Basic life support teaching in the second year predraduate medical curriculum: quality of acquisition after 6 months

Purpose of the study: Basic life support (BLS) and automated externaldefibrillation (AED) represent important skills to be acquired duringpregraduate medical training. Since 3 years, our medical school hasintroduced a BLS-AED course (with certification) for all second yearmedical students. Few reports about quality and persistence over timeof BLS-AED learning are available to date in the medical literature.Comprehensive evaluation of students' acquired skills was performedat the end of the 2008 academic year, 6 month after certification.Materials and methods: The students (N = 142) were evaluated duringa 9 minutes «objective structured clinical examination» (OSCE) station.Out of a standardized scenario, they had to recognize a cardiac arrestsituation and start a resuscitation process. Their performance wererecorded on a PC using an Ambuman(TM) mannequin and the AmbuCPR software kit(TM) during a minimum of 8 cycles (30 compressions:2 ventilations each). BLS parameters were systematically checked. Nostudent-rater interactions were allowed during the whole evaluation.Results: Response of the victim was checked by 99% of the students(N = 140), 96% (N = 136) called for an ambulance and/or an AED. Openthe airway and check breathing were done by 96% (N = 137), 92% (N =132) gave 2 rescue breaths. Pulse was checked by 95% (N=135), 100%(N = 142) begun chest compression, 96% (N = 136) within 1 minute.Chest compression rate was 101 ± 18 per minute (mean ± SD), depthcompression 43 ± 8 mm, 97% (N = 138) respected a compressionventilationratio of 30:2.Conclusions: Quality of BLS skills acquisition is maintained during a6-month period after a BLS-AED certification. Main targets of 2005 AHAguidelines were well respected. This analysis represents one of thelargest evaluations of specific BLS teaching efficiency reported. Furtherfollow-up is needed to control the persistence of these skills during alonger time period and noteworthy at the end of the pregraduatemedical curriculum.

Diagnostic algorithm for a validated displacement grading of pediatric supracondylar fractures.

Background: The first AO comprehensive pediatric long bone fracture classification system has been established following a structured path of development and validation with experienced pediatric surgeons. Methods: A follow-up series of agreement studies was applied to specify and evaluate a grading system for displacement of pediatric supracondylar fractures. An iterative process comprising an international group of 5 experienced pediatric surgeons (Phase 1) followed by a pragmatic multicenter agreement study involving 26 raters (Phase 2) was used. The last evaluations were conducted on a consecutive collection of 154 supracondylar fractures documented by standard anteroposterior and lateral radiographs. Results: Fractures were classified according to 1 of 4 grades: I = incomplete fracture with no or minimal displacement; II = Incomplete fracture with continuity of the posterior (extension fracture) or anterior cortex (flexion fracture); III = lack of bone continuity (broken cortex), but still some contact between the fracture planes; IV = complete fracture with no bone continuity (broken cortex), and no contact between the fracture planes. A diagnostic algorithm to support the practical application of the grading system in a clinical setting, as well as an aid using a circle placed over the capitellum was proposed. The overall kappa coefficients were 0.68 and 0.61 in the Phase 1 and Phase 2 studies, respectively. In the Phase 1 study, fracture grades I, II, III, and IV were classified with median accuracies of 91%, 82%, 83%, and 99.5%, respectively. Similar median accuracies of 86% (Grade I), 73% (Grade II), 83%(Grade III), and 92% were reported for the Phase 2 study. Reliability was high in distinguishing complete, unstable fractures from stable injuries [ie, kappa coefficients of 0.84 (Phase 1) and 0.83 (Phase 2) were calculated]; in Phase 2, surgeons' accuracies in classifying complete fractures were all above 85%. Conclusions: With clear and unambiguous definition, this new grading system for supracondylar fracture displacement has proved to be sufficiently reliable and accurate when applied by pediatric surgeons in the framework of clinical routine as well as research.

Machine learning for spatial environmental data. Theory, applications and software

The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.

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.

