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In this paper, an inverse analysis is used to find an appropriate heat flux distribution over the heater surface of radiant enclosures, filled with nongray media at radiative equilibrium from the knowledge of desired (prespecified) temperature and heat flux distributions over the given design surface. Regular and irregular 2D enclosures filled with nongray combustive gas products are considered. Radiation is considered the dominant mode of heat transfer and the medium temperature is obtained from the energy equation. To evaluate the nongray behavior of the participating gases properly, the spectral‐line weighted‐sum‐of‐gray‐gases (SLW) model with updated correlations is used. The dependence of absorption coefficients and the weights of the SLW model on the temperature of the medium makes the inverse problem nonlinear and difficult to handle. Here, the inverse problem is formulated as an optimization problem and the Levenberg‐Marquardt method has been used to solve it. The finite volume method is exploited for the discretization of the energy equation and the spatial discretization of the radiative transfer equation (RTE). The discrete ordinates method (TN quadrature) is used for the angular discretization of RTE. Five test cases, including homogeneous and inhomogeneous media, are investigated to prove the ability of the present methodology for achieving the desired conditions. [ABSTRACT FROM AUTHOR]

The determination of three‐dimensional geometry and acquisition parameters, the seismic acquisition survey design, is constantly subject of studies in obtaining data with the highest seismic quality, operational efficiency and cost minimization. In this paper, we propose a methodology for inverting geometry parameters of three‐dimensional orthogonal land seismic surveys based on a direct search method using a mixed‐radix based algorithm. In this algorithm, the search space is discretized on a mixed‐radix base, which depends on the extreme values and the search resolution of each parameter. We will show how to reparametrize the orthogonal acquisition geometry elements in order to obtain the independents and integers parameters that are necessary to construct the mixed‐radix base. For the optimization purpose, we define an objective function to contemplate target parameters associated with the elements of the acquisition geometry directly related to the geophysical and operational constraints. Taking in account that the mathematical functions and the objective function we define for the problem have no significant computational cost, all model space parameters are fast and efficiently tested. We applied the algorithm, using as input data, provided by a one‐line roll orthogonal reference geometry, assuming a pair of geological objectives as shallow and deep targets. All selected models that meet both the proposed objectives and the constraints are organized by decreasing order of fitness so that with the mixed‐radix inversion algorithm we found not only the best model, but also a set of suitable models. Likewise, with the best set of geometries, it is possible to establish a direct comparison between them, analysing their adherence to the technical and operational requirements according to the availability and degree of detail of each one. We show the top 10 best results as a table, allowing a direct comparison between all aspects of these geometries, and we summarize the results showing graphically the fitness of all selected geometries and the inverted geometry elements for the 1000 best geometries. These graphical displays provide a direct way to understand how each model behaves as the fitness decreases. The algorithm is very flexible and its application can be extended to any environment and type of acquisition geometry, and in any phase study of an area be it regional, exploratory or development. [ABSTRACT FROM AUTHOR]

BACKGROUND: The thick rind of Fukumoto navel orange is a great barrier to light penetration, which makes it difficult to evaluate the internal quality of Fukumoto navel orange accurately by visible–near‐infrared (Vis‐NIR) transmittance spectroscopy. The information carried by the transmission spectrum is limited. Thus, the application of genetic algorithm (GA) for variable selection may not reach the expected results, and selected variables may contain redundancy. In this paper, we present the use of discrete wavelet transforms for optimizing a GA–partial least squares (PLS) model based on Vis‐NIR transmission spectra of Fukumoto navel orange. Haar, Db, Sym, Coif and Bior wavelets were used to compress the spectral data selected by GA. Then a PLS model was established based on the variables compressed by each wavelet function. RESULTS: The use of Db4, Sym4, Coif2 and Bior3.5 succeeded in further simplification of the GA‐PLS model by reducing the number of variables by 40–44% without decreasing the prediction accuracy. The application of Bior3.5 not only could reduce the number of variables in the GA‐PLS model by 40%, but also increase the value of correlation coefficient of prediction by 1% and decrease the value of root mean square error of prediction by 3%. CONCLUSIONS: The results indicated that the combination of GA and discrete wavelet transforms for variable selection in the internal quality assessment of Fukumoto navel orange by Vis‐NIR transmittance spectroscopy was feasible. © 2019 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

