Aggregation Methodology Research Articles

An Integrated Risk Capital Aggregation Framework Using Nonlinear Classification by Random Forests and Its Proximity Measures

This paper proposes an integrated risk capital aggregation methodology based on the non-linear classification algorithm Random Forests. Random Forests offers the advantages of handling a large amount of data, allows for over-specification and requires neither assumptions about the distributions nor knowledge of the models behind the included risk indicators and capital figures of different risk types. All interactions in the aggregation model are estimated by an adaption of the Random Forests proximities conditional on the risk indicators used to build the forest. The proposed proximity based aggregation model is shown to be accurate yet requires less risk capital in comparison to established aggregation methodologies and reservation models. Additional results are its strong stability over time and that the adapted proximities represent an alternative to the usage of correlation.

Constructing the FEEM sustainability index: A Choquet integral application

This paper presents the development of the FEEM sustainability index (FEEM SI), a composite index including 19 different indicators grouped in the three classical pillars of sustainability – economic, social and environmental. We present the relevance of multi-attribute aggregation methodologies when dealing with such complex concepts and apply an aggregation methodology used for this case study: the Choquet integral operator. First, we normalize each sustainability indicator with the use of a benchmarking procedure with a smooth target of sustainability. We then develop an aggregation tree of sustainability criteria and a questionnaire to measure the values that experts attribute to individual sustainability criteria and their interaction. This survey suggests that a majority of experts consider sustainability criteria as complementary to each other. After combining the preferences of different experts to establish a consensus, we construct the FEEM SI using the Choquet integral aggregation procedure. The results for sustainability levels show that countries that are ranked at higher (lower) positions are those that have better (worse) outcomes in at least in two final pillars, respectively. Finally, we conduct a robustness analysis by repeating the aggregation procedure with different convex combinations of experts’ preferences. The results indicate that, while sustainability levels of countries do vary with the expert preferences, countries’ respective rankings remain mainly the same, irrespective of the combination of experts’ preferences.

Evolution of Management Controlling Framework: Literature Review

Purpose – Definition of Management Controlling Framework (MCF) had undergone many changes during a short period of time. Definition change mostly reflected a scope transformation during this system development. The aim of this paper is to investigate evolution of Management Controlling Framework, to compare different approaches and discuss outcomes, to propose future development directions based on historical background. It presents a historical revision of different trends of management controlling systems in organisations, according to four indicators: scope, outcome, tools and contradictions. Johnson and Kaplan (1987) suggestion was taken as the starting point of current investigation, as it significantly affected viewpoint change and further behaviour.Design/methodology/approach – A systematic literature review of publications in public sector, management and accounting journals since 1990 was conducted with the aim to answer the research questions: 1. How Management Controlling Framework are described? 2. What are the main characteristics of MCF? 3. How scope of Management Controlling Framework changed over time. 4. What are the main contradictions? Data analysis was performed using Theory of Inventive Problem Solving (TIPS, TRIZ), and a special part of this theory — ‘Laws of (technical) systems evolution’ (LTSE).Findings – Overall, the results confirm that Management Controlling Framework (MCF) can be described and trended through Laws of (technical) systems evolution. These findings provide the following insights for future research such as solve contradictions: 1. Overview, but not overload (detalization problem). 2. Subsidiary independent, but over control (HQ involvement problem) 3.Managing Innovation versus Managing Operations (development problem). 4. Differentiation and unification (culture problem). 5. Leadership versus review (GM problem). 6. Common understanding on the control way and results quantification (Measurement identity problem).Research limitations/implications – Generalisation of research results is limited by three main controlling frameworks and Agency theory as additional lever. Only one aggregation methodology was taken as tool - Theory of Inventive Problem Solving.

Heterogeneous Visual Codebook Integration Via Consensus Clustering for Visual Categorization

Most recent category-level object and activity recognition systems work with visual words, i.e., vector-quantized local descriptors. These visual vocabularies are usually built by using a local feature, such as SIFT, and a single clustering algorithm, such as K-means. However, very different clusterings algorithms are at our disposal, each of them discovering different structures in the data. In this paper, we explore how to combine these heterogeneous codebooks and introduce a novel approach for their integration via consensus clustering. Considering each visual vocabulary as one modal, we propose the visual word aggregation (VWA) methodology, to learn a common codebook, where the stability of the visual vocabulary construction process is increased, the size of the codebook is determined in an unsupervised integration, and more discriminative representations are obtained. With the aim of obtaining contextual visual words, we also incorporate the spatial neighboring relation between the local descriptors into the VWA process: the contextual-VWA approach. We integrate over-segmentation algorithms and spatial grids into the aggregation process to obtain a visual vocabulary that narrows the semantic gap between visual words and visual concepts. We show how the proposed codebooks perform in recognizing objects and scenes on very challenging datasets. Compared with unimodal visual codebook construction approaches, our multimodal approach always achieves superior performances.

