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Most commercial vehicles currently on the market are still equipped with a passive suspension system, while some luxury brands may already use an adaptive suspension. Active suspension systems on the other hand are rarely found, however, they offer great opportunities to close the gap of the well-known trade-off between ride comfort and handling. Besides that, they can also be used to mitigate single event disturbances, an objective of the USA army as announced in a solicitation which initiated and motivated this research. In addition to that, several studies were found stating the impact and danger of potholes and their impact on the vehicle and passenger. Reviewing the literature, several control strategies for controlling active suspension systems were found. However, most of these approaches used feedback control and did not try to mitigate single event disturbances. Since literature also suggested making use of look ahead preview, research at the Performance Engineering Research Lab at Virginia Tech was started in 2015 combining look ahead preview and an adaptive system to generate optimal force profiles. This introductory research succeeded and proved the used approach to be very promising. However, the used adaptive system was not designed to operate in real-time and did not show any correlation between different road profiles. Therefore, the main objective of this research project is to evaluate and analyze each of the adaptive systems by searching for correlations in their solutions. The results then should be used in order to design a control law which emulates the adaptive system and can be used in a real-time environment. First, an overall research methodology was derived. According to this a software application was developed which extracts ideal force profiles from single event disturbance signals in order to mitigate their impact to the vehicle. The application uses a quarter car model with a partially loaded active suspension system, a set of predefined road profiles, a road profile preprocessor, and an adaptive algorithm. The preprocessing includes geometric filtering using a Tandem-Cam Model and the adaptive processor used an iterative version of the Filtered-X Last-Mean-Square algorithm. During evaluation and analysis of several generated data sets, high correlations in the generated and adjusted adaptive systems were discovered. From these an empirical and theoretical universal filter model was derived, which was then used to design an open-loop control law named Optimal Force Control. The original control law and an adjusted version designed for a real-time environment were tested for all predefined road profiles over all considered vehicle velocities and prove to perform much better than the offline solution using the adaptive system. In summary, a control law named Optimal Force Control was designed which can be used and implemented in a vehicle to extract an analytical and ideal force profile given a road profile input. Implementing an active suspension system with tracking controller, this approach can be used in order to mitigate single event disturbance signals by reducing the vertical vehicle acceleration. / Master of Science

With the emergence of quantum physics and computer science in the 20th century, a new era was born which can solve very difficult problems in a much faster rate or problems that classical computing just can't solve. In the 21st century, quantum computing needs to be used to solve tough problems in engineering, business, medical, and other fields that required results not today but yesterday. To make this dream come true, engineers in the semiconductor industry need to make the quantum circuits a reality. To realize quantum circuits and make them scalable, they need to be fault tolerant, therefore Clifford+T gates need to be implemented into those circuits. But the main issue is that in the Clifford+T gate set, T gates are expensive to implement. Carry Look-Ahead addition circuits have caught the interest of researchers because the number of gate layers encountered by a given qubit in the circuit (or the circuit's depth) is logarithmic in terms of the input size n. Therefore, this thesis focuses on optimizing previous designs of out-of-place and in-place Carry Look-Ahead Adders to decrease the T-count, sum of all T and T Hermitian transpose gates in a quantum circuit.

