Replacing Copper with New Carbon Nanomaterials in Electrical Machine Windings

Electrical machines have significant improvement potential. Nevertheless, the field is characterized by incremental innovations. Admittedly, steady improvement has been achieved, but no breakthrough development. Radical development in the field would require the introduction of new elements, such that may change the whole electrical machine industry system. Recent technological advancements in nanomaterials have opened up new horizons for the macroscopic application of carbon nanotube (CNT) fibres. With values of 100 MS/m measured on individual CNTs, CNT fibre materials hold promise for conductivities far beyond those of metals. Highly conductive, lightweight and strong CNT yarn is finally within reach; it could replace copper as a potentially better winding material. Although not yet providing low resistivity, the newest CNT yarn offers attractive perspectives for accelerated efficiency improvement of electrical machines. In this article, the potential for using new CNT materials to replace copper in machine windings is introduced. It does so, firstly, by describing the environment for a change that could revolutionize the industry and, secondly, by presenting the breakthrough results of a prototype construction. In the test motor, which is to our knowledge the first in its kind, the presently most electrically conductive carbon nanotube yarn replaces usual copper in the windings.

Design and Drive-Cycle Based Analysis of Direct-Driven Permanent Magnet Synchronous Machine for a Small Urban Use Electric Vehicle

A direct-driven permanent magnet synchronous machine for a small urban use electric vehicle is presented. The measured performance of the machine at the test bench as well as the performance over the modified New European Drive Cycle will be given. The effect of optimal current components, maximizing the efficiency and taking into account the iron loss, is compared with the simple id=0 – control. The machine currents and losses during the drive cycle are calculated and compared with each other.

FANCD2 Western blot as a diagnostic tool for Brazilian patients with Fanconi anemia

Fanconi anemia is a rare hereditary disease showing genetic heterogeneity due to a variety of mutations in genes involved in DNA repair pathways, which may lead to different clinical manifestations. Phenotypic variability makes diagnosis difficult based only on clinical manifestations, therefore laboratory tests are necessary. New advances in molecular pathogenesis of this disease led researchers to develop a diagnostic test based on Western blot for FANCD2. The objective of the present study was to determine the efficacy of this method for the diagnosis of 84 Brazilian patients with Fanconi anemia, all of whom tested positive for the diepoxybutane test, and 98 healthy controls. The FANCD2 monoubiquitinated isoform (FANCDS+/FANCD2L-) was not detected in 77 patients (91.7%). In 2 patients (2.4%), there was an absence of both the monoubiquitinated and the non-ubiquitinated proteins (FANCD2S-/FANCD2L-) and 5 patients (5.9%) had both isoforms (FANCD2S+/FANCD2L+). This last phenotype suggests downstream subtypes or mosaicism. All controls were diepoxybutane negative and were also negative on the FANCD2 Western blot. The Western blot for FANCD2 presented a sensitivity of 94% (79/84) and specificity of 100% (98/98). This method was confirmed as an efficient approach to screen Brazilian patients with deleterious mutations on FANCD2 (FANCD2S-/FANCD2L-) or other upstream genes of the FA/BRCA pathway (FANCDS+/FANCD2L-), to confirm the chromosome breakage test and to classify patients according to the level of FA/BRCA pathway defects. However, patients showing both FANCD2 isoforms (FANCD2S+/FANCD2L+) require additional studies to confirm mutations on downstream Fanconi anemia genes or the presence of mosaicism.

Cell cycle synchronization and BrdU incorporation as a tool to study the possible selective elimination of ErbB1 gene in the micronuclei in A549 cells

Lung cancer often exhibits molecular changes, such as the overexpression of the ErbB1 gene that encodes epidermal growth factor receptor (EGFR). ErbB1 amplification and mutation are associated with tumor aggressiveness and low response to therapy. The aim of the present study was to design a schedule to synchronize the cell cycle of A549 cell line (a non-small cell lung cancer) and to analyze the possible association between the micronuclei (MNs) and the extrusion of ErbB1 gene extra-copies. After double blocking, by the process of fetal bovine serum deprivation and vincristine treatment, MNs formation was monitored with 5-bromo-2-deoxyuridine (BrdU) incorporation, which is an S-phase marker. Statistical analyses allowed us to infer that MNs may arise both in mitosis as well as in interphase. The MNs were able to replicate their DNA and this process seemed to be non-synchronous with the main cell nuclei. The presence of ErbB1 gene in the MNs was evaluated by fluorescent in situ hybridization (FISH). ErbB1 sequences were detected in the MNs, but a relation between the MNs formation and extrusion of amplified ErbB1could not be established. The present study sought to elucidate the meaning of MNs formation and its association with the elimination of oncogenes or other amplified sequences from the tumor cells.

