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Get to know your breasts : A market research concerning AWARE Breast self-examination padAndersson, Leni, Nordell, Nina, Wong, Annie January 2005 (has links)
Background and problem: During the last decade people have become increasingly aware of their health which has led to the establishment of a new market: Over-the-counter test. These tests enable a consumer to individually monitor and examine their health. A decease where such a test could have a large impact is breast cancer. The Breast self-examination pad AWARE has provided women with an opportunity to prevent the course of the decease to reach beyond treatable. This product is shortly made available to the majority of Swedish women. At present there has been no research conducted in Sweden regarding what women think about such a product. Purpose: The purpose of this research thesis is to identify which factors to emphasize in the advertising of AWARE Frame of reference: In this section theories regarding consumer behavior are presented. The chapter in concluded by the creation of a model which aids the fulfillment of the purpose. Method: In order to accomplish the fulfillment the purpose a quantitative method has been utilized. The data collection constitutes of a market research in the Jönköping region where 354 female respondents were included. Conclusion: The result presents to which degree the specific factors are important to enhance in the advertising of AWARE. The authors reached the conclusion that the Psychological factor is of highest importance.
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Supporting Learning Context-aware and Auto-notification Mechanism on an Examination SystemLin, Fong-jheng 04 September 2007 (has links)
In the age of Web2.0, various network services became critical. Exchange of messages between entities in the network is so frequent that information explosion is quite common nowadays. Volume of Information passed is growing up rapidly. With the wide development of web applications, people need to learn how to filter the important messages; service providers have urgent need to trace the ever changing role of users. This research studies the detections of the user interaction scenario, based on the result from the test function in the on-line learning platform.
The learning platform users are divided into two groups, teachers and students, based on their roles. Usually students sit for an on-line examination at the end of each learning activity. The teachers are in charge of helping students with their presentations, encouraging those with good grades, and helping the weaker ones to reach their potential. But in the one-to-many teaching method, a teacher needs to face many students and the resultant grade of an examination becomes a heap of fuzzy and difficult to comprehend numbers. Even though some mathematical tools can help the teachers analyze the data, it is still very difficult to provide appropriate response to each student. The purpose of this research motives building an examination system which combines context-awareness and auto-notification, and bring the advantages of digital examination. An inference engine is used to calculate linear regression of learning curve for each student, then review the old data, and transfer the analysis into the learning context. Then the feedback is given to the students under the various learning context or the teacher will get notification after it compile the analysis. Besides analyzing the past data, the linear regression result will be adjusted to fit the characteristics of learning curve and infer the personal goal of the student. If result is better than expected goal, students should be encouraged. On the other hand, the remediable actions will be administered. Those events can be scheduled by the manager of auto-notification system, published in the appropriate time, and achieve the goal of variety, personalization, and automation.
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Towards High Quality Video Streaming over Urban Vehicular Networks Using a Location-aware Multipath SchemeWang, Renfei 27 June 2012 (has links)
The transmitting of video content over Vehicular Ad Hoc Networks (VANETs) faces a great number of challenges caused by strict QoS (Quality of Service) requirements and highly dynamic network topology. In order to tackle these challenges, multipath forwarding schemes can be regarded as potential solutions. However, route coupling effect and the path length growth severely impair the performance of multipath schemes. In this thesis, the current research status about video streaming over VANETs as well as multipath transmissions are reviewed. With the demand to discover a more suitable solution, we propose the Location-Aware Multipath Video Streaming (LIAITHON+) protocol to address video streaming over urban VANETs. LIAITHON+ uses location information to discover relatively short paths with minimal route coupling effect. The performance results have shown it outperforms the underlying single path solution as well as the node-disjoint multipath solution. In addition, the impact of added redundancy on the multipath solution is investigated through LIAITHON+. According to the results, added redundancy has a different impact depending on the data rate.
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Location Aware Multi-criteria Recommender System for Intelligent Data MiningValencia Rodríguez, Salvador 18 October 2012 (has links)
One of the most important challenges facing us today is to personalize services based on user preferences. In order to achieve this objective, the design of Recommender Systems (RSs), which are systems designed to aid the users through different decision-making processes by providing recommendations to them, have been an active area of research. RSs may produce personalized and non-personalized recommendations. Non-personalized RSs provide general suggestions to a user, based on the number of times an item has been selected in the past. Personalized RSs, on the other hand, aim to predict the most suitable items for a specific user, based on the user’s preferences and constraints. The latter are the focus of this thesis. While Recommender Systems have been successful in many domains, a number of challenges remain. For example, most implementations consider only single criteria ratings, and consequently are unable to identify why a user prefers an item over others. Many systems classify the user into one single group or cluster which is an unrealistic approach, since in real world users share commonalities in different degrees with diverse types of users. Others require a large amount of previously gathered data about users’ interactions and preferences, in order to be successfully applied. In this study, we introduce a methodology for the creation of Personalized Multi Criteria Context Aware Recommender Systems that aims to overcome these shortcomings. Our methodology incorporates the user’s current context information, and techniques from the Multiple Criteria Decision Analysis (MCDA) field of study to analyze and model the user preferences. To this end, we create a multi criteria user preference model to assess the utility of each item for a specific user, to then recommend the items with the highest utility. The criteria considered when creating the user preference model are the user’s location, mobility level and user profile. The latter is obtained by considering the user specific needs, and generalizing the user data from a large scale demographic database. We present a case study where we applied our methodology into PeRS, a personal Recommender System to recommend events that will take place within the Ottawa/Gatineau Region. Furthermore, we conduct an offline experiment performed to evaluate our methodology, as implemented in our case study. From the experimental results we conclude that our RS is capable to accurately narrow down, and identify, the groups from a demographic database where a user may belong, and subsequently generate highly accurate recommendation lists of items that match with his/her preferences. This means that the system has the ability to understand and typify the user. Moreover, the results show that the obtained system accuracy doesn’t depend on the user profile. Therefore, the system is potentially capable to produce equally accurate recommendations for a wide range of the population.
