Subjects -> STATISTICS (Total: 130 journals)
 Showing 1 - 151 of 151 Journals sorted by number of followers Review of Economics and Statistics       (Followers: 148) Statistics in Medicine       (Followers: 134) Journal of Econometrics       (Followers: 83) Journal of the American Statistical Association       (Followers: 72, SJR: 3.746, CiteScore: 2) Advances in Data Analysis and Classification       (Followers: 52) Biometrics       (Followers: 50) Sociological Methods & Research       (Followers: 43) Journal of the Royal Statistical Society, Series B (Statistical Methodology)       (Followers: 41) Journal of Business & Economic Statistics       (Followers: 39, SJR: 3.664, CiteScore: 2) Journal of the Royal Statistical Society Series C (Applied Statistics)       (Followers: 37) Computational Statistics & Data Analysis       (Followers: 35) Oxford Bulletin of Economics and Statistics       (Followers: 33) Journal of Risk and Uncertainty       (Followers: 33) Journal of the Royal Statistical Society, Series A (Statistics in Society)       (Followers: 28) Statistical Methods in Medical Research       (Followers: 28) The American Statistician       (Followers: 26) Journal of Urbanism: International Research on Placemaking and Urban Sustainability       (Followers: 24) Journal of Biopharmaceutical Statistics       (Followers: 23) Journal of Computational & Graphical Statistics       (Followers: 21) Journal of Applied Statistics       (Followers: 20) Journal of Forecasting       (Followers: 20) British Journal of Mathematical and Statistical Psychology       (Followers: 18) Statistical Modelling       (Followers: 18) International Journal of Quality, Statistics, and Reliability       (Followers: 17) Journal of Statistical Software       (Followers: 16, SJR: 13.802, CiteScore: 16) Journal of Time Series Analysis       (Followers: 16) Risk Management       (Followers: 16) Pharmaceutical Statistics       (Followers: 15) Computational Statistics       (Followers: 15) Statistics and Computing       (Followers: 14) Demographic Research       (Followers: 14) Statistics & Probability Letters       (Followers: 13) Journal of Statistical Physics       (Followers: 13) Australian & New Zealand Journal of Statistics       (Followers: 12) International Statistical Review       (Followers: 12) Decisions in Economics and Finance       (Followers: 12) Structural and Multidisciplinary Optimization       (Followers: 12) Statistics: A Journal of Theoretical and Applied Statistics       (Followers: 12) Geneva Papers on Risk and Insurance - Issues and Practice       (Followers: 11) Communications in Statistics - Theory and Methods       (Followers: 11) Advances in Complex Systems       (Followers: 10) Journal of Probability and Statistics       (Followers: 10) The Canadian Journal of Statistics / La Revue Canadienne de Statistique       (Followers: 10) Biometrical Journal       (Followers: 9) Communications in Statistics - Simulation and Computation       (Followers: 9) Scandinavian Journal of Statistics       (Followers: 9) Asian Journal of Mathematics & Statistics       (Followers: 8) Fuzzy Optimization and Decision Making       (Followers: 8) Current Research in Biostatistics       (Followers: 8) Teaching Statistics       (Followers: 8) Multivariate Behavioral Research       (Followers: 8) Stata Journal       (Followers: 8) Argumentation et analyse du discours       (Followers: 7) Journal of Statistical Planning and Inference       (Followers: 7) Handbook of Statistics       (Followers: 7) Journal of Combinatorial Optimization       (Followers: 7) Journal of Educational and Behavioral Statistics       (Followers: 7) Lifetime Data Analysis       (Followers: 7) Queueing Systems       (Followers: 7) Research Synthesis Methods       (Followers: 7) Significance       (Followers: 7) Environmental and Ecological Statistics       (Followers: 7) International Journal of Computational Economics and Econometrics       (Followers: 6) Journal of Mathematics and Statistics       (Followers: 6) Journal of Global Optimization       (Followers: 6) Journal of Nonparametric Statistics       (Followers: 6) Statistical Methods and Applications       (Followers: 6) Law, Probability and Risk       (Followers: 6) Engineering With Computers       (Followers: 5) Optimization Methods and Software       (Followers: 5) CHANCE       (Followers: 5) Handbook of Numerical Analysis       (Followers: 5) Applied Categorical Structures       (Followers: 4) Mathematical Methods of Statistics       (Followers: 4) ESAIM: Probability and Statistics       (Followers: 4) Metrika       (Followers: 4) Statistical Papers       (Followers: 4) Monthly Statistics of International Trade - Statistiques mensuelles du commerce international       (Followers: 3) Sankhya A       (Followers: 3) Journal of Statistical and Econometric Methods       (Followers: 3) Journal of Theoretical Probability       (Followers: 3) Statistical Inference for Stochastic Processes       (Followers: 3) Journal of Algebraic Combinatorics       (Followers: 3) Stochastic Models       (Followers: 2) Building Simulation       (Followers: 2) Stochastics An International Journal of Probability and Stochastic Processes: formerly Stochastics and Stochastics Reports       (Followers: 2) IEA World Energy Statistics and Balances -       (Followers: 2) Optimization Letters       (Followers: 2) TEST       (Followers: 2) Technology Innovations in Statistics Education (TISE)       (Followers: 2) Extremes       (Followers: 2) AStA Advances in Statistical Analysis       (Followers: 2) International Journal of Stochastic Analysis       (Followers: 2) Statistica Neerlandica       (Followers: 1) Wiley Interdisciplinary Reviews - Computational Statistics       (Followers: 1) Measurement Interdisciplinary Research and Perspectives       (Followers: 1) Statistics and Economics Review of Socionetwork Strategies SourceOECD Measuring Globalisation Statistics - SourceOCDE Mesurer la mondialisation - Base de donnees statistiques Journal of the Korean Statistical Society Sequential Analysis: Design Methods and Applications
Similar Journals
 Fuzzy Optimization and Decision MakingJournal Prestige (SJR): 0.878 Citation Impact (citeScore): 3Number of Followers: 8      Hybrid journal (It can contain Open Access articles) ISSN (Print) 1573-2908 - ISSN (Online) 1568-4539 Published by Springer-Verlag  [2469 journals]
• Capacity reliability under uncertainty in transportation networks: an
optimization framework and stability assessment methodology