Summary: In this paper, an L1 adaptive output‐feedback controller is developed for multivariable nonlinear systems subject to constraints using online optimization. In the L1 adaptive architecture, an adaptive law will update the adaptive parameters that represent the nonlinear uncertainties such that the estimation error between the predicted state and the real state is driven to zero at every integration time step. Of course, neglection of the unknowns for solving the error dynamic equations will introduce an estimation error in the adaptive parameters. The magnitude of this error can be lessened by choosing a proper sampling time step. A control law is designed to compensate the nonlinear uncertainties and deliver a good tracking performance with guaranteed robustness. Model predictive control is introduced to solve a receding horizon optimization problem with various constraints maintained. Numerical examples are given to illustrate the design procedures, and the simulation results demonstrate the availability and feasibility of the developed framework. [ABSTRACT FROM AUTHOR]

Concrete is the most widely used construction material. Worldwide consumption of cement, the strength-giving component in concrete, is now estimated to be 4.10 Gt per year, having risen from 2.22 Gt just 10 years ago. This rate of consumption means that cement manufacture alone is estimated to account for 5.2 % of global carbon dioxide emissions. Concrete offers the opportunity to create structures with almost any geometry economically. Yet its unique fluidity is seldom capitalized upon, with concrete instead being cast in rigid, flat moulds to create non-optimized geometries that result in structures with a high material usage and large carbon footprints. This paper will explore flexible formwork construction technologies that embrace the fluidity of concrete to facilitate the practical construction of concrete structures with complex and efficient geometries. This paper presents the current state of the art in flexible formwork technology, highlighting practical uses, research challenges and new opportunities. [ABSTRACT FROM AUTHOR]

Recent years have been characterized by marked progress in industrial instrumentation and mechatronics control technology. This year commemorates the fifth publication year of the IEEJ Journal of Industry Applications (emIEEJ J. IA). Additionally, the Mechatronics Control (MEC) technical committee was formed 3 years ago following a separation from the Industrial Instruments and Control (IIC) technical committee in order to further enhance their respective social contributions. The increased activity of both committees also contributed to the progress of the Journal. This paper discusses the recent advances and outlook in the technical field of industrial instrumentation and mechatronics control based on papers published in the IEEJ J. IA and a few other significant papers, which consider the current activities of the various committees. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Robust parameter design is a widely implemented design methodology for continuous quality improvement by identifying optimal factor level settings with minimum product variation. However, apparent flaws surrounding the original version of robust parameter design have resulted in alternative approaches, of which response surface methodology using the central composite design, in particular, has drawn a great deal of attention. There is a large number of practical situations in which some or all of variables must be integers; however, the design space associated with the traditional central composite design is typically a bounded convex feasible set involving real numbers. The purpose of this paper is twofold. First, we discuss why the Box-Behnken design may be preferred over the central composite design and other three-level designs when maintaining constant or nearly constant prediction variance associated with a second-order model is crucial to integer-valued robust parameter design problems. Second, we lay out the foundation to show how the Box-Behnken design is transformed into a nonlinear integer programming framework. In this paper, we develop Box-Behnken design embedded nonlinear integer programming models, using the sequential quadratic integer programming and the Karush-Khun-Tucker conditions. Comparison studies of the proposed models and traditional counterparts are also conducted. It is believed that the proposed models have the potential to impact a wide range of engineering problems, ultimately leading to process and quality improvement. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Accelerated life testing (ALT) design is usually performed based on assumptions of life distributions, stress-life relationship, and empirical reliability models. Time-dependent reliability analysis on the other hand seeks to predict product and system life distribution based on physics-informed simulation models. This paper proposes an ALT design framework that takes advantages of both types of analyses. For a given testing plan, the corresponding life distributions under different stress levels are estimated based on time-dependent reliability analysis. Because both aleatory and epistemic uncertainty sources are involved in the reliability analysis, ALT data is used in this paper to update the epistemic uncertainty using Bayesian statistics. The variance of reliability estimation at the nominal stress level is then estimated based on the updated time-dependent reliability analysis model. A design optimization model is formulated to minimize the overall expected testing cost with constraint on confidence of variance of the reliability estimate. Computational effort for solving the optimization model is minimized in three directions: (i) efficient time-dependent reliability analysis method; (ii) a surrogate model is constructed for time-dependent reliability under different stress levels; and (iii) the ALT design optimization model is decoupled into a deterministic design optimization model and a probabilistic analysis model. A cantilever beam and a helicopter rotor hub are used to demonstrate the proposed method. The results show the effectiveness of the proposed ALT design optimization model. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an algorithm for the computation of full‐complexity polytopic robust control invariant (RCI) sets, and the corresponding linear state‐feedback control law. The proposed scheme can be applied for linear discrete‐time systems subject to additive disturbances and structured norm‐bounded or polytopic uncertainties. Output, initial condition, and performance constraints are considered. Arbitrary complexity of the invariant polytope is allowed to enable less conservative inner/outer approximations to the RCI sets whereas the RCI set is assumed to be symmetric around the origin. The nonlinearities associated with the computation of such an RCI set structure are overcome through the application of Farkas' theorem and a corollary of the elimination lemma to obtain an initial polytopic RCI set, which is guaranteed to exist under certain conditions. A Newton‐like update, which is recursively feasible, is then proposed to yield desirable large/small volume RCI sets. [ABSTRACT FROM AUTHOR]

