48 resultados para Consumption Volatility


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The primary purpose of this research is to develop an enhanced understanding of how consumption values influence environmentally responsible consumption of print and digital media. Theoretical elaboration considers the associations of functional, social and emotional consumption values, green consumer segmentation and media consumption. Additionally, the purpose is to identify consumer perceptions of print and digital media’s environmental responsibility. Empirical analysis was based on qualitative interviews with a sample of 20 Finnish consumers categorized in two segments: young adults and middle aged consumers. Primary data collection was conducted through individual, semi-structured interviews. To analyze the respondents’ approach on the topic, the interviews disclosed themes of media consumption, perceived environmental friendliness of media, norms of behavior and consumers’ general consumption patterns. The results implicate functional value dominated the consumption decision-making process both in a general level and in media consumption. In addition to functional value, environmental responsibility does provide consumers with both emotional and social values. Analysis on perceived environmental responsibility of media demonstrated consumers generally perceive digital media as an environmentally responsible alternative because it does not create physical paper waste. Nevertheless, the perceptions of environmental responsibility and media consumption patterns lacked a consistent connection. Though, both theory and empirical results indicated an average consumer lacks a comprehensive understanding of digital and print media’s life-cycle and hence their environmental advantages and disadvantages.

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Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to manufacture metal parts layer by layer by assist of laser beam. The development of the technology from building just prototype parts to functional parts is due to design flexibility. And also possibility to manufacture tailored and optimised components in terms of performance and strength to weight ratio of final parts. The study of energy and raw material consumption in LAM is essential as it might facilitate the adoption and usage of the technique in manufacturing industries. The objective this thesis was find the impact of LAM on environmental and economic aspects and to conduct life cycle inventory of CNC machining and LAM in terms of energy and raw material consumption at production phases. Literature overview in this thesis include sustainability issues in manufacturing industries with focus on environmental and economic aspects. Also life cycle assessment and its applicability in manufacturing industry were studied. UPLCI-CO2PE! Initiative was identified as mostly applied exiting methodology to conduct LCI analysis in discrete manufacturing process like LAM. Many of the reviewed literature had focused to PBF of polymeric material and only few had considered metallic materials. The studies that had included metallic materials had only measured input and output energy or materials of the process and compared to different AM systems without comparing to any competitive process. Neither did any include effect of process variation when building metallic parts with LAM. Experimental testing were carried out to make dissimilar samples with CNC machining and LAM in this thesis. Test samples were designed to include part complexity and weight reductions. PUMA 2500Y lathe machine was used in the CNC machining whereas a modified research machine representing EOSINT M-series was used for the LAM. The raw material used for making the test pieces were stainless steel 316L bar (CNC machined parts) and stainless steel 316L powder (LAM built parts). An analysis of power, time, and the energy consumed in each of the manufacturing processes on production phase showed that LAM utilises more energy than CNC machining. The high energy consumption was as result of duration of production. Energy consumption profiles in CNC machining showed fluctuations with high and low power ranges. LAM energy usage within specific mode (standby, heating, process, sawing) remained relatively constant through the production. CNC machining was limited in terms of manufacturing freedom as it was not possible to manufacture all the designed sample by machining. And the one which was possible was aided with large amount of material removed as waste. Planning phase in LAM was shorter than in CNC machining as the latter required many preparation steps. Specific energy consumption (SEC) were estimated in LAM based on the practical results and assumed platform utilisation. The estimated platform utilisation showed SEC could reduce when more parts were placed in one build than it was in with the empirical results in this thesis (six parts).

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Research has highlighted the adequacy of Markov regime-switching model to address dynamic behavior in long term stock market movements. Employing a purposed Extended regime-switching GARCH(1,1) model, this thesis further investigates the regime dependent nonlinear relationship between changes in oil price and stock market volatility in Saudi Arabia, Norway and Singapore for the period of 2001-2014. Market selection is prioritized to national dependency on oil export or import, which also rationalizes the fitness of implied bivariate volatility model. Among two regimes identified by the mean model, high stock market return-low volatility regime reflects the stable economic growth periods. The other regime characterized by low stock market return-high volatility coincides with episodes of recession and downturn. Moreover, results of volatility model provide the evidence that shocks in stock markets are less persistent during the high volatility regime. While accelerated oil price rises the stock market volatility during recessions, it reduces the stock market risk during normal growth periods in Singapore. In contrast, oil price showed no significant notable impact on stock market volatility of target oil-exporting countries in either of the volatility regime. In light to these results, international investors and policy makers could benefit the risk management in relation to oil price fluctuation.

