Convergence and knowledge processing in multi-agent systems

Multi-agent systems are complex systems comprised of multiple intelligent agents that act either independently or in cooperation with one another. Agent-based modelling is a method for studying complex systems like economies, societies, ecologies etc. Due to their complexity, very often mathematical analysis is limited in its ability to analyse such systems. In this case, agent-based modelling offers a practical, constructive method of analysis. The objective of this book is to shed light on some emergent properties of multi-agent systems. The authors focus their investigation on the effect of knowledge exchange on the convergence of complex, multi-agent systems.

The effects of a lutein-based supplement on objective and subjective measures of retinal and visual function in eyes with age-related maculopathy - a randomised controlled trial

Lutein and zeaxanthin are lipid-soluble antioxidants found within the macula region of the retina. Links have been suggested between increased levels of these carotenoids and reduced risk for age-related macular disease (ARMD). Therefore, the effect of lutein-based supplementation on retinal and visual function in people with early stages of ARMD (age-related maculopathy, ARM) was assessed using multi-focal electroretinography (mfERG), contrast sensitivity and distance visual acuity. A total of fourteen participants were randomly allocated to either receive a lutein-based oral supplement (treated group) or no supplement (non-treated group). There were eight participants aged between 56 and 81 years (65·50 (sd 9·27) years) in the treated group and six participants aged between 61 and 83 years (69·67 (sd 7·52) years) in the non-treated group. Sample sizes provided 80 % power at the 5 % significance level. Participants attended for three visits (0, 20 and 40 weeks). At 60 weeks, the treated group attended a fourth visit following 20 weeks of supplement withdrawal. No changes were seen between the treated and non-treated groups during supplementation. Although not clinically significant, mfERG ring 3 N2 latency (P= 0·041) and ring 4 P1 latency (P= 0·016) increased, and a trend for reduction of mfERG amplitudes was observed in rings 1, 3 and 4 on supplement withdrawal. The statistically significant increase in mfERG latencies and the trend for reduced mfERG amplitudes on withdrawal are encouraging and may suggest a potentially beneficial effect of lutein-based supplementation in ARM-affected eyes. Copyright © 2012 The Authors.

Self-calibrated, multi-spectral photometric stereo for 3D face capture

This paper addresses the problem of obtaining 3d detailed reconstructions of human faces in real-time and with inexpensive hardware. We present an algorithm based on a monocular multi-spectral photometric-stereo setup. This system is known to capture high-detailed deforming 3d surfaces at high frame rates and without having to use any expensive hardware or synchronized light stage. However, the main challenge of such a setup is the calibration stage, which depends on the lights setup and how they interact with the specific material being captured, in this case, human faces. For this purpose we develop a self-calibration technique where the person being captured is asked to perform a rigid motion in front of the camera, maintaining a neutral expression. Rigidity constrains are then used to compute the head's motion with a structure-from-motion algorithm. Once the motion is obtained, a multi-view stereo algorithm reconstructs a coarse 3d model of the face. This coarse model is then used to estimate the lighting parameters with a stratified approach: In the first step we use a RANSAC search to identify purely diffuse points on the face and to simultaneously estimate this diffuse reflectance model. In the second step we apply non-linear optimization to fit a non-Lambertian reflectance model to the outliers of the previous step. The calibration procedure is validated with synthetic and real data.

Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity

The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

Clustering web documents using hierarchical representation with multi-granularity

Web document cluster analysis plays an important role in information retrieval by organizing large amounts of documents into a small number of meaningful clusters. Traditional web document clustering is based on the Vector Space Model (VSM), which takes into account only two-level (document and term) knowledge granularity but ignores the bridging paragraph granularity. However, this two-level granularity may lead to unsatisfactory clustering results with “false correlation”. In order to deal with the problem, a Hierarchical Representation Model with Multi-granularity (HRMM), which consists of five-layer representation of data and a twophase clustering process is proposed based on granular computing and article structure theory. To deal with the zero-valued similarity problemresulted from the sparse term-paragraphmatrix, an ontology based strategy and a tolerance-rough-set based strategy are introduced into HRMM. By using granular computing, structural knowledge hidden in documents can be more efficiently and effectively captured in HRMM and thus web document clusters with higher quality can be generated. Extensive experiments show that HRMM, HRMM with tolerancerough-set strategy, and HRMM with ontology all outperform VSM and a representative non VSM-based algorithm, WFP, significantly in terms of the F-Score.

Video-based, real-time multi-view stereo

We investigate the problem of obtaining a dense reconstruction in real-time, from a live video stream. In recent years, multi-view stereo (MVS) has received considerable attention and a number of methods have been proposed. However, most methods operate under the assumption of a relatively sparse set of still images as input and unlimited computation time. Video based MVS has received less attention despite the fact that video sequences offer significant benefits in terms of usability of MVS systems. In this paper we propose a novel video based MVS algorithm that is suitable for real-time, interactive 3d modeling with a hand-held camera. The key idea is a per-pixel, probabilistic depth estimation scheme that updates posterior depth distributions with every new frame. The current implementation is capable of updating 15 million distributions/s. We evaluate the proposed method against the state-of-the-art real-time MVS method and show improvement in terms of accuracy. © 2011 Elsevier B.V. All rights reserved.

