On Bayesian seamless phase I-II designs

Early phase clinical trial designs have long been the focus of interest for clinicians and statisticians working in oncology field. There are several standard phse I and phase II designs that have been widely-implemented in medical practice. For phase I design, the most commonly used methods are 3+3 and CRM. A newly-developed Bayesian model-based mTPI design has now been used by an increasing number of hospitals and pharmaceutical companies. The advantages and disadvantages of these three top phase I designs have been discussed in my work here and their performances were compared using simulated data. It was shown that mTPI design exhibited superior performance in most scenarios in comparison with 3+3 and CRM designs. ^ The next major part of my work is proposing an innovative seamless phase I/II design that allows clinicians to conduct phase I and phase II clinical trials simultaneously. Bayesian framework was implemented throughout the whole design. The phase I portion of the design adopts mTPI method, with the addition of futility rule which monitors the efficacy performance of the tested drugs. Dose graduation rules were proposed in this design to allow doses move forward from phase I portion of the study to phase II portion without interrupting the ongoing phase I dose-finding schema. Once a dose graduated to phase II, adaptive randomization was used to randomly allocated patients into different treatment arms, with the intention of more patients being assigned to receive more promising dose(s). Again simulations were performed to compare the performance of this innovative phase I/II design with a recently published phase I/II design, together with the conventional phase I and phase II designs. The simulation results indicated that the seamless phase I/II design outperform the other two competing methods in most scenarios, with superior trial power and the fact that it requires smaller sample size. It also significantly reduces the overall study time. ^ Similar to other early phase clinical trial designs, the proposed seamless phase I/II design requires that the efficacy and safety outcomes being able to be observed in a short time frame. This limitation can be overcome by using validated surrogate marker for the efficacy and safety endpoints.^

Zone design of specific sizes using adaptive additively weighted voronoi diagrams

Territory or zone design processes entail partitioning a geographic space, organized as a set of areal units, into different regions or zones according to a specific set of criteria that are dependent on the application context. In most cases, the aim is to create zones of approximately equal sizes (zones with equal numbers of inhabitants, same average sales, etc.). However, some of the new applications that have emerged, particularly in the context of sustainable development policies, are aimed at defining zones of a predetermined, though not necessarily similar, size. In addition, the zones should be built around a given set of seeds. This type of partitioning has not been sufficiently researched; therefore, there are no known approaches for automated zone delimitation. This study proposes a new method based on a discrete version of the adaptive additively weighted Voronoi diagram that makes it possible to partition a two-dimensional space into zones of specific sizes, taking both the position and the weight of each seed into account. The method consists of repeatedly solving a traditional additively weighted Voronoi diagram, so that each seed?s weight is updated at every iteration. The zones are geographically connected using a metric based on the shortest path. Tests conducted on the extensive farming system of three municipalities in Castile-La Mancha (Spain) have established that the proposed heuristic procedure is valid for solving this type of partitioning problem. Nevertheless, these tests confirmed that the given seed position determines the spatial configuration the method must solve and this may have a great impact on the resulting partition.

Design and implementation of an adaptive dashboard and visualization interface for the dynamic optimization and control of Data Centers

Over the last few years, the Data Center market has increased exponentially and this tendency continues today. As a direct consequence of this trend, the industry is pushing the development and implementation of different new technologies that would improve the energy consumption efficiency of data centers. An adaptive dashboard would allow the user to monitor the most important parameters of a data center in real time. For that reason, monitoring companies work with IoT big data filtering tools and cloud computing systems to handle the amounts of data obtained from the sensors placed in a data center.Analyzing the market trends in this field we can affirm that the study of predictive algorithms has become an essential area for competitive IT companies. Complex algorithms are used to forecast risk situations based on historical data and warn the user in case of danger. Considering that several different users will interact with this dashboard from IT experts or maintenance staff to accounting managers, it is vital to personalize it automatically. Following that line of though, the dashboard should only show relevant metrics to the user in different formats like overlapped maps or representative graphs among others. These maps will show all the information needed in a visual and easy-to-evaluate way. To sum up, this dashboard will allow the user to visualize and control a wide range of variables. Monitoring essential factors such as average temperature, gradients or hotspots as well as energy and power consumption and savings by rack or building would allow the client to understand how his equipment is behaving, helping him to optimize the energy consumption and efficiency of the racks. It also would help him to prevent possible damages in the equipment with predictive high-tech algorithms.

Design and evaluation of a framework for cooperative and adaptive QoS control of DSRC network for road safety applications

Dedicated short-range communications (DSRC) are a promising vehicle communication technique for collaborative road safety applications (CSA). However, road safety applications require highly reliable and timely wireless communications, which present big challenges to DSRC based vehicle networks on effective and robust quality of services (QoS) provisioning due to the random channel access method applied in the DSRC technique. In this paper we examine the QoS control problem for CSA in the DSRC based vehicle networks and presented an overview of the research work towards the QoS control problem. After an analysis of the system application requirements and the DSRC vehicle network features, we propose a framework for cooperative and adaptive QoS control, which is believed to be a key for the success of DSRC on supporting effective collaborative road safety applications. A core design in the proposed QoS control framework is that network feedback and cross-layer design are employed to collaboratively achieve targeted QoS. A design example of cooperative and adaptive rate control scheme is implemented and evaluated, with objective of illustrating the key ideas in the framework. Simulation results demonstrate the effectiveness of proposed rate control schemes in providing highly available and reliable channel for emergency safety messages. © 2013 Wenyang Guan et al.

