For nearly 100 years the design of highways has incorporated safety through the application of criteria to each individual design element. Design elements are items like the horizontal curve, vertical curves, the cross-section, clear zone and roadside slopes. As a result, safety is only indirectly addressed since the design elements are developed in isolation without a good understanding on the impact of one element on another. To make matters worse, design elements communicate messages to the driver about the appropriate speed for the highway. Long straight tangent sections encourage drivers to drive faster whereas curved highway segments communicate a lower operating speed. This can lead to inconsistent message to the driver when design elements are not coordinated with each other. A new method is proposed that accounts for the interaction between design elements in such a way that the designer can estimate the frequency and societal cost of motor vehicle crashes. With this estimate of cost, the designer can base design decisions on what would minimize the societal cost of both the infrastructure improvement and safety. This method will allow designers to formulate highway designs that achieve a specific level of safety and communicate consistent information to drivers. This research provides a valuable planning and design tool for practitioners and policy makers alike. It represents an important shift in the highway design paradigm.

This thesis focuses on the application of case based reasoning (CBR) to welding fixtures in a computer aided design (CAD) environment. Modular fixtures have become more popular in previous years due to the creation of flexible manufacturing systems. Modular fixtures, since they are composed of many standardized parts, require much iteration to produce a full fixture design. This process is made more complicated when it is applied to more complex parts such as welding assemblies. In an effort to simplify fixture design for such complicated parts, researchers have been working on integrating fixture design into CAD packages. These efforts, generally known as computer aided fixture design (CAFD), do not focus on the transition of experience from more experienced designers but only provide a structure and a virtual environment to create fixtures. The research presented in this thesis will apply to this area. Case based reasoning (CBR) is a method of using previous cases to help aid the development of solutions to new problems. Applied to CAFD, this method is reduced to the application of a database and a retrieval and adaptation system. Current research on CAFD and CBR is limited to only proposing systems for machining fixtures. This thesis presents a methodology of a CAFD and CBR system that is dedicated to welding assemblies and fixtures. The focus is on creating an indexing system that adequately represents the workpiece and fixture, a retrieval system that accurately recovers the previous cases, and a method that integrates designer feedback in each process. The results of this thesis will be shown in a case study using an automobile muffler fixture assembly to define each idea of the methodology and to provide an example.

"Performance based methodologies are becoming increasingly common in fire safety due to the inability of prescriptive codes to account for every architectural feature. Fire Sprinkler suppression systems have long been used to provide property protection and enhance life safety. However, very few methodologies exist to account for the impact of sprinkler sprays on fire scenarios. Current methods are extremely complicated and difficult to use as an engineering tool for performance based design. Twenty four full scale fire tests were conducted at Tyco Fire Suppression & Building Products Global Technology Center to determine a simple method for accounting for the impact of a single residential sprinkler on fire induced doorway flows. It was found that a spraying sprinkler reduced the mass flows at the doorway while maintaining two stratified layers away from the sprinkler spray. The mass flow reduction was consistent and could be predicted through the use of a simple buoyancy based equation. The current study suggests that the buoyancy equation can be altered through the use of a constant cooling coefficient (equal to 0.84 for a Tyco LFII (TY2234) sprinkler) based on the test results reported in this paper. This study is a proof of concept and the results suggest the methodology can be applicable to similar situations."

"Consider two people having a face-to-face conversation. They sometimes listen, sometimes talk, and sometimes interrupt each other. They use facial expressions to signal that they are confused. They point at objects. They jump from topic to topic opportunistically. When another acquaintance walks by, they nod and say hello. All the while they have other concerns on their mind, such as not missing the meeting that starts in 10 minutes. Like many other humans behaviors, these are not easy to replicate in artificial agents. In this work we look into the design requirements of an embodied agent that can participate in such natural conversations in a mixed-initiative, multi-modal setting. Such an agent needs to understand participating in a conversation is not merely a matter of sending a message and then waiting to receive a response -- both partners are simultaneously active at all times. This agent should be able to deal with different, sometimes conflicting goals, and be always ready to address events that may interrupt the current topic of conversation. To address those requirements, we have created a modular architecture that includes distributed functional units that compete with each other to gain control over available resources. Each of these units, called a schema, has its own sense- think-act cycle. In the field of robotics, this design is often referred to as "behavior-based" or "schema-based." The major contribution of this work is merging behavior-based robotics with plan- based human-computer interaction."

