A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

Knowledge assisted data management and retrieval in multimedia database systems

With the proliferation of multimedia data and ever-growing requests for multimedia applications, there is an increasing need for efficient and effective indexing, storage and retrieval of multimedia data, such as graphics, images, animation, video, audio and text. Due to the special characteristics of the multimedia data, the Multimedia Database management Systems (MMDBMSs) have emerged and attracted great research attention in recent years. Though much research effort has been devoted to this area, it is still far from maturity and there exist many open issues. In this dissertation, with the focus of addressing three of the essential challenges in developing the MMDBMS, namely, semantic gap, perception subjectivity and data organization, a systematic and integrated framework is proposed with video database and image database serving as the testbed. In particular, the framework addresses these challenges separately yet coherently from three main aspects of a MMDBMS: multimedia data representation, indexing and retrieval. In terms of multimedia data representation, the key to address the semantic gap issue is to intelligently and automatically model the mid-level representation and/or semi-semantic descriptors besides the extraction of the low-level media features. The data organization challenge is mainly addressed by the aspect of media indexing where various levels of indexing are required to support the diverse query requirements. In particular, the focus of this study is to facilitate the high-level video indexing by proposing a multimodal event mining framework associated with temporal knowledge discovery approaches. With respect to the perception subjectivity issue, advanced techniques are proposed to support users' interaction and to effectively model users' perception from the feedback at both the image-level and object-level.

An Examination of Current Approaches to Integrative Indigenous and Western Knowledge System Implementation in Water Research and Management: A Case Study Encompassing the Colonized Geographies of Canada, Australia, New Zealand, and the United States

The commodification of natural resources and the pursuit of continuous growth has resulted in environmental degradation, depletion, and disparity in access to these life-sustaining resources, including water. Utility-based objectification and exploitation of water in some societies has brought us to the brink of crisis through an apathetic disregard for present and future generations. The ongoing depletion and degradation of the world’s water sources, coupled with a reliance on Western knowledge and the continued omission of Indigenous knowledge to manage our relationship with water has unduly burdened many, but particularly so for Indigenous communities. The goal of my thesis research is to call attention to and advance the value and validity of using both Indigenous and Western knowledge systems (also known as Two-Eyed Seeing) in water research and management to better care for water. To achieve this goal, I used a combined systematic and realist review method to identify and synthesize the peer-reviewed, integrative water literature, followed by semi-structured interviews with first authors of the exemplars from the included literature to identify the challenges and insights that researchers have experienced in conducting integrative water research. Findings suggest that these authors recognize that many previous attempts to integrate Indigenous knowledges have been tokenistic rather than meaningful, and that new methods for knowledge implementation are needed. Community-based participatory research methods, and the associated tenets of balancing power, fostering trust, and community ownership over the research process, emerged as a pathway towards the meaningful implementation of Indigenous and Western knowledge systems. Data also indicate that engagement and collaborative governance structures developed from a position of mutual respect are integral to the realization of a given project. The recommendations generated from these findings offer support for future Indigenous-led research and partnerships through the identification and examination of approaches that facilitate the meaningful implementation of Indigenous and Western knowledge systems in water research and management. Asking Western science questions and seeking Indigenous science solutions does not appear to be working; instead, the co-design of research projects and asking questions directed at the problem rather than the solution better lends itself to the strengths of Indigenous science.

