3D-NoC architectures are the amalgamation of the 3D integration (Die stacking of 3D-IC Technology) with the increased scalability found in NoC. Originally, it was proposed to tackle the problem of increasing the number of cores in the 2D plane which seems incompetent due to long distance interconnects. This architecture is aimed to optimize performance, power consumption, achieve low latency and increase the network bandwidth. Nevertheless, as more dies were being stacked vertically, IC operating frequency increases and this leads to some thermal issues which include high power density which increases average temperature. In addition to that, longer heat dissipation path results in different heat dissipation in each layer of the NoC which worsen the situation. An increase in the overall power consumption increases the average temperature, reduces performance and reliability. In this paper, an adaptive thermal-aware management scheme was proposed for 3D-NoCs, concentrating more on the hotspot regions in the network. This proposed protocol employs the thermal state of intermediate nodes and flits properties in a random uniform distributive way for packet routing. The proposed algorithm increases network availability and tends to distribute the temperature of the system evenly and uniformly within the network and making sure that packets are not forwarded to the hotspot node(s) and only flits with certain properties in the distribution are forwarded to the hotspot node(s). Before or during transmission, these two distributions must be calculated alongside the current node temperature to knowing which state of the distribution that node and flit belong to. The simulation shows this gave better performance in throughput and reliability of the network by reducing the number of hotspot nodes in the NoC. The proposed algorithm also reduces power consumption which is a function of temperature. Simulations show that our proposed algorithm reduces the total power/energy consumed by more than 59\% and throughput is improved by 69\% compared to a traditional XYZ routing. / Graduate

No description available.

Energy demand forecasting, and specifically electricity demand forecasting, is a fun-damental feature in both industry and research. Forecasting techniques assist all electricity market participants in accurate planning, selling and purchasing decisions and strategies. Generation and distribution of electricity require appropriate, precise and accurate forecasting methods. Also accurate forecasting models assist producers, researchers and economists to make proper and beneficial future decisions. There are several research papers, which investigate this fundamental aspect and attempt var-ious statistical techniques. Although weather and economic effects have significant influences on electricity demand, in this study they are purposely eliminated from investigation. This research considers calendar-related effects such as months of the year, weekdays and holidays (that is, public holidays, the day before a public holiday, the day after a public holiday, school holidays, university holidays, Easter holidays and major religious holidays) and includes university exams, general election days, day after elections, and municipal elections in the analysis. Regression analysis, cate-gorical regression and auto-regression are used to illustrate the relationships between response variable and explanatory variables. The main objective of the investigation was to build forecasting models based on this calendar data only and to observe how accurate the models can be without taking into account weather effects and economic effects, hence weather neutral models. Weather and economic factors have to be forecasted, and these forecasts are not so accurate and calendar events are known for sure (error-free). Collecting data for weather and economic factors is costly and time consuming, while obtaining calendar data is relatively easy.

Orientador: Pedro Magalhães Sobrinho / Co-orientador: Teófilo Miguel de Souza / Banca: José Alexandre Matelli / Banca: Márcio Evaristo da Silva / Resumo : A eficiência energética aos poucos vai ganhando espaço nas indústrias, em função da redução dos custos de produção, pela política de sustentabilidade e de preocupação ambiental empregada atualmente. As indústrias de bebidas, como a que o trabalho foi implantado, utilizam muito o sistema de refrigeração e o de ar comprimido. Praticamente 50% do consumo destas fábricas são em função destas utilidades. O objetivo desta dissertação foi desenvolver uma metodologia para ser usada como ferramenta na identificação de oportunidades de redução do consumo de energia em sistemas de refrigeração e ar comprimido. A metodologia desenvolvida foi baseada em conceitos de refrigeração e ar comprimido e, em alguns estudos de casos de eficiência energética implantados em algumas unidades fabris. Este trabalho mostra como esta metodologia foi criada para melhorar a eficiência energética de sistemas de refrigeração e de ar comprimido. Posteriormente esta metodologia foi utilizada em outras unidades desta mesma indústria para reduzir o consumo de energia elétrica. Inicialmente há uma breve descrição dos principais componentes destes sistemas e de conceitos que ajudam na melhoria da eficiência deles. Por fim, são apresentadas algumas boas práticas e projetos implementados que ajudaram na criação da ferramenta ou foram implementados a partir do uso dela. Os resultados do trabalho mostram a ferramenta pronta para ser usada e uma redução do consumo de energia elétrica de mais de 37 GWh/ano, que significam mais de R$ 6.000.000,00 por ano. A principal conclusão desta dissertação é que a metodologia foi criada e, independente do tipo de configuração destes dois sistemas, é possível utilizá-la para melhorá-los / Abstract: Energy efficiency is slowly gaining ground in the industry, especially due to the cost reduction in the production process its present, also to the sustainability policy and environmental concern employed nowadays. Beverage industries use cooling system and compressed air system a lot. Almost 50% of the electricity consumption in these plants refers to those utilities. The objective of this dissertation was to develop a methodology that can be used as a tool for identifying opportunities to reduce energy consumption in those cooling and compressed air systems. The methodology was based on concepts of cooling and compressed air, and also in some case studies in which energy efficiency was implemented in beverage plants. This dissertation shows how this methodology was created to improve the energy efficiency in cooling and air compressed systems. Later this methodology was used in other plants of the same company in which the case study was done to reduce electricity consumption. The study starts with a short description of the main components of these systems and concepts that help to improve their efficiency. And concludes with some good practices operation and projects implemented, which helped to develop the tool or have been implemented using it. The outcome shows that the tool is ready for use and that there is an important reduction in electricity consumption, amount to more than 37 GWh / year, which means more than R$ 6,000,000.00 a year. The main conclusion of this dissertation is that methodology was developed and it is possible to use the methodology to improve the cooling and air compressed systems, apart from the configuration and automation of the equipments in the plant / Mestre

his thesis focuses on optimization of Linux-based operating system for a accumulator-powered device Raspberry Pi 4. Compared to other devices commonly used in Internet of Things projects, the Raspberry Pi 4 offers many functions within one device. However, the disadvantage is the high consumption of electricity. The aim of this thesis is to achieve greatest possible savings in electricity consumption of the Raspberry Pi 4 device, with regard to functionality of the device as a server for data collection from sensors.