Abstract: Destruction of the roads and disruption in transportation networks are the aftermath of natural disasters, particularly if they are of great magnitude. As a version of the network capacity reliability problem, this work researches a post-disaster transportation network, where the reliability and operational capacity of links are uncertain. Uncertainty theory is utilized to develop a model of and solve the uncertain maximum capacity path (UMCP) problem to ensure that the maximum amount of relief materials and rescue vehicles arrive at areas impacted by the disaster. We originally present two new problems of $$\alpha$$ -maximum capacity path ( $$\alpha$$ -MCP), which aims to determine paths of highest capacity under a given confidence level $$\alpha$$ , and most maximum capacity path (MMCP), where the objective is to maximize the confidence level under a given threshold of capacity value. We utilize these auxiliary programming models to explicate the method to, in an uncertain network, achieve the uncertainty distribution of the MCP value. A novel approach is additionally suggested to confront, in the framework of uncertainty programming, the stability analysis problem. We explicitly enunciate the method of computing the links’ tolerances in $${\mathcal{O}}\left( m \right)$$ time or $${\mathcal{O}}\left( {\left {P^{*} } \right m} \right)$$ time (where $$m$$ indicates the number of links in the network and $$\left {{\text{P}}^{*} } \right$$ the number of links on the given MCP $${\text{P}}^{*}$$ ). After all, the practical performance of the method and optimization model is illustrated by adopting two network samples from a real case study to show how our approach works in realistic contexts.
PubDate: 2022-09-01

• Stability analysis for uncertain nonlinear switched systems with
infinite-time domain

Abstract: In this paper, an uncertain nonlinear switched system is a nonlinear switched system disturbed by subjective uncertainties, which can be illustrated by uncertain differential equations. Stability issues have been deeply studied on switched systems while few results about stability analysis for uncertain switched systems were published before. In order to fill this gap, three different types of stabilities called stability in measure, almost sure stability and stability in mean concerning uncertain nonlinear switched systems with infinite-time domain and countable switches are investigated in order. The internal property of the uncertain switched systems will be described and captured from diverse perspectives on the basis of the above stability analysis. The corresponding criteria to judge these stabilities are obtained according to uncertainty theory and stability theory. A numerical example concerning stability in measure is provided to show the effectiveness of the results derived.
PubDate: 2022-09-01

