Communicating Cost Information to Design Engineers using an Activity-based Costing Method

This paper analyzes the possibilities of integrating cost information and engineering design. Special emphasis is on finding the potential of using the activity-based costing (ABC) method when formulating cost information for the needs of design engineers. This paper suggests that ABC is more useful than the traditional job order costing, but the negative issue is the fact that ABC models become easily too complicated, i.e. expensive to build and maintain, and difficult to use. For engineering design the most suitable elements of ABC are recognizing activities of the company, constructing acitivity chains, identifying resources, activity and cost drivers, as wellas calculating accurate product costs. ABC systems including numerous cost drivers can become complex. Therefore, a comprehensive ABC based cost information system for the use of design engineers should be considered criticaly. Combining the suitable ideas of ABC with engineering oriented thinking could give competentresults.

Käyttöliittymä verkonhallintaan sulautetussa Linux-käyttöjärjestelmässä

During the project we get familiar with Linksys WRT54GL wireless router and its network managing methods. Operating system is OpenWRT which is Linux-based distribution for embedded devices. OpenWRT uses two kind of approach for its network administration. The first one is web-based user interface and the second one is command line based. Both methods are working but do not solve all problems that competent network administrator can need for secured network managing. The goal of the project was design an NCurses-based user interface for network administration that can be run from command line. The user interface can be use for example from terminal via SSH which is yet faster and also light to use. The idea is to combine the user friendly of WWW-interface and the advanced options that command line based network managing can offer. Linux-based open source OpenWRT offers good development tools. There exist also a compact development community if there is need for further development of software in future. So far user interface for command line based network administrator is not available.

Ohjelmistoarkkitehtuurien vertailu ja valinta monimediatuotteelle. CASE: AVO

Työn tavoitteena oli tutkia ja vertailla komponenttipohjaisia ohjelmistoarkkitehtuureita (Microsoft .NET ja J2EE). Työn tarkoituksena oli valita ohjelmistoarkkitehtuuri uudelle neuroverkkopohjaiselle urasuunnittelupalvelulle. Tässä työssä selvitettiin myös, miten luodaan kansainvälistettäviä ja lokalisoitavia sovelluksia, sekä kuinka Web-, Windows-, mobiili-, puhe- ja Digi-TV -käyttöliittymät soveltuvat uudelle urasuunnittelupalvelulle. Tutkimustyössä käytettiin alan kirjallisuutta, Microsoftin ja Sun Microsystemsin Web-sivuja. Tutkimustyössä analysoitiin Microsoft Pet Shop- ja Sun Microsystemsin Java Pet Store -esimerkkisovellusten suorituskykyvertailua. Analyysituloksiin perustuen urasuunnittelupalvelussa suositellaan käytettäväksi J2EE-arkkitehtuuria. Uudelle urasuunnittelupalvelulle toimenpide-ehdotus on komponenttipohjainen järjestelmä Web-, puhe- ja Digi-TV -käyttöliittymillä ja personoidulla sisällöllä. Järjestelmä tehdään viisivaiheisena hankkeena, johon sisältyy pilottitestejä. Uuteen urasuunnittelupalveluun liitetään mukaan opiskelijat, oppilaitokset ja työnantajat sekä asiantuntijoita neuroverkon opetusdatan määrittämiseen. Palvelu perustuu integroituun tietokantaan. Eri osajärjestelmissä tuotettua tietoa voidaan hyödyntää kaikkialla urasuunnittelupalvelussa.

Decreasing Proportion of Recent Infections among Newly Diagnosed HIV-1 Cases in Switzerland, 2008 to 2013 Based on Line-Immunoassay-Based Algorithms.

BACKGROUND: HIV surveillance requires monitoring of new HIV diagnoses and differentiation of incident and older infections. In 2008, Switzerland implemented a system for monitoring incident HIV infections based on the results of a line immunoassay (Inno-Lia) mandatorily conducted for HIV confirmation and type differentiation (HIV-1, HIV-2) of all newly diagnosed patients. Based on this system, we assessed the proportion of incident HIV infection among newly diagnosed cases in Switzerland during 2008-2013. METHODS AND RESULTS: Inno-Lia antibody reaction patterns recorded in anonymous HIV notifications to the federal health authority were classified by 10 published algorithms into incident (up to 12 months) or older infections. Utilizing these data, annual incident infection estimates were obtained in two ways, (i) based on the diagnostic performance of the algorithms and utilizing the relationship 'incident = true incident + false incident', (ii) based on the window-periods of the algorithms and utilizing the relationship 'Prevalence = Incidence x Duration'. From 2008-2013, 3'851 HIV notifications were received. Adult HIV-1 infections amounted to 3'809 cases, and 3'636 of them (95.5%) contained Inno-Lia data. Incident infection totals calculated were similar for the performance- and window-based methods, amounting on average to 1'755 (95% confidence interval, 1588-1923) and 1'790 cases (95% CI, 1679-1900), respectively. More than half of these were among men who had sex with men. Both methods showed a continuous decline of annual incident infections 2008-2013, totaling -59.5% and -50.2%, respectively. The decline of incident infections continued even in 2012, when a 15% increase in HIV notifications had been observed. This increase was entirely due to older infections. Overall declines 2008-2013 were of similar extent among the major transmission groups. CONCLUSIONS: Inno-Lia based incident HIV-1 infection surveillance proved useful and reliable. It represents a free, additional public health benefit of the use of this relatively costly test for HIV confirmation and type differentiation.

