetico. La Tesis se ha centrado en el desarrollo de tecnicas que permiten separar y extraer automaticamente pixeles o grupos de pixeles cuya firma espectral difiere de manera discriminante de las que tiene alrededor, adoptando para ello como espacio muestral parte o el conjunto de las bandas espectrales en las que ha registrado radiancia el sensor hiperespectral. Un factor a tener en cuenta en la investigacion ha sido el propio instrumento de medida, es decir, la caracterizacion de los distintos subsistemas, sensores imagen y auxiliares, que intervienen en el proceso. Para poder emplear cuantitativamente los datos medidos ha sido necesario definir las relaciones espaciales y espectrales del sensor con la superficie observada y las potenciales anomalias y patrones objetivos de deteccion. Se ha analizado la repercusion que en la deteccion de anomalias tiene el tipo de sensor, tanto en su configuracion espectral como en las estrategias de diseno a la hora de registrar la radiacion prodecente de las superficies, siendo los dos tipos principales de sensores estudiados los barredores o escaneres de espejo giratorio (whiskbroom) y los barredores o escaneres de empuje (pushbroom). Se han definido distintos escenarios en la investigacion, lo que ha permitido abarcar una amplia variabilidad de entornos geomorfologicos y de tipos de coberturas, en ambientes mediterraneos, de latitudes medias y tropicales. En resumen, esta Tesis presenta una tecnica de deteccion de anomalias para datos hiperespectrales denominada DAFT en su variante de PP, basada en una reduccion de la dimensionalidad proyectando el fondo en un rango de longitudes de onda del espectro termico distinto de la proyeccion de las anomalias u objetivos sin firma espectral conocida. La metodologia propuesta ha sido probada con imagenes hiperespectrales reales de diferentes sensores y en diferentes escenarios o espacios, por lo tanto de diferente fondo espectral tambien, donde los resultados muestran los beneficios de la aproximacion en la deteccion de una gran variedad de objetos cuyas firmas espectrales tienen suficiente desviacion respecto del fondo. La tecnica resulta ser automatica en el sentido de que no hay necesidad de ajuste de parametros, dando resultados significativos en todos los casos. Incluso los objetos de tamano subpixel, que no pueden distinguirse a simple vista por el ojo humano en la imagen original, pueden ser detectados como anomalias. Ademas, se realiza una comparacion entre el enfoque propuesto, la popular tecnica RX y otros detectores tanto en su modalidad global como local. El metodo propuesto supera a los demas en determinados escenarios, demostrando su capacidad para reducir la proporcion de falsas alarmas. Los resultados del algoritmo automatico DAFT desarrollado, han demostrado la mejora en la definicion cualitativa de las anomalias espectrales que identifican a entidades diferentes en o bajo superficie, reemplazando para ello el modelo clasico de distribucion normal con un metodo robusto que contempla distintas alternativas desde el momento mismo de la adquisicion del dato hiperespectral. Para su consecucion ha sido necesario analizar la relacion entre parametros biofisicos, como la reflectancia y la emisividad de los materiales, y la distribucion espacial de entidades detectadas respecto de su entorno. Por ultimo, el algoritmo DAFT ha sido elegido como el mas adecuado para sensores que adquieren datos en el TIR, ya que presenta el mejor acuerdo con los datos de referencia, demostrando una gran eficacia computacional que facilita su implementacion en un sistema de cartografia que proyecte de forma automatica en un marco geografico de referencia las anomalias detectadas, lo que confirma un significativo avance hacia un sistema en lo que se denomina cartografia en tiempo real. The aim of this Thesis is to develop a specific methodology in order to be applied in automatic detection anomalies processes using hyperspectral data also called hyperspectral scenes, and to improve the classification processes. Several scenarios, areas and their relationship with surfaces and objects have been tested. The spectral characteristics of reflectance parameter and emissivity in the pattern recognition of urban materials in several hyperspectral scenes have also been tested. Spectral ranges of the visible-near infrared (VNIR), shortwave infrared (SWIR) and thermal infrared (TIR) from hyperspectral data cubes of AHS (Airborne Hyperspectral System), HyMAP Imaging Spectrometer, CASI (Compact Airborne Spectrographic Imager), AVIRIS (Airborne Visible Infrared Imaging Spectrometer), HYDICE (Hyperspectral Digital Imagery Collection Experiment) and MASTER (MODIS/ASTER Simulator) have been used in this research. It is assumed that there is not prior knowledge of the targets in anomaly detection. Thus, the pixels are automatically separated according to their spectral information, significantly differentiated with respect to a background, either globally for the full scene, or locally by the image segmentation. Several experiments on different scenarios have been designed, analyzing the behavior of the standard RX anomaly detector and different methods based on subspace, image projection and segmentation-based anomaly detection methods. Results and their consequences in unsupervised classification processes are discussed. Detection of spectral anomalies aims at extracting automatically pixels that show significant responses in relation of their surroundings. This Thesis deals with the unsupervised technique of target detection, also