Computer-aided system for morphometric mandibular index computation (Using dental panoramic radiographs)

Objective: We propose and validate a computer aided system to measure three different mandibular indexes: cortical width, panoramic mandibular index and, mandibular alveolar bone resorption index. Study Design: Repeatability and reproducibility of the measurements are analyzed and compared to the manual estimation of the same indexes. Results: The proposed computerized system exhibits superior repeatability and reproducibility rates compared to standard manual methods. Moreover, the time required to perform the measurements using the proposed method is negligible compared to perform the measurements manually. Conclusions: We have proposed a very user friendly computerized method to measure three different morphometric mandibular indexes. From the results we can conclude that the system provides a practical manner to perform these measurements. It does not require an expert examiner and does not take more than 16 seconds per analysis. Thus, it may be suitable to diagnose osteoporosis using dental panoramic radiographs

Calculation analysis of energy saving tools for fan and pump applications

This thesis analyses the calculation of FanSave and PumpSave energy saving tools calculation. With these programs energy consumption of variable speed drive control for fans and pumps can be compared to other control methods. With FanSave centrifugal and axial fans can be examined and PumpSave deals with centrifugal pumps. By means of these programs also suitable frequency converter can be chosen from the ABB collection. Programs need as initial values information about the appliances like amount of flow and efficiencies. Operation time is important factor when calculating the annual energy consumption and information about it are the length and profile. Basic theory related to fans and pumps is introduced without more precise instructions for dimensioning. FanSave and PumpSave contain various methods for flow control. These control methods are introduced in the thesis based on their operational principles and suitability. Also squirrel cage motor and frequency converter are introduced because of their close involvement to fans and pumps. Second part of the thesis contains comparison between results of FanSave’s and PumpSave’s calculation and performance curve based calculation. Also laboratory tests were made with centrifugal and axial fan and also with centrifugal pump. With the results from this thesis the calculation of these programs can be adjusted to be more accurate and also some new features can be added.

On the computation of reducible invariant tori on a parallel computer

We present an algorithm for the computation of reducible invariant tori of discrete dynamical systems that is suitable for tori of dimensions larger than 1. It is based on a quadratically convergent scheme that approximates, at the same time, the Fourier series of the torus, its Floquet transformation, and its Floquet matrix. The Floquet matrix describes the linearization of the dynamics around the torus and, hence, its linear stability. The algorithm presents a high degree of parallelism, and the computational effort grows linearly with the number of Fourier modes needed to represent the solution. For these reasons it is a very good option to compute quasi-periodic solutions with several basic frequencies. The paper includes some examples (flows) to show the efficiency of the method in a parallel computer. In these flows we compute invariant tori of dimensions up to 5, by taking suitable sections.

Impact of quality improvement tools on the performance of firms using different quality management systems

This study compares the impact of quality management tools on the performance of organisations utilising the ISO 9001:2000 standard as a basis for a quality-management system band those utilising the EFQM model for this purpose. A survey is conducted among 107 experienced and independent quality-management assessors. The study finds that organisations with qualitymanagement systems based on the ISO 9001:2000 standard tend to use general-purpose qualitative tools, and that these do have a relatively positive impact on their general performance. In contrast, organisations adopting the EFQM model tend to use more specialised quantitative tools, which produce significant improvements in specific aspects of their performance. The findings of the study will enable organisations to choose the most effective quality-improvement tools for their particular quality strategy

Communication challenges in virtual teams – a case study of implementing computer-mediated communication technologies in inter-organisational virtual teams

This thesis seeks to answer, if communication challenges in virtual teams can be overcome with the help of computer-mediated communication. Virtual teams are becoming more common work method in many global companies. In order for virtual teams to reach their maximum potential, effective asynchronous and synchronous methods for communication are needed. The thesis covers communication in virtual teams, as well as leadership and trust building in virtual environments with the help of CMC. First, the communication challenges in virtual teams are identified by using a framework of knowledge sharing barriers in virtual teams by Rosen et al. (2007) Secondly, the leadership and trust in virtual teams are defined in the context of CMC. The performance of virtual teams is evaluated in the case study by exploiting these three dimensions. With the help of a case study of two virtual teams, the practical issues related to selecting and implementing communication technologies as well as overcoming knowledge sharing barriers is being discussed. The case studies involve a complex inter-organisational setting, where four companies are working together in order to maintain a new IT system. The communication difficulties are related to inadequate communication technologies, lack of trust and the undefined relationships of the stakeholders and the team members. As a result, it is suggested that communication technologies are needed in order to improve the virtual team performance, but are not however solely capable of solving the communication challenges in virtual teams. In addition, suitable leadership and trust between team members are required in order to improve the knowledge sharing and communication in virtual teams.