Aggregation of carbon dioxide sequestration storage assessment units

The U.S. Geological Survey is currently conducting a national assessment of carbon dioxide (CO2) storage resources, mandated by the Energy Independence and Security Act of 2007. Pre-emission capture and storage of CO2 in subsurface saline formations is one potential method to reduce greenhouse gas emissions and the negative impact of global climate change. Like many large-scale resource assessments, the area under investigation is split into smaller, more manageable storage assessment units (SAUs), which must be aggregated with correctly propagated uncertainty to the basin, regional, and national scales. The aggregation methodology requires two types of data: marginal probability distributions of storage resource for each SAU, and a correlation matrix obtained by expert elicitation describing interdependencies between pairs of SAUs. Dependencies arise because geologic analogs, assessment methods, and assessors often overlap. The correlation matrix is used to induce rank correlation, using a Cholesky decomposition, among the empirical marginal distributions representing individually assessed SAUs. This manuscript presents a probabilistic aggregation method tailored to the correlations and dependencies inherent to a CO2 storage assessment. Aggregation results must be presented at the basin, regional, and national scales. A single stage approach, in which one large correlation matrix is defined and subsets are used for different scales, is compared to a multiple stage approach, in which new correlation matrices are created to aggregate intermediate results. Although the single-stage approach requires determination of significantly more correlation coefficients, it captures geologic dependencies among similar units in different basins and it is less sensitive to fluctuations in low correlation coefficients than the multiple stage approach. Thus, subsets of one single-stage correlation matrix are used to aggregate to basin, regional, and national scales.

Framework for Detailed Comparison of Building Environmental Assessment Tools

Understanding how Building Environmental Assessments Tools (BEATs) measure and define “environmental” building is of great interest to many stakeholders, but it is difficult to understand how BEATs relate to each other, as well as to make detailed and systematic tool comparisons. A framework for comparing BEATs is presented in the following which facilitates an understanding and comparison of similarities and differences in terms of structure, content, aggregation, and scope. The framework was tested by comparing three distinctly different assessment tools; LEED-NC v3, Code for Sustainable Homes (CSH), and EcoEffect. Illustrations of the hierarchical structure of the tools gave a clear overview of their structural differences. When using the framework, the analysis showed that all three tools treat issues related to the main assessment categories: Energy and Pollution, Indoor Environment, and Materials and Waste. However, the environmental issues addressed, and the parameters defining the object of study, differ and, subsequently, so do rating, results, categories, issues, input data, aggregation methodology, and weighting. This means that BEATs measure “environmental” building differently and push “environmental” design in different directions. Therefore, tool comparisons are important, and the framework can be used to make these comparisons in a more detailed and systematic way.

Quantifying Sustainability: A New Approach and World Ranking

This paper proposes a new tool to assess sustainability and make the concept of sustainable development operational. It considers its multi-dimensional structure combining the information deriving from a selection of relevant sustainability indicators belonging to economic, social and environmental pillars. It reproduces the dynamics of these indicators over time and countries. Then, it aggregates these indicators using a new approach based on Choquet’s integrals. The main novelties of this approach are indeed: (i) the modelling framework, a recursive-dynamic computable general equilibrium used to calculate the evolution of all indicators over time throughout the world, and (ii) the aggregation methodology to reconcile them in one aggregate index to measure overall sustainability. The former allows capturing the sector and regional interactions and higher-order effects driven by background assumptions on relevant variables to depict future scenarios. The latter makes it possible to compare sustainability performances, under alternative scenarios, across countries and over time. Main results show that the current sustainability at world level differs from what the traditional measure of well-being, the GDP, depicts, highlighting the trade-offs among different components of sustainability. Moreover, in the next decade a slight decrease in world sustainability may occur, in spite of an expected increase in world domestic product. Finally, dedicated policies increase overall sustainability, showing that social and environmental benefits may be greater than the correlated economic costs.

Constructing the FEEM Sustainability Index: A Choquet-Integral Application

This paper presents an application of a multi-attribute aggregation methodology to the construction of a sustainability index. Sustainability is a multi-faceted issue, in which synergies or conflicts may arise among the different components, thus making it a complex concept to which multi attribute methods can be employed. This paper addresses the development of the FEEM Sustainability Index (FEEM SI), a composite index including 19 different indicators grouped in the three classical pillars of sustainability ‒ economic, social and environmental. We present the relevance of multi-attribute aggregation methodologies when dealing with such complex concepts and provide an aggregation methodology used for this case study, the Choquet-integral aggregation. First, we normalize each sustainability indicator with the use of a benchmarking procedure with a smooth target of sustainability. Furthermore, an ad-hoc questionnaire implemented to assess the importance of each sustainability indicator and their interaction with other indicators through expert elicitation. After normalizing each sustainability indicator and computing consensus importance of each sustainability indicator and their interactions for the Choquet-integral aggregation procedure, the overall sustainability index, the FEEM SI is calculated. This paper also conducts robustness analysis and discusses the main implications of the aggregation methodology used.

