There is a lack of quality communication among health care professionals and patients in the hospital setting, which can negatively impact patient satisfaction and increase hospital readmission rates. Interdisciplinary bedside rounding (IBR) is a method of rounding that uses direct communication and discussion of the patient at the bedside, and the use of IRB may improve the quality communication among health care professionals and patients. The purpose of this program outcomes evaluation project was to evaluate whether IBR increased patient satisfaction with nursing communication and if IBR decreased hospital readmission rates. The Iowa model of evidence-based practice provided a framework that was used for this project. This program outcomes evaluation used a retrospective pre-post design to collect data 3 months prior to and 3 months following IBR on 1 medical surgical hospital unit. A convenience sample of 42 IBR patient participants was used. HCAHPS scores were used to evaluate patient satisfaction with nursing communication, with a percent of change comparison evaluated. Thirty day readmission rates were evaluated using a hospital based data set and a direct comparison of data was performed. Findings revealed that IBR did not improve patient satisfaction with nursing communication overall. In regards to hospital readmissions, 1% of the hospital readmissions were from the IRB group versus 10% hospital wide. Those who experienced IBR were less likely to return within 30 days. The use of the IBR program and resultant reduced readmission rates show promise for positive social change by improved patient outcomes and decreased health care costs for all.

Iterative rounding has been an increasingly popular approach to solving network design optimization problems ever since Jain introduced the concept in his revolutionary 2-approximation for the Survivable Network Design Problem (SNDP). This paper looks at several important iterative rounding approximation algorithms and makes improvements to some of their proofs. We generalize a matrix restatement of Nagarajan et al.'s token argument, which we can use to simplify the proofs of Jain's 2-approximation for SNDP and Fleischer et al.'s 2-approximation for the Element Connectivity (ELC) problem. Lau et al. show how one can construct a (2,2B + 3)-approximation for the degree bounded ELC problem, and this thesis provides the proof. We provide some structural results for basic feasible solutions of the Prize-Collecting Steiner Tree problem, and introduce a new problem that arises, which we call the Prize-Collecting Generalized Steiner Tree problem.

In this thesis I focus on cutting planes for large Mixed Integer Programming (MIP) problems. More specifically, I focus on two independent cutting planes studies. The first of these deals with cutting planes for the Traveling Salesman Problem (TSP), and the second with cutting planes for general MIPs. In the first study I introduce a new class of cutting planes which I call the Generalized Domino Parity (GDP) inequalities. My main achievements with regard to these are: (1) I show that these are valid for the TSP and for the graphical TSP. (2) I show that they generalize most well-known TSP inequalities (including combs, domino-parity constraints, clique-trees, bipartitions, paths and stars). (3) I show that a sub-class of these (which contains all clique-tree inequalities w/ a fixed number of handles) can be separated in polynomial time, on planar graphs. My second study can be subdivided in two parts. In the first of these I study the Mixed Integer Knapsack Problem (MIKP) and develop a branch-and-bound based algorithm for solving it. The novelty of the approach is that it exploits the notion of "dominance" in order to effectively prune solutions in the branch-and-bound tree. In the second part, I develop a Mixed Integer Rounding (MIR) cut separation heuristic, and embed the MIKP solver in a column generation algorithm in order to assess the performance of said heuristic. The goal of this study is to understand why no other class of inequalities derived from single-row systems has been able to outperform the MIR. Computational results are presented.

¡@¡@This paper is refer to the chapter 1 to chapter 5 (except chapter 4 ) of the book, Monte Carlo Statistical Methods(second edition), the author is Robert and Casella(2004). The goal is to translate the chapter 1 to chapter 5 contents of this book into Chinese, modify the mistakes, add the details of the examples, translate the algorithm of the examples into Mathematica(7th) codes, and use the Simulated Annealing method to deal with the estimation of parameters by rounding data, and discuss the results. This paper provides Mathematica(7th) codes of almost every example, and show the actual results, so it can be regarded as a toolbook for those people who are interested in reading this book or may solve some problems related to those examples.