BUILDING EFFICIENT AND COST-EFFECTIVE CLOUD-BASED BIG DATA MANAGEMENT SYSTEMS

In today’s big data world, data is being produced in massive volumes, at great velocity and from a variety of different sources such as mobile devices, sensors, a plethora of small devices hooked to the internet (Internet of Things), social networks, communication networks and many others. Interactive querying and large-scale analytics are being increasingly used to derive value out of this big data. A large portion of this data is being stored and processed in the Cloud due the several advantages provided by the Cloud such as scalability, elasticity, availability, low cost of ownership and the overall economies of scale. There is thus, a growing need for large-scale cloud-based data management systems that can support real-time ingest, storage and processing of large volumes of heterogeneous data. However, in the pay-as-you-go Cloud environment, the cost of analytics can grow linearly with the time and resources required. Reducing the cost of data analytics in the Cloud thus remains a primary challenge. In my dissertation research, I have focused on building efficient and cost-effective cloud-based data management systems for different application domains that are predominant in cloud computing environments. In the first part of my dissertation, I address the problem of reducing the cost of transactional workloads on relational databases to support database-as-a-service in the Cloud. The primary challenges in supporting such workloads include choosing how to partition the data across a large number of machines, minimizing the number of distributed transactions, providing high data availability, and tolerating failures gracefully. I have designed, built and evaluated SWORD, an end-to-end scalable online transaction processing system, that utilizes workload-aware data placement and replication to minimize the number of distributed transactions that incorporates a suite of novel techniques to significantly reduce the overheads incurred both during the initial placement of data, and during query execution at runtime. In the second part of my dissertation, I focus on sampling-based progressive analytics as a means to reduce the cost of data analytics in the relational domain. Sampling has been traditionally used by data scientists to get progressive answers to complex analytical tasks over large volumes of data. Typically, this involves manually extracting samples of increasing data size (progressive samples) for exploratory querying. This provides the data scientists with user control, repeatable semantics, and result provenance. However, such solutions result in tedious workflows that preclude the reuse of work across samples. On the other hand, existing approximate query processing systems report early results, but do not offer the above benefits for complex ad-hoc queries. I propose a new progressive data-parallel computation framework, NOW!, that provides support for progressive analytics over big data. In particular, NOW! enables progressive relational (SQL) query support in the Cloud using unique progress semantics that allow efficient and deterministic query processing over samples providing meaningful early results and provenance to data scientists. NOW! enables the provision of early results using significantly fewer resources thereby enabling a substantial reduction in the cost incurred during such analytics. Finally, I propose NSCALE, a system for efficient and cost-effective complex analytics on large-scale graph-structured data in the Cloud. The system is based on the key observation that a wide range of complex analysis tasks over graph data require processing and reasoning about a large number of multi-hop neighborhoods or subgraphs in the graph; examples include ego network analysis, motif counting in biological networks, finding social circles in social networks, personalized recommendations, link prediction, etc. These tasks are not well served by existing vertex-centric graph processing frameworks whose computation and execution models limit the user program to directly access the state of a single vertex, resulting in high execution overheads. Further, the lack of support for extracting the relevant portions of the graph that are of interest to an analysis task and loading it onto distributed memory leads to poor scalability. NSCALE allows users to write programs at the level of neighborhoods or subgraphs rather than at the level of vertices, and to declaratively specify the subgraphs of interest. It enables the efficient distributed execution of these neighborhood-centric complex analysis tasks over largescale graphs, while minimizing resource consumption and communication cost, thereby substantially reducing the overall cost of graph data analytics in the Cloud. The results of our extensive experimental evaluation of these prototypes with several real-world data sets and applications validate the effectiveness of our techniques which provide orders-of-magnitude reductions in the overheads of distributed data querying and analysis in the Cloud.

3D Surveying and Data Management towards the Realization of a Knowledge System for Cultural Heritage

The research activities involved the application of the Geomatic techniques in the Cultural Heritage field, following the development of two themes: Firstly, the application of high precision surveying techniques for the restoration and interpretation of relevant monuments and archaeological finds. The main case regards the activities for the generation of a high-fidelity 3D model of the Fountain of Neptune in Bologna. In this work, aimed to the restoration of the manufacture, both the geometrical and radiometrical aspects were crucial. The final product was the base of a 3D information system representing a shared tool where the different figures involved in the restoration activities shared their contribution in a multidisciplinary approach. Secondly, the arrangement of 3D databases for a Building Information Modeling (BIM) approach, in a process which involves the generation and management of digital representations of physical and functional characteristics of historical buildings, towards a so-called Historical Building Information Model (HBIM). A first application was conducted for the San Michele in Acerboli’s church in Santarcangelo di Romagna. The survey was performed by the integration of the classical and modern Geomatic techniques and the point cloud representing the church was used for the development of a HBIM model, where the relevant information connected to the building could be stored and georeferenced. A second application regards the domus of Obellio Firmo in Pompeii, surveyed by the integration of the classical and modern Geomatic techniques. An historical analysis permitted the definitions of phases and the organization of a database of materials and constructive elements. The goal is the obtaining of a federate model able to manage the different aspects: documental, analytic and reconstructive ones.

The BRAzilian Seismographic Integrated Systems (BRASIS): infrastructure and data management

In geophysics and seismology, raw data need to be processed to generate useful information that can be turned into knowledge by researchers. The number of sensors that are acquiring raw data is increasing rapidly. Without good data management systems, more time can be spent in querying and preparing datasets for analyses than in acquiring raw data. Also, a lot of good quality data acquired at great effort can be lost forever if they are not correctly stored. Local and international cooperation will probably be reduced, and a lot of data will never become scientific knowledge. For this reason, the Seismological Laboratory of the Institute of Astronomy, Geophysics and Atmospheric Sciences at the University of Sao Paulo (IAG-USP) has concentrated fully on its data management system. This report describes the efforts of the IAG-USP to set up a seismology data management system to facilitate local and international cooperation.

