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关键词： Routing   Topology   Roads   Protocols   Licenses   Computer science   Buildings   Independent spanning trees   generalized recursive circulant graphs   interconnection networks  

摘要： The generalized recursive circulant networking can be widely used in the design and implementation of interconnection networks. It consists of a series of processors, each is connected through bidirectional, point-to-point communication channels to different neighbors. In this work, we apply the shortest path routing concept to build independent spanning trees on the generalized recursive circulant graphs. The proposed strategy loosen the restricted conditions in previous research and extended the result to a more general vertex setting by design the specific algorithm to deal with the constraint issue.

关键词： Information technology   Computer science   Health care management  

摘要： As healthcare organizations attempt to improve Health Insurance Portability and Accountability Act (HIPAA) compliance efforts, many evaluate cloud computing environments essential to meet compliance needs. This paper proposed a quantitative, quasi-experimental study to review cloud encryption services and test their ability to secure electronic Protected Health Information (ePHI). This study determined whether cloud encryption technologies effectively assist small-medium healthcare organizations with HIPAA compliance efforts. The researcher created a Microsoft Azure cloud environment configured with two web forms and two SQL databases to perform this quasi-experimental study. Encryption was enabled on one database using Always Encrypted, an Azure cloud service, while encryption was not enabled on the second database. The researcher determined the impact encryption had on the sample ePHI, per requirements identified in the HIPAA Security Rule, by conducting several tests. The significance of this study was to provide a practical cloud migration methodology for small-medium healthcare organizations to efficiently and effectively protect ePHI, using cloud encryption services, to assist with HIPAA compliance efforts.

关键词： Mechanical engineering   Mathematics   Computer science  

摘要： This dissertation contributes toward design, convergence analysis and improving the performance of the current state of knowledge on central and distributed solutions for in-network optimization algorithms. We investigate how mathematical tools can be utilized to develop and analyze distributed optimization algorithms that respect the restrictions inherent to communication and address computational concerns in smart network operation. The results of this dissertation will facilitate the realization and adoption of optimal in-network solutions in many important applications, such as machine learning, smart grids, robotics, sensor coordination and distributed data regression in different sectors. We develop our results by studying the performance of consensus-based algorithm as a common approach to solve the optimization problems in the decentralized way. We first examine the robustness of a dynamic average consensus algorithm to communication delay over strongly connected and weight-balanced (SCWB) digraphs. For such algorithm, in both its continuous-time and discrete-time implementations, we characterize the admissible communication delay range and study the effect of the delay on the rate of convergence and the tracking error bound. Next, we investigate comprehensive study of a long observed phenomenon of increase in the stability margin and so the rate of convergence of a class of linear systems due to time delay. Using our result, we propose an accelerated algorithm for dynamic and static average consensus problem by using outdated feedback. Such algorithm enables agents over the network to achieve faster agreement on a certain quantity. Our study on optimization algorithm design includes proposing a distributed solution for a constrained convex optimization problem over a network of clustered agents each consists of a set of sub-agents. Our proposed distributed algorithm is a novel continuous-time algorithm that is linked to the augmented Lagrangian approach. We

关键词： Quantum physics   Physics   Computer science   Quantum computing   Simulation   Computers   Cooling   Spectrum analysis   Calibration   Real time   Approximation   Noise   Methods   Algorithms   Boundary conditions  

摘要： This thesis looks at how we can leverage current and near future quantum computers to effectively simulate quantum field theories. The scope of this thesis covers how to simulate the (1+1)-D Transverse Ising model on digital quantum computers and the methods to handle multiple types of machine errors to effectively extract real-time dynamic information. We leverage modifications to the transverse Ising model to study the calculation of phase shifts from scattering a particle off of simple potentials and demonstrate that these calculations are feasible on current quantum hardware. In looking toward the future we demonstrate two different state preparation algorithms. One algorithm projected cooling we show can extract information about the second order phase transition in the Transverse Ising Model and has excellent scaling properties. The second algorithm involves leveraging classical field theory simulations to circumvent quantum state preparation methods on that should prove tractable on near term quantum computing hardware. These tools together highlight the promise of quantum computing to tackle interesting problems in high energy physics.

关键词： Computer science   Artificial intelligence  

关键词： Dentistry   Computer science   Surgery  

摘要： The objective of this study is to evaluate the reliability of palatal rugae as a landmark for superimposition in orthodontic patients treated with palatal expansion. Pre- and post-treatment 3D digital scans and Cone Beam Computed Tomography (CBCT) scans were obtained in 15 patients treated with Rapid Palatal Expansion (RPE). The scans from each timepoint were fit to corresponding structures in their associated CBCTs, and the new volumes were oriented to a common coordinate system. Voxel-based superimpositions of pre- and post-treatment volumes were made for each patient using stable structures identified by “gold-standard” Bjork studies. A second set of surface-based superimpositions were made using palatal rugae. Concordance between the two methods was compared, and the two methods of superimposition did not agree. Palatal rugae is not a reliable landmark for superimposition in orthodontic cases treated with rapid palatal expansion.