Commonly, the day-ahead and intraday market on the electricity exchange are treated separately in academia. However, a model that forecasts the direction of the price spread between these two markets creates an opportunity for a market participant to leverage the price spread. In the neighbouring domain, electricity price forecasting, deep learning has proven to excel. Therefore, it is hypothesised that it will do so in directional price spread forecasting as well. A quantitative case study was performed to investigate how accurately a deep learning approach could be in directional electricity price spread forecasting. The case study was conducted on the Nordic electricity exchange Nord Pool in the SE3 region. The deep learning approach was compared with previously suggested machine learning models and a naive heuristic. The results show no statistical difference in error rate between the deep learning model and the machine learning model or naive heuristic. The results suggest that deep learning might not be a suitable approach to the task or that the implementation did not fully exhaust the potential of deep learning. / Vanligtvis behandlas marknaden för day-ahead och intraday på elbörsen separat i den akademiska litteraturen. En modell som prognostiserar riktningen för prisskillnaden mellan dessa två marknader skapar dock en möjlighet för en marknadsaktör att utnyttja prisskillnaden. I grannområdet elprisprognoser har djupinlärning visat sig överträffa andra typer av modeller. Därför antas det att djupinlärning även kommer göra det i riktade prisskillnadsprognoser. En kvantitativ fallstudie utfördes för att undersöka hur precis en djupinlärningsmetod kan vara i prognos för riktad elprisskillnad. Fallstudien genomfördes på den nordiska elbörsen Nord Pool i SE3-regionen. Djupinlärningsmetoden jämfördes med tidigare föreslagna maskininlärningsmodeller och en naiv heuristik. Resultaten visar ingen statistisk skillnad i fel-andel mellan djupinlärningsmodellen och maskininlärningsmodellen eller naiv heuristik. Resultaten antyder att djupinlärning kanske inte är ett lämpligt tillvägagångssätt för uppgiften eller att implementeringen inte helt utnyttjar potentialen för djupinlärning.

The accurate estimation of travel time is valuable for a variety of transportation applications such as freeway performance evaluation and real-time traveler information. Given the extensive availability of traffic data collected by intelligent transportation systems, a variety of travel time estimation methods have been developed. Despite limited success under light traffic conditions, traditional corridor travel time prediction methods have suffered various drawbacks. First, most of these methods are developed based on data generated by dual-loop detectors that contain average spot speeds. However, single-loop detectors (and other devices that emulate its operation) are the most commonly used devices in traffic monitoring systems. There has not been a reliable methodology for travel time prediction based on data generated by such devices due to the lack of speed measurements. Moreover, the majority of existing studies focus on travel time estimation. Secondly, the effect of traffic progression along the freeway has not been considered in the travel time prediction process. Moreover, the impact of incidents on travel time estimates has not been effectively accounted for in existing studies.The objective of this dissertation is to develop a methodology for dynamic travel time prediction based on continuous data generated by single-loop detectors (and similar devices) and incident reports generated by the traffic monitoring system. This method involves multiple-step-ahead prediction for flow rate and occupancy in real time. A seasonal autoregressive integrated moving average (SARIMA) model is developed with an embedded adaptive predictor. This predictor adjusts the prediction error based on traffic data that becomes available every five minutes at each station. The impact of incidents is evaluated based on estimates of incident duration and the queue incurred.Tests and comparative analyses show that this method is able to capture the real-time characteristics of the traffic and provide more accurate travel time estimates particularly when incidents occur. The sensitivities of the models to the variations of the flow and occupancy data are analyzed and future research has been identified.The potential of this methodology in dealing with less than perfect data sources has been demonstrated. This provides good opportunity for the wide application of the proposed method since single-loop type detectors are most extensively installed in various intelligent transportation system deployments.

