Different Aspects Of Complexity Research Articles

Different aspects of plan complexity in prostate VMAT plans

In this work we evaluated VMAT plan complexity by using different methods and approaches: complexity related to the aperture shape, the nature of the dynamic delivery, the impact of delivery variations as well as complexity analyses based on measurements. Prostate cancer treatment plans with different levels of complexity were created for three different patient cases. The plans intended to be most complex were also scored to be the most complex according to the evaluation methods used. The results for the other plans were more diverse. The methods that included 3D spatial information on complexity gave additional information important for the analysis of clinical relevance. In order to use specific complexity estimation methods for taking clinical decisions it is essential to understand how different aspects of complexity are incorporated in each method.

Complexity analysis of three-dimensional stochastic discrete fracture networks with fractal and multifractal techniques

Systematic analysis of the complexity of fracture systems, especially for three-dimensional (3D) fracture networks, is largely insufficient. In this work, we generate different fracture networks with various geometries with a stochastic discrete fracture network method. The fractal dimension (D) and the singularity variation in a multifractal spectrum (Δα) are utilized to quantify the complexity of fracture networks in different aspects (spatial filling and heterogeneity). Influential factors of complexity, including geometrical fracture properties and system size, are then systematically studied. We generalize the analysis by considering two critical (percolative and over-percolative) stages of fracture networks. At the first stage, κ (fracture orientation) is the most significant parameter for D, following a (fracture length) and L (system size). FD (fracture positions) has a weak correlation with D but a strong correlation with Δα. At the second stage, the sensitivity results of each geometrical parameter and the system size are the same as in stage one for D. For Δα, κ and FD become more significant. For both stages, there is a weak finite-size effect for D and no finite-size effect for Δα. Therefore, a large fracture system is more suitable for a stable fractal dimension estimation, but no requirement for the estimation of Δα. D and Δα are almost independent. Therefore, they can separately quantify different aspects of complexity.

Numerical ultrasonic full waveform inversion (FWI) for complex structures in coupled 2D solid/fluid media

Undetected inclusions in engineering components cause tremendous industrial expenses in maintenance and repairs each year, with additional risks of catastrophic failures. This paper introduces a powerful method for inclusion imaging and reconstruction in irregularly-shaped components, based on a cutting-edge imaging technique—full waveform inversion (FWI). We propose an ultrasonic scanning setup for nondestructive evaluation (NDE) that fits a variety of components with different shapes and sizes. The FWI theoretical expressions are summarized, aiming for creating clear explanations for the NDE and material characterization communities. Systematic analysis of the FWI performance using different setups has been conducted, and a variety of case studies show different aspects of complexity that the FWI technique can address. Multiple inclusions have been successfully reconstructed in gears, exhibiting the potential of applying the proposed technique in overcoming various NDE challenges related to the rapidly growing structural and material complexity nowadays.

An Approach to Measuring Ship Design Complexity

Understanding different aspects of complexity and measuring them properly are important steps of handling ship design complexity effectively. The main objective of this article is to develop a practical and comprehensive method to measure ship design complexity. In engineering design, complexity is measured today by different indexes and methods. This paper initially explores the applicability of such measures in a ship design context supported by a review of different relevant user-cases. However, it is acknowledged that most of these measurement methods focus on product-related complexity aspects and rarely address or quantify complexities generated by the design process, the organisation of the firm, or the market situation. Therefore, this paper introduces a new and comprehensive model to measure ship design complexity including all these aspects. The model quantifies ship design complexity by means of the following nine different descriptive factors: directional, spatial, decision-making, structural, behavioral, contextual, perceptual, temporal, and technological complexity.

A comparison of metrics for quantifying cranial suture complexity.

Cranial sutures play critical roles in facilitating postnatal skull development and function. The diversity of function is reflected in the highly variable suture morphology and complexity. Suture complexity has seldom been studied, resulting in little consensus on the most appropriate approach for comparative, quantitative analyses. Here, we provide the first comprehensive comparison of current approaches for quantifying suture morphology, using a wide range of two-dimensional suture outlines across extinct and extant mammals (n = 79). Five complexity metrics (sinuosity index (SI), suture complexity index (SCI), fractal dimension (FD) box counting, FD madogram and a windowed short-time Fourier transform with power spectrum density (PSD) calculation) were compared with each other and with the shape variation in the dataset. Analyses of suture shape demonstrate that the primary axis of variation captured attributes other than complexity, supporting the use of a complexity metric over raw shape data for sutural complexity analyses. Each approach captured different aspects of complexity. PSD successfully discriminates different sutural features, such as looping patterns and interdigitation amplitude and number, while SCI best-captured variation in interdigitation number alone. Therefore, future studies should consider the relevant attributes for their question when selecting a metric for comparative analysis of suture variation, function and evolution.

