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This article addresses the contemporary framework of housing at the EU level in the era of the ‘Housing at the Centre’ approach. More specifically, the research focuses on mass housing neighbourhoods (MHN) as the leading pattern of urban transformation in European cities in the second half of the 20th century, with the intention being to decode the possibilities for its rehabilitation in line with integrated approaches. The article combines (1) a review-based and systematically-oriented approach, in order to provide a state of the art of EU design taxonomy related to the housing issue, and, more specifically, related to MHN, with (2) a comparative study between EU and national design taxonomies, in order to address their conditionality and possible mismatches. The research considers design taxonomy to gain a more comprehensive insight into the content and coherence between programme values and the relevant EU documents (declarations, statements, policy positions, resolutions, reports, communications, charters, action plans, opinions) related to the housing issue, or broader urban issues that include housing as the scope of observation. The taxonomy enables a conceptual methodological framework for a systematic, consistent, and complete description of key research relations. Accordingly, the specific objective of this article is to establish an evaluation framework for reprogramming of MHN based on the EU design taxonomy through (1) the development of the programming matrix for evaluation, which corresponds to the value-based architectural programming model; and (2) introducing Serbian national design taxonomy, in order to demonstrate the anticipation of design values based on the EU taxonomy within the local context. The results indicate the need to examine and test regulatory experimental settings through middle-out approaches, whose central research perspective will be built parallel and coherently through bottom-up inputs, created as the result of collaborative approaches at the community level, and top-down inputs which are the result of the strategic framework established in relation to priorities at the European level.

This paper proposes an accounting framework that breaks up a country's gross exports into various value-added components by source and additional double-counted terms. Our parsimonious framework bridges a gap between official trade statistics (in gross value terms) and national accounts (in value-added terms), and integrates all previous measures of vertical specialization and value-added trade in the literature into a unified framework. To illustrate the potential of such a method, we present a number of applications including re-computing revealed comparative advantages and the magnifying impact of multi-stage production on trade costs.

This paper presents a precision forward design method for 3D printing (3DP) using kinematic sensitivity via Jacobian matrix (KSJM) considering uncertainty. The advanced manufacturing such as 3DP profoundly affects us everywhere. However, in many cases, practical uncertain factors such as mechanical and thermal effects affect the precision unquantifiably. Aiming at realizing forward design from requirements to performance, the various kinematic chains are summarized to propose the concept of kinematic sensitivity. The Jacobian matrix which reflects the relationship between input error and output error is decomposed through singular value decomposition (SVD). The KSJM is hereby proposed by furtherly defining four sensitivity parameters: compositive amplification factor of error, reliability of error, absolute amplification factor of error, and comprehensive index of error. The influence of uncertainty such as thermal deformation on the accuracy of end-effector in Cartesian space is investigated by heat fluid-solid coupling simulation and piecewise fitting of thermal deformation. Taking delta 3DP robot as example, the kinematic chains and error sensitivity of the multi-body system are addressed. The physical experiment is implemented via attitude sensors with accelerometers, gyroscopes, and magnetometer. The results proved that trajectory accuracy and reliability can be improved especially under complex random uncertainty.

Purpose This study aims to present a novel methodology for the evaluation of tribological properties of new nanocomposites with the A356 alloy matrix reinforced with aluminium oxide (Al2O3) nanoparticles. Design/methodology/approach Metal matrix nanocomposites (MMnCs) with varying amounts and sizes of Al2O3 particles were produced using a compocasting process. The influence of four factors, with different levels, on the wear rate, was analysed with the help of the design of experiments (DoE). A regression model was developed by using the response surface methodology (RSM) to establish a relationship between the observed factors and the wear rate. An artificial neural network was also applied to predict the value of wear rate. Adequacy of models was compared with experimental values. The extreme values of wear rate were determined with a genetic algorithm and particle swarm optimization using the RSM model. Findings The combination of optimization methods determined the values of the factors which provide the highest wear resistance, namely, reinforcement content of 0.44 wt.% Al2O3, sliding speed of 1 m/s, normal load of 100 N and particle size of 100 nm. Used methods proved as effective tools for modelling and predicting of the behaviour of aluminium matrix nanocomposites. Originality/value The specific combinations of the optimization methods has not been applied up to now in the investigation of MMnCs. In addition, using of small content of ceramic nanoparticles as reinforcement has been poorly investigated. It can be stated that the presented approach for testing and prediction of the wear rate of nanocomposites is a very good base for their future research.

This paper designs a decentralized sliding mode preview repetitive control (SMPRC) for interconnected nonlinear systems. First, an augmented error system, which is composed of the derivative equation of the available future reference dynamics, the output of the modified repetitive controller and the tracking error dynamics, is constructed. Next, an integral switching surface is designed to verify the robust asymptotic stability of the considered system subject to nonlinearity. Then, the preview repetitive-control (PRC) law design problem is transformed into the stability problem of the augmented system considering the nominal conditions. Thereafter, a sliding mode control (SMC) law cooperates with the PRC law with the purpose to ensure the robustness of the interconnected systems in the presence of nonlinearity. Further, the required stability conditions are derived on the basis of a Lyapunov analysis, linear matrix inequalities (LMI) and the singular-value-decomposition (SVD) technique. Finally, the numerical simulation results demonstrate the effectiveness of the proposed method.