Nichesourcing The Uralic Languages For The Benefit Of Linguistic Research And Lingual Societies

The emerging technologies have recently challenged the libraries to reconsider their role as a mere mediator between the collections, researchers, and wider audiences (Sula, 2013), and libraries, especially the nationwide institutions like national libraries, haven’t always managed to face the challenge (Nygren et al., 2014). In the Digitization Project of Kindred Languages, the National Library of Finland has become a node that connects the partners to interplay and work for shared goals and objectives. In this paper, I will be drawing a picture of the crowdsourcing methods that have been established during the project to support both linguistic research and lingual diversity. The National Library of Finland has been executing the Digitization Project of Kindred Languages since 2012. The project seeks to digitize and publish approximately 1,200 monograph titles and more than 100 newspapers titles in various, and in some cases endangered Uralic languages. Once the digitization has been completed in 2015, the Fenno-Ugrica online collection will consist of 110,000 monograph pages and around 90,000 newspaper pages to which all users will have open access regardless of their place of residence. The majority of the digitized literature was originally published in the 1920s and 1930s in the Soviet Union, and it was the genesis and consolidation period of literary languages. This was the era when many Uralic languages were converted into media of popular education, enlightenment, and dissemination of information pertinent to the developing political agenda of the Soviet state. The ‘deluge’ of popular literature in the 1920s to 1930s suddenly challenged the lexical orthographic norms of the limited ecclesiastical publications from the 1880s onward. Newspapers were now written in orthographies and in word forms that the locals would understand. Textbooks were written to address the separate needs of both adults and children. New concepts were introduced in the language. This was the beginning of a renaissance and period of enlightenment (Rueter, 2013). The linguistically oriented population can also find writings to their delight, especially lexical items specific to a given publication, and orthographically documented specifics of phonetics. The project is financially supported by the Kone Foundation in Helsinki and is part of the Foundation’s Language Programme. One of the key objectives of the Kone Foundation Language Programme is to support a culture of openness and interaction in linguistic research, but also to promote citizen science as a tool for the participation of the language community in research. In addition to sharing this aspiration, our objective within the Language Programme is to make sure that old and new corpora in Uralic languages are made available for the open and interactive use of the academic community as well as the language societies. Wordlists are available in 17 languages, but without tokenization, lemmatization, and so on. This approach was verified with the scholars, and we consider the wordlists as raw data for linguists. Our data is used for creating the morphological analyzers and online dictionaries at the Helsinki and Tromsø Universities, for instance. In order to reach the targets, we will produce not only the digitized materials but also their development tools for supporting linguistic research and citizen science. The Digitization Project of Kindred Languages is thus linked with the research of language technology. The mission is to improve the usage and usability of digitized content. During the project, we have advanced methods that will refine the raw data for further use, especially in the linguistic research. How does the library meet the objectives, which appears to be beyond its traditional playground? The written materials from this period are a gold mine, so how could we retrieve these hidden treasures of languages out of the stack that contains more than 200,000 pages of literature in various Uralic languages? The problem is that the machined-encoded text (OCR) contains often too many mistakes to be used as such in research. The mistakes in OCRed texts must be corrected. For enhancing the OCRed texts, the National Library of Finland developed an open-source code OCR editor that enabled the editing of machine-encoded text for the benefit of linguistic research. This tool was necessary to implement, since these rare and peripheral prints did often include already perished characters, which are sadly neglected by the modern OCR software developers, but belong to the historical context of kindred languages and thus are an essential part of the linguistic heritage (van Hemel, 2014). Our crowdsourcing tool application is essentially an editor of Alto XML format. It consists of a back-end for managing users, permissions, and files, communicating through a REST API with a front-end interface—that is, the actual editor for correcting the OCRed text. The enhanced XML files can be retrieved from the Fenno-Ugrica collection for further purposes. Could the crowd do this work to support the academic research? The challenge in crowdsourcing lies in its nature. The targets in the traditional crowdsourcing have often been split into several microtasks that do not require any special skills from the anonymous people, a faceless crowd. This way of crowdsourcing may produce quantitative results, but from the research’s point of view, there is a danger that the needs of linguists are not necessarily met. Also, the remarkable downside is the lack of shared goal or the social affinity. There is no reward in the traditional methods of crowdsourcing (de Boer et al., 2012). Also, there has been criticism that digital humanities makes the humanities too data-driven and oriented towards quantitative methods, losing the values of critical qualitative methods (Fish, 2012). And on top of that, the downsides of the traditional crowdsourcing become more imminent when you leave the Anglophone world. Our potential crowd is geographically scattered in Russia. This crowd is linguistically heterogeneous, speaking 17 different languages. In many cases languages are close to extinction or longing for language revitalization, and the native speakers do not always have Internet access, so an open call for crowdsourcing would not have produced appeasing results for linguists. Thus, one has to identify carefully the potential niches to complete the needed tasks. When using the help of a crowd in a project that is aiming to support both linguistic research and survival of endangered languages, the approach has to be a different one. In nichesourcing, the tasks are distributed amongst a small crowd of citizen scientists (communities). Although communities provide smaller pools to draw resources, their specific richness in skill is suited for complex tasks with high-quality product expectations found in nichesourcing. Communities have a purpose and identity, and their regular interaction engenders social trust and reputation. These communities can correspond to research more precisely (de Boer et al., 2012). Instead of repetitive and rather trivial tasks, we are trying to utilize the knowledge and skills of citizen scientists to provide qualitative results. In nichesourcing, we hand in such assignments that would precisely fill the gaps in linguistic research. A typical task would be editing and collecting the words in such fields of vocabularies where the researchers do require more information. For instance, there is lack of Hill Mari words and terminology in anatomy. We have digitized the books in medicine, and we could try to track the words related to human organs by assigning the citizen scientists to edit and collect words with the OCR editor. From the nichesourcing’s perspective, it is essential that altruism play a central role when the language communities are involved. In nichesourcing, our goal is to reach a certain level of interplay, where the language communities would benefit from the results. For instance, the corrected words in Ingrian will be added to an online dictionary, which is made freely available for the public, so the society can benefit, too. This objective of interplay can be understood as an aspiration to support the endangered languages and the maintenance of lingual diversity, but also as a servant of ‘two masters’: research and society.