受到封包網路原本忽略時效性特性之影響，對時效性要求極高的多媒體網路服務，如Voice over IP (VoIP)以及Video on Demand (VoD)在All-IP整合的核心網路上提供時，其服務品質低於傳統之電路交換網路。 封包在網路的傳遞過程中受到各種因素之影響，於到達目的地時，可能會造成long delay time，high jitter或packet loss，而在目的地端幾乎已經沒有補救機會，故而如果能在傳遞的過程中，依封包的時效性及重要性做適度的次序調動(rescheduling)而不要依序傳遞(FIFO)，讓過遲的封包提前送出，而將有時間餘裕的封包稍緩送出，如此截長補短，可提高網路效能及整體QoS滿意度。 我們在BBQ (Budget-Base QoS)的架構下發展一套簡單而有效的方法，在單佇列(Single Preemptive Queue)及多佇列(Multiple FIFO Queue)的router架構下，根據封包時效性及重要性賦予合適的profit function，並參考封包在後續路程上各router的負載狀態以便能更精確預估封包是否能及時到達目的地並調整profit function參數以調整封包的送出順序，如此能提高排程的效能。 我們先對單一服務等級的封包排程進行研究，獲得參數調整之技巧，再根據其結果設計多服務等級的封包排程方法，其重點在於如何調配profit function給不同的服務等級。 我們藉由NS-2模擬模擬器進行實驗，評估本方法的效能，實驗結果顯示我們的方法可以較每個router僅根據自身所知的資訊進行排程更可以有效提高網路效能，且能對不同的服務等級做差異化處理以提高整體QoS滿意度。最後在多等級服務的實驗環境及評估指標下，網路高負載的情況，本方法與Simulated Priority Queue排程演算法比較可以提升34%的整體滿意度。 / Running time sensitive multimedia services such as Voice-over-IP (VoIP) and Video-on-Demand (VoD) on All-IP networks may have lower quality than that on the traditional circuit-switched networks. Influenced by many factors, packets transported on a packet-switched network, may suffer from long delay time, large jitter and high packet loss rate. When a packet arrives its destination late, there is no way to correct the problem. Thus, it will be beneficial if routers could forward packets base on their timeliness and importance, instead of using First-In-First-Out (FIFO) service plan, giving important late packets proper precedence. The overall QoS satisfaction will be improved significantly. In this thesis, we develop a simple and effective scheduling policy based on this concept for the environments where packets have predefined hop-by-hop time schedule. Routers are assumed in two different queue architectures: ideal Single Preemptive Queue router and practical Multiple FIFO Queue router. To forward a packet, a router first assigns a suitable profit function to the packet based on its timeliness and importance as well as the loading status in its succeeding routers along its predefined traveling path, then inserts the packet into an appropriate position in the output queues. Taking the loading status of succeeding routers into account could predict more accurately whether the packet could reach its destination on time or not. We conduct the research for the single service class environments first to learn the characteristics of this new scheduling policy, and then for the multiple service class environments based on the knowledge acquired. The challenge is to find the best way to assign proper profit functions to different classes of packets in order to utilize resources more wisely, e.g. urgent and important packets get precedence. We evaluate the performance of this approach by simulation using NS-2 network simulator. Simulation results show that our approach outperforms our previous version which doesn't take the loading status of succeeding routers into account. Furthermore, our approach can outperform the Simulated Priority Queue by at least 34% under heavy load and our evaluation metrics.

