Enhancing RFID data quality and reliability

This thesis addressed the problem of data quality, reliability and energy consumption of networked Radio Frequency Identification systems for business intelligence applications decision making processes. The outcome of the research substantially improved the accuracy and reliability of RFID generated data as well as energy depletion thus prolonging RFID system lifetime.

Brazilian Students and Working Capital: An Analysis of Their Decisions When Using Virtual Market Business Games

This study aims to demonstrate that data from business games can be an important resource for improving efficiency and effectiveness of learning. The proposal presented here was developed from preliminary studies of data from Virtual Market games that pointed the possibility of identifying gaps in learning by analyzing the decisions of students. This proposal helps students to refine their learning processes and equips tutors with strategies for teaching and student assessment. The proposal also complements the group discussion and/or debriefing, which are widely used to enhance learning mediated by games. However, from a management perspective the model has the potential to be erroneous and miss opportunities, which cannot be detected because of the dependence on the characteristics of the individual, such as ability to communicate and work together. To illustrate the proposed technique, data sets from two business games were analyzed with the focus on managing working capital and it was found that students had difficulties managing this task. Similar trends were observed in all categories of students in the study-undergraduate, postgraduate and specialization. This discovery led us to the analysis of data for decisions made in the performance of the games, and it was determined that indicators could be developed that were capable of indentifying inconsistencies in the decisions. It was decided to apply some basic concepts of the finance management, such as management of the operational and non-operational expenditures, as well as production management concepts, such as the use of the production capacity. By analyzing the data from the Virtual Market games using the indicator concept, it was possible to detect the lack of domain knowledge of the students. Therefore, these indicators can be used to analyze the decisions of the players and guide them during the game, increasing their effectiveness and efficiency. As these indicators were developed from specific content, they can also be used to develop teaching materials to support learning. Viewed in this light, the proposal adds new possibilities for using business games in learning. In addition to the intrinsic learning that is achieved through playing the games, they also assist in driving the learning process. This study considers the applications and the methodology used.

Assessment of business incubators green performance: A framework and its application to Brazilian cases

The lack of proposals to evaluate the greening of business incubators or even of elementary discussions about the relations between incubators and the environment becomes apparent when researching this topic in the most prestigious scientific sources. To address this gap, this article reviews the literature on green management and smaller enterprises, business incubator performance and the greening of business incubators. This conceptual big-picture was used to identify variables relevant to the construction of a framework for assessing business incubators green performance. This framework was applied to six business incubators in Brazil. The results show the appropriated applicability of this framework. Furthermore, the empirical research led to the formulation of environmental maturity levels in order to classify business incubators performance. This paper seeks to offer a starting point for discussion and a proposal regarding the role of business incubators in a more sustainable society. © 2011 Elsevier Ltd. All rights reserved.

Particle competition and cooperation to prevent error propagation from mislabeled data in semi-supervised learning

Semi-supervised learning is applied to classification problems where only a small portion of the data items is labeled. In these cases, the reliability of the labels is a crucial factor, because mislabeled items may propagate wrong labels to a large portion or even the entire data set. This paper aims to address this problem by presenting a graph-based (network-based) semi-supervised learning method, specifically designed to handle data sets with mislabeled samples. The method uses teams of walking particles, with competitive and cooperative behavior, for label propagation in the network constructed from the input data set. The proposed model is nature-inspired and it incorporates some features to make it robust to a considerable amount of mislabeled data items. Computer simulations show the performance of the method in the presence of different percentage of mislabeled data, in networks of different sizes and average node degree. Importantly, these simulations reveals the existence of the critical points of the mislabeled subset size, below which the network is free of wrong label contamination, but above which the mislabeled samples start to propagate their labels to the rest of the network. Moreover, numerical comparisons have been made among the proposed method and other representative graph-based semi-supervised learning methods using both artificial and real-world data sets. Interestingly, the proposed method has increasing better performance than the others as the percentage of mislabeled samples is getting larger. © 2012 IEEE.

A model for analysing data portal performance: The biodiversity case

Currently, many museums, botanic gardens and herbariums keep data of biological collections and using computational tools researchers digitalize and provide access to their data using data portals. The replication of databases in portals can be accomplished through the use of protocols and data schema. However, the implementation of this solution demands a large amount of time, concerning both the transfer of fragments of data and processing data within the portal. With the growth of data digitalization in institutions, this scenario tends to be increasingly exacerbated, making it hard to maintain the records updated on the portals. As an original contribution, this research proposes analysing the data replication process to evaluate the performance of portals. The Inter-American Biodiversity Information Network (IABIN) biodiversity data portal of pollinators was used as a study case, which supports both situations: conventional data replication of records of specimen occurrences and interactions between them. With the results of this research, it is possible to simulate a situation before its implementation, thus predicting the performance of replication operations. Additionally, these results may contribute to future improvements to this process, in order to decrease the time required to make the data available in portals. © Rinton Press.