The determination of product features, which can be seen as design specifications, is a crucial problem that must be carried out upstream to quickly validate the product configuration according to some attributes in relation to the user perception. To this end, the design methods must evolve toward an analysis compatible with various kind of data that can be qualitative or quantitative. In this paper, a new approach is introduced able to take into account various kind of information in order to determine some quantitative design specifications in accordance with the users perception. This is done through a mathematical formulation that exploit different types of data coming from sensory analysis and physical quantities. This mathematical formulation is then used in an optimization procedure that takes into account a preference order over the sensory attributes. The solution of this optimization problem gives thus the best user‐centered specifications that must be used for the conception of the final product. [ABSTRACT FROM AUTHOR]

In this paper, optimization methods of implantable receiver for wireless power transfer are studied in order to increase transfer efficiency between resonators positioned on and in the human body. The spiral coil‐resonators of magnetic resonant wireless power transfer (MR‐WPT) are designed and fabricated on a wearable textile substrate, which covers the human body (on‐body) as the transmitter (Tx) and on the acrylic substrate inside the human body (in‐body) as the receiver (Rx). The experiment showed that when the Rx resonator was inserted into a muscle‐mimicking liquid (MML), the transfer efficiency of on/in‐body system decreased significantly. This decrease attributed to the mismatch of the resonant frequency between the Tx resonator in the air and the Rx resonator in the MML. To mitigate this effect, three approaches, which demonstrated the recovery of the transfer efficiency, were investigated using either a selected optimal capacitor or an air‐pocket, and additional approach using pattern designed in the MML. [ABSTRACT FROM AUTHOR]

This paper presents the numerical and experimental results of a miniaturized half‐mode substrate integrated waveguide HMSIW C‐band pass filter with defected ground structure DGS, using two slots and dumbbell shape defected ground structure. These two slots which are etched on the upper plane of the SIW cavity are used to constitute a multiple‐mode resonator, and the dumbbell‐shape fractal DGS etched on the bottom plane can considerably enhance the filter's performances. The manufactured band‐pass filter in half mode based on SIW technology has a size nearly half of that of a normal filter. The measurements results obtained by CST in C‐band show that the manufactured filter has a large transmitted bandwidth of about 1.53 GHz from 5.97 to 7.5 GHz. The higher measured insertion is about −2.6 dB and the lower return loss measured is about −34 dB. The size of filter design achieved is 7.48 × 38.12 mm2 which make it the more compact in comparison with some published works at the C‐band frequency. [ABSTRACT FROM AUTHOR]

Nuclear magnetic resonance (NMR) crystallography—an approach to structure determination that seeks to integrate solid‐state NMR spectroscopy, diffraction, and computation methods—has emerged as an effective strategy to determine structures of difficult‐to‐characterize materials, including zeolites and related network materials. This paper explores how far it is possible to go in determining the structure of a zeolite framework from a minimal amount of input information derived only from solid‐state NMR spectroscopy. It is shown that the framework structure of the fluoride‐containing and tetramethylammonium‐templated octadecasil clathrasil material can be solved from the 1D 29Si NMR spectrum and a single 2D 29Si NMR correlation spectrum alone, without the space group and unit cell parameters normally obtained from diffraction data. The resulting NMR‐solved structure is in excellent agreement with the structures determined previously by diffraction methods. It is anticipated that NMR crystallography strategies like this will be useful for structure determination of other materials, which cannot be solved from diffraction methods alone. [ABSTRACT FROM AUTHOR]