Iterative rounding has been an increasingly popular approach to solving network design optimization problems ever since Jain introduced the concept in his revolutionary 2-approximation for the Survivable Network Design Problem (SNDP). This paper looks at several important iterative rounding approximation algorithms and makes improvements to some of their proofs. We generalize a matrix restatement of Nagarajan et al.'s token argument, which we can use to simplify the proofs of Jain's 2-approximation for SNDP and Fleischer et al.'s 2-approximation for the Element Connectivity (ELC) problem. Lau et al. show how one can construct a (2,2B + 3)-approximation for the degree bounded ELC problem, and this thesis provides the proof. We provide some structural results for basic feasible solutions of the Prize-Collecting Steiner Tree problem, and introduce a new problem that arises, which we call the Prize-Collecting Generalized Steiner Tree problem.

In cell culture, entry into mitosis of many adherent mammalian cells is accompanied by substantial changes in cellular architecture. Flat, spread-out interphase cells detach from the extracellular matrix and become more spherical. These changes in cell shape are mediated by rearrangements in the actin cytoskeleton, a dynamic network of actin filaments that are organized by actin-binding proteins. Filamin A (FLNa) is a 280 kD actin-binding protein that crosslinks actin filaments into parallel bundles or three-dimensional orthogonal networks. We previously identified FLNa as an in vitro substrate of cyclin-dependent kinase 1 (Cdk1), a kinase that regulates entry into mitosis, and hypothesized that Cdk1 phosphorylation of FLNa regulates mitotic actin remodelling. Using mass spectrometry and a p-FLNa antibody, we show that FLNa is phosphorylated in vivo in HeLa cells on multiple Cdk1 sites, including serines 1084, 1459 and 1533. All three sites match the phosphorylation consensus sequence of Cdk1. We further show that p-FLNa is almost fully dephosphorylated by anaphase, consistent with it being a cell cycle-regulated substrate. Using a phospho-specific antibody, we find that p-FLNa has decreased cortical actin localization compared to total FLNa in mitotic cells. To investigate the functional role of mitotic FLNa phosphorylation, we mutated serines 1084, 1459 and 1533 to nonphosphorylatable alanine and expressed this FLNa mutant (FLNa-S1084A, S1459A, S1533A, referred to as “FLNa-AAA GFP”) in FLNa-deficient human M2 melanoma cells. FLNa-AAA GFP-expressing cells have enhanced FLNa-AAA GFP localization at sites of contact between daughter cells and this correlates with defects in cell division and impaired cell migration. Therefore, mitotic delocalization of cortical FLNa is critical for successful cell division and interphase cell behaviour.

abstract: This thesis addresses the following fundamental maximum throughput routing problem: Given an arbitrary edge-capacitated n-node directed network and a set of k commodities, with source-destination pairs (s_i,t_i) and demands d_i> 0, admit and route the largest possible number of commodities -- i.e., the maximum throughput -- to satisfy their demands. The main contributions of this thesis are three-fold: First, a bi-criteria approximation algorithm is presented for this all-or-nothing multicommodity flow (ANF) problem. This algorithm is the first to achieve a constant approximation of the maximum throughput with an edge capacity violation ratio that is at most logarithmic in n, with high probability. The approach used is based on a version of randomized rounding that keeps splittable flows, rather than approximating those via a non-splittable path for each commodity: This allows it to work for arbitrary directed edge-capacitated graphs, unlike most of the prior work on the ANF problem. The algorithm also works if a weighted throughput is considered, where the benefit gained by fully satisfying the demand for commodity i is determined by a given weight w_i>0. Second, a derandomization of the algorithm is presented that maintains the same approximation bounds, using novel pessimistic estimators for Bernstein's inequality. In addition, it is shown how the framework can be adapted to achieve a polylogarithmic fraction of the maximum throughput while maintaining a constant edge capacity violation, if the network capacity is large enough. Lastly, one important aspect of the randomized and derandomized algorithms is their simplicity, which lends to efficient implementations in practice. The implementations of both randomized rounding and derandomized algorithms for the ANF problem are presented and show their efficiency in practice. / Dissertation/Thesis / Masters Thesis Computer Science 2020