• Uncertain seepage equation in fissured porous media

Abstract: Seepage equation in fissured porous media is a partial differential equation describing the variation of pressure of a given area over time. In traditional seepage equation, the strength of mass source is supposed to be deterministic. However, the mass source in practice is often affected by noise such as transformation of underground environment and geological activities. To depict the noise, some scholars attempted to employ a technique called Winner process. Unfortunately, it is unreasonable to model the noise in seepage equation with Winner process, since change rate of pressure will be infinite. As a alternative tool in uncertainty theory, Liu process is introduced to model the noise, which can refrain from the problem of infinity. Then this paper deduces the uncertain seepage equation in fissured porous media driven by Liu process. Furthermore, the analytic solution and its inverse uncertainty distribution are derived. Finally, a paradox of stochastic seepage equation in fissured porous media is presented.
PubDate: 2022-09-01

• A graph model for conflict resolution with inconsistent preferences among
large-scale participants

Abstract: As a flexible and powerful method to resolve strategy conflicts, the graph model for conflict resolution has drawn much attention. In the graph model for conflict resolution, decision-makers need to provide their preference information for all possible scenarios. Most existing studies assumed that decision-makers adopt quantitative representation formats. However, in some real-life situations, decision-makers may tend to use qualitative assessments due to their cognitive expression habits. In addition, stakeholders involved in a graph model can be a group that is composed of a large number of participants. How to manage these participants’ inconsistent preference assessments is also a debatable issue. To fit these gaps, in this study, we propose a graph model for conflict resolution with linguistic preferences, and this model allows participants to use inconsistent assessments. To do this, we first construct a linguistic preference structure, with the necessary concepts being defined. Then, four stability definitions for both a two-decision-maker scenario and an n-decision-maker scenario are introduced. To illustrate the usefulness of the proposed model, an illustrative example regarding the Huawei conflict is provided.
PubDate: 2022-09-01

• An innovative unification process for probabilistic hesitant fuzzy
elements and its application to decision making

Abstract: The probabilistic hesitant fuzzy element (PHFE) is a worthwhile extension of hesitant fuzzy element (HFE) which is a means of allowing the decision makers more flexibility in expressing their preferences by the use of hesitant information in practical decision making process. To derive a more realistic expression of decision information, it is necessary to unify the arrangement of elements in PHFEs without imposing artificial elements. Up to now, several processes concerning the unification and arrangement of elements in PHFEs have been proposed, and while, most suffer from different drawbacks being critically discussed in the present study. The main aim of this study is to propose a PHFE unification process which does not have the shortcomings of existing processes, and does not change the inherent characteristic of PHFE probabilities. Based on the proposed unification process, the current study seeks to extend the theory of arithmetic operations on PHFEs by proposing and developing novel types of PHFS division and subtraction. Finally, the proposed PHFE unification process is applied to a number of multiple criteria decision-making (MCDM) problems for illustrating its vast range of applicability.
PubDate: 2022-09-01

• Some results for the minimal optimal solution of min-max programming
problem with addition-min fuzzy relational inequalities

Abstract: In this study, a BitTorrent-like peer-to-peer (BT-P2P) file-sharing system is reduced into a system of fuzzy relational inequalities (FRI) with addition-min composition. To study the stability of data transmission and network congestion, a min-max programming problem subject to addition-min FRI is proposed. From a cost-saving perspective, the optimal solution to the min-max programming problem may not be the minimal optimal solution. Furthermore, while the “optimal” solution provides better cost performance, the “minimal” solution provides for the least congestion of the file-sharing system. In this paper, we propose adopting a binding variable approach based on certain new theoretical properties to find a minimal optimal solution for the min-max programming problem. It is for these new properties that the minimal optimal solution obtained via the binding variable approach would minimize the maximum transmission level; further, the amounts of data download in the optimal solution would be as balanced as possible. Some numerical examples are provided after each of the new properties to illustrate the advantages of our approach.
PubDate: 2022-09-01

• Variable structure T–S fuzzy model and its application in
maneuvering target tracking