Speed Constraints Handling in USV Swarm Path-Following Frameworks

This paper focuses on the improvement of a swarm-based path-following guidance system for an autonomous marine multi-vehicle system. In the seminal idea a team of Unmanned Surface Vehicles (USVs) is required to join into a formation by means of a potential-based swarm aggregation methodology, while a virtual-target based guidance module drives the whole formation towards a desired reference path. Such a framework is then enhanced by taking into account the vehicles' positive surge speed constraint and maximum limit, typical of marine systems. The analysis of the results is reported to prove the feasibility and reliability of the proposed methodology, as well as the performance evaluation of the overall system.

Constructing the Feem Sustainability Index: A Choquet-Integral Application

This paper presents an application of a multi-attribute aggregation methodology to the construction of a sustainability index. Sustainability is a multi-faceted issue, in which synergies or conflicts may arise among the different components, thus making it a complex concept to which multi attribute methods can be applied. This paper addresses the development of the FEEM Sustainability Index (FEEM SI), a composite index including 19 different indicators grouped in the three classical pillars of sustainability ‒ economic, social and environmental. We present the relevance of multi-attribute aggregation methodologies when dealing with such complex concepts and provide an aggregation methodology used for this case study, the Choquet-integral aggregation. In particular, since this methodology requires the assignment of weights on indicators and their coalitions, an ad hoc questionnaire is implemented to assess the importance of sustainability indicators through expert elicitation. After computing consensus weights for the Choquet-integral aggregation procedure the overall sustainability index, the FEEM SI is calculated. This paper also conducts robustness analysis and discusses the main implications of the aggregation methodology used.

A fuzzy and bipolar approach to preference modeling with application to need and desire

Fuzziness and bipolarity allow representing human knowledge, taking into account the gradual and the dialectic properties of language, focusing on the meaning of concepts. Under this cognitive and linguistic approach, we explore preference relations, examining their semantic decomposition through fuzzy preference structures and the specification of meaningful opposites. In particular, we introduce the Preference–Aversion (P–A) model, which allows analyzing, under an independent aggregation methodology, the possible gains and losses, like pros and cons, towards a given set of alternatives. As an attractive feature of this proposal, we show that the P–A model allows distinguishing between need and desire, contrary to common preference models where both notions are indistinguishable.

Packet Aggregation and Abnormal Traffic Fitering Methodology for Network System Performance

Packet Aggregation and Abnormal Traffic Fitering Methodology for Network System Performance

A hierarchical mobile‐agent‐based security operation center

SUMMARYThe continuous evolvement of the e‐domain has led to a significant increase in the amount of sensitive personal information stored on networked hosts. These hosts are invariably protected by security mechanisms such as intrusion detection systems, Intrusion Prevention System (IPS), antivirus software, firewalls, and so forth. However, they still remain vulnerable to the threat of malicious attacks, theft and intrusion. The high false positive alarm rate of such mechanisms is particularly troublesome because false alarms greatly degrade the efficiency of the security framework. Security operation centers (SOCs) provide an automated solution for analyzing the threat to a network such that appropriate protective measures can be put in place. This paper proposes a novel hierarchical mobile‐agent‐based SOC to overcome the vulnerability of traditional static SOCs to single point of failure attacks. In addition, the network is partitioned into multiple divisions, each with its own alert detection and aggregation methodology to improve the computational efficiency of the data collection and fusion process. The data acquired in the various divisions are fused and correlated in an efficient manner via intrusion detection message exchange format, XML, session and timer methods The experimental results confirm the effectiveness and efficiency of the proposed hierarchical mobile‐agent‐based SOC framework. Copyright © 2012 John Wiley & Sons, Ltd.

Using the natural capital index framework as a scalable aggregation methodology for regional biodiversity indicators

There is an increasing need for aggregated biodiversity indicators to inform policy decisions at all levels from local to global. Despite their similar policy goals, low-level (e.g. local, regional) and high-level (e.g. continental, global) indicator development is generally performed independently, and the resulting indicators are often incompatible both in their structure and data requirements. In this paper we focus on a particularly flexible aggregation framework originally developed for global assessments, the Natural Capital Index. We show that with the use of appropriate fine-scale data, the NCI framework can be applied in low-level policy contexts as well. To support this statement, we show that several established low-level indicators are essentially conforming to the NCI framework, and can be seen as existing low-level NCI implementations. The concept is illustrated with an implementation for Hungary, and the potential advantages and shortcomings of low level NCI implementations are discussed. NCI-based low level indicators can be implemented in any region, where a local indicator of ecological quality is systematically surveyed. Given the recent surge in monitoring activities worldwide, fuelled by global change and reporting obligations, fine-scale NCI implementations can become important additions to existing ecological state indicators useful in a wide range of local and regional policy contexts.