Cette thèse s'intéresse à plusieurs aspects des marchés de gros de l'électricité. L'achat et vente d'électricité se négocient sur les marchés à terme et sur le marché day-ahead. Sur ce dernier se pratique un type d'enchère très spécifique, où les enchères des acteurs prennent la forme de fonctions d'offre et de demande. Chapitre 2 prend comme point de départ un résultat de Zachmann et von Hirschhausen (2008) qui constatent une réponse asymétrique du prix de gros de l'électricité en Allemagne au changement du prix des permis d'émission négociable ( EUA ). Cependant, en contradiction avec les résultats existants, il est démontré que l'asymétrie a disparu suite à la publication d'un rapport d'enquête par l'autorité de la concurrence. Chapitre 3 porte sur l'interaction des marchés à terme et day-ahead dans un jeu d'oligopole répété. L'effet du marché à terme sur la stabilité des collusions est étudié dans le cas où les stratégies sur le marché spot prennent la forme des fonctions d'offre. Il est démontré que la simple existence d'un marché à terme peut élargir l'intervalle des valeurs du facteur d'actualisation pour lesquelles la collusion est soutenable. Chapitre 4 examine si une réaction asymétrique au changement du prix du C02 est également présente dans les fonctions d'offre du marché d'électricité day-ahead. À cette fin, les outils de l'analyse des données fonctionnelles sont adoptés et appliquées à des données des enchères. Chapitre 5 développe un test pour l'auto-corrélation dans un panel d'observations fonctionnelles. Une simulation Monte-Carlo montre une bonne puissance du test dans des échantillons de taille habituellement utilisé dans la recherche appliquée. / This thesis addresses aspects of interacting markets in electricity wholesale. Electricity is traded in forward markets and in day-ahead auctions, which implement a very specifie market design. The bids of market participants take the fonn of supply and demand functions. Chapter 2 builds upon a finding of Zachmann and von Hirschhausen (2008) who report an asymmetric response of electricity wholesale prices for Gennany to changes in the price of EV Emission Allowances (EVA). ln contrast to the fonner contribution, it is shown that the asymmetry disappeared in response to a report on investigations by the competition authority. Chapter 3 addresses the interaction offorward markets and day-ahead auctions in a repeated oligopoly game. The effect offorward trading on the sustainability of collusion is studied for the case that spot market strategies take the fonn of supply functions. It is shown that the existence of forward markets enlarges the range of discount factors for which collusion can be sustained. Chapter 4 examines if an asymmetric reaction to EVA prices can also be found in the supply functions from the day-ahead market. To this end, tools from the field of functionaJ data analysis are adopted and applied to observed bids from the day-ahead auction. Chapter 5 develops a test for autocorrelation in functional panel data. Asymptotic nonnality of the statistic is proved, and Monte-Carlo simulation sho\l good power of the test in sample sizes which frequently prevail in applied research.

<p>This thesis is a study of how cooling fan control can be improved by using road topography information. Two such controllers are presented, one that uses information available in vehicles produced today, and one that combines GPS-information with digital topographic maps to use information about the road ahead of the vehicle.</p><p>Simulations show that significant energy savings can be obtained, especially during warm conditions and hilly roads. Compared to conventional fan controllers, energy consumption can be cut by up to three quarters. Moreover, this is possible without any hardware redesign.</p>

<p>The use of positioning systems in a vehicle is a research intensive field. In the first part of this thesis an increase in new applications is disclosed through a mapping of patent documents on how positioning systems can support adaptive cruise control, gear changing systems and engine control. Many ideas are presented and explained and the ideas are valued. Furthermore, a new method for selective catalytic reduction (SCR) control using a positioning system is introduced. It is concluded that look-ahead control, where the vehicle position in relation to the upcoming road section is utilized could give better fuel efficiency, lower emissions and less brake, transmission and engine wear.</p><p>In the second part of this thesis a real time test platform for predictive speed control algorithms has been developed and tested in a real truck. Previously such algorithms could</p><p>only be simulated. In this thesis an algorithm which utilizes model predictive control (MPC) and dynamic programming (DP) been implemented and evaluated. An initial comparative fuel test shows a reduction in fuel consumption when the MPC algorithm is used.</p>

<p>Aim:</p><p>This is a study of social media in the Future Valley media network.</p><p>•To study social media is important because it ischanges the rules of marketing forever. The new economy gives the individual power.</p><p>•In this study it is found how the Future Valley view development of social media, but also how the valley can use social media to develop its future competence and networks.</p><p>Method: This study is built on the qualitative method. For the theory part I have used sources and to get empirical data I have made sixteen interviews with managers within the network of Ahead - Media & Communication. The restriction in this report is that I focused on blogs and social spaces.</p><p>Results & Conclusion: Trademarks can be built with social media,but to do that the sender must be able to communicate back through the media, which takes a lot of time. The use of social media will increase.</p><p>The Future Valley and the network Ahead - Media & Communication is in need of strategies for social media. I suggest: social media mix, service community and international cooperation with other clusters.</p><p>Suggestions for future research: Investigations that could be done is to find target groups. Behavioural and psychological factors could then be studied. New ideas for social media can be found in the US.</p><p>Contribution of the study: This study contributes to the field of social media. It investigates networking and competence development in a strategic perspective.</p>