Abstract: To realize the adaptive identification of T–S fuzzy model structure, we propose a variable structure T–S fuzzy model algorithm. Compare to traditional multi-input single-output in the T–S fuzzy model, we extend single-output fuzzy rules to multi-dimensional output fuzzy rules, which has the advantage that all multi-dimensional outputs share the same premise parameter; Then the joint block structure sparse ridge regression model is used to realize the identification of the consequent parameter, which provides a regression model. In this model, some regression coefficient blocks with small contribution will be reduced to zero accurately, while maintaining high prediction accuracy. Otherwise, the Fuzzy Expectation Maximization (FEM) is proposed to coarse fine the premise parameter. Finally, the variable structure T–S fuzzy model is applied to the maneuvering target tracking without filter. The simulation results show that the proposed algorithm is more accurate and stable than the Interacting Multiple Model (IMM), Interacting Multiple Model Unscented Kalman Filtering (IMMUKF), Interacting Multiple Model Rao-Blackwellized Particle Filtering (IMMRBPF) and T–S Fuzzy semantic Model (TS-FM) algorithms in dealing with uncertain problems in nonlinear maneuvering target tracking systems.
PubDate: 2022-07-25

• Dynamic pricing and production control for perishable products under
uncertain environment

Abstract: In actual dynamic system, uncertainty is absolute and certainty is relative. This paper presents the optimal dynamic pricing and production control strategy for perishable products in finite horizon. The influence of external environmental disturbance on the system is considered by means of a special uncertain process (Liu process). Then based on uncertainty theory and Hurwicz criterion, the optimization model is built, where control variables are restricted to an admissible control set. In addition, uncertain differential equation is used to describe the changes of inventory. By applying the optimality equation, we determine the optimal price and production strategy to maximize profit. Besides, both the optimal price and production rate are linearly decreasing with inventory. Afterwards, two numerical examples are given, the results reveal that reducing the uncertain disturbance of inventory and expanding the potential market size are beneficial to improving the optimal profit. Moreover, risk-loving decision makers can gain more profits while facing large risks.
PubDate: 2022-07-22

• Multiple stage optimization driven group decision making method with
interval linguistic fuzzy preference relations based on ordinal
consistency and DEA cross-efficiency

Abstract: Interval linguistic term (ILT) is highly useful to express decision-makers’ (DMs’) uncertain preferences in the decision-making process. This paper proposes a new group decision-making (GDM) method with interval linguistic fuzzy preference relations (ILFPRs) by integrating ordinal consistency improvement algorithm, cooperative game, Data Envelopment Analysis (DEA) cross-efficiency model, and stochastic simulation. Firstly, the ordinal consistency of ILFPR is developed. For improving the ordinal consistency of an ILFPR, a two-stage integer optimization model is presented to derive an ILFPR with ordinal consistency. Then, a weight-determination method for obtaining DMs’ weights is presented based on cooperative games. Moreover, a DEA cross-efficiency model is presented to obtain the priorities of linguistic preference relation derived from ILFPR. Meanwhile, the expected ranking vector of ILFPR is obtained based on the DEA cross-efficiency model by integrating stochastic preference analysis and Monte Carlo stochastic simulation. Finally, a numerical example of emergency logistics selection illustrates the applicability and credibility of the proposed method.
PubDate: 2022-07-04

• Green supplier selection and order allocation using linguistic Z-numbers
MULTIMOORA method and bi-objective non-linear programming

Abstract: Supplier selection and order allocation are major tasks to companies in green supply chain management. Most literatures consider these two tasks as independent sub-problems. In this paper, we propose an integrated two-stage multiple criteria programming approach to solve them systematically. The approach includes both quantitative and qualitative analyses. In the first stage, an MULTIMOORA method based on linguistic Z-Numbers is employed to rank the green suppliers under multiple qualitative criteria (but that is not the final decision). In the second stage, the ranking result is input to a bi-objective non-linear integer programming model. The model then determines the suppliers selected and the quantity of order allocated to them. Furthermore, the model should determine the configuration of the productions because different configuration implies different resource needed. We present the comparative result with other quantitative methods. An illustrative example proves that our proposed model can achieve the desired consistency among objectives.
PubDate: 2022-06-17

