Stricter regulations and evolving environmental concerns have been exerting ever-increasing pressure on the automotive industry to produce low carbon vehicles that reduce emissions. As a result, increasing numbers of alternative powertrain architectures have been released into the marketplace to address this need. However, with a myriad of possible alternative powertrain configurations, which is the most appropriate type for a given vehicle class and duty cycle? To that end, comparative analyses of powertrain configurations have been widely carried out in literature; though such analyses only considered limited types of powertrain architectures at a time. Collating the results from these literature often produced findings that were discontinuous, which made it difficult for drawing conclusions when comparing multiple types of powertrains. The aim of this research is to propose a novel methodology that can be used by practitioners to improve the methods for comparative analyses of different types of powertrain architectures. Contrary to what has been done so far, the proposed methodology combines an optimisation algorithm with a Modular Powertrain Structure that facilitates the simultaneous approach to optimising multiple types of powertrain architectures. The contribution to science is two-folds; presenting a methodology to simultaneously select a powertrain architecture and optimise its component sizes for a given cost function, and demonstrating the use of multi-objective optimisation for identifying trade-offs between cost functions by powertrain architecture selection. Based on the results, the sizing of the powertrain components were influenced by the power and energy requirements of the drivecycle, whereas the powertrain architecture selection was mainly driven by the autonomy range requirements, vehicle mass constraints, CO2 emissions, and powertrain costs. For multi-objective optimisation, the creation of a 3-dimentional Pareto front showed multiple solution points for the different powertrain architectures, which was inherent from the ability of the methodology to concurrently evaluate those architectures. A diverging trend was observed on this front with the increase in the autonomy range, driven primarily by variation in powertrain cost per kilometre. Additionally, there appeared to be a trade-off in terms of electric powertrain sizing between CO2 emissions and lowest mass. This was more evident at lower autonomy ranges, where the battery efficiency was a deciding factor for CO2 emissions. The results have demonstrated the contribution of the proposed methodology in the area of multi-objective powertrain architecture optimisation, thus addressing the aims of this research.

People with diabetes suffer from a high risk of developing foot related diseases. It is therefore important to perform a blood pressure measurement on the toe to be able to diagnose and treat in time. Using laser Doppler flowmetry has been proven to be a useful technique for this purpose during a standard blood pressure measurement procedure using a cuff. The laser Doppler probe detects once the blood flow returns which can then be related to the pressure value. However, the algorithm currently used by the company for detection of return of blood flow is in need of improvements. This thesis aims to develop an improved algorithm, which is more robust against artifacts. Furthermore, a warning system for uncertainties in the detection will be developed and integrated with the new algorithm. To create the algorithm an investigation of the signals’ appearances was performed to obtain an understanding of what artifacts and characteristics the algorithm should be able to handle. First three different basic approaches were implemented and tested, namely model curve, threshold and pulsations. These algorithms were then combined into two different more complex algorithms. One of them consisted of the model curve and the pulsation algorithm, the second combined algorithm consisted of the threshold algorithm and the pulsation algorithm. From the result it was found that the second combined algorithm performed best. It had a high accuracy and a well-functioning warning system. However, the algorithm had problems to correctly detect the return of flow when it is characterised by a slow increase of the perfusion. The biggest contribution by this thesis is the newly developed warning system. A false detection can lead to a false diagnose to be given if the operator is not attentive. The warning system is therefore an important feature since it can prevent this from occurring.

International Telemetering Conference Proceedings / October 28-31, 1996 / Town and Country Hotel and Convention Center, San Diego, California / The process of generating a telemetry format is currently more of an ad-hoc art than a science. Telemetry stream formats conform to traditions that seem to be obsolete given today's computing power. Most format designers would have difficulty explaining why they use the development heuristics they use and even more difficulty explaining why the heuristics work. The formats produced by these heuristics tend to be inefficient in the sense that bandwidth is wasted. This paper makes an important step in establishing a theory on which to base telemetry format construction. In particular it describes an O(nlog n) algorithm for automatically generating telemetry formats. The algorithm also has the potential of efficiently filling a telemetry stream without wasting bits.

International Telemetering Conference Proceedings / October 26-29, 1998 / Town & Country Resort Hotel and Convention Center, San Diego, California / GPS signal fixed dwell and variable dwell time sequential search algorithms are compared with probability of false alarm and detection and searching rate. An adaptive search algorithm is proposed according to different work modes and interference or jam circumstance, which has effectively improved signal acquiring speed and reliability. Mathematical simulation shows its correction and feasible.