called anomaly detection. Since this technique assumes no prior knowledge about the target or the statistical characteristics of the data, the only available option is to look for objects that are differentiated from the background. Several methods have been developed in the last decades, allowing a better understanding of the relationships between the image dimensionality and the optimization of search procedures as well as the subpixel differentiation of the spectral mixture and its implications in anomalous responses. In other sense, image spectrometry has proven to be efficient in the characterization of materials, based on statistical methods using a specific reflection and absorption bands. Spectral configurations in the VNIR, SWIR and TIR have been successfully used for mapping materials in different urban scenarios. There has been an increasing interest in the use of high resolution data (both spatial and spectral) to detect small objects and to discriminate surfaces in areas with urban complexity. This has come to be known as target detection which can be either supervised or unsupervised. In supervised target detection, algorithms lean on prior knowledge, such as the spectral signature. The detection process for matching signatures is not straightforward due to the complications of converting data airborne sensor with material spectra in the ground. This could be further complicated by the large number of possible objects of interest, as well as uncertainty as to the reflectance or emissivity of these objects and surfaces. An important objective in this research is to establish relationships that allow linking spectral anomalies with what can be called informational anomalies and, therefore, identify information related to anomalous responses in some places rather than simply spotting differences from the background. The development in recent years of new hyperspectral sensors and techniques, widen the possibilities for applications in remote sensing of the Earth. Remote sensing systems measure and record electromagnetic disturbances that the surveyed objects induce in their surroundings, by means of different sensors mounted on airborne or space platforms. Map updating is important for management and decisions making people, because of the fast changes that usually happen in natural, urban and semi urban areas. It is necessary to optimize the methodology for obtaining the best from remote sensing techniques from hyperspectral data. The first problem with hyperspectral data is to reduce the dimensionality, keeping the maximum amount of information. Hyperspectral sensors augment considerably the amount of information, this allows us to obtain a better precision on the separation of material but at the same time it is necessary to calculate a bigger number of parameters, and the precision lowers with the increase in the number of bands. This is known as the Hughes effects (Bellman, 1957) . Hyperspectral imagery allows us to discriminate between a huge number of different materials however some land and urban covers are made up with similar material and respond similarly which produces confusion in the classification. The training and the algorithm used for mapping are also important for the final result and some properties of thermal spectrum for detecting land cover will be studied. In summary, this Thesis presents a new technique for anomaly detection in hyperspectral data called DAFT, as a PP's variant, based on dimensionality reduction by projecting anomalies or targets with unknown spectral signature to the background, in a range thermal spectrum wavelengths. The proposed methodology has been tested with hyperspectral images from different imaging spectrometers corresponding to several places or scenarios, therefore with different spectral background. The results show the benefits of the approach to the detection of a variety of targets whose spectral signatures have sufficient deviation in relation to the background. DAFT is an automated technique in the sense that there is not necessary to adjust parameters, providing significant results in all cases. Subpixel anomalies which cannot be distinguished by the human eye, on the original image, however can be detected as outliers due to the projection of the VNIR end members with a very strong thermal contrast. Furthermore, a comparison between the proposed approach and the well-known RX detector is performed at both modes, global and local. The proposed method outperforms the existents in particular scenarios, demonstrating its performance to reduce the probability of false alarms. The results of the automatic algorithm DAFT have demonstrated improvement in the qualitative definition of the spectral anomalies by replacing the classical model by the normal distribution with a robust method. For their achievement has been necessary to analyze the relationship between biophysical parameters such as reflectance and emissivity, and the spatial distribution of detected entities with respect to their environment, as for example some buried or semi-buried materials, or building covers of asbestos, cellular polycarbonate-PVC or metal composites. Finally, the DAFT method has been chosen as the most suitable for anomaly detection using imaging spectrometers that acquire them in the thermal infrared spectrum, since it presents the best results in comparison with the reference data, demonstrating great computational efficiency that facilitates its implementation in a mapping system towards, what is called, Real-Time Mapping.