• Uncertain hypothesis test for uncertain differential equations

Abstract: Uncertain hypothesis test is a statistical tool that uses uncertainty theory to determine whether some hypotheses are correct or not based on observed data. As an application of uncertain hypothesis test, this paper proposes a method to test whether an uncertain differential equation fits the observed data or not. In order to demonstrate the test method, some numerical examples are provided. Finally, both uncertain currency model and stochastic currency model are used to model US Dollar to Chinese Yuan (USD–CNY) exchange rates. As a result, it is shown that the uncertain currency model fits the exchange rates well, but the stochastic currency model does not.
PubDate: 2022-06-03

• An analytic solution for multi-period uncertain portfolio selection
problem

Abstract: The return rates of risky assets in financial markets are usually assumed as random variables or fuzzy variables. For the ever-changing real asset market, this assumption may not always be satisfactory. Thus, it is sometimes more realistic to take the return rates as uncertain variables. However, for the existing works on multi-period uncertain portfolio selection problems, they do not find analytic optimal solutions. In this paper, we propose a method for deriving an analytic optimal solution to a multi-period uncertain portfolio selection problem. First, a new uncertain risk measure is defined to model the investment risk. Then, we formulate a bi-criteria optimization model, where the investment return is maximized, while the investment risk is minimized. On this basis, an equivalent transformation is presented to convert the uncertain bi-criteria optimization problem into an equivalent bi-criteria optimization problem. Then, by applying dynamic programming method, an analytic optimal solution is obtained. Finally, a numerical simulation is carried out to show that the proposed model is realistic and the method being developed is applicable and effective.
PubDate: 2022-06-01
DOI: 10.1007/s10700-021-09367-8

• Uncertain hypothesis test with application to uncertain regression
analysis

Abstract: This paper first establishes uncertain hypothesis test as a mathematical tool that uses uncertainty theory to help people rationally judge whether some hypotheses are correct or not, according to observed data. As an application, uncertain hypothesis test is employed in uncertain regression analysis to test whether the estimated disturbance term and the fitted regression model are appropriate. In order to illustrate the test process, some numerical examples are documented.
PubDate: 2022-06-01
DOI: 10.1007/s10700-021-09365-w

• Type-2 fuzzy numbers made simple in decision making

Abstract: For the decision-making problems based on decision makers’ judgments in terms of linguistic terms, we propose type-2 fuzzy numbers (T2FNs) that allow decision makers better formalize their judgments. A T2FN has two components: a primary membership and a secondary membership. Compared with T1FSs and interval type-2 fuzzy sets, T2FNs consider an additional dimension by introducing the secondary membership. The primary membership indicates the truth degree of judgment, and the secondary membership further indicates the reliability degree of the truth. We define simple operation rules on T2FNs such that they can be easily used to deal with decision-making problems, such as multi-criteria decision making and multi-stages decision making. Compared with existing related approaches, we verify our approach with several numerical examples.
PubDate: 2022-06-01
DOI: 10.1007/s10700-021-09363-y

• Min–max programming problem with constraints of addition-min-product
fuzzy relation inequalities

Abstract: In this paper, we study a new type of fuzzy relation system called fuzzy relational inequalities with addition-min-product composition operations to model a peer-to-peer (P2P) file sharing system. Some properties of this addition-min-product system are investigated. We then characterize the structure of the solution set. Furthermore, to reduce the network congestion and improve the stability of data transmission, a min–max programming problem with constraints of addition-min-product fuzzy relation inequalities is established and investigated. We divide this min–max programming problem into several subproblems with the constraint of a single equation. Based on the optimal solutions to these subproblems, we can solve the original fuzzy relation min–max programming problem. Two algorithms, with polynomial computational complexity, are developed to search for an optimal solution to our studied problem. The validity of the algorithms is examined through a numerical example.
PubDate: 2022-06-01
DOI: 10.1007/s10700-021-09368-7

• Multiple attribute decision-making method based on projection model for
dual hesitant fuzzy set