Dividing‐wall columns are a well‐known and proven technology to separate a ternary mixture into pure products with significant savings in capital and operational costs compared to standard two‐column configurations. A consequent advancement are multiple dividing‐wall columns, which allow the separation of multicomponent mixtures in one column shell. However, due to their high complexity, no practical realization has been reported yet. This paper briefly discusses the current state of the art followed by a detailed description of a robust initialization of rigorous flow sheet simulations based on Vmin diagrams. With the data from the simulation a multi‐objective optimization can be performed. The knowledge from the simulations shall be used to build the first multiple dividing‐wall column worldwide. Multiple dividing‐wall columns offer energy savings of around 50 % for quaternary mixtures compared to conventional setups. Accordingly, the research at the Institute of Chemical Engineering at Ulm University focuses on the simulation, optimization, design and operation of them with the goal to build the first multiple dividing wall column worldwide. [ABSTRACT FROM AUTHOR]

Voltage stability is very important, as without it voltage collapse will occur. There is therefore a need to incorporate the consideration of voltage stability into the optimal power flow (OPF). This paper presents a comparison of the effectiveness of five voltage stability indices (VSIs) when incorporated in an OPF. The improved particle swarm optimization (IPSO) algorithm is used to solve the OPF problem. The five VSIs investigated are the L‐index, fast voltage stability index (FVSI), line stability index (Lmn), online voltage stability index (LVSI), and voltage collapse proximity indicator (VCPI). The effectiveness of each VSI is considered in the terms of the generation cost, emission, transmission loss, and voltage stability. The IEEE standard 14‐, 30‐, 57‐, and 118‐bus test systems are used for the comparison. It is found that considering each voltage stability index as part of the objective function for the OPF provided different values of generation cost, emission, transmission loss, and maximum loadability. The results suggest that FVSI and Lmn provide the minimum generation cost values for all test systems, while VCPI and LVSI provide lower emission values for most systems. VCPI gives the lowest transmission losses for all systems, and the L‐index provides the maximum loadability for most systems. Incorporation of these indices into the OPF can provide the optimal values in different terms, and the most suitable voltage stability index will depend on the situation and size of the system, which needs to be judiciously chosen. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Integration of all available data in reservoir characterization is critically important. 2D mapping is a reliable and robust technique that allows integration of multiple secondary data, including geological and geophysical surfaces and maps, to generate realistic summaries of reservoir quality at each location in an area of interest with an associated measure of uncertainty. This is achieved in 2D mapping with a more straightforward implementation, requiring significantly less time and fewer resources than three‐dimensional modelling. In this paper, we propose an approach for the empirical calculation and optimization of differential compaction maps by leveraging existing well control for the use in 2D mapping. Success of the proposal is demonstrated through tests of accuracy, precision and fairness of the local uncertainty distributions for 100 new stratigraphical wells drilled in the Christina Lake and Kirby East area. [ABSTRACT FROM AUTHOR]

Nitinol superelastic stents have been widely used to treat the vascular stenosis due to its excellent mechanical behavior and biocompatibility. However, there exist conflicts between the functional properties and mechanical properties of the stent. An optimization method has been employed to deal with the conflictions with the consideration of the whole implementation process of the stent in this paper. A straight vascular with tumor inside is considered. A commonly used NiTinol superleastic stent with diamond shape strut is employed. The vascular wall tissue and stenotic plaque are also treated as hyperelastic materials. Softwares Isight, ABAQUS and Solidworks are utilized to perform the optimization job. It can be seen that the stresses are high at the areas around the fillets of the stent due to the stress concentration from a primary analysis. Therefore, the two fillets radius, thickness and radius of the stent are chosen as four optimization variables. The optimization object is to decrease the maximum stress of stent and increase the displacement of the plaque. After the optimization, the maximum stress can be decreased by 8.2 %, which implies that the stent's work life can be increased. The stenosis of the blood vessel can be decreased from 56 % to 40.0 %. [ABSTRACT FROM AUTHOR]

Balancing problems in national accounts and similar applications may be addressed by optimization methods that aim to maximize preservation of specific characteristics of the unadjusted data, for example, levels or time‐series movements. However, published methods do not always indicate the assumptions that underpin these methods, making it hard to identify when those assumptions might be violated or how to generalize them to complex cases. Previous authors have observed that least‐squares estimation methods correspond to maximum likelihood estimation (MLE) under normality assumptions. This paper explores this relationship in the context of published "movement preservation"/"level preservation" methods, showing how the MLE interpretation identifies implicit assumptions made by these methods and, hence, helps inform decisions about their use. It also notes a case where the MLE and "preservation" approaches diverge, and gives a framework for generalizing MLE approaches to complex scenarios. [ABSTRACT FROM AUTHOR]