Measurement and Modelling of Dependencies in Economic Capital

This paper covers a number of different topics related to the measurement and modelling of dependency within economic capital models. The scope of the paper is relatively wide. We address in some detail the different approaches to modelling dependencies ranging from the more common variance-covariance matrix approach, to the consideration of the use of copulas and the more sophisticated causal models that feature feedback loops and other systems design ideas.There are many data and model uncertainties in modelling dependency and so we have also endeavoured to cover topics such as spurious relationships and wrong-way risk to highlight some of the uncertainties involved.With the advent of the internal model approval process under Solvency II, senior management needs to have a greater understanding of dependency methodology. We have devoted a section of this paper to a discussion of possible different ways to communicate the results of modelling to the board, senior management and other interested parties within an insurance company.We have endeavoured throughout this paper to include as many numerical examples as possible to help in the understanding of the key points, including our discussion of model parameterisation and the communication to an insurance executive of the impact of dependency on economic capital modelling results.The economic capital model can be seen as a combination of two key components: the marginal risk distribution of each risk and the aggregation methodology which combines these into a single aggregate distribution or capital number. This paper is concerned with the aggregation part, the methods and assumptions employed and the issues arising, and not the determination of the marginal risk distributions which is equally of importance and in many cases equally as complex.

From the Relative Women Disadvantage Index to Women’s Quality‐of‐Life

Using Sen’s capability approach and an aggregation methodology based on the fuzzy set approach, this article attempts to move beyond the main criticisms of the United Nations Development Programme indices for analysis of gender inequality. The Relative Women Disadvantage Index can be used to measure gender inequality in three domains (health, education, participation). It is complemented by the Women’s Quality‐of‐Life Index, constructed from indicators that concern only women and children. However, these two indices are strongly correlated and seem to buttress the idea that the battle against gender inequalities is a condition for improving human development.

Aggregation Methodology for the Circum-Arctic Resource Appraisal

This paper presents a methodology that intends to aggregate the results of a recent assessment of undiscovered conventional oil and gas resources of the Arctic by the U.S. Geological Survey. The assessment occurred in 48 geologically defined regions called assessment units. The methodology includes using assessor specified pair-wise correlations as the basis to construct a correlation matrix. Sampling from this matrix generates more realistic uncertainty estimates of aggregated resources than if assumptions of total independence or total dependence are made. The latter two assumptions result in overly narrow or overly broad estimates. Aggregation results for resources in regions north of the Arctic Circle are presented.

Should you believe in the Shanghai ranking?

This paper proposes a critical analysis of the “Academic Ranking of World Universities”, published every year by the Institute of Higher Education of the Jiao Tong University in Shanghai and more commonly known as the Shanghai ranking. After having recalled how the ranking is built, we first discuss the relevance of the criteria and then analyze the proposed aggregation method. Our analysis uses tools and concepts from Multiple Criteria Decision Making (MCDM). Our main conclusions are that the criteria that are used are not relevant, that the aggregation methodology is plagued by a number of major problems and that the whole exercise suffers from an insufficient attention paid to fundamental structuring issues. Hence, our view is that the Shanghai ranking, in spite of the media coverage it receives, does not qualify as a useful and pertinent tool to discuss the “quality” of academic institutions, let alone to guide the choice of students and family or to promote reforms of higher education systems. We outline the type of work that should be undertaken to offer sound alternatives to the Shanghai ranking.

The assessment of sustainable tourism: Application to Spanish coastal destinations

This paper introduces an indicator system to evaluate sustainability in established coastal tourism destinations, applying the recommendations and definitions of the World Tourism Organization (WTO). We also develop a new synthetic indicator to simplify the measurement of sustainability and facilitate the comparative analysis of destination ranking. This measurement was obtained by applying a procedure to reduce the number of subjective decisions made by the analyst, using a novel two-stage aggregation methodology based on principal component analysis and on the distance to a reference point. The synthetic indicator obtained was applied to Spanish coastal destinations, and the results serve as a guideline for tourism planning. The conclusions of this research can be extrapolated to the study of other tourism destinations.

Stabilizing switching design for switched linear systems: A state-feedback path-wise switching approach

This paper addresses the problem of switching stabilization for discrete-time switched linear systems. Based on the abstraction–aggregation methodology, we propose a state-feedback path-wise switching law, which is a state-feedback concatenation from a finite set of switching paths each defined over a finite time interval. We prove that the set of state-feedback path-wise switching laws is universal in the sense that any stabilizable switched linear system admits a stabilizing switching law in this set. We further develop a computational procedure to calculate a stabilizing switching law in the set.