关键词： Proteins   Middle Eastern studies   Near Eastern studies   Microbiology   Food science   Biochemistry   Genetics   Computer science  

关键词： Mechanical engineering   Cellular biology   Computer science   Systematic biology  

摘要： Coordinated cellular motion is crucial for proper tissue organization and function. The ability to efficiently analyze group behaviors within large epithelial tissues (>50,000 cells) offers the exciting potential for new discoveries in morphogenesis, growth, wound healing, and possibly even cancer invasion. In recent years, a number of techniques, particularly in the deep learning space, have emerged as promising tools for managing the complexity of large populations of cells. My research focuses on the problem of discovering collective phenomena to better understand and control large epithelial tissues, with an emphasis on deep-learning-driven methods for automated analysis. There are multiple challenges that I have addressed towards this end. First, methods for gathering data pertaining to the physical and dynamical properties of cells (location, size, shape) must be both efficient and minimally disruptive to cell behavior. I have developed an algorithm to perform automatic reconstruction of sub-cellular features directly from transmitted light microscopy images, thereby mitigating the need for expensive, time-consuming, and phototoxic fluorescence images, while enabling rapid post-processing of massive datasets. Second, patterns of cell proliferation and migration must be analyzed in expanding tissues of larger sizes (at the millimeter-scale) and over longer times to capture crucial dynamics. I present data comprising the first comprehensive study of macro-scale, long-term epithelial expansion. Third, automated methods for the discovery of collective phenomena in large tissues must realistically capture biological complexity. I apply deep attention networks to epithelial cell trajectory data in order to gain insight into collective rules, with recommendations towards future research directions. In addition to my collective dynamics work, I led a team of engineers in response to the CoVID-19 pandemic, designing a low-cost, pressure-controlled ventilator. The open-

关键词： Energy   Applied Mathematics   Computer science   Fluid mechanics   Mathematics   Mechanics   Physics   Transportation  

摘要： Electrified vehicles are an essential part in reducing emissions from the transportation sector. Their development comes with a variety of new challenges. Most of them revolve around the energy efficiency of the vehicles as it directly relates to the range that can be covered with one charge. In the area of vehicle thermal management, this means that the focus shifts from a pure cooling perspective towards providing a thermal environment in which the electric power components can operate most efficiently. As the required amount of cooling air through the front is lower than in conventional combustion vehicles, an additional benefit can be gained from smaller front openings that reduce the aerodynamic drag. However, this requires a deeper knowledge of the flow physics in the underhood environment in order to utilise the available cooling air efficiently. Computational Fluid Dynamics (CFD) is an important tool for the investigation of the underhood flow, since it gives the possibility to look at the flow field even in areas where measurement equipment cannot reach. In the first part of this work, the focus is on the simulation of the axial cooling fan. Different methods to simulate an axial cooling fan were compared to each other and to experimental data that was acquired using Laser-Doppler-Anemometry. The commonly used Multiple Reference Frame approach was shown not to be suitable for investigating underhood flow, as the stationary blades leave an imprint on the wake flow. In addition, inhomogeneous temperature distributions experienced an unphysical rotation due to the switch in reference frame. These issues do not occur with the Rigid Body Motion approach, and the simulation results compared well to the measurements. In the second part of this project, it was investigated how the flow downstream of a fan is affected by different components placed up- and downstream. A simplified underhood rig was designed and constructed to provide a controlled, vehicle-like envir

关键词： Computer science   Artificial intelligence  

摘要： Mimicking the ideal of human cognition has always been a high-level goal of technology; however, while computers have excelled at solving objective calculation tasks, there is substantial room left for improvement in the world of creative tasks. Image generation is one of the most explored of such creative tasks. However, much of the existing research in image generation has concentrated on single-objective tasks that attempt to produce images that fall within the distribution of a single cohesive training dataset. In this work, we propose a method to generate original, creative images satisfying multiple objectives. Further, we show that such images can be generated even when most or even all of the images in the training dataset fail to meet the multiple objectives. As an illustration, we present GAN-based neural network solutions for generating original images resembling a specified subject and evoking a specified emotion, such as joy, anger, or energy. Additionally, we leverage research from the domain of psychology to develop an emotion-based image classifier that circumvents the problems of developing large, labelled datasets with unknown human biases.