Gintropy: Gini Index Based Generalization of Entropy.

Entropy is being used in physics, mathematics, informatics and in related areas to describe equilibration, dissipation, maximal probability states and optimal compression of information. The Gini index, on the other hand, is an established measure for social and economical inequalities in a society. In this paper, we explore the mathematical similarities and connections in these two quantities and introduce a new measure that is capable of connecting these two at an interesting analogy level. This supports the idea that a generalization of the Gibbs–Boltzmann–Shannon entropy, based on a transformation of the Lorenz curve, can properly serve in quantifying different aspects of complexity in socio- and econo-physics.

Complexity in nursing practice : Toward a new conceptual framework in nursing care

While complexity theory has gradually influenced the field of health and social sciences, it has also had an impact on nursing care by introducing a wealth of terminology into the field. The terms “complex patient,” “complex case,” “complex care,” “complex practice,” and “complex needs” have been proposed to describe different aspects of complexity in nursing care. As these qualifiers reflect, nurses become actors in multidefined care and must integrate complexity into their reflective practice. By way of a narrative literature review, this article aims to offer a new perspective on nursing by explaining the different terms used in the discipline, using a multi-level approach. At the end of this review, the authors propose a new integrative conceptual framework for complexity in nursing practice.

Recent advances in network medicine: From disease mechanisms to new treatment strategies

Conventional reductionist approaches have guided most of our understanding in disease diagnostic and treatment. However, most diseases are not consequence of perturbations in a single protein or metabolite, but rather of the effect that these perturbations have in their cellular context. The emerging field of network medicine offers a set of tools to explore molecular networks and to retrieve insights about mechanisms of different diseases. The study of the protein interactome, the map of physical interactions among human proteins, revealed that disease proteins tend to interact with each other, linking diseases to well-defined interactome neighborhoods. These disease-associated neighborhoods have been defined as disease modules, and they can uncover the biological significance of genes identified by genetic studies, reveal molecular mechanisms that connect different phenotypes, and help identify new pharmacological strategies for disease treatment. Therefore, network medicine offers a framework in which the complexity of different aspects of multiple sclerosis can be explored in an integrative fashion, which can ultimately provide insights about disease mechanisms and treatment.

Complementarity of information obtained by Kolmogorov and Aksentijevic–Gibson complexities in the analysis of binary time series

Abstract Understanding and measuring complexity is one of the emerging fields in physics and science more generally. The original impetus was given by Shannon's information theory which quantifies disorder and uncertainty by means of relative probabilities of different outcomes and arrangements of symbols. Next came Kolmogorov complexity (KC) which defines complexity as the length of the shortest description/algorithm needed to describe a string. Since this measure is non-computable it is calculated approximately by means of the Lempel–Ziv algorithm (LZA). KC has been used widely in different branches of physics and other sciences to provide overall estimates of the randomness of data structures, especially time series. Here, we consider the information measure Aksentijevic–Gibson complexity (AG), which defines complexity as amount of change at all levels of a pattern, and compare its performance with KC. We argue that KC and AG in their current implementations are complementary in that they focus on different aspects of complexity—with the former providing efficient omnibus complexity estimates for long time series in different sciences and the latter precisely indexing data structure and locating regions of complexity change. The complementarity of these two measures was demonstrated on one deterministic (logistic equation), and four measured time series: physical (Rn-222 concentration), hydrological (streamflow), meteorological (atmospheric noise) and economic (yield rate) time series, which in further text will be denoted as logistic, Radon, Rio Brazos, random and Imlek, respectively. In addition, we examine spatial transformations of a famous painting in order to demonstrate the sensitivity of AG complexity to spatial information. Finally, we discuss possible applications of the measure in different areas of science.

How to improve success of technology projects in health and social care.

Technologies are often viewed as the route to better, safer and more efficient care, but technology projects rarely deliver all the anticipated benefits. This is usually because they are too complex - and because the complexity is suboptimally handled. This article summarises a new framework to improve the success of technology projects: the nonadoption, abandonment, scale-up, spread and sustainability (NASSS) framework. The framework is based on a narrative systematic review and empirical work, and addresses the different domains in technology projects and how different aspects of complexity may be handled in each of them.