Background: The topology of the blood supply chain network can take different forms in different settings, depending on geography, politics, costs, etc. Many developed countries are moving towards centralized networks. The goal for all blood distribution networks, regardless of topology, remains the same: to satisfy demand at minimal cost and minimal wastage. Study Design and Methods: Mathematically, the blood supply system design can be viewed as a location‐allocation problem, where the aim is to find the optimal location of collection and production facilities and to assign hospitals to them to minimize total system cost. However, most location‐allocation models in the blood supply chain literature omit several important aspects of the problem, such as selecting amongst differing methods of collection and production. In this paper, we present a location‐allocation model that takes these factors into account to support strategic decision‐making at different levels of centralization. Results: Our approach is illustrated by a case study (Colombia) to redesign the national blood supply chain under a range of realistic travel time limitations. For each scenario, an optimal supply chain configuration is obtained, together with optimal collection and production strategies. We show that the total costs for the most centralized scenario are around 40% of the costs for the least centralized scenario. Conclusion: Centralized systems are more efficient than decentralized systems. However, the latter may be preferred for political or geographical reasons. Our model allows decision‐makers to redesign the supply network per local circumstances and determine optimal collection and production strategies that minimize total costs. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents and reviews the current application fields of mathematical programming in integrated iron‐ and steelmaking research. Three different fields of mathematical programming applications are identified and discussed: unit operation optimization, by‐product gas distribution, and integrated system optimization and design. Based on current research activities in the iron and steel industry, development trends for mathematical programming in integrated iron‐ and steelmaking research, such as the cogeneration of chemicals aided by renewable energy grid integration, are presented. [ABSTRACT FROM AUTHOR]

In cognitive radio (CR) networks, secondary users should effectively use unused licensed spectrums, unless they cause any harmful interference to the primary users. Therefore, spectrum sensing and channel resource allocation are the 2 main functionalities of CR networks, which play important roles in the performance of a CR system. To maximize the CR system utility, we propose a joint out-of-band spectrum sensing and operating channel allocation scheme based on genetic algorithm for frequency hopping-based CR networks. In this paper, to effectively sense the primary signal on hopping channels at each hopping slot time, a set of member nodes sense the next hopping channel, which is called out-of-band sensing. To achieve collision-free cooperative sensing reporting, the next channel detection notification mechanism is presented. Using genetic algorithm, the optimum sensing and data transmission schedules are derived. It selects a sensing node set that participate the spectrum sensing for the next expected hopping channel during the current channel hopping time and another set of nodes that take opportunity for transmitting data on the current hopping channel. The optimum channel allocation is performed in accordance with each node's individual traffic demand. Simulation results show that the proposed scheme can achieve reliable spectrum sensing and efficient channel allocation. [ABSTRACT FROM AUTHOR]

Purpose: Recent applications of iterative image reconstruction algorithms to multislice helical CT have shown that iterative reconstruction can significantly improve image quality and reduce artifacts. In this paper, the authors introduce a combination of two different algorithms with different convergence properties: ordered subsets separable paraboloidal surrogates (OS-SPS) and iterative coordinate descent (ICD). The first one updates image voxels simultaneously, slightly changing attenuation values iteration by iteration. The second algorithm updates image voxel by voxel, each time performing full forward and backward projections of the voxel. It has been shown that ICD converges better at high-frequency areas and requires more iterations to reconstruct low-frequency components of the image. In contrast to ICD, SPS requires multiple iterations to reconstruct high-frequency areas. In this paper, the authors introduce an algorithm which leverages the benefits of both ICD and SPS. Methods: The idea is to update the entire image with SPS, determine high-frequency components, and focus ICD computations on it using nonhomogeneous ICD update. Results: The authors have successfully implemented OS-SPS, ICD, their hybrid approach, and few variations of ICD based on spatially nonuniform updates. Conclusions: The authors have examined the convergence of different algorithms and found that proposed algorithm converges better than OS-SPS, ICD, as well as various improved variants of ICD. [ABSTRACT FROM AUTHOR]

