A Scalability Study and New Algorithms for Large-Scale Many-Objective Optimization

Many real-world optimization problems contain multiple (often conflicting) goals to be optimized concurrently, commonly referred to as multi-objective problems (MOPs). Over the past few decades, a plethora of multi-objective algorithms have been proposed, often tested on MOPs possessing two or three objectives. Unfortunately, when tasked with solving MOPs with four or more objectives, referred to as many-objective problems (MaOPs), a large majority of optimizers experience significant performance degradation. The downfall of these optimizers is that simultaneously maintaining a well-spread set of solutions along with appropriate selection pressure to converge becomes difficult as the number of objectives increase. This difficulty is further compounded for large-scale MaOPs, i.e., MaOPs possessing large amounts of decision variables. In this thesis, we explore the challenges of many-objective optimization and propose three new promising algorithms designed to efficiently solve MaOPs. Experimental results demonstrate the proposed optimizers to perform very well, often outperforming state-of-the-art many-objective algorithms.

Properties and algorithms of the (n, k)-star graphs

The (n, k)-star interconnection network was proposed in 1995 as an attractive alternative to the n-star topology in parallel computation. The (n, k )-star has significant advantages over the n-star which itself was proposed as an attractive alternative to the popular hypercube. The major advantage of the (n, k )-star network is its scalability, which makes it more flexible than the n-star as an interconnection network. In this thesis, we will focus on finding graph theoretical properties of the (n, k )-star as well as developing parallel algorithms that run on this network. The basic topological properties of the (n, k )-star are first studied. These are useful since they can be used to develop efficient algorithms on this network. We then study the (n, k )-star network from algorithmic point of view. Specifically, we will investigate both fundamental and application algorithms for basic communication, prefix computation, and sorting, etc. A literature review of the state-of-the-art in relation to the (n, k )-star network as well as some open problems in this area are also provided.

Properties and algorithms of the (n, k)-arrangement graphs

The (n, k)-arrangement interconnection topology was first introduced in 1992. The (n, k )-arrangement graph is a class of generalized star graphs. Compared with the well known n-star, the (n, k )-arrangement graph is more flexible in degree and diameter. However, there are few algorithms designed for the (n, k)-arrangement graph up to present. In this thesis, we will focus on finding graph theoretical properties of the (n, k)- arrangement graph and developing parallel algorithms that run on this network. The topological properties of the arrangement graph are first studied. They include the cyclic properties. We then study the problems of communication: broadcasting and routing. Embedding problems are also studied later on. These are very useful to develop efficient algorithms on this network. We then study the (n, k )-arrangement network from the algorithmic point of view. Specifically, we will investigate both fundamental and application algorithms such as prefix sums computation, sorting, merging and basic geometry computation: finding convex hull on the (n, k )-arrangement graph. A literature review of the state-of-the-art in relation to the (n, k)-arrangement network is also provided, as well as some open problems in this area.

Properties and algorithms of the hyper-star graph and its related graphs

The hyper-star interconnection network was proposed in 2002 to overcome the drawbacks of the hypercube and its variations concerning the network cost, which is defined by the product of the degree and the diameter. Some properties of the graph such as connectivity, symmetry properties, embedding properties have been studied by other researchers, routing and broadcasting algorithms have also been designed. This thesis studies the hyper-star graph from both the topological and algorithmic point of view. For the topological properties, we try to establish relationships between hyper-star graphs with other known graphs. We also give a formal equation for the surface area of the graph. Another topological property we are interested in is the Hamiltonicity problem of this graph. For the algorithms, we design an all-port broadcasting algorithm and a single-port neighbourhood broadcasting algorithm for the regular form of the hyper-star graphs. These algorithms are both optimal time-wise. Furthermore, we prove that the folded hyper-star, a variation of the hyper-star, to be maixmally fault-tolerant.

Comparison of classification ability of hyperball algorithms to neural network and k-nearest neighbour algorithms

The main focus of this thesis is to evaluate and compare Hyperbalilearning algorithm (HBL) to other learning algorithms. In this work HBL is compared to feed forward artificial neural networks using back propagation learning, K-nearest neighbor and 103 algorithms. In order to evaluate the similarity of these algorithms, we carried out three experiments using nine benchmark data sets from UCI machine learning repository. The first experiment compares HBL to other algorithms when sample size of dataset is changing. The second experiment compares HBL to other algorithms when dimensionality of data changes. The last experiment compares HBL to other algorithms according to the level of agreement to data target values. Our observations in general showed, considering classification accuracy as a measure, HBL is performing as good as most ANn variants. Additionally, we also deduced that HBL.:s classification accuracy outperforms 103's and K-nearest neighbour's for the selected data sets.

A Narrative Study of Patient Encounter Accounts of Physicians, Nurses, and Medical Receptionists after Two Decades of a Paradigm of Patient-Centered Care

Despite recent well-known advancements in patient care in the medical fields, such as patient-centeredness and evidence-based medicine and practice, there is rather less known about their effects on the particulars of clinician-patient encounters. The emphasis in clinical encounters remains mostly on treatment and diagnosis and less on communicative competency or engagement for medical professionals. The purpose of this narrative study was to explore interactive competencies in diagnostic and therapeutic encounters and intake protocols within the context of the physicians’, nurses’, and medical receptionists’ perspectives and experiences. Literature on narrative medicine, phenomenology and medicine, therapeutic relationships, cultural and communication competency, and non-Western perspectives on human communication provided the guiding theoretical frameworks for the study. Three data sets including 13 participant interviews (5 physicians, 4 nurses, and 4 medical receptionists), policy documents (physicians, nurses, and medical receptionists) and a website (Communication and Cultural Competency) were used. The researcher then engaged in triangulated analyses, including N-Vivo, manifest and latent, Mishler’s (1984, 1995) narrative elements and Charon’s (2005, 2006a, 2006b, 2013) narrative themes, in recursive, overlapping, comparative and intersected analysis strategies. A common factor affecting physicians’ relationships with their clients was limitation of time, including limited time (a) to listen, (b) to come up with a proper diagnosis, and (c) to engage in decision making in critical conditions and limited time for patients’ visits. For almost all nurse participants in the study establishing therapeutic relationships meant being compassionate and empathetic. The goals of intake protocols for the medical receptionists were about being empathetic to patients, being an attentive listener, developing rapport, and being conventionally polite to patients. Participants with the least iv amount of training and preparation (medical receptionists) appeared to be more committed to working narratively in connecting with patients and establishing human relationships as well as in listening to patients’ stories and providing support to narrow down the reason for their visit. The diagnostic and intake “success stories” regarding patient clinical encounters for other study participants were focused on a timely securing of patient information, with some acknowledgement of rapport and emapathy. Patient-centeredness emerged as a discourse practice, with ambiguous or nebulous enactment of its premises in most clinical settings.