The SB-index and the HSB-index: efficient indices for spatial data warehouses

Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.

La gestione dei rifiuti urbani nel comune di Pisa

L’elaborazione di questa tesi è stata svolta con l’ausilio di strumenti di Business Intelligence. In particolare, si è dapprima alimentato un data warehouse territoriale, in cui sono stati inseriti, dopo averli elaborati, i dati messi a disposizione dagli osservatori territoriali nazionali e dall’azienda Geofor spa. A partire da questi, sono stati prodotti degli indicatori statistici e dei report, utili per evidenziare andamenti e trend di crescita di alcuni particolari indici. Il principale strumento utilizzato è StatPortal, un portale Web di Business Intelligence OLAP per la realizzazione di Data warehouse territoriali. L’argomento sarà approfondito nel capitolo sette, dedicato agli strumenti utilizzati, ma in breve, questo sistema consente di raccogliere, catalogare e condividere informazione statistica e geostatistica, nonché di produrre indicatori e reportistica. Il lavoro è organizzato come segue: inizialmente c’è una prima parte di definizione e classificazione dei rifiuti che ha l’obiettivo di permettere al lettore di inquadrare il tema e prendere coscienza del problema. Successivamente, è stata sviluppata una parte più storica, con una rapida analisi temporale per comprendere il “tipping point”, cioè il momento in cui i rifiuti hanno iniziato a essere percepiti come un problema per la comunità, concludendo con un accenno agli scenari attuali e futuri. In seguito, si è indirizzata l’attenzione sul panorama italiano, europeo e mondiale citando alcuni interessanti e originali esempi di efficienza nella gestione dei rifiuti, che potrebbero servire da spunto per qualche stakeholder nazionale. Si è poi introdotta quella che è la normativa vigente, sottolineando quali sono gli obiettivi che impone ed entro quali tempi dovranno essere raggiunti, elencando quindi i principi fondamentali del D.lgs.152/2006 e del D.lgs 36/2003. Continuando su questo filo logico, si è voluto introdurre al lettore, la questione dei Rifiuti Solidi Urbani (RSU) nel Comune di Pisa. Sono stati definiti: lo stato dell’arte dell’igiene urbana pisana, i sistemi implementati nella città con i vari pregi e difetti e quali sono state le azioni pratiche messe in atto dall’Amministrazione per far fronte al tema. Il capitolo sei rappresenta uno dei due punti focali dell’intero lavoro: il Rapporto sullo Stato dell’Ambiente della città di Pisa in tema di rifiuti urbani. Qui saranno analizzati i vari indici e report prodotti ad hoc con lo strumento Statportal appena menzionato, con lo scopo di segnalare evidenze e obiettivi dell’Amministrazione. Nel settimo capitolo si analizza la fase di progettazione del Data Warehouse. Sono elencati i passi fondamentali nella costruzione di un DW dimensionale, esponendone in primo luogo la specifica dei requisiti del progetto ed elencando per ognuno di essi le dimensioni, le misure e le aggregazioni relative. In seguito saranno descritti nel dettaglio la fase di progettazione concettuale e lo schema logico. In ultimo, sarà presentato l’altro punto focale di questa tesi, nonché la parte più interattiva: un portale web creato appositamente per il Comune con l’obiettivo di coinvolgere ed aiutare i cittadini nel conferimento dei rifiuti da loro prodotti. Si tratta di una sorta di manuale interattivo per individuare come eseguire una corretta differenziazione dei rifiuti. Lo scopo primario è quello di fare chiarezza alle utenze nella differenziazione, il che, in maniera complementare, dovrebbe incrementare la qualità del rifiuto raccolto, minimizzando i conferimenti errati. L’obiettivo principale di questo lavoro resta quindi il monitoraggio e l’analisi delle tecniche e dei processi di gestione dei rifiuti nel Comune di Pisa. Analogamente si vuole coinvolgere e suscitare l’interesse del maggior numero di persone possibile al tema della sostenibilità ambientale, rendendo consapevole il lettore che il primo passo verso un mondo più sostenibile spetta in primis a Noi che quotidianamente acquistiamo, consumiamo ed infine gettiamo via i residui senza troppo preoccuparci. Il fatto che anche in Italia, si stia sviluppando un senso civico e una forte responsabilizzazione verso l’ambiente da parte dei cittadini, fa ben sperare. Questo perché si è riusciti a imprimere il concetto che le soluzioni si ottengano impegnandosi in prima persona. E’ alla nostra comunità che si affida il dovere di non compromettere l’esistenza delle generazioni future, incaricandola del compito di ristabilire un equilibrio, ormai precario, tra umanità e ambiente, se non altro perché, come recita un vecchio proverbio Navajo: “il mondo non lo abbiamo in eredità dai nostri padri ma lo abbiamo in prestito dai nostri figli”.