Background: Careful airway management, including tracheal intubation, is important when performing anaesthesia in order to achieve safe tracheal intubation. Aim: To study airway management in anaesthesia care from both the professional and patient perspectives. Methods: 11 RNAs performed three airway tests in 87 patients, monitored in a study-specific questionnaire. The tests usefulness for predicting an easy intubation was analysed (Study I). 68 of 74 anaesthesia departments in Sweden answered a self-reported questionnaire about the presence of airway guidelines (Study II). 20 anaesthesiologists were interviewed; a phenomenographic analysis was performed to describe how anaesthesiologists' understand algorithms for management of the difficult airway (Study III). 13 patients were interviewed; content analysis was performed to describe patients' experiences of being awake fiberoptic intubated (Study IV). Results: The Mallampati classification is a good screening test for predicting easy intubation and intubation can be safely performed by RNAs (Study I). The presence of airway guidelines in Swedish anaesthesia departments is poorly implemented (Study II). Algorithms can be understood as law-like rules, a succinct plan to follow in difficult airway situations, an action plan kept in the back of one's mind while creating flexible and versatile personal algorithms, or as consensus guidelines based on expert opinion in order to be followed in clinical practice (Study III). One theme emerged describing experiences of being awake intubated; feelings of being in a vulnerable situation but cared for in safe hands, described in five categories: a need for tailored information, distress and fear of the intubation, acceptance and trust of the staff's competence, professional caring and support, and no hesitation about new awake intubation (Study IV). Conclusions: The Mallampati classification is a good screening test for predicting easy intubation, when the airway assessment is performed in a structured manner by RNAs. The presence of airway guidelines in Swedish anaesthesia departments was poorly implemented and should receive higher priority. Algorithms need to be simple and easy to follow and based on the best available scientific evidence. Tailored information about what to expect, ensuring eye contact, and giving breathing instructions during the procedure may reduce patients' feeling distress.

International Telemetering Conference Proceedings / October 21, 2002 / Town & Country Hotel and Conference Center, San Diego, California / This paper presents the basic concept, construction principle and implementation work for the Automatic Dependent Surveillance (ADS) system. As a part of ADS system, the ADS message processing system based on PC computer was given more attention. Furthermore, the paper introduces the ADS trial status and points out that the ADS implementation will bring tremendous economical and social efficiency.

Active control of the flow over an airfoil is an area of heightened interest in the aerospace community. Previous research on flow control design processes heavily depended on trial and error and the designers knowledge and intuition. Such an approach cannot always meet the growing demands of higher design quality in less time. Successful application of computational fluid dynamics (CFD) to this kind of control problem critically depends on an efficient searching algorithm for design optimization. CFD in conjunction with Genetic Algorithms (GA) potentially offers an efficient and robust optimization method and is a promising solution for current flow control designs. But the traditional binary GA and its operators need to be transformed or re-defined to meet the requirements of real world engineering problems. Current research has combined different existing GA techniques and proposed a realcoded Explicit Adaptive Range Normal Distribution (EARND) genetic algorithm with diversity control to solve the convergence problems. First, a traditional binary-coded GA is replaced by a real-coded algorithm in which the corresponding design variables are encoded into a vector of real numbers that is conceptually closest to the real design space. Second, to address the convergence speed problem, an additional normal distribution scheme is added into the basic GA in order to monitor the global optimization process; meanwhile, design parameters boundaries are explicitly updated to eliminate unnecessary evaluations (computation) in un-promising areas to balance the workload between the global and local searching process. Third, during the initial 20% evolution (search process), the diversity of the individuals within each generation are controlled by a formula in order to conquer the problem of preliminary convergence to the local optimum. In order to better understand the two-jet control optimization results and process, at first, a single jet with a width of 2.5% the chord length is placed on a NACA 0012 airfoils upper surface simulating the blowing and suction control under Re=500,000 and angle of attack 18 degree. Nearly 300 numerical simulations are conducted over a range of parameters (jet location, amplitude and angle). The physical mechanisms that govern suction and blowing flow control are determined and analyzed, and the critical values of suction and blowing locations, amplitudes, and angles are discussed. Moreover, based on the results of single suction/blowing jet control on a NACA 0012 airfoil, the design parameters of a two-jet system are proposed. Our proposed algorithm is built on top of the CFD code, guiding the movement of two jets along the airfoils upper surface. The reasonable optimum control values are determined within the control parameter range. The current study of Genetic Algorithms on airfoil flow control has been demonstrated to be a successful optimization application.