The development in wireless technology, mobile smart devices and Internet of Things has gave birth to a booming era or the wireless indoor geolocation. This technology have been increasingly used within our daily life and help people to build up the tracking system which could be used by fulfillment centers and grocery stores. To achieve higher localization accuracy with wireless geolocation, we need a higher density of deployment which involves high deployment and maintenance cost. To balance the accuracy and the cost, people have begun using wireless localization employing inertial navigation system (INS) which provide speed and direction of movement. When we combine Radio Frequency (RF) localization with INS, we have a hybrid INS/RF localization system which can achieve high localization accuracy with low cost. In this thesis, we use accelerometers and magnetometers in an Android smart phone to build a hybrid INS/RF system and use two different technologies for RF localization: Radio Frequency Identification Device (RFID) and Wi-Fi. Using this system, we conducted measurements of the hybrid localization system and evaluate its performance. The specific contributions of the thesis are: (1)Empirical performance evaluation of the INS/RFID localization system. It relates the localization error to the number and position of RFID tags. (2)Model the effect of metallic objects on accuracy of magnetometer. The model shows the relation between direction error and distance to metallic component. (3)Model shadow fading in close proximity of RF transmitter. It builds a distance dependent shadow fading model. (4)Model based performance evaluation of hybrid localization. The test bench uses our models to simulate the hybrid localization data.

Digitized by Kansas Correctional Industries

*LITERATURE REVIEW* Abstract Background: Insomnia is an increasing public health epidemic, affecting healthy, sub-clinical and clinical populations. Cognitive Behaviour Therapy for insomnia (CBT-I) is the most evidence-based treatment endorsed by the National Institute of Clinical Excellence (NICE) which provides guidance to health and social services in England. Research has demonstrated, however, that CBT-I has low or uncertain efficacy within various populations including those with coexisting health problems and clinical diagnoses. Furthermore, CBT-I is not accessible to most people due to poor prioritisation within services and a paucity of clinicians skilled in insomnia treatment. There is an urgent need to develop alternative interventions for this persistent and highly debilitating complaint. Acceptance based approaches to insomnia including mindfulness-based stress reduction (MBSR) provide an alternative model for holistic treatment of sleep distress. Objectives: This review summarises and synthesises the available literature investigating the effectiveness of MBSR as a treatment for insomnia in community and clinical populations (with some specific populations excluded). Method: Systematic review of all relevant quantitative and qualitative literature to date using PsycINFO, PsycARTICLES and Web of Knowledge databases. Results: 13 relevant articles were included (3 abstracts): randomised control trials (RCTs), experimental, quasi-experimental and qualitative studies. Conclusions: Overall, the limited research in this area was assessed to be of moderate quality and to provide preliminary evidence that MBSR offers an effective intervention for insomnia symptoms and disorder in various populations. The review highlighted the paucity of research specifically MBSR AND INSOMNIA SYMPTOMS 10 investigating the acceptability of MBSR as an insomnia treatment, particularly for more complex presentations. It is possible that MBSR provides holistic and bi-directional benefits for sleep and emotional well-being, however, further research is required to determine how participants experience the course process in relation to their sleep. Keywords: Insomnia, CBT-I, MBSR. *EMPIRICAL PAPER* Abstract: There is an urgent need to improve the availability and acceptability of interventions for insomnia. Low-levels of help-seeking and high levels of functional impairment are often characteristic of individuals with unremitting complaints. Ambivalence about the significance of insomnia and/or a helpless resignation can be further compounded by lack of available treatments and socio-cultural attitudes towards sleep. Insomnia is often complicated with coexisting mental and physical health problems, a syndromal presentation. Theoretical and empirical evidence suggests that eight-week, mindfulness-based stress reduction (MBSR) programmes may offer a holistic intervention to relieve emotional disturbance that may underlie the complaint. This research sought to understand the experience of MBSR for individuals in the community with persistent insomnia, to gain insight into its acceptability. Methods: Holloway and Jefferson’s psychosocial method was used which posits the ‘defended subject’ as key to data construction and analysis (2013). Defences, free associations, researcher-interviewee dynamic, textual information, cultural and sociological knowledge all contributed to an understanding of the ‘whole’ of the experience of interviewees as communicated within Free Association Narrative Interviewing. Results: Results indicate that for highly defended individuals with insomnia, MBSR can be a challenging intervention to engage with and to embody. Barriers to acceptability included: limited insight into emotional distress, (unconscious) relational secondary gains to insomnia, limited understanding of sleep as a physiological process, restricted understanding or misconceptions about mindfulness prior to participation, resistance to acknowledging insomnia MBSR AND INSOMNIA SYMPTOMS 66 as a mental health complaint and practical issues of delivery. Researcher-interviewee dynamics suggested significant unmet relational needs of many interviewees. An exceptional case was discussed where relational distress was not understood to underlie insomnia and where significant benefits to sleep were reported from MBSR. Conclusion: The methodology enabled novel insights into the challenges for highly defended individuals with complex insomnia for accessing MBSR. By contrast, it is possible that for less complex but acute and recurrent insomnia, MBSR is more readily acceptable. Study limitations, future research needs and recommendations for improving the acceptability of MBSR for complex cases of insomnia are discussed.