The paper introduces a new computationally efficient algorithm to determine a lower bound on the real structured singular value μ. The algorithm is based on a pole migration approach where an optimization solver is used to compute a lower bound on real μ independent of a frequency sweep. A distinguishing feature of this algorithm from other frequency independent one-shot tests is that multiple localized optima (if they exist) are identified and returned from the search. This is achieved by using a number of alternative methods to generate different initial conditions from which the optimization solver can initiate its search from. The pole migration algorithm presented has also been extended to determine lower bounds for complex parametric uncertainties as well as full complex blocks. However, the results presented are for strictly real and repeated parametric uncertainty problems as this class of problem is the focus of this paper and are in general the most difficult to solve. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose: Volumetric modulated arc therapy (VMAT) optimization is a computationally challenging problem due to its large data size, high degrees of freedom, and many hardware constraints. High-performance graphics processing units (GPUs) have been used to speed up the computations. However, GPU's relatively small memory size cannot handle cases with a large dose-deposition coefficient (DDC) matrix in cases of, e.g., those with a large target size, multiple targets, multiple arcs, and/or small beamlet size. The main purpose of this paper is to report an implementation of a column-generation-based VMAT algorithm, previously developed in the authors' group, on a multi- GPU platform to solve the memory limitation problem. While the column-generation-based VMAT algorithm has been previously developed, the GPU implementation details have not been reported. Hence, another purpose is to present detailed techniques employed for GPU implementation. The authors also would like to utilize this particular problem as an example problem to study the feasibility of using a multi-GPU platform to solve large-scale problems in medical physics. Methods: The column-generation approach generates VMAT apertures sequentially by solving a pricing problem (PP) and a master problem (MP) iteratively. In the authors' method, the sparse DDC matrix is first stored on a CPU in coordinate list format (COO). On the GPU side, this matrix is split into four submatrices according to beam angles, which are stored on four GPUs in compressed sparse row format. Computation of beamlet price, the first step in PP, is accomplished using multi-GPUs. A fast inter-GPU data transfer scheme is accomplished using peer-to-peer access. The remaining steps of PP and MP problems are implemented on CPU or a single GPU due to their modest problem scale and computational loads. Barzilai and Borwein algorithm with a subspace step scheme is adopted here to solve the MP problem. A head and neck (H&N) cancer case is then used to validate the authors' method. The authors also compare their multi-GPU implementation with three different single GPU implementation strategies, i.e., truncating DDC matrix (S1), repeatedly transferring DDC matrix between CPU and GPU (S2), and porting computations involving DDC matrix to CPU (S3), in terms of both plan quality and computational efficiency. Two more H&N patient cases and three prostate cases are used to demonstrate the advantages of the authors' method. Results: The authors' multi-GPU implementation can finish the optimization process within ~1 min for the H&N patient case. S1 leads to an inferior plan quality although its total time was 10 s shorter than the multi-GPU implementation due to the reduced matrix size. S2 and S3 yield the same plan quality as the multi-GPU implementation but take ~4 and ~6 min, respectively. High computational efficiency was consistently achieved for the other five patient cases tested, with VMAT plans of clinically acceptable quality obtained within 23-46 s. Conversely, to obtain clinically comparable or acceptable plans for all six of these VMAT cases that the authors have tested in this paper, the optimization time needed in a commercial TPS system on CPU was found to be in an order of several minutes. Conclusions: The results demonstrate that the multi-GPU implementation of the authors' columngeneration- based VMAT optimization can handle the large-scale VMAT optimization problem efficiently without sacrificing plan quality. The authors' study may serve as an example to shed some light on other large-scale medical physics problems that require multi-GPU techniques. [ABSTRACT FROM AUTHOR]

Location modelling is employed in urban and regional planning to site facilities that provide services of some sort. Issues to be considered usually include the number of facilities to locate, where to site those facilities and how demand is to be served. Given the geographic nature of location problems, a key issue is how to represent facilities and demand in geographic space. Traditionally, spatial abstraction as discrete demand is assumed as it simplifies model formulation and reduces computational complexity. However, errors in derived solutions are likely not negligible, especially when demand varies continuously across a region. This paper discusses a single facility location problem that considers demand to be continuously distributed and allows a facility to be located anywhere in space, the continuous Weber problem. An approach for dealing with continuous demand is proposed that is integrated through geographical information system (GIS) functionality. Empirical results highlight the advantages of the developed approach and the importance of solution integration with GIS. [ABSTRACT FROM AUTHOR]