Quality assurance of refuse derived fuel with machine vision

This thesis studies the use of machine vision in RDF quality assurance and manufacturing. Currently machine vision is used in recycling and material detection and some commer- cial products are available in the market. In this thesis an on-line machine vision system is proposed for characterizing particle size. The proposed machine vision system is based on the mapping between image segmenta- tion and the ground truth of the particle size. The results shows that the implementation of such machine vision system is feasible.

Sentence Compression with Supervised Machine Learning

The subject of the thesis is automatic sentence compression with machine learning, so that the compressed sentences remain both grammatical and retain their essential meaning. There are multiple possible uses for the compression of natural language sentences. In this thesis the focus is generation of television program subtitles, which often are compressed version of the original script of the program. The main part of the thesis consists of machine learning experiments for automatic sentence compression using different approaches to the problem. The machine learning methods used for this work are linear-chain conditional random fields and support vector machines. Also we take a look which automatic text analysis methods provide useful features for the task. The data used for machine learning is supplied by Lingsoft Inc. and consists of subtitles in both compressed an uncompressed form. The models are compared to a baseline system and comparisons are made both automatically and also using human evaluation, because of the potentially subjective nature of the output. The best result is achieved using a CRF - sequence classification using a rich feature set. All text analysis methods help classification and most useful method is morphological analysis. Tutkielman aihe on suomenkielisten lauseiden automaattinen tiivistäminen koneellisesti, niin että lyhennetyt lauseet säilyttävät olennaisen informaationsa ja pysyvät kieliopillisina. Luonnollisen kielen lauseiden tiivistämiselle on monta käyttötarkoitusta, mutta tässä tutkielmassa aihetta lähestytään television ohjelmien tekstittämisen kautta, johon käytännössä kuuluu alkuperäisen tekstin lyhentäminen televisioruudulle paremmin sopivaksi. Tutkielmassa kokeillaan erilaisia koneoppimismenetelmiä tekstin automaatiseen lyhentämiseen ja tarkastellaan miten hyvin erilaiset luonnollisen kielen analyysimenetelmät tuottavat informaatiota, joka auttaa näitä menetelmiä lyhentämään lauseita. Lisäksi tarkastellaan minkälainen lähestymistapa tuottaa parhaan lopputuloksen. Käytetyt koneoppimismenetelmät ovat tukivektorikone ja lineaarisen sekvenssin mallinen CRF. Koneoppimisen tukena käytetään tekstityksiä niiden eri käsittelyvaiheissa, jotka on saatu Lingsoft OY:ltä. Luotuja malleja vertaillaan Lopulta mallien lopputuloksia evaluoidaan automaattisesti ja koska teksti lopputuksena on jossain määrin subjektiivinen myös ihmisarviointiin perustuen. Vertailukohtana toimii kirjallisuudesta poimittu menetelmä. Tutkielman tuloksena paras lopputulos saadaan aikaan käyttäen CRF sekvenssi-luokittelijaa laajalla piirrejoukolla. Kaikki kokeillut teksin analyysimenetelmät auttavat luokittelussa, joista tärkeimmän panoksen antaa morfologinen analyysi.