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基于地理位置的社交网络近年得到了非常多的关注。为了提升用戶粘性和吸引用戶，社交問路提供商会提供給用戶基于地理信息的广告和优惠券等服务。方了让广告和优惠券的投递更有效， 预测用戶下个可能访问的地点变得尤为重要。但是，预测地点一个不可避免的挑战就是數一百万计的候选地点构成了庞大的預測空间，使得整个预测过程变成复杂且缓慢。在本论文中，我們利用用戶签到的类別信息对潜在的用戶运动模式進行了建模并提出了一个混合隐马尔可夫模型去预测用戶下个可能访问的地点类别。基于预测出的类别，我們继而对用戶可能访问的地点进行了預測。在类別层次进行建模的好处是能有效地減少候选地点的个數并且能准确地描述用戶行动的实际意义。一般来說，用戶的行为会受到令人偏好的影响，基于这个現象，我們还运用分类的方法对用戶根据其令人愛好的不同進行了划分并对每个组群制定各自的隐马尔可夫模型。实验結果表示如果先预测用可能访问的地点类别，能使得地点预测空间极大地减少预测精度也会变高。 / 在预测用可能访问的地点之后，另外一个很重要的问题是选择将优惠券投递给哪些用从而将产品或地点的影响最大化。在实际运用中，这种将影响最大化的算法会遇到速度上的壁垒。在本论文中，我们研究了在基于地理位置的社交网络中的影响最大化问题，并提出了一个分割方法能有效地提升算法的运行速度。实验结果显示我们的算法在于业界标准方法达到几乎一致的影响力的前提下，能更快地运行。 / Location-based social networks have been gaining increasing popularity in recent years. To increase users’ engagement with location-based services, it is important to provide attractive features, one of which is geo-targeted ads and coupons. To make ads and coupons delivery more effective, it is essential to predict the location that is most likely to be visited by a user at the next step. However, an inherent challenge in location prediction is a huge prediction space, with millions of distinct check-in locations as prediction target. In this thesis we exploit the check-in category information to model the underlying user movement pattern. We propose a framework which uses a mixed hidden Markov model to predict the category of user activity at the next step and then predicts the most likely location given the estimated category distribution. The advantages of modeling on the category level include a significantly reduced prediction space and a precise expression of the semantic meaning of user activities. In addition, as user check-in behaviors are heavily influenced by their preferences, we take a clustering approach to group users with similar preferences, and train a separate hidden Markov model for each group. Extensive experimental results show that, with the predicted category distribution, the number of location candidates for prediction is much smaller, while the location prediction accuracy becomes higher. / Choosing the right users to deliver the coupons and maximizing the influence spread is also an important problem in LBSN, which is called influence maximization problem. In practice speed is an important issue to solve the influence maximization problem. In this thesis, we study the influence maximization problem in location-based social networks and propose a scalable partition approach to solve the influence maximization problem efficiently. Experimental results show that our partition approach achieves quite similar influence spread performance with the original influence maximization approach, while running much faster. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Zhu, Zhe. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 93-101). / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.vi / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Background Study --- p.11 / Chapter 2.1 --- Location prediction --- p.11 / Chapter 2.2 --- Influence maximization --- p.16 / Chapter 3 --- User Activity and Location Prediction in Location-based Social Networks --- p.20 / Chapter 3.1 --- Data Analysis --- p.20 / Chapter 3.1.1 --- Data Collection --- p.21 / Chapter 3.1.2 --- Dataset Properties --- p.22 / Chapter 3.2 --- User Activity Prediction --- p.26 / Chapter 3.2.1 --- Definitions --- p.27 / Chapter 3.2.2 --- Category Prediction based on HMM --- p.28 / Chapter 3.2.3 --- Mixed HMM with Temporal and Spatial Covariates --- p.34 / Chapter 3.2.4 --- User Preference Modeling --- p.41 / Chapter 3.3 --- Location Prediction --- p.43 / Chapter 3.4 --- Experimental Evaluation --- p.45 / Chapter 3.4.1 --- Data Preparation --- p.46 / Chapter 3.4.2 --- Category Prediction --- p.47 / Chapter 3.4.3 --- Location Prediction --- p.51 / Chapter 3.5 --- Summary --- p.58 / Chapter 4 --- A Partition Approach to Scalable Influence Maximization in Location-based Social Networks --- p.60 / Chapter 4.1 --- Problem definition --- p.60 / Chapter 4.2 --- Influence probability --- p.62 / Chapter 4.2.1 --- Base model --- p.62 / Chapter 4.2.2 --- Distance and similarity model --- p.65 / Chapter 4.2.3 --- Location entropy model --- p.72 / Chapter 4.3 --- Partition approach --- p.74 / Chapter 4.4 --- Evaluation --- p.79 / Chapter 4.4.1 --- Data preparation --- p.79 / Chapter 4.4.2 --- Precision evaluation --- p.80 / Chapter 4.4.3 --- Influence spread evaluation --- p.83 / Chapter 4.4.4 --- Running time --- p.86 / Chapter 4.5 --- Summary --- p.88 / Chapter 5 --- Conclusion --- p.90 / Bibliography --- p.93