International tourists and road safety in Australia: developing a national research and management programme

Motor vehicle crashes are the leading cause of injury death for international tourists. This makes road safety an important issue for tourism authorities. Unfortunately, as it is in other areas of tourist health, the common response from the travel and tourism industry is to remain silent about this problem and to leave any mishaps in the hands of insurers. At the same time, but for different reasons, international tourists are not usually targeted for road safety initiatives by transport authorities. Given that there are considerable 'hidden' costs associated with international tourists and motor vehicle crashes, the topic should be of concern to both tourism and transport groups. This paper examines issues concerned with driving in unfamiliar surroundings for international visitors in Australia, and proposes a national research and management programme to guide policy and planning in the area. (C) 1999 Elsevier Science Ltd. All rights reserved.

Evaluation and optimization of a session-based middleware for data management

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

Cellular DBMS : customizable and autonomous data management using a RISC-style architecture

Magdeburg, Univ., Fak. für Informatik, Diss., 2011

Fishery statistics of the United States / prepared by Data Management and Statistics Division.

1975

ODiSEA: International Registry on Research Data

El artículo revisa los temas principales en la preservación y reuso de los datos de investigación (beneficios, ciclo de vida, proyectos, normativas ) e identifica la falta de un registro mundial de bancos, repositorios y bibliotecas de datos. Expone la creación de una herramienta web que recoja este tipo de depósitos y los clasifique por áreas disciplinares: ODiSEA International Registry on Research Data. Ofrecemos resultados sobre número y tipología temática de este tipo de depósitos a escala mundial. Esta aportación facilita el descubrimiento de nuevos conjuntos de datos cuya recombinación desde una perspectiva multidisciplinar fomentará la innovación y la rentabilidad de la inversión en ciencia.

Order-flow Standardization with Product Data Management Ideology

Tämän diplomityön päämääränä oli kuvata tilaus-toimitusprosessin eri toimintojen työnkulku, kun tuotetiedonhallintajärjestelmä on osa työympäristöä. Työn teoreettisessa osassa tarkasteltiin liiketoimintaprosessien uudistamista ja prosessien määrittämistä sekä esiteltiin tuotetiedonhallinnan (PDM) keskeiset osa-alueet. Kohdeyrityksen tausta ja strategiat esiteltiin, minkä jälkeen muutoksia arvioitiin suhteessa teoriaosuuden tuloksiin. Nykyisten toimintatapojen määrittämistä varten haastateltiin henkilöitä jokaisesta tilaus-toimitusprosessin vaiheesta tuotantoyksikön sisällä. Lopuksi kuvattiin yrityksen tuotetiedonhallintaperiaatteet ja määritettiin työnkulku prosessin eri vaiheissa. Samalla kuin uusi tuotetiedonhallintajärjestelmä otetaan käyttöön, on yrityksessä omaksuttava tuotetiedonhallinnan ajatusmalli. Tuoterakenteen hallinta jakautuu nyt eri toimintojen kesken, jolloin suunnittelun rakenne, tuotannon rakenne ja huoltorakenne ovat eri ihmisten vastuulla. Näiden eri rakenteiden konfigurointi tilaus-toimitus prosessin aikana määrää missä järjestyksessä toiminnot on suoritettava eri järjestelmien välillä. Monikansallinen suunnitteluorganisaatio on myös otettava huomioon tilauksenkulun aikana. Tuotetiedonhallintajärjestelmää käytetään yhdessä tuttujen suunnitteluohjelmien sekä toiminnanohjausjärjestelmän (ERP) kanssa. Työnkulkukaaviossa määritellään koko yritystä koskeva malli siitä, miten ja missä järjestyksessä tehtävät on suoritettava eri järjestelmissä tilaus-toimitus prosessin aikana. Tässä työssä tutkittiin tuotteen määrittelyn ja suunnittelutiedon hallinnan kannalta oleellisimmat tilaus-toimitusprosessiin kuuluvat toiminnot; myynti, myynnin tuki, tuotannon ohjaus, sovellussuunnittelu ja dokumentointi. Tulevaisuudessa on suositeltavaa pohtia tuotetiedonhallintajärjestelmän käyttöönottoa myös tuotannossa ja ostoissa. Tilaus-toimitusprosessiin liittyvät kehitysmahdollisuudet kannattaisi seuraavaksi kohdistaa tilauksen määrittelyvaiheeseen myyjä-asiakas rajapinnassa, jossa tehdyt virheet kertautuvat jokaisessa prosessin vaiheessa.

