The development of a performance measurement framework for FE/HE co-location construction projects

Project success is understood differently by project participants because it is multifaceted, requiring many performance measures to determine success. Previous studies have underrepresented the business context of projects and their role in contributing to the success of the instigating organisation. This issue becomes particularly significant when two or more further and higher education (FE/HE) organisations co-locate their educational operations on a shared site and seek diverse goals from a single project. The relationship between construction project success and long-term educational success created the need for a comprehensive performance measurement framework that defines the contribution of the construction project in supporting FE/HE collaborating institutions through providing a learning environment that enhances the shared educational activities. This study explores the success of constructing a co-located further and higher education (FE/HE) campus when a project definition that continues beyond construction project completion and commissioning, and which encompasses the client’s views of expected business benefits, is adopted. The research developed a measurement framework capable of measuring the performance of FE/HE co-location construction projects, in light of this broader definition. The methodology used to achieve the research aim, influenced by the pragmatic views of the researcher, combined several methods. A focus group identified success criteria for constructing FE/HE co-location campuses. A questionnaire survey elicited the relationships between success criteria from representatives of the directors, senior administrators, and estates managers of further and higher education providers throughout Scotland. Finally, a Delphi survey validated the performance measurement framework by capturing the views of experts in FE/HE co-location. The thesis contributes a comprehensive performance measurement framework structured around two distinctive performance perspectives (performance drivers and performance results) which incorporates multiple project success dimensions and measures. The framework provides a structured way of aggregating performance measures to characterise the representation of thematic performance dimensions

Towards Developing A Framework for Managing an Information Security Policy in Healthcare Organizations

In today\u27s interconnected high-tech world, healthcare organizations are especially concerned with managing and securing health-related information. Threats exist from different sources, and breaches have undesirable impact on the healthcare organization. In order to enhance the organization\u27s security, a precise and clear information security policy must be introduced and enforced. This is an important area of concern that should be addressed properly to successfully manage health organizations‟ security. This is a research-in-progress that examines the need for the adoption of standardized policies and regulations when it comes to dealing with the issue of information security in healthcare organizations. As an outcome of this research we hope to develop a simplified framework that can assist healthcare organizations in the implementation and management of an effective information security policy (ISP). The intended framework is expected to be of great benefit to the smaller healthcare organizations that may be lacking the necessary information security expertise. A study will be conducted on the status of information security within Saudi Arabian healthcare organizations in an effort to strengthen the recommendations of the proposed framework

Improving Inverse Dynamics Accuracy in a Planar Walking Model Based on Stable Reference Point

Physiologically and biomechanically, the human body represents a complicated system with an abundance of degrees of freedom (DOF). When developing mathematical representations of the body, a researcher has to decide on how many of those DOF to include in the model. Though accuracy can be enhanced at the cost of complexity by including more DOF, their necessity must be rigorously examined. In this study a planar seven-segment human body walking model with single DOF joints was developed. A reference point was added to the model to track the body’s global position while moving. Due to the kinematic instability of the pelvis, the top of the head was selected as the reference point, which also assimilates the vestibular sensor position. Inverse dynamics methods were used to formulate and solve the equations of motion based on Newton-Euler formulae. The torques and ground reaction forces generated by the planar model during a regular gait cycle were compared with similar results from a more complex three-dimensional OpenSim model with muscles, which resulted in correlation errors in the range of 0.9–0.98. The close comparison between the two torque outputs supports the use of planar models in gait studies

Multi-agent distributed coverage control and multi-target tracking in complex and dynamic environments