Fully probabilistic control design in an adaptive critic framework

Optimal stochastic controller pushes the closed-loop behavior as close as possible to the desired one. The fully probabilistic design (FPD) uses probabilistic description of the desired closed loop and minimizes Kullback-Leibler divergence of the closed-loop description to the desired one. Practical exploitation of the fully probabilistic design control theory continues to be hindered by the computational complexities involved in numerically solving the associated stochastic dynamic programming problem. In particular very hard multivariate integration and an approximate interpolation of the involved multivariate functions. This paper proposes a new fully probabilistic contro algorithm that uses the adaptive critic methods to circumvent the need for explicitly evaluating the optimal value function, thereby dramatically reducing computational requirements. This is a main contribution of this short paper.

Adaptive E-learning Content Design and Delivery Based on Learning Styles and Knowledge Level

ACM Computing Classification System (1998): K.3.1, K.3.2.

The role of parametric assumptions in adaptive Bayesian estimation.

Variants of adaptive Bayesian procedures for estimating the 5% point on a psychometric function were studied by simulation. Bias and standard error were the criteria to evaluate performance. The results indicated a superiority of (a) uniform priors, (b) model likelihood functions that are odd symmetric about threshold and that have parameter values larger than their counterparts in the psychometric function, (c) stimulus placement at the prior mean, and (d) estimates defined as the posterior mean. Unbiasedness arises in only 10 trials, and 20 trials ensure constant standard errors. The standard error of the estimates equals 0.617 times the inverse of the square root of the number of trials. Other variants yielded bias and larger standard errors.

A matlab-based toolbox for the simulation and design of L1 adaptive controllers

This thesis introduces the L1 Adaptive Control Toolbox, a set of tools implemented in Matlab that aid in the design process of an L1 adaptive controller and enable the user to construct simulations of the closed-loop system to verify its performance. Following a brief review of the existing theory on L1 adaptive controllers, the interface of the toolbox is presented, including a description of the functions accessible to the user. Two novel algorithms for determining the required sampling period of a piecewise constant adaptive law are presented and their implementation in the toolbox is discussed. The detailed description of the structure of the toolbox is provided as well as a discussion of the implementation of the creation of simulations. Finally, the graphical user interface is presented and described in detail, including the graphical design tools provided for the development of the filter C(s). The thesis closes with suggestions for further improvement of the toolbox.

Adaptive lighting design as a holistic approach to public lighting

Dissertação para obtenção do grau de Doutor em Design, apresentada na Universidade de Lisboa - Faculdade de Arquitetura.

Toward adaptive management of coastal MPAs: The influence of different conservation targets and costs on the design of no-take areas

There is still much discussion on the most appropriate location, size and shape of marine protected areas (MPAs). These three factors were analyzed for a small coastal MPA, the Luiz Saldanha Marine Park (LSMP), for which a very limited amount of local ecological information was available when implemented in 1998. Marxan was used to provide a number of near-optimal solutions considering different levels of protection for the various conservation features and different costs. These solutions were compared with the existing no-take area of the LSMP. Information on 11 habitat types and distribution models for 3 of the most important species for the local artisanal fisheries was considered. The human activities with the highest economic and ecological impact in the study area (commercial and recreational fishing and scuba diving) were used as costs. The results show that the existing no-take area is actually located in the best area. However, the no-take area offers limited protection to vagile fish and covers a very small proportion of some of the available habitats. An increase in the conservation targets led to an increase in the number of no-take areas. The comparative framework used in this study can be applied elsewhere, providing relevant information to local stakeholders and managers in order to proceed with adaptive management. (C) 2015 Elsevier B.V. All rights reserved.

Indoor environments : design, productivity and health

In a typical large office block, by far the largest lifetime expense is the salaries of the workers - 84% for salaries compared with : office rent (14%), total energy (1%), and maintenance (1%). The key drive for business is therefore the maximisation of the productivity of the employees as this is the largest cost. Reducing total energy use by 50% will not produce the same financial return as 1% productivity improvement? The aim of the project which led to this review of the literature was to understand as far as possible the state of knowledge internationally about how the indoor environment of buildings does influence occupants and the impact this influence may have on the total cost of ownership of buildings. Therefore one of the main focus areas for the literature has been identifying whether there is a link between productivity and health of building occupants and the indoor environment. Productivity is both easy to define - the ratio of output to input - but at the same time very hard to measure in a relatively small environment where individual contributions can influence the results, in particular social interactions. Health impacts from a building environment are also difficult to measure well, as establishing casual links between the indoor environment and a particular health issue can be very difficult. All of those issues are canvassed in the literature reported here. Humans are surprisingly adaptive to different physical environments, but the workplace should not test the limits of human adaptability. Physiological models of stress, for example, accept that the body has a finite amount of adaptive energy available to cope with stress. The importance of, and this projects' focus on, the physical setting within the integrated system of high performance workplaces, means this literature survey explores research which has been undertaken on both physical and social aspects of the built environment. The literature has been largely classified in several different ways, according to the classification scheme shown below. There is still some inconsistency in the use of keywords, which is being addressed and greater uniformity will be developed for a CD version of this literature, enabling searching using this classification scheme.

Knowledge discovery for adaptive negotiation agents in e-marketplaces

Intelligent software agents are promising in improving the effectiveness of e-marketplaces for e-commerce. Although a large amount of research has been conducted to develop negotiation protocols and mechanisms for e-marketplaces, existing negotiation mechanisms are weak in dealing with complex and dynamic negotiation spaces often found in e-commerce. This paper illustrates a novel knowledge discovery method and a probabilistic negotiation decision making mechanism to improve the performance of negotiation agents. Our preliminary experiments show that the probabilistic negotiation agents empowered by knowledge discovery mechanisms are more effective and efficient than the Pareto optimal negotiation agents in simulated e-marketplaces.