Big data: il valore dei dati e applicazioni all'analisi strategica

Il presente lavoro di tesi tende a un duplice scopo: il primo è quello di fornire una accurata analisi tecnica, applicativa e culturale riguardante il vasto mondo dei big data e il secondo quello di trovare connessioni con l’analisi strategica verificando se e in quale modo i big data possano risultare una risorsa distintiva in campo aziendale. Nello specifico il primo capitolo presenta i big data nelle sue caratteristiche più importanti cercando di approfondire gli aspetti tecnici del fenomeno, le fonti di produzione dei dati, le metodologie principali di analisi e l’impatto sulla società. Il secondo capitolo descrive svariate applicazioni dei big data in campo aziendale concentrandosi sul rapporto tra questi e l’analisi strategica, non trascurando temi come il vantaggio competitivo e la business intelligence. Infine il terzo capitolo analizza la condizione attuale, il punto di vista italiano ed eventuali sviluppi futuri del fenomeno.

Realizzazione di un sistema di what-if analysis per analisi relative alla vendita e alla gestione dei premi a cliente

L’obiettivo della tesi, sviluppata presso l’azienda Onit Group s.r.l., è stato quello di realizzare un sistema d’analisi what-if che consenta di effettuare valutazioni economiche in maniera rapida, precisa, ed in totale autonomia. L’applicativo sviluppato, richiesto dalla direzione commerciale dall’azienda Orogel, ha il compito di assegnare percentuali di premio agli acquisti effettuati dai clienti su determinate famiglie di vendita. Il programma è il primo progetto di tipo data entry sviluppato nel reparto di Business Unit Data Warehouse e Business Intelligence di Onit e offre una duplice utilità. Da un lato semplifica la gestione dell’assegnamento dei premi annuali che ogni anno sono rinegoziati, su cui l’utente della direzione commerciale può fare delle stime sulla base dei premi definiti l’anno precedente. D’altra parte rendere la direzione commerciale di Orogel più autonoma offrendo all’utenza un unico ambiente su cui muoversi.

Progettazione e sviluppo di una soluzione Hadoop per il calcolo di Big Data Analytics

Il presente elaborato ha come oggetto la progettazione e lo sviluppo di una soluzione Hadoop per il Calcolo di Big Data Analytics. Nell'ambito del progetto di monitoraggio dei bottle cooler, le necessità emerse dall'elaborazione di dati in continua crescita, ha richiesto lo sviluppo di una soluzione in grado di sostituire le tradizionali tecniche di ETL, non pi�ù su�fficienti per l'elaborazione di Big Data. L'obiettivo del presente elaborato consiste nel valutare e confrontare le perfomance di elaborazione ottenute, da un lato, dal flusso di ETL tradizionale, e dall'altro dalla soluzione Hadoop implementata sulla base del framework MapReduce.

The German business and information technologies project

The Business and Information Technologies (BIT) project strives to reveal new insights into how modern IT impacts organizational structures and business practices using empirical methods. Due to its international scope, it allows for inter-country comparison of empirical results. Germany — represented by the European School of Management and Technologies (ESMT) and the Institute of Information Systems at Humboldt-Universität zu Berlin — joined the BIT project in 2006. This report presents the result of the first survey conducted in Germany during November–December 2006. The key results are as follows: • The most widely adopted technologies and systems in Germany are websites, wireless hardware and software, groupware/productivity tools, and enterprise resource planning (ERP) systems. The biggest potential for growth exists for collaboration and portal tools, content management systems, business process modelling, and business intelligence applications. A number of technological solutions have not yet been adopted by many organizations but also bear some potential, in particular identity management solutions, Radio Frequency Identification (RFID), biometrics, and third-party authentication and verification. • IT security remains on the top of the agenda for most enterprises: budget spending was increasing in the last 3 years. • The workplace and work requirements are changing. IT is used to monitor employees' performance in Germany, but less heavily compared to the United States (Karmarkar and Mangal, 2007).1 The demand for IT skills is increasing at all corporate levels. Executives are asking for more and better structured information and this, in turn, triggers the appearance of new decision-making tools and online technologies on the market. • The internal organization of companies in Germany is underway: organizations are becoming flatter, even though the trend is not as pronounced as in the United States (Karmarkar and Mangal, 2007), and the geographical scope of their operations is increasing. Modern IT plays an important role in enabling this development, e.g. telecommuting, teleconferencing, and other web-based collaboration formats are becoming increasingly popular in the corporate context. • The degree to which outsourcing is being pursued is quite limited with little change expected. IT services, payroll, and market research are the most widely outsourced business functions. This corresponds to the results from other countries. • Up to now, the adoption of e-business technologies has had a rather limited effect on marketing functions. Companies tend to extract synergies from traditional printed media and on-line advertising. • The adoption of e-business has not had a major impact on marketing capabilities and strategy yet. Traditional methods of customer segmentation are still dominating. The corporate identity of most organizations does not change significantly when going online. • Online sales channel are mainly viewed as a complement to the traditional distribution means. • Technology adoption has caused production and organizational costs to decrease. However, the costs of technology acquisition and maintenance as well as consultancy and internal communication costs have increased.