In the present study, compact water cooling of highdensity, high-speed, very-large-scale integrated (VLSI) circuits with the help of microchannel heat exchangers were investigated analytically. This study also presents the result of mathematical analysis based on the modified Bessel function of laminar fluid flow and heat transfer through combined conduction and convection in a microchannel heat sink with triangular extensions. The main purpose of this paper is to find the dimensions of a heat sink that give the least thermal resistance between the fluid and the heat sink, and the results are compared with that of rectangular fins. It is seen that the triangular heat sink requires less substrate material as compared to rectangular fins, and the heat transfer rate per unit volume has been almost doubled by using triangular heat sinks. It is also found that the effectiveness of the triangular fin is higher than that of the rectangular fin. Therefore, the triangular heat sink has the ability to dissipate large amounts of heat with relatively less temperature rise for the same fin volume. Alternatively, triangular heat sinks may thus be more cost effective to use for cooling ultra-high speed VLSI circuits than rectangular heat sinks. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a 16‐channel power‐efficient neural/muscular stimulation integrated circuit for peripheral nerve prosthesis. First, the theoretical analysis is presented to show the power efficiency optimization in a stimulator. Moreover, a continuous‐time, biphasic exponential‐current‐waveform generation circuit is designed based on Taylor series approximation and implemented in the proposed stimulation chip to optimize the power efficiency. In the 16‐channel stimulator chip design, each channel of the stimulator consists of a current copier, an exponential current generator, an active charge‐balancing circuit, and a 24‐V output stage. Stimulation amplitude, pulse width, and frequency can be set and adjusted through an external field‐programmable gate array by sending serial commands. Finally, the proposed stimulator chip has been fabricated in a 0.18‐μm advanced complementary metal‐oxide‐semiconductor process with 24‐V laterally diffused metal oxide semiconductor option. The maximum stimulation power efficiency of 95.9% is achieved at the output stage with an electrode model of 10‐kΩ resistance and 100‐nF capacitance. Animal experiment results further demonstrate the power efficiency improvement and effectiveness of the stimulator. [ABSTRACT FROM AUTHOR]

The present study evaluates the suitability of ultrasound pretreatment in n‐hexane solvent as well as enzymatic treatment with cellulase enzyme to extract oil from peanut seed powders. To optimize this process, the effects of ultrasonic time (0–70 min), cellulase enzyme concentration (0–2%) and pH (4–5.5) are investigated on peanut oil extraction yield (EY) as well as the quality attributes of the extracted oil containing total phenolic content (TPC), peroxide value (PV), and color parameters of L, a, and b using response surface methodology (RSM). The optimum condition of ultrasound‐assisted enzymatic extraction using n‐hexane solvent (UAEE) is found as ultrasonic pretreatment time of 33.23 min, cellulase concentration of 1.47%, and pH of 4.61 before incubation process at temperature of 56 °C for 120 min. Scanning electronic microscopy (SEM) represented considerable interspaces, holes, and porous structure of peanut meal after optimal UAEE treatment compared to that after shaking incubation extraction using n‐hexane solvent (SIE). It is found that the peanut oil extracted by optimal UAEE treatment had considerable high levels of L color parameter and TPC and significantly more EY and b color parameters than those extracted by SIE, ultrasound‐assisted aqueous enzymatic extraction (UAAEE), and aqueous shaking incubation extraction (ASIE) treatments. Practical Applications: This paper describes an innovative oil extraction method of ultrasound‐assisted enzymatic process using n‐hexane solvent. This new extraction technique makes it possible to increase the extraction yield, total phenolic content, and yellowness of extracted peanut oil. The results illustrated that ultrasound‐assisted enzymatic extraction using n‐hexane solvent method was a far more efficient extracting technique than the individual shaking incubation extraction using n‐hexane solvent, ultrasound‐ assisted aqueous enzymatic extraction and aqueous shaking incubation extraction treatments and would be a promising alternative for conventional oil extraction techniques. Comparison of two treatments of optimal ultrasound‐enzymatic extraction and individual shaking incubation extraction of oil from peanut seed powders. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we analyze an eigenvalue problem related to the nonlocal p‐Laplace operator plus a potential. After reviewing some elementary properties of the first eigenvalue of these operators (existence, positivity of associated eigenfunctions, simplicity and isolation) we investigate the dependence of the first eigenvalue on the potential function and establish the existence of some optimal potentials in some admissible classes. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we propose a method to detect the damage and estimate the degree of damage by means of a multifield‐based inverse analysis. The fields being considered are displacement, temperature, and water pressure. Furthermore, the uncertainties due to the size of the damage, the errors in the measurement data, and the errors in the model parameters are also investigated. The uncertainty due to the measurements is quantified by assuming different sources of noise in the measurements. The inverse problem is solved repeatedly by a sampling process. The uncertainties in the inverse solutions can be quantified by their probability distributions. This method can be applied to identify damages in masonry dams using coupled nonlinear thermo‐hydro‐mechanical problems. [ABSTRACT FROM AUTHOR]

In this paper, we study the optimal scheduling problem in coordinated multipoint (CoMP) transmission-based cellular networks. We consider joint transmission and coordinated scheduling together in CoMP transmission-based cellular networks and develop an optimization framework to compute the optimal max-min throughput and the optimal scheduling of the transmissions to the users. The optimization problem is found to be a complex linear program with number of variables in [ABSTRACT FROM AUTHOR]