Typing competencies in Alzheimer's disease: An exploration of copy tasks

BackgroundThe diagnostic work-up of Alzheimer Disease (AD) is complex, time-consuming, expensive, and quite demanding for the patients. Therefore, there is a growing need for simple non-invasive tools that add to the diagnostic work-up of patients. ObjectivesThis paper investigates a new method for monitoring motor functions in AD using everyday interactions related to writing with a computer, i.c. executing a copy task. MethodsAn experimental exploratory study was set up in which a carefully designed copy task was presented to three groups of participants: young adults (n = 20), cognitively healthy elderly (n = 20) and age-matched elderly with mild cognitive impairment (MCI) or mild dementia due to AD (n = 12). The task consisted of ten different sub-tasks in which specific bigram characteristics were manipulated. The participants' typing behavior was monitored with keystroke logging. ResultsThe three groups differed significantly from each other in performing the copy task. Typing speed gradually decreased with age. Moreover, the cognitively impaired age-matched adults performed slower on all subtasks expressed in longer interkey intervals within the targeted bigrams. Integrative multilevel modelling showed that all the manipulated bigram characteristics contributed significantly to the model. ConclusionThis explorative study shows the potential relevance of using a typing copy task in the diagnostic work-up of patients with neurodegenerative brain disorders. It relates to a natural task, is non-invasive and easy to automatize. In comparison to other motor tasks it allows for fine-grained measurements at an individual level and combines different aspects of complex and fine motor activities in one task.

The Applicability of Integrated Solutions Offerings: Differential Effects of Product Complexity

The purpose of this article is to develop a conceptual model of the influences of product complexity on the applicability and adoption of solutions offerings as a marketing strategy. Qualitative data from in-depth interviews with executives at 7 furniture manufacturing firms were investigated and a conceptual model was developed. Based on the results, a model for relationships between different aspects of complexity and solutions is proposed and an expansion of the complexity concept suggested. The article expands the knowledge on both solutions strategy and complexity and may also guide managers in the development of their marketing strategies.

A composite complexity measure for component-based systems

The increasing importance of software measurement has led to design and development of new software measures. Controlling and minimizing software complexity is the most important objective of each software development paradigm because it affects all other software quality attributes like reusability, reliability, testability, maintainability etc. For this purpose, a number of software complexity measures have been reported to quantify different aspects of complexity. Component-based software development (CBSD) is an evolving paradigm where emphasis is laid on reuse of existing components and effective designing of new components. As the development of component-based software is rising, more and more complexity metrics are being developed for the same. In this paper, we have attempted to design a composite complexity measure to quantify important aspects of complexity of a component-based system. The proposed measure takes into account two major complexities of a component-based system : one due to individual component and the other due to its interaction with other components. Individual component complexity may arise due to size of a component, type and nesting level of control structures present in code component. Component's interaction complexity may be due to its interface with other components. Graph theoretic notions and concept of weights have been used to illustrate interaction among software components and to compute complexity. The proposed measure has been applied to four cases chosen for present study and yields quiet encouraging results which may further help in controlling the complexity of component-based systems so as to minimize both integration and maintenance efforts.

Biodiversity in a complex world: consolidation and progress in functional biodiversity research

The global decline of biodiversity caused by human domination of ecosystems worldwide is supposed to alter important process rates and state variables in these ecosystems. However, there is considerable debate on the prevalence and importance of biodiversity effects on ecosystem function (BDEF). Here, we argue that much of the debate stems from two major shortcomings. First, most studies do not directly link the traits leading to increased or decreased function to the traits needed for species coexistence and dominance. We argue that implementing a trait-based approach and broadening the perception of diversity to include trait dissimilarity or trait divergence will result in more realistic predictions on the consequences of altered biodiversity. Second, the empirical and theoretical studies do not reflect the complexity of natural ecosystems, which makes it difficult to transfer the results to natural situations of species loss. We review how different aspects of complexity (trophic structure, multifunctionality, spatial or temporal heterogeneity, and spatial population dynamics) alter our perception of BDEF. We propose future research avenues concisely testing whether acknowledging this complexity will strengthen the observed biodiversity effects. Finally, we propose that a major future task is to disentangle biodiversity effects on ecosystem function from direct changes in function due to human alterations of abiotic constraints.

EAE: An immunologist's magic eye

EAE comes in many shapes and colors. Individual variants of EAE present a baffling complexity of different aspects and traits, clinical, immunological, and structural. But, embedded in this seemingly chaotic image, the educated eye will discern patterns that retrace fundamental features of immune response, in particular, autoimmunity and self-tolerance. EAE and its variants thus can be likened to an autostereogram, i.e. they are an immunologist's magic eye.