Software Process Modeling with Eclipse Process Framework

The software development industry is constantly evolving. The rise of the agile methodologies in the late 1990s, and new development tools and technologies require growing attention for everybody working within this industry. The organizations have, however, had a mixture of various processes and different process languages since a standard software development process language has not been available. A promising process meta-model called Software & Systems Process Engineering Meta- Model (SPEM) 2.0 has been released recently. This is applied by tools such as Eclipse Process Framework Composer, which is designed for implementing and maintaining processes and method content. Its aim is to support a broad variety of project types and development styles. This thesis presents the concepts of software processes, models, traditional and agile approaches, method engineering, and software process improvement. Some of the most well-known methodologies (RUP, OpenUP, OpenMethod, XP and Scrum) are also introduced with a comparison provided between them. The main focus is on the Eclipse Process Framework and SPEM 2.0, their capabilities, usage and modeling. As a proof of concept, I present a case study of modeling OpenMethod with EPF Composer and SPEM 2.0. The results show that the new meta-model and tool have made it possible to easily manage method content, publish versions with customized content, and connect project tools (such as MS Project) with the process content. The software process modeling also acts as a process improvement activity.

Electronic Business Model for International Software Market

Tämän diplomityön tavoitteena on muodostaa sähköinen liiketoimintamalli kansainvälisen ohjelmistoyrityksen tarpeisiin. Ohjelmiston uusi ominaisuus antaa kolmansille osapuolille mahdollisuuden määritellä itse rakennusmallintamisessa tarvittavia komponentteja, mikä luo mahdollisuuden uuteen liiketoimintaan. Liiketoimintamallien teoria ja asiantuntijoiden haastattelut tulevat osoittamaan, että paras ratkaisu tässä tapauksessa on portaali, joka rakentuu komponenttimarkkinoista, e-kaupasta ja virtuaaliyhteisöstä. Komponenttimarkkinat on jaettu vapaaseen vaihdantaan ja sertifioitujen kehittäjien kaupankäyntiin. Tämä tarjoaa mahdollisuuksia kehittäjille valita sitoutuneisuutensa taso, samoin kuin motivoi heitä osallistumaan. E-kauppa on suunniteltu sovelluksille ja monimutkaisemmille komponenteille. Virtuaaliyhteisön kautta käyttäjät voivat keskustella mielipiteistään ja saada tukea ohjelmiston käyttämiseen sekä komponenttien kehittämiseen.

Managing an intellectual property right portfolio in the software industry

Tutkimuksen tavoitteena oli määrittää etuja, joita huolellinen immateriaali-oikeussalkun hallinnointi ohjelmistoalalla luo yritykselle. Tutkimusaineisto on kerätty haastattelemalla eri asemissa olevia ihmisiä kolmesta suomalaisesta ohjelmistoalan tuote- ja palveluyrityksestä. Tutkimuksesta käy ilmi, että ohjelmistoyritysten immateriaalioikeussalkut koostuvat liikesalaisuuksista, tekijänoikeudesta, tavaramerkeistä, verkkotunnuksista ja muutamista patenteista. Kiinnostus patentteihin ohjelmistoalalla on kasvanut erityisesti niiden tuoman tekijänoikeutta vahvemman suojan takia. Tällä hetkellä Euroopassa suhtautuminen ohjelmistopatentteihin on kuitenkin vielä käymistilassa. Jos ohjelmistopatentit hyväksytään, immateriaalioikeussalkun strateginen merkitys kasvaa. Tällöin salkunn hallinnointi tukee yrityksen tavoitteita - esimerkiksi oman toimintavapauden turvaamista - avustaen hakemus-prosessissa, tarkkaillen markkinoita sekä arvioiden yrityksen oman immateriaalioikeussalkun erilaisia hyväksikäyttömahdollisuuksia.