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Tässä diplomityössä on tutkittu lauhdekapasiteetin ennenaikaisen markkinoilta poistumisen energiataloudellisia vaikutuksia. Tarkastelu toteutettiin sähkömarkkinamallinnuksen avulla luomalla kaksi erilaista lauhdekapasiteettiskenaariota perustuen arvioituun lauhdekapasiteetin poistumiseen sekä vastavuoroisesti sen säilymiseen markkinoilla. Skenaarioiden vaikutuksia tutkittiin myös herkkyystarkasteluin ja tuloksia analysoitiin energiataloudellisesta näkökulmasta. Työn tavoitteena oli selvittää lauhdekapasiteetin ennenaikaisen poistumisen energiataloudellista kustannusta. Viime vuosien pitkittynyt talouden taantuma on hillinnyt kysynnän ennakoitua kehitystä johtaen alhaiseen sähkön markkinahintatasoon. Samalla tiukentuneet energiatuotannon ympäristövaatimukset asettavat investointirasitteita perinteisille voimalaitoksille heikentäen niiden taloudellisen kannattavuuden edellytyksiä. Markkinasähkön alhainen hintataso yhdessä investointirasitteiden kanssa asettaa haasteita etenkin usein rajatuotantomuotona toimiville lauhdelaitoksille. Alhaisen kannattavuuden seurauksena lauhdekapasiteettia arvioidaan poistuvan ennen teknisen käyttöiän täyttymistä markkinoilta merkittävästi lähivuosina. Kapasiteetin poistuminen kasvattaa oman tuotannon ja kysynnän välistä tehovajetta, minkä vuoksi sähköjärjestelmän nähdään tiukentuvan merkittävästi ennen rakenteilla olevan ydinvoimalaitoksen valmistumista. Työssä toteutettujen mallinnusten perusteella lauhdekapasiteetin väheneminen nostaa sähkön hintatasoa sekä lisää korkeiden hintapiikkien esiintymistä merkittävästi suhteessa korkeamman kapasiteetin tuloksiin. Sähköjärjestelmä on hyvin tiukka ennen rakenteilla olevan ydinvoimalaitoksen käyttöönottoa, minkä vuoksi lauhdekapasiteetin eroavaisuuksien vaikutukset ovat merkittävä etenkin poikkeuksellisen kylmänä vuotena. Lauhdekapasiteetin merkitys pienenee selvästi 2020-luvulla, kun oma tuotantokapasiteetti kasvaa. Työn tulosten perusteella lähivuosina alhaisemman lauhdekapasiteetin aiheuttama vuotuinen energiataloudellinen kustannus on huomattavasti korkeampi kuin laitosten kannattavan ylläpidon vaatima kustannus.

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Battery consumption in mobile applications development is a very important aspect and has to be considered by all the developers in their applications. This study will present an analysis of different relevant concepts and parameters that may have impact on energy consumption of Windows Phone applications. This operating system was chosen because there is limited research even though there are related studies for Android an iOS operating systems. Furthermore, another reason is the increasing number of Windows Phone users. The objective of this research is to categorise the energy consumption parameters (e.g. use of one thread or several thread for the same output). The result for each group of experiment will be analyzed and a rule will be derived. The set of derived rules will serve as a guide for developers who intend to develop energy efficient Windows Phone applications. For each experiment, one application is created for each concept and the results are presented in two ways: a table and a chart. The table presents the duration of the experiment, the battery consumed by the experiment, the expected battery lifetime and the energy consumption, while the charts display the energy distribution based on the main threads: UI thread, application thread and network thread.

