975 resultados para Android Market application


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El projecte escollit tracta de fer un videojoc de caràcter lectiu per a Android fent servir Unity. El videojoc estaria orientat a un públic infantil, justificant així la simplicitat del mateix. Consisteix en fer volar un avió agafant unes lletres que pengen en l'aire amb la finalitat de formar una paraula.

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El projecte desenvolupa una aplicació visual per a dispositius mòbils basada en PhoneGap - Cordova (HTML + CSS + JavaScript) per al control del dispositiu ODControl de l'empresa OpenDomo Services.

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Creación de un juego tipo runner para plataforma Android usando Unity3D e Inkscape.

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Aquest treball tracta sobre la realització d’una aplicació per a dispositius Android que permeti visualitzar imatges mèdiques. Amb la col·laboració del parc Taulí de Sabadell s’han realitzat tasques de recerca de requeriments com l’elaboració d’una entrevista o la realització d’una maqueta de paper que s’ha sotmès a una avaluació heurística en un procés iteratiu. Finalment, s’ha implementat una aplicació on es poden visualitzar imatges mèdiques, fer accions sobre elles com canviar el color o fer zoom i accedir a informació del pacient.

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L’objectiu d’aquest projecte és desenvolupar una aplicació per a mòbils Android que permeti visualitzar missatges curts en un monitor d’ordinador o TV. Els missatges es gestionaran a partir d’una aplicació de mòbil que inclourà la generació, gestió i transmissió dels missatges al monitor

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L'objectiu del projecte és el desenvolupament d'una aplicacióper a mòbils amb plataforma Android que generi una gimcana, per poder realitzar unagimcana més completa i propera a la nostra era actual; incorporant totes lesfuncionalitats que tenen els telèfons mòbils a les eines per resoldre un joc de proves, icrear així un concepte més actual del que és una gimcana tradicional. La creació del'aplicació pretén fomentar i establir un diàleg de saber col•laboratiu i d'aportació deconeixements entre els components del mateix grup, que potencia la implicació en lacreació de la resposta al misteri o la realització de la prova

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An optimization tool has been developed to help companies to optimize their production cycles and thus improve their overall supply chain management processes. The application combines the functionality that traditional APS (Advanced Planning System) and ARP (Automatic Replenishment Program) systems provide into one optimization run. A qualitative study was organized to investigate opportunities to expand the product’s market base. Twelve personal interviews were conducted and the results were collected in industry specific production planning analyses. Five process industries were analyzed to identify the product’s suitability to each industry sector and the most important product development areas. Based on the research the paper and the plastic film industries remain the most potential industry sectors at this point. To be successful in other industry sectors some product enhancements would be required, including capabilities to optimize multiple sequential and parallel production cycles, handle sequencing of complex finishing operations and to include master planning capabilities to support overall supply chain optimization. In product sales and marketing processes the key to success is to find and reach the people who are involved directly with the problems that the optimization tool can help to solve.

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The objective of this study is to explore how the Open Innovation paradigm is applied in by small and medium-size enterprises in Russia. The focus of the study is to understand how the processes of research and development and commercialization proceed in these kind of companies and to which extent they apply open innovation principles. Russian leadership makes certain steps for transition from the export of raw materials to an innovative model of economic growth. The research aims to disclose actual impact of these attempts. The closed innovation model and the erosion factors which lead to the destruction of an old one and emergence of new model are described. Features of open innovation implementation and intellectual property rights protection in small and medium enterprises are presented. To achieve the objective, a qualitative case study approach was chosen. Research includes facts and figures, views and opinions of management of studied companies related to innovation process in the company and in Russia in general. The research depicts the features of Open Innovation implementation by SMEs in Russia. A large number of research centers with necessary equipment and qualified personnel allow case companies to use external R&D effectively. They cooperate actively with research institutes, universities and laboratories. Thus, they apply inbound Open Innovation. On the contrary, lack of venture capital, low demand for technologies within the domestic market and weak protection of intellectual property limit the external paths to new markets. Licensing-out and creation of spin-off are isolated cases. Therefore, outbound Open Innovation is not a regular practice.