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Restructuring Wireless Systems using PHY Layer InformationSen, Souvik January 2012 (has links)
<p>Wireless and mobile systems play an increasingly important role in our lives. Fueled by an array of innovative services and applications, mobile data traffic is surging rapidly. Traditionally, wireless traffic growth is met by acquiring new spectrum. However, wireless spectrum demand is soon going to surpass it's availability. Thus, there is an urgent need for major innovations in wireless network architecture, so that our spectrum utilization can achieve its full potential. Motivated by this problem, we explore an alternative design of physical layer aware wireless systems.</p><p>Typical approaches towards improving wireless performance is confined within the physical (PHY) or link layers of the networking stack, providing only partial so- lutions. In this thesis, we advocate to consider the entire network architecture holis- tically. We show how rich PHY layer information can be utilized to address existing challenges in wireless networking - contention resolution, rate control, interference management, etc. We design, implement, and experimentally evaluate protocols to understand network-wide implications of PHY-aware systems. We also pursue the observation that PHY layer not only encode bits but also contain rich information about the ambience, and hence can be viewed as a sensor. This sensing informa- tion can be further coupled with other phone sensors, thereby benefitting pervasive mobile services and applications. We demonstrate how this synergy can contribute towards designing precise indoor localization systems, an important building block for next generation mobile applications.</p> / Dissertation
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Get to know your breasts : A market research concerning AWARE Breast self-examination padAndersson, Leni, Nordell, Nina, Wong, Annie January 2005 (has links)
<p>Background and problem: During the last decade people have become increasingly aware of their health which has led to the establishment of a new market: Over-the-counter test. These tests enable a consumer to individually monitor and examine their health. A decease where such a test could have a large impact is breast cancer. The Breast self-examination pad AWARE has provided women with an opportunity to prevent the course of the decease to reach beyond treatable. This product is shortly made available to the majority of Swedish women. At present there has been no research conducted in Sweden regarding what women think about such a product.</p><p>Purpose: The purpose of this research thesis is to identify which factors to emphasize in the advertising of AWARE</p><p>Frame of reference: In this section theories regarding consumer behavior are presented. The chapter in concluded by the creation of a model which aids the fulfillment of the purpose.</p><p>Method: In order to accomplish the fulfillment the purpose a quantitative method has been utilized. The data collection constitutes of a market research in the Jönköping region where 354 female respondents were included.</p><p>Conclusion: The result presents to which degree the specific factors are important to enhance in the advertising of AWARE. The authors reached the conclusion that the Psychological factor is of highest importance.</p>
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Visual place categorizationWu, Jianxin. January 2009 (has links)
Thesis (Ph.D)--Computing, Georgia Institute of Technology, 2010. / Committee Chair: Rehg, James M.; Committee Member: Christensen, Henrik; Committee Member: Dellaert, Frank; Committee Member: Essa, Irfan; Committee Member: Malik, Jitendra. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Effective test case selection for context-aware applications based on mutation testing and adequacy testing from a context diversityperspectiveWang, Huai, 王怀 January 2013 (has links)
Mutation testing and adequacy testing are two major technologies to assure the quality of software. In this thesis, we present the first work that alleviates the high cost of mutation testing and ineffectiveness of adequacy testing for context-aware applications. We also present large-scale multi-subject case studies to evaluate how our work successfully alleviates these problems.
Mutation testing incurs a high execution cost if randomly selected test inputs kill a small percentage of remaining live mutants. To address this problem, we formulate the notion of context diversity to measure the context changes inherent in test inputs, and propose three context-aware strategies in the selection of test inputs. The empirical results show that the use of test inputs with higher context diversity can significantly benefit mutation testing in terms of resulting in fewer test runs, fewer test case trials, and smaller resultant test suites that achieve a high mutation score level. The case study also shows that at the test case level, the context diversity of test inputs positively and strongly correlates with multiple types of adequacy metrics, which provide a foundation on why context diversity contributes to the effectiveness of test cases in revealing faults in context-aware applications.