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The energy consumption of IT equipments is becoming an issue of increasing importance. In particular, network equipments such as routers and switches are major contributors to the energy consumption of internet. Therefore it is important to understand how the relationship between input parameters such as bandwidth, number of active ports, traffic-load, hibernation-mode and their impact on energy consumption of a switch. In this paper, the energy consumption of a switch is analyzed in extensive experiments. A fuzzy rule-based model of energy consumption of a switch is proposed based on the result of experiments. The model can be used to predict the energy saving when deploying new switches by controlling the parameters to achieve desired energy consumption and subsequent performance. Furthermore, the model can also be used for further researches on energy saving techniques such as energy-efficient routing protocol, dynamic link shutdown, etc.

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At present, one of the main concerns of green network is to minimize the power consumption of network infrastructure. Surveys show that, the highest amount of power is consumed by the network devices during its runtime. However to control this power consumption it is important to know which factors has highest impact on this matter. This paper is focused on the measurement and modeling the power consumption of an Ethernet switch during its runtime considering various types of input parameters with all possible combinations. For the experiment, three input parameters are chosen. They are bandwidth, link load and number of connections. The output to be measured is the power consumption of the Ethernet switch. Due to the uncertain power consuming pattern of the Ethernet switch a fully-comprehensive experimental evaluation would require an unfeasible and cumbersome experimental phase. Because of that, design of experiment (DoE) method has been applied to obtain adequate information on the effects of each input parameters on the power consumption. The whole work consists of three parts. In the first part a test bed is planned with input parameters and the power consumption of the switch is measured. The second part is about generating a mathematical model with the help of design of experiment tools. This model can be used for measuring precise power consumption in different scenario and also pinpoint the parameters with higher influence in power consumption. And in the last part, the mathematical model is evaluated by comparing with the experimental values.

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The power is still today an issue in wearable computing applications. The aim of the present paper is to raise awareness of the power consumption of wearable computing devices in specific scenarios to be able in the future to design energy efficient wireless sensors for context recognition in wearable computing applications. The approach is based on a hardware study. The objective of this paper is to analyze and compare the total power consumption of three representative wearable computing devices in realistic scenarios such as Display, Speaker, Camera and microphone, Transfer by Wi-Fi, Monitoring outdoor physical activity and Pedometer. A scenario based energy model is also developed. The Samsung Galaxy Nexus I9250 smartphone, the Vuzix M100 Smart Glasses and the SimValley Smartwatch AW-420.RX are the three devices representative of their form factors. The power consumption is measured using PowerTutor, an android energy profiler application with logging option and using unknown parameters so it is adjusted with the USB meter. The result shows that the screen size is the main parameter influencing the power consumption. The power consumption for an identical scenario varies depending on the wearable devices meaning that others components, parameters or processes might impact on the power consumption and further study is needed to explain these variations. This paper also shows that different inputs (touchscreen is more efficient than buttons controls) and outputs (speaker sensor is more efficient than display sensor) impact the energy consumption in different way. This paper gives recommendations to reduce the energy consumption in healthcare wearable computing application using the energy model.

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Volatility has a central role in various theoretical and practical applications in financial markets. These include the applications related to portfolio theory, derivatives pricing and financial risk management. Both theoretical and practical applications require good estimates and forecasts for the asset return volatility. The goal of this study is to examine the forecast performance of one of the more recent volatility measures, model-free implied volatility. Model-free implied volatility is extracted from the prices in the option markets, and it aims to provide an unbiased estimate for the market’s expectation on the future level of volatility. Since it is extracted from the option prices, model-free implied volatility should contain all the relevant information that the market participants have. Moreover, model-free implied volatility requires less restrictive assumptions than the commonly used Black-Scholes implied volatility, which means that it should be less biased estimate for the market’s expectations. Therefore, it should also be a better forecast for the future volatility. The forecast performance of model-free implied volatility is evaluated by comparing it to the forecast performance of Black-Scholes implied volatility and GARCH(1,1) forecast. Weekly forecasts for six years period were calculated for the forecasted variable, German stock market index DAX. The data consisted of price observations for DAX index options. The forecast performance was measured using econometric methods, which aimed to capture the biasedness, accuracy and the information content of the forecasts. The results of the study suggest that the forecast performance of model-free implied volatility is superior to forecast performance of GARCH(1,1) forecast. However, the results also suggest that the forecast performance of model-free implied volatility is not as good as the forecast performance of Black-Scholes implied volatility, which is against the hypotheses based on theory. The results of this study are consistent with the majority of prior research on the subject.