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Longitudinal surveys are increasingly used to collect event history data on person-specific processes such as transitions between labour market states. Surveybased event history data pose a number of challenges for statistical analysis. These challenges include survey errors due to sampling, non-response, attrition and measurement. This study deals with non-response, attrition and measurement errors in event history data and the bias caused by them in event history analysis. The study also discusses some choices faced by a researcher using longitudinal survey data for event history analysis and demonstrates their effects. These choices include, whether a design-based or a model-based approach is taken, which subset of data to use and, if a design-based approach is taken, which weights to use. The study takes advantage of the possibility to use combined longitudinal survey register data. The Finnish subset of European Community Household Panel (FI ECHP) survey for waves 1–5 were linked at person-level with longitudinal register data. Unemployment spells were used as study variables of interest. Lastly, a simulation study was conducted in order to assess the statistical properties of the Inverse Probability of Censoring Weighting (IPCW) method in a survey data context. The study shows how combined longitudinal survey register data can be used to analyse and compare the non-response and attrition processes, test the missingness mechanism type and estimate the size of bias due to non-response and attrition. In our empirical analysis, initial non-response turned out to be a more important source of bias than attrition. Reported unemployment spells were subject to seam effects, omissions, and, to a lesser extent, overreporting. The use of proxy interviews tended to cause spell omissions. An often-ignored phenomenon classification error in reported spell outcomes, was also found in the data. Neither the Missing At Random (MAR) assumption about non-response and attrition mechanisms, nor the classical assumptions about measurement errors, turned out to be valid. Both measurement errors in spell durations and spell outcomes were found to cause bias in estimates from event history models. Low measurement accuracy affected the estimates of baseline hazard most. The design-based estimates based on data from respondents to all waves of interest and weighted by the last wave weights displayed the largest bias. Using all the available data, including the spells by attriters until the time of attrition, helped to reduce attrition bias. Lastly, the simulation study showed that the IPCW correction to design weights reduces bias due to dependent censoring in design-based Kaplan-Meier and Cox proportional hazard model estimators. The study discusses implications of the results for survey organisations collecting event history data, researchers using surveys for event history analysis, and researchers who develop methods to correct for non-sampling biases in event history data.

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Electricity price forecasting has become an important area of research in the aftermath of the worldwide deregulation of the power industry that launched competitive electricity markets now embracing all market participants including generation and retail companies, transmission network providers, and market managers. Based on the needs of the market, a variety of approaches forecasting day-ahead electricity prices have been proposed over the last decades. However, most of the existing approaches are reasonably effective for normal range prices but disregard price spike events, which are caused by a number of complex factors and occur during periods of market stress. In the early research, price spikes were truncated before application of the forecasting model to reduce the influence of such observations on the estimation of the model parameters; otherwise, a very large forecast error would be generated on price spike occasions. Electricity price spikes, however, are significant for energy market participants to stay competitive in a market. Accurate price spike forecasting is important for generation companies to strategically bid into the market and to optimally manage their assets; for retailer companies, since they cannot pass the spikes onto final customers, and finally, for market managers to provide better management and planning for the energy market. This doctoral thesis aims at deriving a methodology able to accurately predict not only the day-ahead electricity prices within the normal range but also the price spikes. The Finnish day-ahead energy market of Nord Pool Spot is selected as the case market, and its structure is studied in detail. It is almost universally agreed in the forecasting literature that no single method is best in every situation. Since the real-world problems are often complex in nature, no single model is able to capture different patterns equally well. Therefore, a hybrid methodology that enhances the modeling capabilities appears to be a possibly productive strategy for practical use when electricity prices are predicted. The price forecasting methodology is proposed through a hybrid model applied to the price forecasting in the Finnish day-ahead energy market. The iterative search procedure employed within the methodology is developed to tune the model parameters and select the optimal input set of the explanatory variables. The numerical studies show that the proposed methodology has more accurate behavior than all other examined methods most recently applied to case studies of energy markets in different countries. The obtained results can be considered as providing extensive and useful information for participants of the day-ahead energy market, who have limited and uncertain information for price prediction to set up an optimal short-term operation portfolio. Although the focus of this work is primarily on the Finnish price area of Nord Pool Spot, given the result of this work, it is very likely that the same methodology will give good results when forecasting the prices on energy markets of other countries.

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This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.

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In recent decades, business intelligence (BI) has gained momentum in real-world practice. At the same time, business intelligence has evolved as an important research subject of Information Systems (IS) within the decision support domain. Today’s growing competitive pressure in business has led to increased needs for real-time analytics, i.e., so called real-time BI or operational BI. This is especially true with respect to the electricity production, transmission, distribution, and retail business since the law of physics determines that electricity as a commodity is nearly impossible to be stored economically, and therefore demand-supply needs to be constantly in balance. The current power sector is subject to complex changes, innovation opportunities, and technical and regulatory constraints. These range from low carbon transition, renewable energy sources (RES) development, market design to new technologies (e.g., smart metering, smart grids, electric vehicles, etc.), and new independent power producers (e.g., commercial buildings or households with rooftop solar panel installments, a.k.a. Distributed Generation). Among them, the ongoing deployment of Advanced Metering Infrastructure (AMI) has profound impacts on the electricity retail market. From the view point of BI research, the AMI is enabling real-time or near real-time analytics in the electricity retail business. Following Design Science Research (DSR) paradigm in the IS field, this research presents four aspects of BI for efficient pricing in a competitive electricity retail market: (i) visual data-mining based descriptive analytics, namely electricity consumption profiling, for pricing decision-making support; (ii) real-time BI enterprise architecture for enhancing management’s capacity on real-time decision-making; (iii) prescriptive analytics through agent-based modeling for price-responsive demand simulation; (iv) visual data-mining application for electricity distribution benchmarking. Even though this study is from the perspective of the European electricity industry, particularly focused on Finland and Estonia, the BI approaches investigated can: (i) provide managerial implications to support the utility’s pricing decision-making; (ii) add empirical knowledge to the landscape of BI research; (iii) be transferred to a wide body of practice in the power sector and BI research community.