Tuottavuuden ja investointitehokkuuden parantaminen kunnallisteknisissä töissä

Tutkimuksen tavoitteena oli selvittää keinoja parantaa tuottavuutta ja investointitehokkuutta kunnallisteknisissä töissä. Tutkimusmenetelmäksi valittiin konstruktiivinen tutkimusmenetelmä, jossa käytännölliseen ongelmaan luodaan teoriapohjan kautta ratkaisuehdotus. Työn teoriaosuus käsittelee palveluiden tuottavuutta ja sen mittaamista. Työn tuloksena syntyi excel-työkalu, jonka avulla on mahdollista tarkastella palveluntuottajan konekannan aiheuttamia kustannuksia ja tuottoja. Työkalu laskee konekohtaiset kustannukset ja tuotot, joiden avulla palveluntuottajalle on mahdollista osoittaa aiempien investointien kannattavuus. Työkalu laskee kustannus- ja tuottoarvion myös vaihtoehtoiselle konekannalle, jossa alhaisen käyttöasteen koneita korvataan monipuolisemmalla kalustolla. Palveluntuottajan konekannan hallinta ja kustannusrakenteen tarkka määrittely ovat tärkeässä roolissa tuottavuuden ja kannattavuuden kehittämisessä. Työkalu mahdollistaa myös eri kustannuserissä tapahtuvien muutosten vaikutusten arvioinnin, mikä auttaa palveluntuottajia toiminnan pitkäjänteisessä kehittämisessä.

Automated static image analysis as a novel tool in describing the physical properties of dietary fiber

Abstract The growing interest in the usage of dietary fiber in food has caused the need to provide precise tools for describing its physical properties. This research examined two dietary fibers from oats and beets, respectively, in variable particle sizes. The application of automated static image analysis for describing the hydration properties and particle size distribution of dietary fiber was analyzed. Conventional tests for water holding capacity (WHC) were conducted. The particles were measured at two points: dry and after water soaking. The most significant water holding capacity (7.00 g water/g solid) was achieved by the smaller sized oat fiber. Conversely, the water holding capacity was highest (4.20 g water/g solid) in larger sized beet fiber. There was evidence for water absorption increasing with a decrease in particle size in regards to the same fiber source. Very strong correlations were drawn between particle shape parameters, such as fiber length, straightness, width and hydration properties measured conventionally. The regression analysis provided the opportunity to estimate whether the automated static image analysis method could be an efficient tool in describing the hydration properties of dietary fiber. The application of the method was validated using mathematical model which was verified in comparison to conventional WHC measurement results.

A Project Portfolio Tool for Forecasting Small Projects Profitability

The case company in this study is a large industrial engineering company whose business is largely based on delivering a wide-range of engineering projects. The aim of this study is to create and develop a fairly simple Excel-based tool for the sales department. The tool’s main function is to estimate and visualize the profitability of various small projects. The study also aims to find out other possible and more long-term solutions for tackling the problem in the future. The study is highly constructive and descriptive as it focuses on the development task and in the creation of a new operating model. The developed tool focuses on estimating the profitability of the small orders of the selected project portfolio currently on the bidding-phase (prospects) and will help the case company in the monthly reporting of sales figures. The tool will analyse the profitability of a certain project by calculating its fixed and variable costs, then further the gross margin and operating profit. The bidding phase of small project is a phase that has not been covered fully by the existing tools within the case company. The project portfolio tool can be taken into use immediately within the case company and it will provide fairly accurate estimate of the profitability figures of the recently sold small projects.