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This thesis examines the interdependence of macroeconomic variables, stock market returns and stock market volatility in Latin America between 2000 and 2015. Argentina, Brazil, Chile, Colombia, Mexico and Peru were chosen as the sample markets, while inflation, interest rate, exchange rate, money supply, oil and gold were chosen as the sample macroeconomic variables. Bivariate VAR (1) model was applied to examine the mean return spillovers between the variables, whereas GARCH (1, 1) – BEKK model was applied to capture the volatility spillovers. The sample was divided into two smaller sub-periods, where the first sub-period covers from 2000 to 2007, and the second sub-period covers from 2007 to 2015. The empirical results report significant shock transmissions and volatility spillovers between inflation, interest rate, exchange rate, money supply, gold, oil and the selected markets, which suggests interdependence between the variables.

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Return and volatility dynamics in financial markets across the world have recently become important for the purpose of asset pricing, portfolio allocation and risk management. However, volatility, which come about as a result of the actions of market participants can help adapt to different situations and perform when it really matters. With recent development and liberalization among financial markets in emerging and frontier markets, the need for how the equity and foreign exchange markets interact and the extent to which return and volatility spillover are spread across countries is of importance to investors and policy makers at large. Financial markets in Africa have received attention leading to investors diversifying into them in times of crisis and contagion effects in developed countries. Regardless of the benefits these markets may offer, investors must be wary of issues such as thin trading, volatility that exists in the equity and currency markets and its related fluctuations. The study employs a VAR-GARCH BEKK model to study the return and volatility dynamics between the stock and foreign exchange sectors and among the equity markets of Egypt, Kenya, Nigeria, South Africa and Tunisia. The main findings suggest a higher dependence of own return in the stock markets and a one way return spillover from the currencies to the equity markets except for South Africa which has a weaker interrelation among the two markets. There is a relatively limited integration among the equity markets. Return and volatility spillover is mostly uni-directional except for a bi-directional relationship between the equity markets of Egypt and Tunisia. The study implication still proves a benefit for portfolio managers diversifying in these African equity markets, since they are independent of each other and may not be highly affected by the influx of negative news from elsewhere. However, there is the need to be wary of return and volatility spillover between the equity and currency markets, hence devising better hedging strategies to curb them.

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Climate change is one of the biggest challenges faced by this generation. Despite being the single most important environmental challenge facing the planet and despite over two decades of international climate negotiations, global greenhouse gas (GHG) emissions continue to rise. By the middle of this century, GHGs must be reduced by as much as 40-70% if dangerous climate change is to be avoided. In the Kyoto Protocol no quantitative emission limitation and reduction commitments were placed on the developing countries. For the planning of the future commitments period and possible participation of developing countries, information of the functioning of the energy systems, CO2 emissions development in different sectors, energy use and technological development in developing countries is essential. In addition to the per capita emissions, the efficiency of the energy system in relation to GHG emissions is crucial for the decision of future long-term burden sharing between countries. Country’s future development of CO2 emissions can be defined by the estimated CO2 intensity of the future and the estimated GDP growth. The changes in CO2 intensity depend on several factors, but generally developed countries’ intensity has been increasing in the industrialization phase and decreasing when their economy shifts more towards the system dominated by the service sector. The level of the CO2 intensity depends by a large extent on the production structure and the energy sources that are used. Currently one of the most urgent issues regarding global climate change is to decide the future of the Kyoto Protocol. Negotiations on this topic have already been initiated, with the aim of being finalised by the 2015. This thesis provides insights into the various approaches that can be used to characterise the concept of comparable efforts for developing countries in a future international climate agreement. The thesis examines the post-Kyoto burden sharing questions for developing countries using the contraction and convergence model, which is one approach that has been proposed to allocate commitments regarding future GHG emissions mitigation. This new approach is a practical tool for the evaluation of the Kyoto climate policy process and global climate change negotiations from the perspective of the developing countries.