In this work, we study and investigate problems associated with decentralized/distributed area coverage control and deployment of multi-agent networks as well as density estimation, path planning and motion coordination of the latter networks for multi-target tracking in dynamic and complex environments. In particular, we consider deployment (which includes target tracking applications) and area coverage problems in which the members of the multi-agent network have to deploy and allocate themselves over a given domain in accordance with a time-varying Gaussian mixture reference density function (demand function for the network) in complex and non-complex environments (domains with or without obstacles (which can be either static or dynamic)). The latter density function can either represent the reference coverage density or the reference tracking density according to the application considered in each scenario. Hence, different scenarios of the latter problems are investigated in which the proposed problem is comprised of two sub-problems which are coupled and interconnected with each other. The first problem (high-level/macroscopic problem) corresponds to a density path planning and / or density estimation (implemented in a centralized manner) whereas the second problem (low-level/microscopic problem) to a decentralized and distributed control and motion coordination problem. Our proposed approach is based on a combination of the macroscopic and microscopic descriptions of the multi-agent network. The macroscopic description of the network corresponds to the probability distribution of the agents' locations over a given region. In this description, the multi-agent network is treated as one unit (characterized by the networks PDF). The microscopic description of the network corresponds to the collection of all individual positions of the network's agents. The objective of our work is to find control algorithms that will allow a multi-agent network to attain a spatial distribution that matches the reference density function (macroscopic high-level problem) through the local interactions of the agents at the individual level (microscopic low-level distributed control problem). The high-level problem is associated with an interpolation problem in the class of Gaussian Mixtures (GMs) which seeks to find a density path that connects two boundary GMs. Moreover, the low-level control problem is addressed by utilizing the Lloyd's algorithm together with Voronoi tessellations and a time-varying GM reference density function which corresponds to the solution of the high-level problem. Because the high-level and the low-level problems of all the considered scenarios are inherently coupled to each other (interconnected in the sense that in order to solve the second problem we require the solution of the first problem), we propose an iterative scheme that combines the solutions of the first and the second problems in order to solve and address the path planning/density estimation, motion coordination, deployment and area coverage control problems of multi-agent networks in dynamic and complex environments in a successful, complete, safe and holistic way. In the first scenario (Scenario 1 presented in Chapter 2), the goal of the multi-agent network is to track the time-varying GM reference coverage density function that reshapes the agents' distribution from an initial single Gaussian probability distribution to a Gaussian mixture distribution in a domain with no obstacles (non-complex environment). In the second scenario (Scenario 2 presented in Chapter 3) the aim is to transfer the distribution of the agents from an initial GM to a final desired GM over a cluttered complex domain populated by static obstacles that the agents must not collide with while at all times as they are moving and trying to track the time-varying GM reference coverage density. In Scenarios 1 and 2, the high-level problem (first problem) was solved analytically by providing a closed form solution. The low-level control problem (second problem) corresponds to a decentralized and distributed control problem (collision avoidance requirement is now enforced at all times) which is solved by utilizing Lloyd's algorithm together with Voronoi tessellations and a time-varying GM reference coverage density function which corresponds to the centralized solution of the high-level coverage control problem (first problem). For Scenario 2, our approach utilizes a modified version of Voronoi tessellations which are comprised of what we refer to as Obstacle-Aware Voronoi Cells (OAVC) in order to enable coverage control while ensuring obstacle avoidance. In contrast with the first two scenarios (Scenarios 1 and 2), the next scenarios to be discussed (Scenarios 3 and 4) the time-varying GM reference densities are not known a priori and will correspond to the reference tracking density of a multi-target system which is characterized as a GM tracking density utilized to steer the agents to follow the targets; thus, in the first problems of the latter scenarios, state-of the-art estimation techniques will be employed to obtain their solutions. In the third scenario (Scenario 3 presented in Chapter 4) we address a multi-target tracking problem for a multi-agent network. Thus, we consider a density estimation, path planning and distributed/decentralized motion coordination problem for a multi-agent network whose members have to track multiple moving targets over a cluttered complex environment with static obstacles. In the first problem, which corresponds to a density estimation and path planning problem, the goal is to obtain a GM reference tracking density path of the multi-target network that the multi-agent system must track as a whole. In the proposed solution approach of the latter problem, the probability density of the multi-target system is characterized by a Gaussian mixture distribution density which is estimated by an adaptive Gaussian sum filter (AGSF) in order incorporate the complete evolution of the targets' PDFs between two measurements during the estimation. Therefore, the weights (mixing proportions) of the Gaussian components/ mixands (which correspond to the individual target's PDF) update continuously at every time step during the propagation of the state PDFs between two measurements by solving a convex optimization problem which requires the GM approximation to satisfy the so called Fokker-Planck-Kolmogorov equation (FPKE) for continuous time dynamical systems. In the second problem, which corresponds to a distributed and decentralized motion coordination problem, we seeks to find the individual control inputs that steer the agents to follow and track the mobile targets (by tracking the GM reference tacking density estimated solution of the first problem) while avoiding collisions at all times. Hence the same solution approach utilized for Scenario 2 will be employed to solve the second problem of Scenario 3. In the Fourth scenario (Scenario 4 presented in Chapter 5) we address an optimal path planning, density estimation and motion coordination problem for a very-large-scale multi-agent network whose members are aimed to track a very-large-scale system of mobile targets that maneuver while avoiding dynamic moving obstacles in an uncertain changing environment. The goal of the multi-agent network is to follow the targets by tracking their optimal reference estimated probability density which is represented as a GM distribution while avoiding collision with all the dynamic obstacles over the uncertain region. The estimated reference density is optimal in the sense that it represents the GM density of the targets as they seek the shortest path to reach their final destinations in the shortest time while avoiding the dynamic obstacles in the uncertain domain. The first problem corresponds to the optimal path planning and density estimation of the VLST system in the uncertain dynamic environment while the second problem is the motion coordination problem of the very-large-scale multi-agent network. Therefore, the solution approach to tackle the first problem depends on the utilization of an adaptive distributed optimal control (ADOC) framework which is in turn based on tools and concepts from optimal mass transport theory as well as reinforcement learning and approximate dynamic programming (and optimization) in the Wasserstein-GMM space where the value functional is defined in terms of the PDF (corresponds to a GM density) of the targets and the time-varying obstacle map function which describes the dynamic uncertain environment. The key challenge in the latter approach, is estimating and the continuously updating the PDF of the VLST system in accordance with the real time/"online" approximation of the time-varying obstacle map which describe the dynamic obstacles and the uncertain changing environmental information which affect the estimation of latter PDF. The second problem of Scenario 4 will be addressed similarly to that of Scenarios 2 and 3.Aerospace Engineerin