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Älytelevisiomarkkinat ovat nykyisellään pirstaloituneet eri valmistajien kehittäessä omia älytelevisioalustoitaan, mikä tekee sovelluskehittämisestä erittäin työlästä, kun kehitystyö pitää tehdä jokaiselle alustalle erikseen. LG:n ja Philipsin perustama Smart TV Alliance pyrkii yksinkertaistamaan sovelluskehittäjien työtä, samalla houkutellen lisää kehittäjiä alalle. Työssä tutustutaan tuotealustoihin, avoimeen ja suljettuun innovaatioon, sekä alliansseihin. Lisäksi perehdytään älytelevisioihin sekä tietenkin itse Smart TV Allianceen. Lisäksi tarkastellaan nykyistä markkina-asetelmaa ja arvioidaan yksittäisten toimijoiden tilannetta ja mahdollisia toimenpiteitä. Työn painopiste on fyysisen laitevalmistajan ja käyttöjärjestelmän kehittäjän/ylläpitäjän näkökulmasta. Työn kannalta tärkeässä roolissa ovat ohjelmistopohjaiset tuotealustat. Eritoten työssä käsitellään älytelevisioiden ohjelmistoa tuotealustana, mutta hyvä vaihtoehtoinen ja eritoten monille käytännönläheisempi esimerkki on tietokoneen käyttöjärjestelmä, kuten Microsoft Windows tai useat Linux-pohjaiset käyttöjärjestelmät. Keskeisenä ominaisuutena näissä kaikissa on, että itse käyttöjärjestelmä toimii yhteisenä pohjana, jonka päälle voidaan rakentaa muuta toiminnallisuutta, kuten pelejä ja toimistosovelluksia.

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The recent emergence of a new generation of mobile application marketplaces has changed the business in the mobile ecosystems. The marketplaces have gathered over a million applications by hundreds of thousands of application developers and publishers. Thus, software ecosystems—consisting of developers, consumers and the orchestrator—have emerged as a part of the mobile ecosystem. This dissertation addresses the new challenges faced by mobile application developers in the new ecosystems through empirical methods. By using the theories of two-sided markets and business ecosystems as the basis, the thesis assesses monetization and value creation in the market as well as the impact of electronic Word-of-Mouth (eWOM) and developer multihoming— i. e. contributing for more than one platform—in the ecosystems. The data for the study was collected with web crawling from the three biggest marketplaces: Apple App Store, Google Play and Windows Phone Store. The dissertation consists of six individual articles. The results of the studies show a gap in monetization among the studied applications, while a majority of applications are produced by small or micro-enterprises. The study finds only weak support for the impact of eWOM on the sales of an application in the studied ecosystem. Finally, the study reveals a clear difference in the multi-homing rates between the top application developers and the rest. This has, as discussed in the thesis, an impact on the future market analyses—it seems that the smart device market can sustain several parallel application marketplaces.

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Tässä työssä esiteltiin Android laitteisto- ja sovellusalustana sekä kuvattiin, kuinka Android-pelisovelluksen käyttöliittymä voidaan pitää yhtenäisenä eri näyttölaitteilla skaalauskertoimien ja ankkuroinnin avulla. Toisena osiona työtä käsiteltiin yksinkertaisia tapoja, joilla pelisovelluksien suorituskykyä voidaan parantaa. Näistä tarkempiin mittauksiin valittiin matalatarkkuuksinen piirtopuskuri ja näkymättömissä olevien kappaleiden piilotus. Mittauksissa valitut menetelmät vaikuttivat demosovelluksen suorituskykyyn huomattavasti. Tässä työssä rajauduttiin Android-ohjelmointiin Java-kielellä ilman ulkoisia kirjastoja, jolloin työn tuloksia voi helposti hyödyntää mahdollisimman monessa eri käyttökohteessa.