Evaluation of hemifield sector analysis protocol in multifocal visual evoked potential (MFVEP) objective perimetry for the diagnosis and early detection of glaucomatous field defects

Visual field assessment is a core component of glaucoma diagnosis and monitoring, and the Standard Automated Perimetry (SAP) test is considered up until this moment, the gold standard of visual field assessment. Although SAP is a subjective assessment and has many pitfalls, it is being constantly used in the diagnosis of visual field loss in glaucoma. Multifocal visual evoked potential (mfVEP) is a newly introduced method used for visual field assessment objectively. Several analysis protocols have been tested to identify early visual field losses in glaucoma patients using the mfVEP technique, some were successful in detection of field defects, which were comparable to the standard SAP visual field assessment, and others were not very informative and needed more adjustment and research work. In this study, we implemented a novel analysis approach and evaluated its validity and whether it could be used effectively for early detection of visual field defects in glaucoma. OBJECTIVES: The purpose of this study is to examine the effectiveness of a new analysis method in the Multi-Focal Visual Evoked Potential (mfVEP) when it is used for the objective assessment of the visual field in glaucoma patients, compared to the gold standard technique. METHODS: 3 groups were tested in this study; normal controls (38 eyes), glaucoma patients (36 eyes) and glaucoma suspect patients (38 eyes). All subjects had a two standard Humphrey visual field HFA test 24-2 and a single mfVEP test undertaken in one session. Analysis of the mfVEP results was done using the new analysis protocol; the Hemifield Sector Analysis HSA protocol. Analysis of the HFA was done using the standard grading system. RESULTS: Analysis of mfVEP results showed that there was a statistically significant difference between the 3 groups in the mean signal to noise ratio SNR (ANOVA p<0.001 with a 95% CI). The difference between superior and inferior hemispheres in all subjects were all statistically significant in the glaucoma patient group 11/11 sectors (t-test p<0.001), partially significant 5/11 (t-test p<0.01) and no statistical difference between most sectors in normal group (only 1/11 was significant) (t-test p<0.9). sensitivity and specificity of the HAS protocol in detecting glaucoma was 97% and 86% respectively, while for glaucoma suspect were 89% and 79%. DISCUSSION: The results showed that the new analysis protocol was able to confirm already existing field defects detected by standard HFA, was able to differentiate between the 3 study groups with a clear distinction between normal and patients with suspected glaucoma; however the distinction between normal and glaucoma patients was especially clear and significant. CONCLUSION: The new HSA protocol used in the mfVEP testing can be used to detect glaucomatous visual field defects in both glaucoma and glaucoma suspect patient. Using this protocol can provide information about focal visual field differences across the horizontal midline, which can be utilized to differentiate between glaucoma and normal subjects. Sensitivity and specificity of the mfVEP test showed very promising results and correlated with other anatomical changes in glaucoma field loss.

Servitization capabilities for advanced services:a multi-actor perspective

Servitization is the process by which manufacturers add services to their product offerings and even replace products with services. The capabilities necessary to develop and deliver advanced services as part of servitization are often discussed in the literature from the manufacturer’s perspective, e.g., having a service-focused culture or the ability to sell solutions. Recent research has acknowledged the important role of customers and, to a lesser extent, other actors (e.g., intermediaries) in bringing about successful servitization, particularly for use-oriented and results-oriented advanced services. The objective of this study is to identify the capabilities required to successful develop advanced services as part of servitization by considering the perspective of manufacturers, intermediaries and customers. This study involved interviews with 33 managers in 28 large UK-based companies from these three groups, about servitization capabilities. The findings suggest that there are eight broad capabilities that are important for advanced services; 1) personnel with expertise and deep technical product knowledge, 2) methodologies for improving operational processes, helping to manage risk and reduce costs, 3) the evolution from being a product- focused manufacturer to embracing a services culture, 4) developing trusting relationships with other actors in the network to support the delivery of advanced services, 5) new innovation activities focused on financing contracts (e.g., ‘gain share’) and technology implementation (e.g., Web-based applications), 6) customer intimacy through understanding their business challenges in order to develop suitable solutions, 7) extensive infrastructure (e.g., personnel, service centres) to deliver a local service, and 8) the ability to tailor service offerings to each customer’s requirements and deliver these responsively to changing needs. The capabilities required to develop and deliver advanced services align to a need to enhance the operational performance of supplied products throughout their lifecycles and as such require greater investment than the capabilities for base and intermediate services.