Distributed control of multi-agent networks

Motivated by the challenges that arise in controlling mobile agents operating in areas with nonuniform time-varying densities, in this paper we propose a distributed steering control framework for a network of autonomous mobile multi-agents whose members have to deploy and allocate themselves in critical positions over a given region in accordance with a time-varying coverage density function. Our method is based on a two-level description of the multi-agent network. The second level reflects the macroscopic description of the network which corresponds to the probability distribution of the agents' locations over a given region in which the network of multi-agents is treated as one unit. The second level reflects the microscopic description of the network which is described in terms of the collection of all individual positions of all of its agents. Thus, the goal of the multi-agent network is to attain a spatial distribution that matches the reference coverage density function (macroscopic high-level control problem) through the local interactions of the agents at the individual level (microscopic low-level control problem). The high-level control problem is addressed by associating it with a desired reference Gaussian probability density. Moreover, the low control problem is addressed by utilizing the Lloyd's algorithm with a time-varying coverage density function. Therefore, the control laws provided would allow the agents to achieve a desired macroscopic behavior of the network, using only distributed algorithms and local information. Each agent will control its own velocity, based only on knowledge of a few neighboring agents, but in such a way that a desired probability distribution is obtained. Finally, a set of simulation results are provided to show the convergence of the mobile agents to their critical locations and to show the effectiveness of the proposed approach.Aerospace Engineerin

Function theory related to H∞ control

We define Γ(E), a subset of C³, related to the structured singular value μ of 2x2 matrices. μ is used to analyse performance and robustness of linear feedback systems in control engineering. We find a characterisation for the elements of Γ(E) and establish a necessary and sufficient condition for the existence of an analytic function from the unit disc into Γ(E) satisfying an arbitrary finite number of interpolation conditions. We prove a Schwarz Lemma for Γ(E) when one of the points in Γ(E) is (0,0,0), then we show that in this case, the Carathéodory and Kobayashi distances between the two points in Γ(E) coincide. We also give a characterisation of the interior, the topological boundary and the distinguished boundary of Γ(E), then we define Γ(E)-inner functions and show that if there exists an analytic function from the unit disc into Γ(E) that satisfies the interpolating conditions, then there is a rational Γ(E)-inner function that interpolates.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

High-Performance Liquid Chromatographic Method for Determination of Phenytoin in Rabbits Receiving Sildenafil