Digital libraries for the preservation of research methods and associated artifacts

New digital artifacts are emerging in data-intensive science. For example, scientific workflows are executable descriptions of scientific procedures that define the sequence of computational steps in an automated data analysis, supporting reproducible research and the sharing and replication of best-practice and know-how through reuse. Workflows are specified at design time and interpreted through their execution in a variety of situations, environments, and domains. Hence it is essential to preserve both their static and dynamic aspects, along with the research context in which they are used. To achieve this, we propose the use of multidimensional digital objects (Research Objects) that aggregate the resources used and/or produced in scientific investigations, including workflow models, provenance of their executions, and links to the relevant associated resources, along with the provision of technological support for their preservation and efficient retrieval and reuse. In this direction, we specified a software architecture for the design and implementation of a Research Object preservation system, and realized this architecture with a set of services and clients, drawing together practices in digital libraries, preservation systems, workflow management, social networking and Semantic Web technologies. In this paper, we describe the backbone system of this realization, a digital library system built on top of dLibra.

Cooperative ITS communications architecture: the FOTsis project approach and beyond

With the continuous development in the fields of sensors, advanced data processing and communications, road transport oriented intelligent applications and services have reached a significant maturity and complexity. Cooperative ITS services, based on the idea of sharing accurate information among road entities, are currently being tested on a large scale by different initiatives. The field operational test (FOTsis) project contributes to the deployment environment with services that involve a significant number of entities out of the vehicle. This made necessary the specification of an architecture which, based on the ISO ITS station reference architecture for communications, could support the requirements of the services proposed in the project. During the project, internal implementation tests and external interoperability tests have resulted in the validation of the proposed architecture. At the same time, these tests have had as a result the awareness of areas in which the FOTsis architecture could be completed, mainly to take full advantage of all the emerging and foreseeable data sources which may be relevant in the road environment. In this study, the authors will outline an approach that, based on the current cooperative ITS architecture and the SmartCities and Internet Of Things (IoT) architectures, can provide a common convergence platform to maximise the information available for ITS purposes.

The Research Funding Service: a model for expanded library services

Traditionally, libraries have provided a modest amount of information about grants and funding opportunities to researchers in need of research funding. Ten years ago, the University of Washington (UW) Health Sciences Libraries and Information Center joined in a cooperative effort with the School of Medicine to develop a complete, library-based grant and funding service for health sciences researchers called the Research Funding Service. The library provided space, access to the library collection, equipment, and electronic resources, and the School of Medicine funded staff and operations. The range of services now includes individual consultation appointments, an extensive Web site, classes on funding database searching and writing grant applications, a discussion series that frequently hosts guest speakers, a monthly newsletter with funding opportunities of interest to the six health sciences schools, extensive files on funding sources, and referral services.

Perceptions of Usability and Usefulness in Digital Libraries

This paper provides an overview of a case study research that investigated the use of Digital Library (DL) resources in two undergraduate classes and explored faculty and students’ perceptions of educational digital libraries. This study found that students and faculty use academic DLs primarily for textual resources, but turn to the open Web for visual and multimedia resources. The study participants did not perceive academic libraries as a useful source of digital images and used search engines when searching for visual resources. The limited use of digital library resources for teaching and learning is associated with perceptions of usefulness and ease of use, especially if considered in a broader information landscape, in conjunction with other library information systems, and in the context of Web resources. The limited use of digital libraries is related to the following perceptions: 1) Library systems are not viewed as user-friendly, which in turn discourages potential users from trying DLs provided by academic libraries; 2) Academic libraries are perceived as places of primarily textual resources; perceptions of usefulness, especially in regard to relevance of content, coverage, and currency, seem to have a negative effect on user intention to use DLs, especially when searching for visual materials.