In adequacy testing, many strategies randomly select test cases to construct adequate test suites with respect to program-based adequacy criteria. They usually exclude redundant test cases that are unable to improve the coverage of the test requirements of an adequacy criterion achieved by constructing test suites. These strategies have not explored in the diversity in test inputs to improve the test effectiveness of test suites. To address this problem, we propose three context-aware refined strategies to check whether redundant test cases can replace previously selected test cases to achieve the same coverage level but with different context diversity levels. The empirical study shows that context diversity can be significantly injected into adequate test suites, and favoring test cases with higher context diversity can significantly improve the fault detection rates of adequate test suites for testing context-aware applications.
In conclusion, this thesis makes the significant contributions to the research in testing context-aware applications: (1) It has formulated context diversity, a novel metric to measure context changes inherent in test inputs. (2) It has proposed three context-aware strategies to select test cases with different levels of context diversity. Compared with the baseline strategy, the strategy CAS-H that uses test cases with higher context diversity can significantly reduce the cost of mutation testing over context-aware applications in terms of less number of test runs, smaller adequate test suites, and less number of test inputs used to construct test suites. (3) It has defined three context-aware refined strategies to construct adequate test suites with different context diversity levels. Compared with the baseline strategy, the strategy CARS-H that favors test cases with higher context diversity can significantly improve the effectiveness of adequacy testing in terms of higher fault detection rates. / published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy
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FAST flexible allocation for sensing tasksLe, Thao P. January 2013 (has links)
The allocation of resources to tasks in a computationally efficient manner is a key problem in computer science. One important application domain for solutions to this class of problem is the allocation of sensing resources for environmental monitoring, surveillance, or similar sensing tasks. Within this domain, however, the complexity of the problem is compounded by a number of factors: new tasks may arrive at any time, resources may be shared between tasks under some conditions, tasks may be composed of inter-dependent sub-tasks, and tasks may compete for sensor resources. These factors combined with the dynamic nature of the topology of sensor networks (e.g. sensors may move out of range or become damaged) mean that it is extremely difficult or impossible to have a solution using existing techniques. In this thesis, we propose an efficient, agent-based solution (FAST for Flexible Allocation for Sensing Tasks) to this complex dynamic problem. The sensing resources in FAST can be either static or mobile or a mixture of both. Particularly, each resource is managed by a task leader agent (i.e. the actual sensor that is closest to the task central point). The problem is then modelled as a coordination problem where the task agents employ a novel multi-round Knapsack-based algorithm (GAP-E) to obtain a solution. If there are dependencies between sub-tasks, such relationships are solved prior to the actual allocation. At execution time, if there is any environment change that affects the task sensing type requirements, the previously determined sensor types for tasks are revised. When applicable, the agents are cooperative through exchanging and sharing resources to maximise their profits. In addition, FAST addresses the situation where sensor resource sharing is not possible and there is no incentive for sensor resources to be exchanged. In such situations, an additional post-process step underpinned by mechanism for exchanging resources through negotiation were introduced. Through those mechanisms, agents may, in a decentralized manner, decide the means to deliver on a sensing task given local conditions, and to alleviate the impact of task arrival time on the quality of the global solution. Via empirical evaluation, these steps significantly improved the number of sensing tasks that can be successfully completed with only a minor impact on execution time.
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Architectural Surfaces and Structures from Circular ArcsShi, Ling 12 1900 (has links)
In recent decades, the popularity of freeform shapes in contemporary architecture poses new challenges to digital design. One of them is the process of rationalization, i.e. to make freeform skins or structures affordable to manufacture, which draws the most attention from geometry researchers. In this thesis, we aim to realize this process with simple geometric primitives, circular arcs. We investigate architectural surfaces and structures consisting of circular arcs. Our focus is lying on how to employ them nicely and repetitively in architectural design, in order to decrease the cost in manufacturing.
Firstly, we study Darboux cyclides, which are algebraic surfaces of order ≤ 4. We provide a computational tool to identify all families of circles on a given cyclide based on the spherical model of M ̈obius geometry. Practical ways to design cyclide patches that pass through certain inputs are presented. In particular, certain triples of circle families on Darboux cyclides may be suitably arranged as 3-webs. We provide a complete classification of all possible 3-webs of circles on Darboux cyclides.
We then investigate the circular arc snakes, which are smooth sequences of circu- lar arcs. We evolve the snakes such that their curvature, as a function of arc length, remains unchanged. The evolution of snakes is utilized to approximate given surfaces by circular arcs or to generated freeform shapes, and it is realized by a 2-step pro- cess. More interestingly, certain 6-arc snake with boundary constraints can produce a smooth self motion, which can be employed to build flexible structures.
Another challenging topic is approximating smooth freeform skins with simple panels. We contribute to this problem area by approximating a negatively-curved
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surface with a smooth union of rational bilinear patches. We provide a proof for
vertex consistency of hyperbolic nets using the CAGD approach of the rational B ́ezier form. Moreover, we use Darboux transformations for the generation of smooth sur- faces composed of Darboux cyclide patches. In this way we not only eliminate the restriction to surfaces with negative Gaussian curvature, but, also obtain surfaces consisting of circular arcs.
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