Abstract: In the decision-making process, retaining the original data information has become a most crucial step. Dual hesitant fuzzy sets (DHFS), which can reflect the original membership degree and non-membership degree information given by the DMs, is a kind of new tool for the DMs to provide the original information as much as possible. In this paper, we focus on the decision- making problem by a projection model (Algorithm I) whose attribute values are given in the forms of dual hesitant fuzzy elements (DHFEs). In order to reflect the information of the data more accurately, we first divide the dual hesitant fuzzy decision matrix into membership degree matrix and non-membership degree matrix. Then we gain the virtual positive ideal solution from the membership degree matrix and the negative positive ideal solution from the non-membership degree matrix. And then the projection values from every solution to the virtual positive ideal solution and the negative positive ideal solution are calculated. In combination with the two projection values, the relative consistent degree is further calculated to rank all the alternatives. At the same time, in order to guarantee the rationality of the decision-making result, a variation coefficient method is developed to determine the weights of the attributes under dual hesitant fuzzy environment objectively. Finally, the existing algorithms (Algorithm II and Algorithm III, Algorithm IV, Algorithm V) are compared with our algorithm (Algorithm I). The comparison result shows that Algorithm I is a valuable tool for decision making.
PubDate: 2022-06-01
DOI: 10.1007/s10700-021-09366-9

• Fuzzy chance-constrained data envelopment analysis: a structured
literature review, current trends, and future directions

Abstract: Fuzzy data envelopment analysis (FDEA) is one of the most applicable approaches for performance assessment of peer decision making units under ambiguity which is evolving rapidly and gaining popularity under uncertain data envelopment analysis field. The goal of this paper is to review some FDEA models based on applied possibility, necessity, credibility, general fuzzy measures and chance-constrained programming to deal with data ambiguity. The study presents a comprehensive and structured literature review of fuzzy chance-constrained data envelopment analysis (FCCDEA) studies including 87 studies from 2000 to 2020. The main contributions of this research include the following details: (1) Review of fuzzy chance-constrained programming, (2) Survey of FCCDEA models based on different fuzzy measures, (3) Analysis of FCCDEA applications and features, (4) Classification of FCCDEA studies from modeling and uncertainty type viewpoints, (5) Bibliometric analysis of FCCDEA literature, and (6) Extraction of main research gaps and guidelines for future research directions.
PubDate: 2022-06-01
DOI: 10.1007/s10700-021-09364-x

• Evaluation and its derived classification in a Server-to-Client
architecture based on the fuzzy relation inequality

Abstract: Server-to-Client network system is one of the most important architectures for data transmission. Fuzzy relation inequalities have been introduced to manage the quality levels in such system. In most existing works, relevant optimization models have been studied for providing some optional schemes to the manager. In this paper, we first define the concept of evaluation score for the server, embodying the service capability for supplying its local resources to the clients. Then the servers could be ordered according to their evaluation scores. Some interesting properties of the evaluation score vector are investigated. Applying our proposed evaluation model, we further construct an equivalence relation, based on which the complete solution set of the fuzzy relation inequalities could be divided into several equivalence classes. In such classification, each equivalence class corresponds to a unique evaluation score vector. Numerical examples are provided to illustrate our proposed evaluation model and classification method.
PubDate: 2022-05-30

• Optimality conditions for nonlinear optimization problems with
interval-valued objective function in admissible orders

Abstract: This paper addresses the optimization problems with interval-valued objective function. We consider three types of total order relationships on the interval space. For each total order relationship, we introduce interval-valued convex functions and obtain Karush-Kuhn-Tucker (KKT) optimality conditions in an optimization problem with interval-valued objective function. In order to illustrate these conditions, some numerical examples have been considered and solved.
PubDate: 2022-05-21
DOI: 10.1007/s10700-022-09391-2

• Three-way investment decisions during the epidemic with Choquet-based
bi-projection method

Abstract: The outbreak of epidemic has had a big impact on the investment market of China. Facing the turbulence in the investment market, many enterprises find it difficult to judge the development prospects of investment projects and make the right investment decisions. The three-way decisions offer a novel study perspective to solve this problem. Then the developed model is applied to select the investment projects. Firstly, some relevant attributes of the project are described with the double hierarchy hesitant fuzzy linguistic term sets. And a double hierarchy hesitant fuzzy linguistic information system is constructed for each project. Secondly, the weights of attributes are determined with the Choquet integral method. And the closeness degree calculated by Choquet-based bi-projection method is taken as the conditional probability that the project will be profitable. Next, considering the influence of the bounded rationality of decision makers, the threshold parameters are calculated based on prospect theory. Finally, the decision results about investment projects during four stages are deduced based on the principle of maximum-utility, which demonstrates the practicability and effectiveness of the proposed model.
PubDate: 2022-05-07
DOI: 10.1007/s10700-022-09388-x

JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762