Development of a New Process for Determining Design Year Traffic Demands, TR-528, 2007

Researchers should continuously ask how to improve the models we rely on to make financial decisions in terms of the planning, design, construction, and maintenance of roadways. This project presents an alternative tool that will supplement local decision making but maintain a full appreciation of the complexity and sophistication of today’s regional model and local traffic impact study methodologies. This alternative method is tailored to the desires of local agencies, which requested a better, faster, and easier way to evaluate land uses and their impact on future traffic demands at the sub-area or project corridor levels. A particular emphasis was placed on scenario planning for currently undeveloped areas. The scenario planning tool was developed using actual land use and roadway information for the communities of Johnston and West Des Moines, Iowa. Both communities used the output from this process to make regular decisions regarding infrastructure investment, design, and land use planning. The City of Johnston case study included forecasting future traffic for the western portion of the city within a 2,600-acre area, which included 42 intersections. The City of West Des Moines case study included forecasting future traffic for the city’s western growth area covering over 30,000 acres and 331 intersections. Both studies included forecasting a.m. and p.m. peak-hour traffic volumes based upon a variety of different land use scenarios. The tool developed took goegraphic information system (GIS)-based parcel and roadway information, converted the data into a graphical spreadsheet tool, allowed the user to conduct trip generation, distribution, and assignment, and then to automatically convert the data into a Synchro roadway network which allows for capacity analysis and visualization. The operational delay outputs were converted back into a GIS thematic format for contrast and further scenario planning. This project has laid the groundwork for improving both planning and civil transportation decision making at the sub-regional, super-project level.

Evaluation of the user-friendliness of seven new generation intensive care ventilators.

OBJECTIVE: To explore the user-friendliness and ergonomics of seven new generation intensive care ventilators. DESIGN: Prospective task-performing study. SETTING: Intensive care research laboratory, university hospital. METHODS: Ten physicians experienced in mechanical ventilation, but without prior knowledge of the ventilators, were asked to perform eight specific tasks [turning the ventilator on; recognizing mode and parameters; recognizing and setting alarms; mode change; finding and activating the pre-oxygenation function; pressure support setting; stand-by; finding and activating non-invasive ventilation (NIV) mode]. The time needed for each task was compared to a reference time (by trained physiotherapist familiar with the devices). A time >180 s was considered a task failure. RESULTS: For each of the tests on the ventilators, all physicians' times were significantly higher than the reference time (P < 0.001). A mean of 13 +/- 8 task failures (16%) was observed by the ventilator. The most frequently failed tasks were mode and parameter recognition, starting pressure support and finding the NIV mode. Least often failed tasks were turning on the pre-oxygenation function and alarm recognition and management. Overall, there was substantial heterogeneity between machines, some exhibiting better user-friendliness than others for certain tasks, but no ventilator was clearly better that the others on all points tested. CONCLUSIONS: The present study adds to the available literature outlining the ergonomic shortcomings of mechanical ventilators. These results suggest that closer ties between end-users and manufacturers should be promoted, at an early development phase of these machines, based on the scientific evaluation of the cognitive processes involved by users in the clinical setting.

Pavement Instrumentation, HR-293, 1988

The report documents the development and installation of an instrumented pavement on I-80 in Iowa for the purposes of demonstration and answering current pavement questions. Its two primary objectives include documentation of the installation and verification of existing design procedures through monitoring of the continuous traffic stream reactions in the pavement. Some 120 instruments were installed in a forty foot segment of reconstructed pavement. The instruments included concrete strain gages, weldable strain gages on dowels, LVDT-deflection gages and temperature sensors in the concrete and base material. Five tubes were placed under three joints and two midslabs to measure the relative moisture and density at the interface between the pavement and base with atomic equipment. The instruments were placed ahead of the paving and over 92% of the instruments responded after paving. Planning requirements, problems encountered and costs of installation are presented. The site will use piezoelectric cables in a weigh-in-motion arrangement to trigger the data collection, a microcomputer controlled data acquisition system to analyze multiple sensors simultaneously, and telemetry to monitor the site remotely. Details provide the first time user of instrumentation with valuable information on the planning, problems, costs and coordination required to establish and operate such a site.

User experience strategy

L'objectiu d'aquest projecte era desenvolupar una metodologia de user experience strategy per aconseguir que el client d'una pàgina web tingui una mateixa experiència tant si fa servir una plataforma com una altra, aplicant diferents tècniques de disseny centrades en l'usuari.