Using the max-sum algorithm for supply chain emergence in dynamic multiunit environments

Supply chain formation (SCF) is the process of determining the set of participants and exchange relationships within a network with the goal of setting up a supply chain that meets some predefined social objective. Many proposed solutions for the SCF problem rely on centralized computation, which presents a single point of failure and can also lead to problems with scalability. Decentralized techniques that aid supply chain emergence offer a more robust and scalable approach by allowing participants to deliberate between themselves about the structure of the optimal supply chain. Current decentralized supply chain emergence mechanisms are only able to deal with simplistic scenarios in which goods are produced and traded in single units only and without taking into account production capacities or input-output ratios other than 1:1. In this paper, we demonstrate the performance of a graphical inference technique, max-sum loopy belief propagation (LBP), in a complex multiunit unit supply chain emergence scenario which models additional constraints such as production capacities and input-to-output ratios. We also provide results demonstrating the performance of LBP in dynamic environments, where the properties and composition of participants are altered as the algorithm is running. Our results suggest that max-sum LBP produces consistently strong solutions on a variety of network structures in a multiunit problem scenario, and that performance tends not to be affected by on-the-fly changes to the properties or composition of participants.

A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments

Integrated supplier selection and order allocation is an important decision for both designing and operating supply chains. This decision is often influenced by the concerned stakeholders, suppliers, plant operators and customers in different tiers. As firms continue to seek competitive advantage through supply chain design and operations they aim to create optimized supply chains. This calls for on one hand consideration of multiple conflicting criteria and on the other hand consideration of uncertainties of demand and supply. Although there are studies on supplier selection using advanced mathematical models to cover a stochastic approach, multiple criteria decision making techniques and multiple stakeholder requirements separately, according to authors' knowledge there is no work that integrates these three aspects in a common framework. This paper proposes an integrated method for dealing with such problems using a combined Analytic Hierarchy Process-Quality Function Deployment (AHP-QFD) and chance constrained optimization algorithm approach that selects appropriate suppliers and allocates orders optimally between them. The effectiveness of the proposed decision support system has been demonstrated through application and validation in the bioenergy industry.

HW Implementation of a Optimized Algorithm for the Application of Active Rules in a Transition P-system

P systems or Membrane Computing are a type of a distributed, massively parallel and non deterministic system based on biological membranes. They are inspired in the way cells process chemical compounds, energy and information. These systems perform a computation through transition between two consecutive configurations. As it is well known in membrane computing, a configuration consists in a m-tuple of multisets present at any moment in the existing m regions of the system at that moment time. Transitions between two configurations are performed by using evolution rules which are in each region of the system in a non-deterministic maximally parallel manner. This work is part of an exhaustive investigation line. The final objective is to implement a HW system that evolves as it makes a transition P-system. To achieve this objective, it has been carried out a division of this generic system in several stages, each of them with concrete matters. In this paper the stage is developed by obtaining the part of the system that is in charge of the application of the active rules. To count the number of times that the active rules is applied exist different algorithms. Here, it is presents an algorithm with improved aspects: the number of necessary iterations to reach the final values is smaller than the case of applying step to step each rule. Hence, the whole process requires a minor number of steps and, therefore, the end of the process will be reached in a shorter length of time.

A PVT-Type Algorithm for Minimizing a Nonsmooth Convex Function

2000 Mathematics Subject Classification: 90C25, 68W10, 49M37.

Multi-model fitting based on minimum spanning tree

This paper presents a novel approach to the computation of primitive geometrical structures, where no prior knowledge about the visual scene is available and a high level of noise is expected. We based our work on the grouping principles of proximity and similarity, of points and preliminary models. The former was realized using Minimum Spanning Trees (MST), on which we apply a stable alignment and goodness of fit criteria. As for the latter, we used spectral clustering of preliminary models. The algorithm can be generalized to various model fitting settings, without tuning of run parameters. Experiments demonstrate the significant improvement in the localization accuracy of models in plane, homography and motion segmentation examples. The efficiency of the algorithm is not dependent on fine tuning of run parameters like most others in the field.

More than money:developing an integrative multi-factorial measure of entrepreneurial success

This article conceptualises and operationalizes ‘subjective entrepreneurial success’ in a manner which reflects the criteria employed by entrepreneurs, rather than those imposed by researchers. Using two studies, a first qualitative enquiry investigated success definitions using interviews with 185 German entrepreneurs; five factors emerged from their reports: firm performance, workplace relationships, personal fulfilment, community impact, and personal financial rewards. The second study developed a questionnaire, the Subjective Entrepreneurial Success–Importance Scale (SES-IS), to measure these five factors using a sample of 184 entrepreneurs. We provide evidence for the validity of the SES-IS, including establishing systematic relationships of SES-IS with objective indicators of firm success, annual income and entrepreneur satisfaction with life and financial situation. We also provide evidence for the cross-cultural invariance of SES-IS using a sample of Polish entrepreneurs. The quintessence of our studies being that subjective entrepreneurial success is a multi-factorial construct, i.e. entrepreneurs value various indicators of success with money as only one possible option.

On Pareto Sets in Multi-Criteria Optimization

Здравко Д. Славов - В тази работа се разглеждат Паретовските решения в непрекъсната многокритериална оптимизация. Обсъжда се ролята на някои предположения, които влияят на характеристиките на Паретовските множества. Авторът се е опитал да премахне предположенията за вдлъбнатост на целевите функции и изпъкналост на допустимата област, които обикновено се използват в многокритериалната оптимизация. Резултатите са на базата на конструирането на ретракция от допустимата област върху Парето-оптималното множество.