Value added logistical support service. Part 1 : Trends and new concept model

The aim of `Valssi' study was to find out the service requirements in `business-to-business' (B2B) markets and to present a new logistics service concept, where the traditional logistics service is expanded with significant manufacturing and value addedfacilities. The traditional third-party logistics service providers are not necessarily able to offer services, which cover widely the needs of potential customers. The study has been outlined to spare part markets in metal industry. In the second phase of the Valssi-project the aim is to examine the economical conditions and potentiality of the new logistics business concept. This research report (Part 1) concentrates on examining current trends in global and domestic logistics markets. Based on detailed survey among the participating companies, the study presents basis for a new logistics business concept model. The developed concept consists of 12 different service modules, which are split into deeper details of processes. The integration of worldwide supplier and service provider network together with customer companies systems is a challenge. The report focuses on evaluating the requirements for the new business concept from the customer-companies point of view. The study paints an overall picture of distribution and service provider network including an abstract about the software and system integration possibilities. As a result of the survey, it can be concluded that thereis need for the new business concept among the participating companies, and a modular service concept meets the requirements of them, because the new sophisticated concept considers the specialities involved in spare part logistics in metal industry.

Technology selection and group decision support systems: Case studies on supporting strategic technology selection processes

The objective of the dissertation is to increase understanding and knowledge in the field where group decision support system (GDSS) and technology selection research overlap in the strategic sense. The purpose is to develop pragmatic, unique and competent management practices and processes for strategic technology assessment and selection from the whole company's point of view. The combination of the GDSS and technology selection is approached from the points of view of the core competence concept, the lead user -method, and different technology types. In this research the aim is to find out how the GDSS contributes to the technology selection process, what aspects should be considered when selecting technologies to be developed or acquired, and what advantages and restrictions the GDSS has in the selection processes. These research objectives are discussed on the basis of experiences and findings in real life selection meetings. The research has been mainly carried outwith constructive, case study research methods. The study contributes novel ideas to the present knowledge and prior literature on the GDSS and technology selection arena. Academic and pragmatic research has been conducted in four areas: 1) the potential benefits of the group support system with the lead user -method,where the need assessment process is positioned as information gathering for the selection of wireless technology development projects; 2) integrated technology selection and core competencies management processes both in theory and in practice; 3) potential benefits of the group decision support system in the technology selection processes of different technology types; and 4) linkages between technology selection and R&D project selection in innovative product development networks. New type of knowledge and understanding has been created on the practical utilization of the GDSS in technology selection decisions. The study demonstrates that technology selection requires close cooperation between differentdepartments, functions, and strategic business units in order to gather the best knowledge for the decision making. The GDSS is proved to be an effective way to promote communication and co-operation between the selectors. The constructs developed in this study have been tested in many industry fields, for example in information and communication, forest, telecommunication, metal, software, and miscellaneous industries, as well as in non-profit organizations. The pragmatic results in these organizations are some of the most relevant proofs that confirm the scientific contribution of the study, according to the principles of the constructive research approach.

Are Evaluation of ICTs Investment Using Decision Support Systems:Case Applications from Distributor's and End User's Perspective Group Decision

The evaluation of investments in advanced technology is one of the most important decision making tasks. The importance is even more pronounced considering the huge budget concerning the strategic, economic and analytic justification in order to shorten design and development time. Choosing the most appropriate technology requires an accurate and reliable system that can lead the decision makers to obtain such a complicated task. Currently, several Information and Communication Technologies (ICTs) manufacturers that design global products are seeking local firms to act as their sales and services representatives (called distributors) to the end user. At the same time, the end user or customer is also searching for the best possible deal for their investment in ICT's projects. Therefore, the objective of this research is to present a holistic decision support system to assist the decision maker in Small and Medium Enterprises (SMEs) - working either as individual decision makers or in a group - in the evaluation of the investment to become an ICT's distributor or an ICT's end user. The model is composed of the Delphi/MAH (Maximising Agreement Heuristic) Analysis, a well-known quantitative method in Group Support System (GSS), which is applied to gather the average ranking data from amongst Decision Makers (DMs). After that the Analytic Network Process (ANP) analysis is brought in to analyse holistically: it performs quantitative and qualitative analysis simultaneously. The illustrative data are obtained from industrial entrepreneurs by using the Group Support System (GSS) laboratory facilities at Lappeenranta University of Technology, Finland and in Thailand. The result of the research, which is currently implemented in Thailand, can provide benefits to the industry in the evaluation of becoming an ICT's distributor or an ICT's end user, particularly in the assessment of the Enterprise Resource Planning (ERP) programme. After the model is put to test with an in-depth collaboration with industrial entrepreneurs in Finland and Thailand, the sensitivity analysis is also performed to validate the robustness of the model. The contribution of this research is in developing a new approach and the Delphi/MAH software to obtain an analysis of the value of becoming an ERP distributor or end user that is flexible and applicable to entrepreneurs, who are looking for the most appropriate investment to become an ERP distributor or end user. The main advantage of this research over others is that the model can deliver the value of becoming an ERP distributor or end user in a single number which makes it easier for DMs to choose the most appropriate ERP vendor. The associated advantage is that the model can include qualitative data as well as quantitative data, as the results from using quantitative data alone can be misleading and inadequate. There is a need to utilise quantitative and qualitative analysis together, as can be seen from the case studies.