Multistage designs in the genomic era: Providing balance in complex disease studies

In this summary paper, we describe the contributions included in the Multistage Design group (Group 14) at the Genetic Analysis Workshop 15, which was held during November 12-14, 2006. Our group contrasted and compared different approaches to reducing complexity in a genetic study through implementation of staged designs. Most groups used the simulated dataset (problem 3), which provided ample opportunities for evaluating various staged designs. A wide range of multistage designs that targeted different aspects of complexity were explored. We categorized these approaches as reducing phenotypic complexity, model complexity, analytic complexity or genetic complexity. In general we learned that: (1) when staged designs are carefully planned and implemented, the power loss compared to a single-stage analysis can be minimized and study cost is greatly reduced; (2) a joint analysis of the results from each stage is generally more powerful than treating the second stage as a replication analysis.

Aspects of complexity in visual–spatial working memory: indication for the application of strategies?

Visual–spatial working memory is commonly assumed to consist of two systems: One for spatial-dynamic information and one for visual-static information. Four experiments were carried out to disentangle aspects of complexity in visual–spatial working memory using the Corsi Block Test and the Matrix Task. In Experiment 1 adult subjects were asked to memorize Corsi-sequences and Matrix-patterns of different complexity each consisting of a fixed amount of items. Results show that complexity in the Corsi Test is defined by the absolute length of the sequence-path, the number of path crossings and the number of blocks that were crossed by the imagined path but actually not involved in the sequence. Additionally it was found that sequences which form a path on basis of Gestalt criteria are easier to remember. Complexity in the Matrix Task is defined by the degree of symmetry of the pattern and the possibility to integrate items to an overall structure. Based on these findings a span procedure for both tasks was constructed in Experiment 2. Aspects of complexity were found to be relevant in both tasks, showing that complexity lowers the overall span in visual and spatial working memory. Experiment 3 investigated the role of visual and spatial complexity in children aged from 6 to 10 years by using the span procedures of Experiment 2. Results reveal reliable complexity effects within the Corsi and the Matrix Task across all age groups. Next to clear age effects, different developmental trends were found for the visual-static and the spatial-dynamic task. In Experiment 4 the serial demand within the Corsi Tasks was examined by varying the speed given to encode spatial location: Adult subjects had to memorize sequences consisting of a fixed amount of blocks. Next to the aspects of complexity the presentation time for the sequences was varied. The memorization of easy sequences was not influenced by the reduction of presentation time, whereas memory for complex sequences showed a significant decline. Generally our findings indicate that the processing demand of visual-static and spatial-dynamic information varies with task complexity. Particularly the application of strategies, like spatial rehearsal or chunking, seems to be influenced by different aspects of complexity. The fact that this effect can be found in younger children points towards an early acquisition of visual–spatial strategies. Serial demands within the Corsi Task are not yet clear, but it can be assumed that they play an important role in the processing of spatial-dynamic information.

On the Communication Complexity of Multilateral Trading: Extended Report

We study the complexity of a multilateral negotiation framework, where autonomous agents agree on a sequence of deals to exchange sets of discrete resources in order to both further their own goals and to achieve a distribution of resources that is socially optimal. When analysing such a framework, we can distinguish different aspects of complexity: How many deals are required to reach an optimal allocation of resources? How many communicative exchanges are required to agree on one such deal? How complex a communication language do we require? And finally, how complex is the reasoning task faced by each agent?

An exploratory investigation of the effects of supply chain complexity on delivery performance

As just-in-time delivery has become increasingly commonplace and customer demands continue to tighten, the importance of fast, reliable delivery cannot be overstated. This is particularly true for firms competing internationally, where the complexity of the supply chain must be managed within a global network. To explore the linkage between supply chain complexity and delivery, a two-dimensional framework is proposed that conceptualizes the degree of complexity embedded in a supply chain along two major dimensions: (1) form of technology and (2) nature of information processing. Technology is characterized using a conventional operations strategy framework of structural and infrastructural elements. In contrast, information processing captures both the level of complicatedness and of uncertainty that exists in the supply chain. Collectively, these two dimensions create a two-by-two framework that defines supply chain complexity and provides a strong theoretical basis for linking different aspects of complexity to delivery performance. An exploratory empirical investigation using an international database focused on immediate upstream and downstream echelons of a supply chain at the firm level. Results show strong support for the linkages between delivery performance and both complicatedness of the product/process and uncertainty of the management systems. In contrast, little evidence was found that greater product variety and more complicated supply networks adversely affected performance. Thus, management initiatives to improve delivery performance are best focused on improving informational flows within the supply chain and leveraging new process technologies that offer flexibility to respond to uncertainty.

Is there a general factor of preference for complexity?

It has been assumed that preferences for different aspects of complexity in visual patterns are intercorrelated. Evidence purporting to demonstrate this was examined and found to be inconclusive. The preferences of 111 Ss using three sets of patterns showed no correlation between preference for asymmetry, for multiplicity, and for heterogeneity of elements.