Aplicação do algoritmo Rough Sets em um Data Warehouse

This Project aims to develop methods for data classification in a Data Warehouse for decision-making purposes. We also have as another goal the reduction of an attribute set in a Data Warehouse, in which a given reduced set is capable of keeping the same properties of the original one. Once we achieve a reduced set, we have a smaller computational cost of processing, we are able to identify non-relevant attributes to certain kinds of situations, and finally we are also able to recognize patterns in the database that will help us to take decisions. In order to achieve these main objectives, it will be implemented the Rough Sets algorithm. We chose PostgreSQL as our data base management system due to its efficiency, consolidation and finally, it’s an open-source system (free distribution)

Estudo da implementação do Warehouse Management System em uma empresa produtora de embreagens

In the supply chain management there are several risk factors that must be mitigated to increase the flow of production and as a possible solution the literature cites the implementation of a warehouse management system, but this subject is few explored. This thesis has as main objective the study of the implementation of a warehouse management system in a company from the automotive sector that produces clutches. As results, are shown data of the characterization of items; as well as data and comparisons between disruptions in production reports due to lack of material before and after the implementation of WMS and is presented the result of a questionnaire applied to the involved on the implementation of the system, the results were associated with the risk factors on the implementation of the system studied on the literature review, and enumeration of the results that are not associated with any factors previously studied. And finally, the study is concluded and are recommended future studies related to the theme

Prototipo di un sistema data warehouse per le Università italiane basato su tecnologie semantiche

Tesi riguardante le differenze tra Semantic Web e Web Tradizionale

Data warehouse e cruscotto direzionale per l'analisi del personale in un'azienda di servizi

Obiettivo della tesi è la progettazione e lo sviluppo di un sistema di BI e di relativa reportistica per un'azienda di servizi. Il tutto realizzato mediante la suite Microsoft Business Intelligence.

Progettazione ed implementazione di un data warehouse di supporto alla profilazione dei consumi energetici domestici

Sviluppo e analisi di un dataset campione, composto da circa 3 mln di entry ed estratto da un data warehouse di informazioni riguardanti il consumo energetico di diverse smart home.

Progettazione di Data Warehouse di dati genomici su piattaforma Hadoop

Negli ultimi anni la biologia ha fatto ricorso in misura sempre maggiore all’informatica per affrontare analisi complesse che prevedono l’utilizzo di grandi quantità di dati. Fra le scienze biologiche che prevedono l’elaborazione di una mole di dati notevole c’è la genomica, una branca della biologia molecolare che si occupa dello studio di struttura, contenuto, funzione ed evoluzione del genoma degli organismi viventi. I sistemi di data warehouse sono una tecnologia informatica che ben si adatta a supportare determinati tipi di analisi in ambito genomico perché consentono di effettuare analisi esplorative e dinamiche, analisi che si rivelano utili quando si vogliono ricavare informazioni di sintesi a partire da una grande quantità di dati e quando si vogliono esplorare prospettive e livelli di dettaglio diversi. Il lavoro di tesi si colloca all’interno di un progetto più ampio riguardante la progettazione di un data warehouse in ambito genomico. Le analisi effettuate hanno portato alla scoperta di dipendenze funzionali e di conseguenza alla definizione di una gerarchia nei dati. Attraverso l’inserimento di tale gerarchia in un modello multidimensionale relativo ai dati genomici sarà possibile ampliare il raggio delle analisi da poter eseguire sul data warehouse introducendo un contenuto informativo ulteriore riguardante le caratteristiche dei pazienti. I passi effettuati in questo lavoro di tesi sono stati prima di tutto il caricamento e filtraggio dei dati. Il fulcro del lavoro di tesi è stata l’implementazione di un algoritmo per la scoperta di dipendenze funzionali con lo scopo di ricavare dai dati una gerarchia. Nell’ultima fase del lavoro di tesi si è inserita la gerarchia ricavata all’interno di un modello multidimensionale preesistente. L’intero lavoro di tesi è stato svolto attraverso l’utilizzo di Apache Spark e Apache Hadoop.

In need of psychiatric help--leave a message after the beep

Every day, a substantial proportion of the general population experiences the distressing and frightening signs of an upcoming psychiatric illness. The consequences can be enormous because severe psychiatric disorders typically cause the loss of the ability to work and often mean a long-term burden for both the patients and their families. Even though most developed countries have an exceptionally high density of general practitioners and psychiatrists in private practice, getting a mental health appointment and seeing a doctor is often very difficult for patients with acute psychiatric symptoms. This study aimed at quantifying the time delay involved in seeking medical attendance when psychiatric disorders begin to develop.

Development of a process model for the automatic miniload warehouse expansion

This paper provides an insight to the development of a process model for the essential expansion of the automatic miniload warehouse. The model is based on the literature research and covers four phases of a warehouse expansion: the preparatory phase, the current state analysis, the design phase and the decision making phase. In addition to the literature research, the presented model is based on a reliable data set and can be applicable with a reasonable effort to ensure the informed decision on the warehouse layout. The model is addressed to users who are usually employees of logistics department, and is oriented on the improvement of the daily business organization combined with the warehouse expansion planning.

DOES THE MESSAGE MATTER? ENHANCING PATIENT ADHERENCE THROUGH PERSUASIVE MESSAGES

To improve health and reduce costs, we need to encourage patients to make better healthcare decisions. Many informatics interventions are aimed at improving health outcomes by influencing patient behavior. However, we know little about how the content of a message in these interventions can influence a health-related decision. In this research we formulate a conceptual model to help explain and guide the design of “persuasive messages”, those which can change and influence patient behavior. We apply the conceptual model to design persuasive appointment reminder messages using humancentered design principles. Finally, we empirically test our hypotheses in a randomized controlled trial in order to determine the effectiveness of persuasive appointment reminders to reduce the number of missed appointments in a sample of 1016 subjects in a community health center. The results of the study confirm that reminder messages are effective in reducing missed appointment compared with no reminders (p=0.028). Further, reminder messages that incorporate heuristic cues such as authority, commitment, liking, and scarcity are more effective than reminder messages without such cues (p=0.006). However, the addition of systematic arguments or reasons for attending appointments have no effect on appointment adherence (p=0.646). The results of this research suggest that the content of reminder messages may be an important factor in helping to reduce missed appointments.

The Prophets of Israel : from the eigth to the fifth century ; their faith and their message

by Moses Buttenwieser