Simulation of a Virtual Campus at the Open University of Catalonia

Peer-reviewed

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Maasulkuvirtojen kehitys ja kompensointi Haminan Energia Oy:n keskijänniteverkossa

Tässä työssä tutkitaan maasulkuvirtoja sekä niiden vaikutusta ja kehitystä Haminan Ener-gia Oy:n keskijänniteverkossa. Lisäksi tarkastellaan erilaisia mahdollisuuksia rajoittaa maasulkuvirtojen suuruuksia. Tutkimusalueena käytetään koko Haminan Energia Oy:n keskijänniteverkkoaluetta. Maasulkuvirtojen suuruuden ja vaikutusten tutkimiseksi suori-tetaan erilaisin lähtökriteerein maasulkujen vikavirtalaskennat verkkotietojärjestelmällä. Verkon kehittymisen analysoimiseksi selvitetään sen ikätietoja, kaava-alueiden muutok-sia sekä päämuuntaja- ja varasyöttökapasiteetteja. Analyysien pohjalta saatujen tulosten perusteella työssä laaditaan arvio maasulkuvirtojen kehityksestä tulevaisuudessa. Maasulkuvirtojen kompensoimiseksi päädytään rakenta-maan uusi päämuuntaja Laurilan sähköasemalle sekä parantamaan eräiden muuntamoiden ja erottimien maadoituksia. Nämä parannusehdotukset toteuttamalla pystytään sähkötur-vallisuusmääräykset täyttämään maasulkujen osalta pitkälle tulevaisuuteen sekä vähentä-mään asiakkaiden kokemia keskeytyksiä. Lisäksi työssä tehdään ohjeistus Haminan Energia Oy:lle maasulkuvirtojen laskentaa varten.

Design and evaluation of learning algorithms for dynamic resource management in virtual networks

Network virtualisation is considerably gaining attentionas a solution to ossification of the Internet. However, thesuccess of network virtualisation will depend in part on how efficientlythe virtual networks utilise substrate network resources.In this paper, we propose a machine learning-based approachto virtual network resource management. We propose to modelthe substrate network as a decentralised system and introducea learning algorithm in each substrate node and substrate link,providing self-organization capabilities. We propose a multiagentlearning algorithm that carries out the substrate network resourcemanagement in a coordinated and decentralised way. The taskof these agents is to use evaluative feedback to learn an optimalpolicy so as to dynamically allocate network resources to virtualnodes and links. The agents ensure that while the virtual networkshave the resources they need at any given time, only the requiredresources are reserved for this purpose. Simulations show thatour dynamic approach significantly improves the virtual networkacceptance ratio and the maximum number of accepted virtualnetwork requests at any time while ensuring that virtual networkquality of service requirements such as packet drop rate andvirtual link delay are not affected.

Rule-based machine translation between Bulgarian and Macedonian

This paper describes the development of a two-way shallow-transfer rule-based machine translation system between Bulgarian and Macedonian. It gives an account of the resources and the methods used for constructing the system, including the development of monolingual and bilingual dictionaries, syntactic transfer rules and constraint grammars. An evaluation of thesystem's performance was carried out and compared to another commercially available MT system for the two languages. Some future work was suggested.

Flow analysis-hydride generation-gas phase derivative molecular absorption spectrophotometric determination of antimony in antileishmanial drugs

In the present work, the development of a method based on the coupling of flow analysis (FA), hydride generation (HG), and derivative molecular absorption spectrophotometry (D-EAM) in gas phase (GP), is described in order to determine total antimony in antileishmanial products. Second derivative order (D²224nm) of the absorption spectrum (190 - 300 nm) is utilized as measurement criterion. Each one of the parameters involved in the development of the proposed method was examined and optimized. The utilization of the EAM in GP as detection system in a continuous mode instead of atomic absorption spectrometry represents the great potential of the analytic proposal.