Cette thèse porte sur l'optimisation et la commande prédictive des centrales de production d'énergie en utilisant des modèles physiques des installations. Les modèles sont réalisés à l'aide du langage Modelica, un langage équationnel adapté à la modélisation de systèmes multi-physiques. La modélisation de systèmes physiques dans ce langage est présentée dans une première partie, ainsi que les traitements symboliques réalisés par les compilateurs Modelica pour mettre les modèles sous une forme adaptée à l'optimisation. On présente dans une seconde partie le développement d'une méthode d'optimisation dynamique hybride pour les centrales de production d'énergie, qui fournit une trajectoire optimisée de l'installation sur un horizon long. Les trajectoires calculées incluent les trajectoires des commandes continues ainsi que les décisions d'engagement des différents équipements. L'algorithme d'optimisation combine la méthode de collocation et une méthode nommée Sum Up Rounding (SUR) pour la prise en compte des décisions d'engagement. Un algorithme de commande prédictive (MPC) est enfin introduit afin de garantir le suivi des trajectoires optimales et de prendre en compte en temps réel la présence de perturbations et les erreurs du modèle d'optimisation. L'algorithme MPC utilise des modèles linéarisés tangents générés automatiquement à partir du modèle non linéaire. / This thesis deals with hybrid optimal control and Model Predictive Control (MPC) of power plants by use of physical models. Models of the facilities are developped with Modelica, an equation based language tailored for modelling multi-physics systems. Modeling of physical systems with Modelica is introduced in a first part, as well as some of the symbolic processing done by Modelica compilers that transform the original model to a form suited for optimization. Then, a method to solve optimal control problems on hybrid systems (such as power plants) is presented. This methods provides an optimal trajectory for the power plant on a long horizon. The optimal trajectory computed by the method includes the trajectories of continuous inputs as well as switching decisions for components in the plant. The optimization algorithm combines the collocation method and a method named Sum Up Rounding (SUR) for dealing with switches. Finally, a Model Predictive Controller is developped in order to follow this optimal trajectory in real time, and to cope with disturbances on the actual system and modelling errors. The proposed MPC uses tangent linear models of the plant that are derived automatically from the nonlinear model.

Cette thèse porte sur l'optimisation et la commande prédictive des centrales de production d'énergie en utilisant des modèles physiques des installations. Les modèles sont réalisés à l'aide du langage Modelica, un langage équationnel adapté à la modélisation de systèmes multi-physiques. La modélisation de systèmes physiques dans ce langage est présentée dans une première partie, ainsi que les traitements symboliques réalisés par les compilateurs Modelica pour mettre les modèles sous une forme adaptée à l'optimisation. On présente dans une seconde partie le développement d'une méthode d'optimisation dynamique hybride pour les centrales de production d'énergie, qui fournit une trajectoire optimisée de l'installation sur un horizon long. Les trajectoires calculées incluent les trajectoires des commandes continues ainsi que les décisions d'engagement des différents équipements. L'algorithme d'optimisation combine la méthode de collocation et une méthode nommée Sum Up Rounding (SUR) pour la prise en compte des décisions d'engagement. Un algorithme de commande prédictive (MPC) est enfin introduit afin de garantir le suivi des trajectoires optimales et de prendre en compte en temps réel la présence de perturbations et les erreurs du modèle d'optimisation. L'algorithme MPC utilise des modèles linéarisés tangents générés automatiquement à partir du modèle non linéaire. / This thesis deals with hybrid optimal control and Model Predictive Control (MPC) of power plants by use of physical models. Models of the facilities are developped with Modelica, an equation based language tailored for modelling multi-physics systems. Modeling of physical systems with Modelica is introduced in a first part, as well as some of the symbolic processing done by Modelica compilers that transform the original model to a form suited for optimization. Then, a method to solve optimal control problems on hybrid systems (such as power plants) is presented. This methods provides an optimal trajectory for the power plant on a long horizon. The optimal trajectory computed by the method includes the trajectories of continuous inputs as well as switching decisions for components in the plant. The optimization algorithm combines the collocation method and a method named Sum Up Rounding (SUR) for dealing with switches. Finally, a Model Predictive Controller is developped in order to follow this optimal trajectory in real time, and to cope with disturbances on the actual system and modelling errors. The proposed MPC uses tangent linear models of the plant that are derived automatically from the nonlinear model.