New kernel functions and learning methods for text and data mining

Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

Development of a systematic computer vision-based method to analyse and compare images of false identity documents for forensic intelligence purposes-Part I: acquisition, calibration and validation issues

Following their detection and seizure by police and border guard authorities, false identity and travel documents are usually scanned, producing digital images. This research investigates the potential of these images to classify false identity documents, highlight links between documents produced by a same modus operandi or same source, and thus support forensic intelligence efforts. Inspired by previous research work about digital images of Ecstasy tablets, a systematic and complete method has been developed to acquire, collect, process and compare images of false identity documents. This first part of the article highlights the critical steps of the method and the development of a prototype that processes regions of interest extracted from images. Acquisition conditions have been fine-tuned in order to optimise reproducibility and comparability of images. Different filters and comparison metrics have been evaluated and the performance of the method has been assessed using two calibration and validation sets of documents, made up of 101 Italian driving licenses and 96 Portuguese passports seized in Switzerland, among which some were known to come from common sources. Results indicate that the use of Hue and Edge filters or their combination to extract profiles from images, and then the comparison of profiles with a Canberra distance-based metric provides the most accurate classification of documents. The method appears also to be quick, efficient and inexpensive. It can be easily operated from remote locations and shared amongst different organisations, which makes it very convenient for future operational applications. The method could serve as a first fast triage method that may help target more resource-intensive profiling methods (based on a visual, physical or chemical examination of documents for instance). Its contribution to forensic intelligence and its application to several sets of false identity documents seized by police and border guards will be developed in a forthcoming article (part II).

Identifying Specific Cues and Contexts Related to Smoking Craving for the Development of Effective Virtual Environments

Craving is considered the main variable associated with relapse after smoking cessation. Cue Exposure Therapy (CET) consists of controlled and repeated exposure to drug-related cues with the aim of extinguishing craving responses. Some virtual reality (VR) environments, such as virtual bars or parties, have previously shown their efficacy as tools for eliciting smoking craving. However, in order to adapt this technology to smoking cessation interventions, there is a need for more diverse environments that enhance the probability of generalization of extinction in real life. The main objective of this study was to identify frequent situations that produce smoking craving, as well as detecting specific craving cues in those contexts. Participants were 154 smokers who responded to an ad hoc self-administered inventory for assessing craving level in 12 different situations. Results showed that having a drink in a bar/pub at night, after having lunch/dinner in a restaurant and having a coffee in a cafe or after lunch/dinner at home were reported as the most craving-inducing scenarios. Some differences were found with regard to participants' gender, age, and number of cigarettes smoked per day. Females, younger people, and heavier smokers reported higher levels of craving in most situations. In general, the most widely cited specific cues across the contexts were people smoking, having a coffee, being with friends, and having finished eating. These results are discussed with a view to their consideration in the design of valid and reliable VR environments that could be used in the treatment of nicotine addicts who wish to give up smoking.

Disseny i implementació d'un programari d'adquisició de dades de la producció d'una línia automàtica de palets

This thesis presents a software that allows data acquisition production process, in this case, an automatic pallet nailing line. The recording of these data will enable them to make a track and analyze them later, either with the analytical tools of the application or by the transfer of such data to an Excel sheet or database. The programming language has been developed made by Ladder for the application in the PLC that controls the line of nailing. Control pages for the HMI application that monitors the process. Finally, the Visual Basic language for the production department computer application. To extract production variables from the process, the developed software communicates with the network formed by the PLC and the HMI terminal which stores and control the process using the Modbus TCP/IP protocol.

Plataforma "Cloud Computing" per la comunicació entre pares i professors (Saas)

El projecte que es presenta a continuació és el resultat fruit de la detecció d’un problema de comunicació entre les escoles (sobretot de primària) i el pares dels alumnes que hi cursen els estudis, i la necessitat de trobar-hi una solució. Amb aquesta premissa, i tenint en compte que la tecnologia cada vegada ens ofereix més i millors eines per gestionar les nostres necessitats, es porta a terme la construcció d’un servei al núvol (Saas) capaç de cobrir aquestes necessitats i de fer-ho de la manera més senzilla i eficient possible. La plataforma Aula és un servei on tant professors com pares dels alumnes poden comunicar-se i consultar la informació referent als seus alumnes (en el cas del professors), i dels seus fills (en el cas dels pares/tutors). La solució adoptada ha de ser capaç de funcionar sobre qualsevol aparell (ordinador, tablet o mòbil) i en qualsevol lloc on hi hagi connexió a Internet. No s’ha de realitzar cap tipus d’instal·lació un cop el sistema estigui funcionant, i s’hi podran registrar tants centres com siguin necessaris, així com professionals i pares dels alumnes. També s’ha valorat el manteniment mínim del sistema i la seva escalabilitat, per poder fer front a diferents volums de dades. Així doncs, el projecte Aula es presenta com una solució per gestionar el dia a dia dels professors i alumnes, però que no pretén ser substitut de cap altre sistema de gestió que pugui tenir el centre.

Validation of a computer-assisted system on classifying lower third molars

Objectives: The present study evaluates the reliability of the Radio Memory® software (Radio Memory; Belo Horizonte,Brasil.) on classifying lower third molars, analyzing intra- and interexaminer agreement of the results. Study Design: An observational, descriptive study of 280 lower third molars was made. The corresponding orthopantomographs were analyzed by two examiners using the Radio Memory® software. The exam was repeated 30 days after the first observation by each examiner. Both intra- and interexaminer agreement were determined using the SPSS v 12.0 software package for Windows (SPSS; Chicago, USA). Results: Intra- and interexaminer agreement was shown for both the Pell & Gregory and the Winter classifications, p<0.01, with 99% significant correlation between variables in all the cases. Conclusions: The use of Radio Memory® software for the classification of lower third molars is shown to be a valid alternative to the conventional method (direct evaluation on the orthopantomograph), for both clinical and investigational applications.

Tools and data services registry: a community effort to document bioinformatics resources.

Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand.Here we present a community-driven curation effort, supported by ELIXIR-the European infrastructure for biological information-that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners.As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.