An Exploratory Study of Data Quality Management Practices in the ERP Software Systems Context

Quality data are not only relevant for successful Data Warehousing or Business Intelligence applications; they are also a precondition for efficient and effective use of Enterprise Resource Planning (ERP) systems. ERP professionals in all kinds of businesses are concerned with data quality issues, as a survey, conducted by the Institute of Information Systems at the University of Bern, has shown. This paper demonstrates, by using results of this survey, why data quality problems in modern ERP systems can occur and suggests how ERP researchers and practitioners can handle issues around the quality of data in an ERP software Environment.

Monitorización inteligente de redes de comunicación

El avance tecnológico de los últimos años ha aumentado la necesidad de guardar enormes cantidades de datos de forma masiva, llegando a una situación de desorden en el proceso de almacenamiento de datos, a su desactualización y a complicar su análisis. Esta situación causó un gran interés para las organizaciones en la búsqueda de un enfoque para obtener información relevante de estos grandes almacenes de datos. Surge así lo que se define como inteligencia de negocio, un conjunto de herramientas, procedimientos y estrategias para llevar a cabo la “extracción de conocimiento”, término con el que se refiere comúnmente a la extracción de información útil para la propia organización. Concretamente en este proyecto, se ha utilizado el enfoque Knowledge Discovery in Databases (KDD), que permite lograr la identificación de patrones y un manejo eficiente de las anomalías que puedan aparecer en una red de comunicaciones. Este enfoque comprende desde la selección de los datos primarios hasta su análisis final para la determinación de patrones. El núcleo de todo el enfoque KDD es la minería de datos, que contiene la tecnología necesaria para la identificación de los patrones mencionados y la extracción de conocimiento. Para ello, se utilizará la herramienta RapidMiner en su versión libre y gratuita, debido a que es más completa y de manejo más sencillo que otras herramientas como KNIME o WEKA. La gestión de una red engloba todo el proceso de despliegue y mantenimiento. Es en este procedimiento donde se recogen y monitorizan todas las anomalías ocasionadas en la red, las cuales pueden almacenarse en un repositorio. El objetivo de este proyecto es realizar un planteamiento teórico y varios experimentos que permitan identificar patrones en registros de anomalías de red. Se ha estudiado el repositorio de MAWI Lab, en el que se han almacenado anomalías diarias. Se trata de buscar indicios característicos anuales detectando patrones. Los diferentes experimentos y procedimientos de este estudio pretenden demostrar la utilidad de la inteligencia de negocio a la hora de extraer información a partir de un almacén de datos masivo, para su posterior análisis o futuros estudios. ABSTRACT. The technological progresses in the recent years required to store a big amount of information in repositories. This information is often in disorder, outdated and needs a complex analysis. This situation has caused a relevant interest in investigating methodologies to obtain important information from these huge data stores. Business intelligence was born as a set of tools, procedures and strategies to implement the "knowledge extraction". Specifically in this project, Knowledge Discovery in Databases (KDD) approach has been used. KDD is one of the most important processes of business intelligence to achieve the identification of patterns and the efficient management of the anomalies in a communications network. This approach includes all necessary stages from the selection of the raw data until the analysis to determine the patterns. The core process of the whole KDD approach is the Data Mining process, which analyzes the information needed to identify the patterns and to extract the knowledge. In this project we use the RapidMiner tool to carry out the Data Mining process, because this tool has more features and is easier to use than other tools like WEKA or KNIME. Network management includes the deployment, supervision and maintenance tasks. Network management process is where all anomalies are collected, monitored, and can be stored in a repository. The goal of this project is to construct a theoretical approach, to implement a prototype and to carry out several experiments that allow identifying patterns in some anomalies records. MAWI Lab repository has been selected to be studied, which contains daily anomalies. The different experiments show the utility of the business intelligence to extract information from big data warehouse.