This paper presents a topology optimization approach that is innovative with respect to two distinct matters. First of all the proposed formulation is capable to handle static and dynamic topology optimization with virtually no modifications. Secondly, the approach is inherently a multi-input multi-output one, i.e., multiple objectives can be pursued in the presence of multiple loads. The input-to-output transfer matrix, say G , is the key ingredient that governs the algebraic mapping between applied loads and structural response. In statics G depends on the design variables only, whereas it depends on the frequency variable as well in the dynamic case. The Singular Value Decomposition (SVD) of G represents then the core of the proposed approach. Singular values are shown to be the gains of the input/output mapping and are used to compute proper norms of G that represent the goal functions to be minimized. Singular vectors provide at no extra cost the plant directions, i.e., the load combination factors that stress the structure the most. Numerical examples are discussed in much detail and open issues object of ongoing investigations are highlighted. A full Matlab code handling the static topology optimization problem is provided as an online Appendix to the manuscript. Its extension to the dynamic case may be gathered following the formulation proposed in Sect.  5 .

For some experimenters, a disadvantage of the standard optimal design approach is that it does not consider explicitly the aliasing of specified model terms with terms that are potentially important but are not included in the model. For example, when constructing an optimal design for a first-order model, aliasing of main effects and interactions is not considered. This can lead to designs that are optimal for estimation of the primary effects of interest, yet have undesirable aliasing structures. In this article, we construct exact designs that minimize the squared norm of the alias matrix subject to constraints on design efficiency. We demonstrate use of the method for the construction of screening and response surface designs.

Purpose The performance of the measurement matrix directly affects the quality of reconstruction of compressive sensing signal, and it is also the key to solve practical problems. In order to solve data collection problem of wireless sensor network (WSN), the authors design a kind of optimization of sparse matrix. The paper aims to discuss these issues. Design/methodology/approach Based on the sparse random matrix, it optimizes the seed vector, which regards elements in the diagonal matrix of Hadamard matrix after passing singular value decomposition (SVD). Compared with the Toeplitz matrix, it requires less number of independent random variables and the matrix information is more concentrated. Findings The performance of reconstruction is better than that of Gaussian random matrix. The authors also apply this matrix to the data collection scheme in WSN. The result shows that it costs less energy and reduces the collection frequency of nodes compared with general method. Originality/value The authors design a kind of optimization of sparse matrix. Based on the sparse random matrix, it optimizes the seed vector, which regards elements in the diagonal matrix of Hadamard matrix after passing SVD. Compared with the Toeplitz matrix, it requires less number of independent random variables and the matrix information is more concentrated.

This paper deals with the problem of robust H ∞ impulsive control for time-varying delays descriptor Markovian jump systems based on impulse instants correlative Lyapunov–Krasovskii functional. By exploiting singular value decomposition technique and matrix transformation method, a desired impulsive feedback controller is designed, which not only ensures the stochastic admissibility of time-varying delays descriptor jump system, but also meets the H ∞ performance index. An improved impulse instants correlative Lyapunov–Krasovskii functional is utilized to obtain novel conditions of stochastic admissibility and realize impulsive feedback controller design, which are derived from a set of linear matrix inequalities. Finally, the validity of the results is illustrated by a numerical example and a reservoir fish culture model.

PurposeThe circular economy concept emerged as the resolution to the destructive linear economy practices. Nevertheless, the transition to a circular built environment is hindered due to the ambiguities of the economic value of the concept. Conversely, numerous decision-making tools are applied in the construction industry in assessing economic alternatives, even if there is a gap in utilising these tools in appraising circular economic practices. Hence, this study investigates the potential benefits of applying proven decision-making practices, particularly criteria scoring matrices, in developing circular built environments.Design/methodology/approachA qualitative approach was followed to achieve the aim of the study. A conceptual design of a criteria scoring matrix was developed with a comprehensive literature survey. Semi-structured interviews of a three-round Delphi expert survey were employed to assess the matrix qualitatively and develop the matrix further. Data were analysed using the content analysis method.FindingsThe lack of a value assessment tool in economically assessing the circular economy principles is a key barrier to transcending to a circular built environment. In addressing this issue, this study develops a criteria scoring matrix for circularity value assessment during the design stage of a construction project.Originality/valueThis research contributes to the theory by developing a criteria scoring matrix to measure the economic contribution of circular economy principles. Further, this research contributes to the practice by allowing construction alternatives to be selected, balancing the potential economic return options of a project with the project's contribution to a circular economy.