Our related research review on propagation models reveals six factors that are significant in last mile connectivity via LAP: path loss, elevation angle, LAP altitude, coverage area, power consumption, operation frequency, interference, and antenna type. These factors can help with monitoring system performance, network planning, coverage footprint, receivers' line-of-sight, quality of service requirements, and data rates which may all vary in response to geomorphology characteristics. Several competing propagation models have been proposed over the years but whilst they collectively raise many shortcomings such as limited altitude up to few tens of meters, lack of cover across different environments, low perdition accuracy they also exhibit several advantages. Four propagation models, which are representatives of their types, have been selected since they exhibit advantages in relation to high altitude, wide coverage range, adaption across different terrains. In addition, all four have been extensively deployed in the past and as a result their correction factors have evolved over the years to yield extremely accurate results which makes the development and evaluation aspects of this research very precise. The four models are: ITU-R P.529-3, Okumura, Hata-Davidson, and ATG. The aim of this doctoral research is to design a new propagation model for last-mile connectivity using LAPs technology as an alternative to aerial base station that includes all six factors but does not exhibit any of the shortcomings of existing models. The new propagation model evolves from existing models using machine learning. The four models are first adapted to include the elevation angle alongside the multiple-input multiple-output diversity gain, our first novelty in propagation modelling. The four adapted models are then used as input in a Neural Network framework and their parameters are clustered in a Self-Organizing-Map using a minimax technique. The framework evolves an optimal propagation model that represents the main research contribution of this research. The optimal propagation model is deployed in two proof-of-concept applications, a wireless sensor network, and a cellular structure. The performance of the optimal model is evaluated and then validated against that of the four adapted models first in relation to predictions reported in the literature and then in the context of the two proof-of-concept applications. The predictions of the optimised model are significantly improved in comparison to those of the four adapted propagation models. Each of the two proof-of-concept applications also represent a research novelty.