Selected Aspects Related to Pre-development Stages of International Software projects. Case of Finland and Russia

The question of Pilot Project creation, due to support pre-development stage of software product elaboration, nowadays might be used as an approach, which allows improving the whole scheme of information technology project running. This subject is not new, but till now no model has been presented, which gives deep description of this important stage on the early phase of project. This Master's Thesis represents the research's results and findings concerning the pre-development study from the Software Engineering point of view. The aspects of feasibility study, pilot prototype developments are analyzed in this paper. As the result, the technique of Pilot Project is formulated and scheme has been presented. The experimental part is focused on particular area Pilot Project scheme's implementation- Internationally Distributed Software projects. The specific characteristic, aspects, obstacles, advantages and disadvantages are considered on the example of cross border region of Russia and Finland. The real case of Pilot Project technique implementation is given.

Multilayer switch hardware support for Linux

VDSL on teknologia, joka mahdollistaa nopeat Internet-yhteydet tavallista puhelinlinjaa käyttäen. Tätä varten käyttäjä tarvitsee VDSL-modeemin ja Internet-operaattori reitittimen, johon VDSL-linjat kytketään. Reitittimen on oltava suorituskykyinen, jotta kaikki VDSL-liikenne voidaan reittittää eteenpäin. Tehokkuutta haetaan tekemällä suuri osa reitityksestä erityisillä reititinpiireillä. Tässä diplomityössä käsitellään reititinpiirien teoriaa ja niiden hallintaa. Lisäksi vertailtiin kolmen suuren valmistajan tuotteita. Tuotteiden tarjoamat ominaisuudet vaikuttivat hyvin yhteneväisiltä. Ominaisuuksien hallinta ja toteutus olivat erilaisia. Työn tavoitteena oli löytää ohjelmistoarkkitehtuuri piirien ohjaamiseen niin, että Linux-käyttöjärjestelmän ytimen palveluja voitaisiin käyttää mahdollisimman hyödyllisesti. Työssä havaittiin, että ohjelmistoarkkitehtuurin voi määritellä monella eri tavalla riippuen siitä, miten piiri on kytketty prosessoriin, mitä piirin ominaisuuksia halutaan käyttää ja miten arkkitehtuuria halutaan jatkossa laajentaa.