Desarrollo de una aplicación informática para la gestión de actividades docentes

Este proyecto consiste en el desarrollo de una aplicación informática que permite gestionar de forma automatizada y consistente los datos requeridos para la actividad docente de un profesor universitario. La aplicación permite gestionar: plan docente, asignaturas, horario docente, calendario de exámenes y proyectos final de carrera. Todas estas opciones tienen las funciones de, agregar, buscar, modificar y eliminar datos. Además tiene otras opciones como calendario docente y webs, cuya finalidad será consultar, de forma directa, páginas web de interés docente. Finalmente, la opción material docente tendrá como finalidad, crear, modificar y eliminar ficheros de diferente formato (word, excel, powerpoint, pdf) asociados a las asignaturas registradas en la aplicación. La aplicación se ha implementado en el sistema operativo Windows en el lenguaje de programación Java. Los datos utilizados se almacenan en la base de datos MySql Workbench. Para las validaciones de entrada de datos se ha utilizado JavaScript y JQuery. El diseño de la interfaz se ha llevado a cabo con Java Server Pages, Html, Css y framework Struts.

Yield and performance of sugarcane in on-farm interface with rubber in Brazil

Agroforestry systems are indicated as an alternative for sugarcane (Saccharum officinarum) cultivation in Piracicaba, SP, Brazil, however there are not many field experiments on plant performance under these conditions in the world. The objective of this work was to assess crop yield and partitioning in a sugarcane-rubber (Hevea brasiliensis) interface in on-farm conditions. The availability of irradiance for the crop along the interface was simulated and its effe ct over sugarcane dry matter production was tested. Crop yield was negatively affected by distance of the trees, but development and sucrose were not affected. Above ground dry matter increased from 16.6 to 51.5 t ha-1 from trees. Partitioning did not have a defined standard, as harvest index increased from 0.85 to 0.93, but specific leaf area was not significant along the transect, ranging from 13.48 to 15.73 m² kg-1. Light is the main factor of competition between the trees and the crop, but the relative importance of below ground interactions increases closer to the trees. Feasibility of the system depends on maturity of the trees and management strategies.

Development of Object-Oriented Design and Specifications for Iowa DOT and Urban Standards: Phase I, TR-487, 2004

Currently, individuals including designers, contractors, and owners learn about the project requirements by studying a combination of paper and electronic copies of the construction documents including the drawings, specifications (standard and supplemental), road and bridge standard drawings, design criteria, contracts, addenda, and change orders. This can be a tedious process since one needs to go back and forth between the various documents (paper or electronic) to obtain information about the entire project. Object-oriented computer-aided design (OO-CAD) is an innovative technology that can bring a change to this process by graphical portrayal of information. OO-CAD allows users to point and click on portions of an object-oriented drawing that are then linked to relevant databases of information (e.g., specifications, procurement status, and shop drawings). The vision of this study is to turn paper-based design standards and construction specifications into an object-oriented design and specification (OODAS) system or a visual electronic reference library (ERL). Individuals can use the system through a handheld wireless book-size laptop that includes all of the necessary software for operating in a 3D environment. All parties involved in transportation projects can access all of the standards and requirements simultaneously using a 3D graphical interface. By using this system, users will have all of the design elements and all of the specifications readily available without concerns of omissions. A prototype object-oriented model was created and demonstrated to potential users representing counties, cities, and the state. Findings suggest that a system like this could improve productivity to find information by as much as 75% and provide a greater sense of confidence that all relevant information had been identified. It was also apparent that this system would be used by more people in construction than in design. There was also concern related to the cost to develop and maintain the complete system. The future direction should focus on a project-based system that can help the contractors and DOT inspectors find information (e.g., road standards, specifications, instructional memorandums) more rapidly as it pertains to a specific project.

Development of LRFD Procedures for Bridge Pile Foundations in Iowa Volume III: Recommended Resistance Factors with Consideration of Construction Control and Setup, TR-584, 2012

The Federal Highway Administration (FHWA) mandated utilizing the Load and Resistance Factor Design (LRFD) approach for all new bridges initiated in the United States after October 1, 2007. As a result, there has been a progressive move among state Departments of Transportation (DOTs) toward an increased use of the LRFD in geotechnical design practices. For the above reasons, the Iowa Highway Research Board (IHRB) sponsored three research projects: TR-573, TR-583 and TR-584. The research information is summarized in the project web site (http://srg.cce.iastate.edu/lrfd/). Two reports of total four volumes have been published. Report volume I by Roling et al. (2010) described the development of a user-friendly and electronic database (PILOT). Report volume II by Ng et al. (2011) summarized the 10 full-scale field tests conducted throughout Iowa and data analyses. This report presents the development of regionally calibrated LRFD resistance factors for bridge pile foundations in Iowa based on reliability theory, focusing on the strength limit states and incorporating the construction control aspects and soil setup into the design process. The calibration framework was selected to follow the guidelines provided by the American Association of State Highway and Transportation Officials (AASHTO), taking into consideration the current local practices. The resistance factors were developed for general and in-house static analysis methods used for the design of pile foundations as well as for dynamic analysis methods and dynamic formulas used for construction control. The following notable benefits to the bridge foundation design were attained in this project: 1) comprehensive design tables and charts were developed to facilitate the implementation of the LRFD approach, ensuring uniform reliability and consistency in the design and construction processes of bridge pile foundations; 2) the results showed a substantial gain in the factored capacity compared to the 2008 AASHTO-LRFD recommendations; and 3) contribution to the existing knowledge, thereby advancing the foundation design and construction practices in Iowa and the nation.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Work Zone Simulation Model, 1999