A validated high-performance liquid chromatographic (HPLC) method for determination of phenytoin (PHN), para-hydroxy metabolite of phenytoin (POH) and sildenafil (SIL) in rabbit plasma is described. The method is based on extraction on Sep-Pak C18 solid support using ethyl acetate and ether as eluents and monitoring at 220 nm. The extracted samples were analyzed by HPLC using Agilent Zorbax Extended C18 column (150 mm × 4.6 mm internal diameter) and isocratic elution with a mobile phase consist of 29% acetonitrile and 71% sodium acetate solution (0.02 M, pH 4.6). The method was fully validated for linearity and range, selectivity, precision, stability, recovery, and robustness. The linearity of the method was in the range of 0.15 to 39 μg /ml for PHN and 0.15 to 33 μg/ml for both POH and SIL. Limits of detection (LOD) of PHN, POH, and SIL were 0.15 ± 0.01, 0.15 ± 0.01, and 0.15 ± 0.01 μg/ml, respectively. The % recovery of PHN, POH, and SIL from rabbit plasma were, 101.88 ± 0.12, 99.16 ± 0.25, and 99.49 ± 0.33, respectively. The method was applied on plasma collected from rabbits at different time intervals after receiving 30 mg/kg PHN-Na with (and without) 8 mg/kg SIL citrate

Knowledge, attitudes and practices toward cervical cancer and screening among sexually active Saudi females visiting a primary care center in Saudi Arabia

Background/Aim: Women’s knowledge of cervical cancer (CC) and awareness of screening procedures are important to improve adherence and reduce mortality. This study was conducted to determine the knowledge, attitudes, and practices toward cervical cancer and screening among sexually active Saudi females visiting a primary care center in Riyadh, Saudi Arabia. Methods: We conducted a cross-sectional study among sexually active Saudi females who visited the primary care center of our institution using a self-administered survey questionnaire between July and December 2020. Results: Six hundred and one Saudi women participated in the survey with a mean age of 34.0 ± 10.8 years. Three in four women (75.7%) were aware of cervical cancer and 325 (54.1%) believed that doing a Paps smear helped them diagnose and prevent CC. However, 479 participants (79.7%) do not see the need to go for CC screening (n = 199, 41.5%) and 113 (23.6%) had not heard of Paps smear screening. There were 109 women (18.1%) who has good knowledge of cervical cancer and screening and 492 women (81.9%) had poor knowledge. Conclusion: There was a high proportion of women with poor knowledge and awareness about cervical cancer and screening. Most women do not feel the need to undergo screening. Primary care physicians and healthcare providers should revisit the implementation of policies or information dissemination of programs and materials to increase awareness and knowledge for cervical cancer screening and vaccination throughout primary healthcare centers

Machine Learning in Nonlinear Material Physics

Researchers and developers can accelerate the development of innovative materials, methods, and procedures by using machine learning technologies. In materials science, one key objective of employing such methods is to make it easier to identify and quantify high features throughout the chain of manipulation, organization, possessions, and efficiency. An overview of effective uses of automated learning and statistics is given in this piece, which addresses specific challenges in continuous materials mechanics. The classification of these applications is based on their nature, categorized as descriptive, predictive, or prescriptive, all aiming to identify, anticipate, or optimize crucial attributes. The selection of the most suitable machine learning technique is influenced by factors such as the unique use case, content type, data characteristics, geographical and temporal scales, formats, targeted knowledge gain, and affordable computing expenses. Various examples are explored, including using various artificially generated share network architectures on an as-needed basis in conjunction with additional data-driven approaches such as basic constituent assessment, decisions shrubs, models, woods, trees, supported matrix, and Gaussian learners

Machine Learning Skills To K–12

The promise of data-driven methodology in various computer disciplines has been shown by the many real-world implementations of methods based on Machine Learning (ML) over the last couple of decades. ML is finding its way into the computer curriculum in higher education, and an increasing number of organizations are introducing it into computer education in grades K–12. Researching how agency and intuition grow in these situations is critical as computational learning becomes increasingly common in K–12 computer instruction. However, knowing the difficulties associated with teaching algorithmic learning through grades K–12 presents an even more difficult barrier for computer education research, given the difficulties educators and schools now face in integrating traditional learning. This article describes the prospects in data mining schooling for grades K–12. These developments include adjustments to philosophy, technology, and practice. The research addresses several distinctions that K–12 computer educators should consider while addressing this problem and places the current results into the broader context of computing education. The research focuses on crucial elements of the fundamental change needed to properly incorporate ML into more comprehensive K–12 computer courses. Giving up on the idea that rule-based, "traditional" programming is necessary for next-generation computational thinking is a crucial first step