El plan de lengua y cohesión social en Catañunya: primeros datos de una investigación = Language and Social Cohesion Plan in Catalonia: Initial research data

Los programas de inmersión lingüística han constituido y constituyen dentro del Sistema Educativo catalánla principal forma para que el alumnado de lengua familiar no-catalana aprenda una nueva lengua, el catalán,sin que, en su proceso de aprendizaje, vea mermado ni el desarrollo de su propia lengua ni su rendimientoacadémico. El éxito de la inmersión lingüística en las décadas anteriores ha sido frecuentemente utilizado comouno de los argumentos orientativos para justificar la política lingüística que se sigue en la escolarización de lainfancia extranjera. Sin embargo, los resultados obtenidos por investigaciones recientes parece que no avalanempíricamente dicho argumento. Este artículo analiza dichos resultados y expone, a partir del Plan para laLengua y Cohesión Social puesto en marcha por el Departamento de Educación de la Generalitat de Cataluña,cuáles son los retos que se presentan a su Sistema Educativo dentro del nuevo marco que supone el aumento de ladiversidad cultural y lingüística en la actual sociedad catalana

Recent research data on the removal of pharmaceuticals from sewage treatment plants (STP)

Pharmaceutical compounds have been detected in sewage treatment plant (STP) effluents, surface waters and, less frequently, in groundwater and drinking water, all over the world. Different sources are responsible for their appearance in the aquatic environment, however, it is widely accepted that the main sources of this type of pollutant are STP effluents. The adverse effects of pharmaceuticals in the environment include aquatic toxicity, development of resistance in pathogenic bacteria, genotoxicity and endocrine disruption. Thus, the discharge of these compounds to the environment in STP effluents should be minimized.

Sukupolvenvaihdos yrityskauppana Case: Global Research & Data Services

Sukupolvenvaihdoksella tarkoitetaan yrityksen omistajasuhteiden muutoksia. Siinä yritys siirretään omistajan elinaikana tai se siirtyy hänen kuoltuaan henkilölle, joka jatkaa yrityksen toimintaa. Suomessa on lähivuosina odotettavissa 60–80.000 sukupolvenvaihdosta. Vaihdosten onnistuminen ei ole itsestäänselvyys, sillä yleinen ongelma näyttäisi olevan, että sukupolvenvaihdosta tarvitsevia yrityksiä on enemmän kuin sopivia jatkajia. Sukupolvenvaihdosten onnistuminen on merkittävä lähivuosien yhteiskunnallinen kysymys sekä yritysten liiketoiminnan jatkuvuuden että työpaikkojen säilymisen kannalta. Tällä hetkellä epäonnistuneet sukupolvenvaihdokset maksavat valtiolle noin 1,25 miljardia euroa eikä Suomella ole varaa menettää yhtään yritystä. Sukupolvenvaihdos on ajankohtainen asia myös tämän tutkimuksen case-yrityksessä, Global Research & Data Services:ssa. Yrityksen toimialana on markkinatutkimus. Tutkimuksia tehdään eri toimialoilta ja eri maista. Vaihdos on tarkoitus suorittaa kevään/kesän 2010 aikana ja se on tarkoitus toteuttaa yrityskauppana. Tässä tutkimuksessa on tarkoituksena selvittää mm., mitä eri vaihtoehtoja yrityksellä on toteuttaa sukupolvenvaihdos yrityskauppana, mitä tulee ottaa huomioon, miten kauppaa tulisi valmistella ja mitkä ovat mahdolliset rahoituslähteet. Tutkimuksen laatimisessa käytettiin apuna valmiina olevaa materiaalia, niin kirjoja kuin Internet-lähteitäkin. Tutkimuksen toisessa luvussa on käsitelty sukupolvenvaihdosta yleisesti käsitteenä sekä tämän hetkistä tilannetta Suomessa. Kolmannessa luvussa on esitelty tutkimuksen case-yritys. Neljännessä luvussa on esitelty sukupolvenvaihdoksen juridiset toteutusmallit lyhyesti. Tutkimuksen viidennessä luvussa on keskitytty tutkimuksen ydinasiaan eli sukupolvenvaihdoksen suorittamiseen yrityskauppana. Käsiteltyjä aiheita ovat mm. yrityksen valmistaminen vaihdosta varten, yrityksen arvon määritys ja yrityskaupan rahoitusvaihtoehdot. Asioita on käsitelty niin yleisesti kuin case-yrityksen tilanne huomioiden. Viimeisessä luvussa on tutkimuksen yhteenveto.