To support the analysis of driver behavior at rural freeway work zone lane closure merge points, Center for Transportation Research and Education staff collected traffic data at merge areas using video image processing technology. The collection of data and the calculation of the capacity of lane closures are reported in a companion report, "Traffic Management Strategies for Merge Areas in Rural Interstate Work Zones". These data are used in the work reported in this document and are used to calibrate a microscopic simulation model of a typical, Iowa rural freeway lane closure. The model developed is a high fidelity computer simulation with an animation interface. It simulates traffic operations at a work zone lane closure. This model enables traffic engineers to visually demonstrate the forecasted delay that is likely to result when freeway reconstruction makes it necessary to close freeway lanes. Further, the model is also sensitive to variations in driver behavior and is used to test the impact of slow moving vehicles and other driver behaviors. This report consists of two parts. The first part describes the development of the work zone simulation model. The simulation analysis is calibrated and verified through data collected at a work zone in Interstate Highway 80 in Scott County, Iowa. The second part is a user's manual for the simulation model, which is provided to assist users with its set up and operation. No prior computer programming skills are required to use the simulation model.

Aplicación móvil para el autocontrol de anticoagulantes orales

El tratamiento indefinido con anticoagulantes orales requiere la realización de controles analíticos periódicos y de un estricto control clínico. El uso de una aplicación móvil facilita la integración del autocontrol realizado por los pacientes y el personal médico, evitando visitas innecesarias en centros de salud. En este trabajo se diseña un aplicativo que hace posible la comunicación entre médico y paciente, empleando el Diseño Centrado en Usuario (D.C.U.). Se desarrolla la aplicación en PhoneGap, junto con los frameworks jQuery y jQuery Mobile, para ofrecer una interface más homogénea entre distintas plataformas, evitando el uso de funciones nativas.

Probing functional groups at the gas-aerosol interface using heterogeneous titration reactions: a tool for predicting aerosol health effects?

The complex chemical and physical nature of combustion and secondary organic aerosols (SOAs) in general precludes the complete characterization of both bulk and interfacial components. The bulk composition reveals the history of the growth process and therefore the source region, whereas the interface controls--to a large extent--the interaction with gases, biological membranes, and solid supports. We summarize the development of a soft interrogation technique, using heterogeneous chemistry, for the interfacial functional groups of selected probe gases [N(CH(3))(3), NH(2)OH, CF(3)COOH, HCl, O(3), NO(2)] of different reactivity. The technique reveals the identity and density of surface functional groups. Examples include acidic and basic sites, olefinic and polycyclic aromatic hydrocarbon (PAH) sites, and partially and completely oxidized surface sites. We report on the surface composition and oxidation states of laboratory-generated aerosols and of aerosols sampled in several bus depots. In the latter case, the biomarker 8-hydroxy-2'-deoxyguanosine, signaling oxidative stress caused by aerosol exposure, was isolated. The increase in biomarker levels over a working day is correlated with the surface density N(i)(O3) of olefinic and/or PAH sites obtained from O(3) uptakes as well as with the initial uptake coefficient, γ(0), of five probe gases used in the field. This correlation with γ(0) suggests the idea of competing pathways occurring at the interface of the aerosol particles between the generation of reactive oxygen species (ROS) responsible for oxidative stress and cellular antioxidants.