Background: Treadmill walking should closely simulate overground walking for research validation and optimal skill transfer. Traditional fixed-speed treadmill (FS) walking may not simulate natural walking because of the fixed belt speed and lack of visual cues. Self-paced (SP) treadmill walking, especially feedback controlled SP treadmill walking, enables close-to-real-time belt speed changes with users' speed changes. Different sensitivity levels of SP treadmill feedback determine how fast the treadmill respond to user's speed change. Few studies have examined the differences between FS and SP treadmill walking, or the difference between sensitivity levels of SP treadmills, and their methods were questionable because of averaging kinematics and kinetics parameters, and failing to examine directly treadmill and subjects' speed data. This study compared FS with two SP modes with variation of treadmill speed and user's speed as dependent variables. Method: Thirteen young healthy subjects participated. Subjects walked on a motorized split-belt treadmill under FS, high sensitivity SP (SP-H) and low sensitivity SP (SP-L) conditions at normal walking speed. Root mean square error (RMSE) for subject's pelvis global speed (Vpg), pelvis speed with respect to treadmill speed (Vpt), and treadmill speed (Vtg) data were collected for all trials. Results: Significant condition effects were found between FS and the two SP modes in all RMSE values (p < 0.001). The two sensitivity levels of SP had similar speed patterns. Large subject × condition interaction effects were found for all variables (p < 0.001). Only small subject effects were found. Conclusions: The results of the study reveal different walking patterns between FS and SP. However, the two sensitivity levels failed to differ much. More habituation time may be needed for subjects to learn to optimally respond to the SP algorithm. Future work should include training subjects for more natural responses, applying a feed-forward algorithm, and testing the effect of optic flow on FS and SP speed variation. / text

Data-mining has become a hot topic in recent years. It consists of extracting relevant information or structures from data such as: pictures, textual material, networks, etc. Such information or structures are usually not trivial to obtain and many techniques have been proposed to address this problem, including Independent Component Analysis, Latent Sematic Analysis, etc. Nonnegative Matrix Factorization is yet another technique that relies on the nonnegativity of the data and the nonnegativity assumption of the underlying model. The main advantage of this technique is that nonnegative objects are modeled by a combination of some basic nonnegative parts, which provides a physical interpretation of the construction of the objects. This is an exclusive feature that is known to be useful in many areas such as Computer Vision, Information Retrieval, etc. In this thesis, we look at several aspects of Nonnegative Matrix Factorization, focusing on numerical algorithms and their applications to different kinds of data and constraints. This includes Tensor Nonnegative Factorization, Weighted Nonnegative Matrix Factorization, Symmetric Nonnegative Matrix Factorization, Stochastic Matrix Approximation, etc. The recently proposed Rank-one Residue Iteration (RRI) is the common thread in all of these factorizations. It is shown to be a fast method with good convergence properties which adapts well to many situations.

<p>Mobile communication systems are experiencing a huge growth. While traditional communication paradigms deal with fixed networks, mobility raises a new set of questions, techniques, and solutions. This work focuses on wireless sensor networks (WSNs) where each node is a mobile device. The main objectives of this thesis have been to develop algorithms and protocols enabling WSNs with a special interest in overcoming mobility support limitations of standards such as Bluetooth and Zigbee. The contributions of this work may be divided in four major parts related to mobility support. The first part describes the implementation of local positioning services in Bluetooth since local positioning is not supported in Bluetooth v1.1. The obtained results are used in later implemented handover algorithms in terms of deciding when to perform the handover. Moreover local positioning information may be used in further developed routing protocols. The second part deals with handover as a solution to overcome the getting out of range problem. Algorithms for handover have been implemented enabling mobility in Bluetooth infrastructure networks. The principal achievement in this part is the significant reduction of handover latency since sensor cost and quality of service are directly affected by this parameter. The third part solves the routing problems originated with handovers. The main contribution of this part is the impact of the Bluetooth scatternet formation and routing protocols, for multi-hop data transmissions, in the system quality of service. The final part is a comparison between Bluetooth and Zigbee in terms of mobility support. The main outcome of this comparison resides on the conclusions, which can be used as a technology election guide.</p><p>The main scientific contribution relies on the implementation of a mobile WSN with Bluetooth v1.1 inside the scope of the ”Multi Monitoring Medical Chip (M3C) for Homecare Applications” European Union project (Sixth Framework Program (FP6) Reference: 508291) offering multi-hop routing support and improvements in handover latencies with aid of local positioning services.</p>