Managing R&D Content with Web-based KM Software

Työssä tutkittiin tehokasta tietojohtamista globaalin metsäteollisuusyrityksen tutkimus ja kehitys verkostossa. Työn tavoitteena oli rakentaa kuvaus tutkimus ja kehitys sisällön hallintaan kohdeyrityksen käyttämän tietojohtamisohjelmiston avulla. Ensin selvitettiin käsitteitä tietämys ja tietojohtaminen kirjallisuuden avulla. Selvityksen perusteella esitettiin prosessimalli, jolla tietämystä voidaan tehokkaasti hallita yrityksessä. Seuraavaksi analysoitiin tietojohtamisen asettamia vaatimuksia informaatioteknologialle ja informaatioteknologian roolia prosessimallissa. Verkoston vaatimukset tietojohtamista kohtaan selvitettiin haastattelemalla yrityksen avainhenkilöitä. Haastatteluiden perusteella järjestelmän tuli tehokkaasti tukea virtuaalisten projektiryhmien työskentelyä, mahdollistaa tehtaiden välinen tietämyksen jakaminen ja tukea järjestelmään syötetyn sisällön hallintaa. Ensiksi järjestelmän käyttöliittymän rakenne ja salaukset muokattiin vastaamaan verkoston tarpeita. Rakenne tarjoaa työalueen työryhmille ja alueet tehtaiden väliseen tietämyksen jakamiseen. Sisällönhallintaa varten järjestelmään kehitettiin kategoria, profiloitu portaali ja valmiiksi määriteltyjä hakuja. Kehitetty malli tehostaa projektiryhmien työskentelyä, mahdollistaa olemassa olevan tietämyksen hyväksikäytön tehdastasolla sekä helpottaa tutkimus ja kehitys aktiviteettien seurantaa. Toimenpide-ehdotuksina esitetään järjestelmän integrointia tehtaiden operatiivisiin ohjausjärjestelmiin ja ohjelmiston käyttöönottoa tehdastason projektinhallinta työkaluksi.Ehdotusten tavoitteena on varmistaa sekä tehokas tietämyksen jakaminen tehtaiden välillä että tehokas tietojohtaminen tehdastasolla.

Software process improvement using an electronic process guide

Kasvava kiinnostus ohjelmistojen laatua kohtaan on herättänyt ohjelmistoprosesseihin ja niiden kehittämiseen kohdistuvaa huomiota viime vuosina. Ohjelmistoyritykset ympäri maailmaa ovat ottaneet käyttöön ohjelmistoprosessin kehittämismalleja, kuten CMM ja SPICE, pyrkiessään kohti parempilaatuisia ohjelmistotuotteita. Samalla on huomattu, että tehokas prosessien parantaminen ja suorittaminen tarvitsee tuekseen kuvauksen prosessista, jotta prosessin perusteellinen ymmärtäminen ja kommunikointi olisi mahdollista. Ohjelmistoprosesseja voidaan kuvata monilla eri tavoilla. Prosessiopas on prosessin esitysmuoto, jonka päätarkoituksena on helpottaa prosessin ymmärtämistä ja kommunikointia. Elektroninen prosessiopas on Web-teknologiaa hyödyntävä prosessiopas. Tässä työssä luodaan kehitysympäristö elektronisille prosessioppaille, joiden tarkoituksena on tukea ohjelmistoprosessin kehittämistä ja suorittamista. Ympäristö mahdollistaa ohjelmistoprosessinmallintamisen sekä yksilöllisten oppaiden luomisen ja muokkaamisen. Kehitysympäristöä käytetään mallintamaan tietoliikenneohjelmistoja valmistavan yrityksen ohjelmistoprosessia sekä luomaan elektronisia prosessioppaita tukemaan prosessin kehitystä ja suorittamista. Lopuksi pohditaan prosessioppaiden tarjoamaa tukea sekä mahdollisuuksia kohdeyrityksessä.

Web Software Engineering - value added approach

Taking the maximum advantage of technological innovations and the investment in them is of key importance for businesses. The IT industry offers a wide range of innovative high-technology solutions to manage information processing and distribution. However for end-user businesses to make informed decisions in this area is challenging. The aim of this research is to identify the key differences in principal solutions, and what the selection criteria should be for those involved. Existing methodologies for software development are classified, and some key criteria are described to help IT system developers and users determine what are the most important factors in system selection, development and deployment. Statistical data is researched and analysed, a theoretical basis is developed and reviewed, key issues from case studies are identified and generalized to be presented along with the conclusions in the current study. The results give a good basis for corporate consideration and provide overall support to the key decisions in developing web-based software. The conclusion is that new web developments should be considered the stakeholders as an evolution of existing business systems, but they should then pay particular attention to the new advantages that web-based software offers in terms of standardised interfaces and procedures, universal deployment opportunities, and a range of other benefits the study highlights.