Matemaattiset opetusympäristöt ja matemaattisen käyttöliittymän käytettävyys

Tämän diplomityön tarkoituksena on kuvata Lappeenrannan teknillisessä yliopistossa kehitetyn luentojen tueksi tarkoitetun Matematiikan virtuaalimateriaalin hallintaympäristön kehityskaari. Järjestelmä luotiin parantamaanopetuksen laatua siten, että sen avulla opiskelijat saavat helposti käyttöönsä suomenkielistä, laadukkaalla kirjoitusjäljellä olevaa opiskelumateriaalia 24 tuntia vuorokaudessa. Lisäksi järjestelmän tavoitteena oli helpottaa opettajien työtaakkaa siten, että he pystyvät luomaan viikoittaiset harjoitustehtäväpaketit sekä tentit suoraan tietokannasta. Järjestelmän kehitys alkoi vuonna 2001, jonka jälkeen sitä on jatkuvasti muokattu opettajien ja opiskelijoiden avustuksella yhäkäyttäjäystävällisempään suuntaan. Testausmenetelminä on käytetty asiantuntijatestausta, lomakkeita ja varsinaista loppukäyttäjätestausta. Kehityksen tuloksenaon saatu järjestelmä, joka voidaan ottaa käyttöön kaikessa matematiikan perusopetuksessa.

Paikka- ja tilannetiedon hyödyntäminen sovelluksissa

Erilaisten mobiiliverkkojen käytön yleistyessä nousee esiin uudenlaisia sovellusalueita, kuten esimerkiksi paikkatietoiset sovellukset. Mobiiliudesta johtuen sovellusten käyttötilanteet vaihtelevat. Käyttötilanteista voidaan kerätä tietoa ja käyttää tätä hyödyksi. Tilannetiedolla tarkoitetaan sovelluksen käyttötilanteeseen tai käyttäjään liittyvää lisätietoa. Paikka- ja tilannetietoisten sovellusten kehittäminen vaati monia ohjelmistokehitystä tukevia järjestelmiä. Tilannetiedon väljän määritelmän takia tilannetietoisten sovellusten kehitykselle ei ole vielä selkeitä toimintamalleja. Tilannetietoisten sovellusten kehitystä avustavia järjestelmiä on luotu etenkin tutkimuksessa, mutta nämä eivät ole vielä yleistyneet laajempaan käyttöön. Paikkatiedon käyttö sen sijaan on hyvinkin standardoitua, mutta paikkatieto nähdään vain osana tilannetietoa. Tässä diplomityössä toteutettiin paikka- ja tilannetiedon sovelluskehitystä tukevia järjestelmiä, joilla paikka- ja tilannetiedon hyödyntäminen sovelluksissa mahdollistettiin. WLAN - verkosta saadun paikkatiedon hyödyntämiseen toteutettiin SOAP -palvelurajapinta. Tilannetiedon hyödyntämiseksi toteutettiin MUPE -sovellusympäristöön välittäjäkomponentteja paikka-, sää- ja kuntopyörän harjoitustiedolle sekä RFID -havaintotiedoille. Näitä komponetteja käytettiin tilannetietoisten sovellusten luomiseen sekä tietoliikennetekniikan laitoksen codecamp -kursseilla, että tilannetietoisessa pelisovelluksessa. Työn tuloksena saatiin toimivia sovelluksia, ja välittäjäkomponentit sovellusten luomiseen. Työn tuloksena voidaan todeta, että ilman tilannetietoista sovelluskehitystä tukevia komponentteja, olisi tämäntyyppinen sovelluskehitys huomattavasti vaativampaa. Tukevat komponentit helpottavat sovelluskehitystä, mutta helposti myös rajaavat kehitysmahdollisuuksia.

Java Specification Request development on a mobile device

Nykyaikaiset Java-teknologiaa sisältävät matkapuhelimet kehittyvät vauhdikkaasti prosessoritehon, muistin määrän sekä uusien käyttöjärjestelmäversioiden tarjoamien ominaisuuksien myötä. Laitteiden näyttöjen koko tulee pysymään pienenä,mutta silti moninaista multimediasisältöä äänen, videon ja kuvan osilta voidaanhuomattavasti parantaa JSR 234:n eli kehittyneen multimedialaajennuksen avulla.Erityisesti edistyneet ääniominaisuudet ovat tervetullut lisä, sillä viime aikojen kehitys matkapuhelimissa on saanut aikaan niiden muuntumisen myös kannettavaksi musiikkisoittimiksi. Diplomityössä JSR 234 -spesifikaation tietty osa kehitettiin ympäristössä, joka koostui Series 60 -ohjelmistoalustankolmannesta versiosta sekä Symbian OS v9.1 käyttöjärjestelmästä. Tuloksena syntynyt Java-rajapinta tarjoaa sovelluskehittäjille yksinkertaisemman lähestymistavan Symbianin efektirajapintaan piilottaen samalla alla olevan käyttöjärjestelmänmonimutkaisuuden. Toteutuksen täytyy olla läpikotaisin testattu, jotta voidaan varmentua sen noudattavan tarkkaan JSR 234 -spesifikaatiota. Työssä on esitelty useita eri testausmenetelmiä tarkoituksena saavuttaa projektissa paras mahdollinen laatu.