This report is about the evaluation of different microcontrollers and their current con-sumption, specifically microcontrollers that will run AI models. The company Sensorbeeneeds a new microcontroller for their future projects. One of the areas of use will be AImodels. The most important parameter for Sensorbee is current consumption, minimizingcurrent consumption is a top priority as their products are powered by batteries or solarpanels. At the beginning of the project, the focus was on which microcontroller had thelowest current consumption. For AI models in particular, however, it turned out to be avery big difference in the optimization of the software. A well-optimized AI model canquickly classify data, which in turn leads to the microcontroller being able to spend muchof its time in sleep mode. This meant that not only the current consumption of the micro-controller could be taken into account, but how fast it ran through an AI model was at leastas important, if not more important. Even how easy it was for Sensorbee to get startedwith the new processor had to be evaluated, as Sensorbee is a small company that has littleresources to move around with. The candidate that was most promising in the beginningproved to be useless as the performance of the AI model was too poor and the general sup-port for the microcontroller was unsatisfactory. It turns out that there are a lot of variablesto consider when choosing a microcontroller and not just what is in the datasheet.

Elkonsumtion är ett ämne med både personliga och globala ändamål. Det gynnar  den privata ekonomin likväl som miljöbelastningen. För att spara el är det  fördelaktigt om man förstå mekanismerna i elförbrukningen. De senaste åren har  det skapats både hårdvara och mjukvara för att överblicka elförbrukningen i detalj  än bara den totala energiförbrukningen. Studerar man varje elektrisk apparats  förbrukning över till exempel ett år ökas därmed insikten om hur hushållets  energiförbrukning är fördelad.   En app har designats för att presentera denna information. Användare får gå  igenom appen för att sedan testas för att se om de kan förstå och använda appen.  Testerna visar att användarna har ökat sin förståelse genom visualiseringen av  datan som presenteras i appen. / Consumption of electricity is a subject with both personal and global purposes.  Reducing the use of power is positive both for the private finances and the  environment. In order to make such a reduction, it is helpful to understand how  the electricity is spent. In the recent years both hardware and software solutions to  display more detailed information on an individual’s consumption than just their  total use. If they could see how much their devices use and how their usage levels  changes over a year, they might increase their understanding of how they spend  their electricity.   An app has been designed to show this information. Users can then use the app for  a while before being tested with questions that can only be answered correctly by  using the app. These tests do show that the users have increased their  understanding of their electricity consumption

A research report submitted to the Faculty of Science, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Science May 23, 2017 / The aim of this study was to investigate the relationship and direction between electricity consumption and gross domestic product including energy infrastructure as a third variable in South Africa using the time series data from 1993 to 2015. The relationship was modelled in South Africa focusing on the industry sectors that influence economic growth and using techniques such as ARIMA model, Multivariate Regression Analysis, Vector Autoregressive and Granger Causal Test. The Vector Autoregressive model performed better than Multivariate Regression analysis in modelling the relationship between consumption and economic growth in South Africa. The Granger causal effect illustrated a direction from consumption to economic growth and again Granger cause effect from infrastructure to economic growth. The results from these models revealed that there was a relationship between electricity consumption and economic growth, as well as electricity infrastructure. South Africa supports a growth hypothesis meaning that South Africa is energy dependent. The results of the study signals that the electricity consumption of South Africa have an effect on the economic growth. / MT 2017

No description available.

Froth Flotation is an industrial separation process commonly used in the primary enrichment of run-of-mine mineral material. Over the past 100 years, much of the process's development has come from empirical evolution, rather than fundamental understanding. While many of the governing sub-processes are still poorly understood, the primary influential factors lie within the chemical, equipment, and operational variables unique to each flotation system. This investigation focuses on the phenomenological investigation of the equipment variables, particularly the rotor design, at the laboratory scale. During this study, several small-scale flotation systems were developed, including various rotor and stator designs, tank sizes, and flow conditions. Experimental techniques were also developed to identify operational performance in four criteria: power consumption, gas dispersion, operational robustness, and flotation kinetics. Evaluation of the various rotors was conducted in two campaigns: (1) an exploratory campaign which featured 14 rotors in limited operational conditions (2) a detailed campaign which featured three rotors in an exhaustive set of conditions. The results show that different rotors exhibited varying degrees of performance when judged by the aforementioned performance criteria. In general, excessive fluid pumping leads to an increase range of stable operation at the expense of greater power consumption. However, this increased power consumption does not necessarily correspond to increased flotation performance, as the data generally confirms the linearly proportional relationship of flotation rate and bubble surface area flux. Consequently, enhanced flotation kinetics can be achieved by rotors which disperse high rates of gas while retaining a small bubble size. / Master of Science