Many public-key cryptosystems currently in use are threatened by the possibility of large-scale quantum computers being built in the future. To counteract this, a process of developing quantum-resistant cryptographic algorithms is underway. This process also emphasizes the importance of protecting algorithms from Side-Channel Analysis (SCA). National Institute of Standards and Technology (NIST) oversees this process, and candidates for new standards are submitted into a public evaluation to be examined, updated, and possibly eliminated in order to ensure quality and security of the future standard. To develop knowledge of how to prevent SCA on Field Programmable Gate Array (FPGA) targets, this thesis investigated SCA using the ChipWhisperer-lite capture board and a RISC-V architecture synthesized on a PolarFire FPGA development board as the custom target. Various tests and attempts to detect and verify side-channel leakage are presented. Also included is a study and continuation of a previously explored deep neural network-based SCA on Saber Key Encapsulation Mechanism, which is one of the finalists of NIST post-quantum cryptography standardization process. Changes to the network were made to enable attacks using a tenth of the previously used traces for training. In addition, by utilizing t-test, spectrum analysis, and persistence plots, this thesis was able to verify data-dependent leakage from an S-Box implemented on the FPGA target. However, the key extraction using correlation power analysis was not successful, and therefore the hypothesis for mitigation methods could not be explored. As a result, the thesis’ main contribution is to provide a theoretical background and an introduction to the field and its challenges. The lessons learnt and methods used to connect the ChipWhisperer to the FPGA target might save time and facilitate SCA for the more experienced hardware security researchers. Future work should continue to further investigate this field in order to prevent SCA. / Utvecklingen av kvantdatorer hotar många av de konventionella och idag vitt använda krypteringsalgoritmerna. Därför pågår en process att utveckla och standardisera kvantdatorsäkra krypteringsalgoritmer. Som ett viktigt steg i denna process säkerställs även deras motståndskraft mot sidokanalsattacker. Detta sker i en öppen process modererad av National Institute of Standards and Technology. Kandidaterna till de nya algoritmerna utvärderas, justeras och anslås i en öppen process likt en tävling. Målet med detta examensarbete är att bidra med kunskap och insikter kring hur sidokanalsattacker utförs och motverkas. Attacker kommer riktas mot FPGA-hårdvara konfigurerad med en RISC-V arkitektur istället för de vanligt förekommande ChipWhisperer-måltavlorna. Sidokanalsläckage skall först identifieras och verifieras för att motåtgärder skall kunna testas och utvärderas. I arbetet återskapas en tidigare utförd attack med hjälp av neurala nätverk. Den nya återskapade attacken utförs på SaberKEM, men med stor begränsning utav antalet mätserier. Detta examensarbete kunde verifiera läckage ifrån RISC-V arkitekturen när den utförde AES krypteringssteget, S-Box. Verifieringen utfördes genom användning av T-test, spektrumanalys samt studerande av överlapp hos signalerna. Dock lyckades inte attackerna extrahera känslig nyckelinformation från varken S-Box eller lösenordsjämförelser. På grund av att dessa misslyckades kunde inte arbetet fortsätta vidare till testning av hypoteser för motåtgärder. Därför bör bidraget från detta arbete främst ses som en bakgrund och introduktion till ämnet. Kapitlen Introduktion och Bakgrund bör vara en god genomgång för nybörjare för att förstå viktiga begrepp och principer. För de mer erfarna är troligen metoderna för att koppla ihop och konfigurera FPGA-målet mer intressanta. Genom att dra lärdom av arbetets svårigheter, misstag och utmaningar kan tid sparas. Slutligen uppmanas framtida arbeten att utföra attacker på svårare mål utan direkta mätpunkter för att bli bättre på att anfalla och designa säkrare system.