Rovakaira Oy:n keskijänniteverkon kehittämissuunnitelma toimitusvarmuuskriteeristön näkökulmasta

Diplomityössä tavoitteena on etsiä teknistaloudellisimmat ratkaisut sekä tutkia niiden vaikutuksia sähkönjakeluverkoston käyttövarmuuteen ja luotettavuuteen toimitusvarmuuskriteeristön näkökulmasta. Lisäksi työssä esitetään uusi tunnusluku kriteeristön ylityksestä aiheutuvan haitan arvostukseen. Merkittävä osa Rovakaira Oy:n keskijänniteverkosta joudutaan uusimaan lähivuosikymmeninä teknistaloudellisen pitoajan täyttyessä. Verkon uusiminen antaa mahdollisuuden toteuttaa verkkoa nykyisiin vaatimuksiin paremmin sopivilla ratkaisuilla. Kehitysvaihtoehtoina vertaillaan johdon tien varteen siirtoa, maastokatkaisijoiden lisäämistä, pienitehoisten ja päättyvien haarajohtojen korvaamista 1 kV tekniikalla sekä pienoissähköaseman kannattavuutta. Työssä tarkastellaan yksityiskohtaisemmin Sodankylän käyttövarmuuden parantamista sähköasemavian aikana ja alueen kuormituksenkasvuun varautumista.

Application of fuzzy logic for the evaluation of livestock slaughtering

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.

Finnish cleantech SMEs in China: Challenges and solutions

The rapid economic growth in China has resulted in environmental challenges ranging from air pollution to water-related issues. Thus supporting clean technology, or cleantech, that encompasses industries that focus on alternative energy, pollution and recycling, power supplies and conservation has become one of the focal points in the Chinese economic policy for the next decade. Simultaneously, the Finnish government has initiated programs to support the internationalisation of domestic cleantech companies in an attempt to spiral the industry into one of the pillars of Finnish economic growth. This study concentrates on the conjunction of these two themes and studies the challenges faced by Finnish cleantech SMEs in the Chinese market. Consequently, the study answers the following sub questions: 1. What human and financial resource-based challenges do Finnish cleantech SMEs face in the Chinese market and what are their solutions? 2. What knowledge-based challenges do Finnish cleantech SMEs face in the Chinese market and how can these difficulties be resolved? 3. What network-based challenges do Finnish cleantech SMEs face in the Chinese market, how do they relate to the resource- and knowledge-based challenges, and how can these difficulties be resolved? This qualitative study is conducted by analysing four semi structured interviews collected from four Finnish SMEs that operate in China. The findings of the study indicate that in human resources the most important challenges are related to the hiring and retaining of employees. In contrast to extant academic literature results distinguish salary and social status as the main solutions to this challenge. Regarding financial resources it is discovered that cleantech companies enjoy a benign business environment in China and benefit from the Chinese government’s support for cleantech industry. Challenges related to knowledge resources can be grouped into categories with the most interesting knowledge flows being the stream of local market knowledge into to the foreign parent company and the outward flow of manufacturing and business practice information into the target venture. The challenge related to the first flow is gathering relevant information and the main solutions are clustering at the foreign location and hiring knowledge prior to internationalisation. Regarding the second flow the main challenge is related to intellectual property rights and the most interesting solution is the purposeful transformation of explicit knowledge into tacit knowledge. Finally, it is discovered that networks, called guanxi in China, greatly affect the business processes. Within the guanxi system there is the concept of face which was found to affect employee propensity to stay as well as, as a novel academic result, employees’ knowledge sharing intention.

Fuzzy ontology for knowledge mobilisation and decision support

A growing concern for organisations is how they should deal with increasing amounts of collected data. With fierce competition and smaller margins, organisations that are able to fully realize the potential in the data they collect can gain an advantage over the competitors. It is almost impossible to avoid imprecision when processing large amounts of data. Still, many of the available information systems are not capable of handling imprecise data, even though it can offer various advantages. Expert knowledge stored as linguistic expressions is a good example of imprecise but valuable data, i.e. data that is hard to exactly pinpoint to a definitive value. There is an obvious concern among organisations on how this problem should be handled; finding new methods for processing and storing imprecise data are therefore a key issue. Additionally, it is equally important to show that tacit knowledge and imprecise data can be used with success, which encourages organisations to analyse their imprecise data. The objective of the research conducted was therefore to explore how fuzzy ontologies could facilitate the exploitation and mobilisation of tacit knowledge and imprecise data in organisational and operational decision making processes. The thesis introduces both practical and theoretical advances on how fuzzy logic, ontologies (fuzzy ontologies) and OWA operators can be utilized for different decision making problems. It is demonstrated how a fuzzy ontology can model tacit knowledge which was collected from wine connoisseurs. The approach can be generalised and applied also to other practically important problems, such as intrusion detection. Additionally, a fuzzy ontology is applied in a novel consensus model for group decision making. By combining the fuzzy ontology with Semantic Web affiliated techniques novel applications have been designed. These applications show how the mobilisation of knowledge can successfully utilize also imprecise data. An important part of decision making processes is undeniably aggregation, which in combination with a fuzzy ontology provides a promising basis for demonstrating the benefits that one can retrieve from handling imprecise data. The new aggregation operators defined in the thesis often provide new possibilities to handle imprecision and expert opinions. This is demonstrated through both theoretical examples and practical implementations. This thesis shows the benefits of utilizing all the available data one possess, including imprecise data. By combining the concept of fuzzy ontology with the Semantic Web movement, it aspires to show the corporate world and industry the benefits of embracing fuzzy ontologies and imprecision.