This paper addresses the problem of estimating the state for a class of uncertain discrete-time linear systems with constraints by using an optimization-based approach. The proposed scheme uses the moving horizon estimation philosophy together with the game theoretical approach to the [ABSTRACT FROM AUTHOR]

Many corrosion test experiments, using a range of testing methods and car body materials, are done by the automotive industry worldwide to meet the corrosion requirements in the field. In this paper, we use test data and climate field data for data driven modeling of the test results. One contribution reported here is to find the most influencing factors for corrosion test progress and field correlation. Therefore, iron and zinc panels with automotive paintings conducted in several corrosion tests are measured and transformed into suitable data. The corrosion parameters are defined as factors and the result of corrosion testing (i.e., scribe creepage values) as output variable. With this data, a statistical model is generated and validated. The best fit model is analyzed to find sensible testing parameters effecting the corrosion results. The same procedure is also applied for climatic field data, which is first transformed into characteristics such as humidity, duration of wetness, and salt load. The data from corrosion testing experiments are then mapped to the climatic load in the field. A match to the field correlation can be found, as demonstrated by our results. [ABSTRACT FROM AUTHOR]

Raman spectroscopy is a very powerful analytical technique with an increasing acceptance in the scientific community. For the optimization of the Raman acquisition, two main parameters, the integration time and the number of accumulations, need to be adjusted to the sample under analysis, as the sample, or even different spots on the same sample, can provide very different Raman responses one from another. In this paper, we present a suite of algorithms to automate the acquisition parameter adjustment to the sample under analysis, addressing issues such as spectral saturation, fluorescence, cosmic ray detection and removal, and adjustment of the acquisition parameters to optimize the acquired spectral data. This suite has been developed in the framework of the Raman Laser Spectrometer (RLS) instrument development for the Exomars mission but can be applied to any Raman spectrometer. This will allow the spectrometer to adapt to the characteristics of the sample that is being analyzed, optimizing the total operative time, while improving the usability and overall efficiency of the system. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This paper studies reactive extraction of formic (FA), acetic (AA), propionic (PA) and butyric (BA) acids from aqueous solutions by tri- n-butyl amine/diluent, with particular focus on proper optimization and modeling of extraction equilibria. The uptake capacities of amine/diluent and diluent alone approximate the following order: oleyl alcohol > octyl acetate > diisobutyl ketone and BA > PA > AA ≈ FA. An intrinsic optimization structure has been applied to the description of optimum extraction field of relevant systems, based on analyzing the variation profiles of separation ratio R and synergistic enhancement SE factors through the derivative variation method. We present new solvation molecular models extended-linear solvation energy relation (e-LSER), SPR1 and SPR2 (solvation probability relation), and an extension to group-contribution approach A-UNIFAC (Association-UNIFAC). A-UNIFAC predicts phase equilibria using new group interaction parameters regressed from vapor-liquid equilibrium data. The e-LSER model involves eight descriptors used for expressing solvent effects. By performing SPR1 and SPR2, we are able to scale up the probability range and activation energy of solvation effect. The strength of acid-amine association is calculated with chemodel. e-LSER, A-UNIFAC, SPR and chemodel simulate accurately the observed performance with average deviations inferior to 4.8%, 24.1%, 0.8% and 16.2%, respectively. © 2017 Curtin University and John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a new particle swarm optimization-based approach is proposed for the geometrical optimization of the nanowires solar cells to achieve improved optical performance. The proposed hybrid approach combines the 3-D numerical analysis using accurate solutions of Maxwell's equations and metaheuristic investigation to boost the solar cell total absorbance efficiency. Our purpose resides on modulating the electric field and increasing the light trapping capability by optimizing the radial solar cell geometrical parameters. Moreover, a comprehensive study of vertical core-shell nanowire arrays optical parameters such as the integral absorption, reflection, and total absorbance efficiency is carried out, in order to reveal the optimized radial solar cells optical performance for low-cost photovoltaic applications. We find that the proposed hybrid approach plays a crucial role in improving the nanowires solar cells optical performance, where the optimized design exhibits superior total absorbance efficiency and lower total reflection in comparison with those provided by the conventional planar design. The obtained results make the proposed global optimization approach valuable for providing high-efficiency nanowires solar cells. [ABSTRACT FROM AUTHOR]

Abstract: Graphene oxide (GO) is an important material used as precursor for the synthesis of graphene, its derivatives and various graphene based composite materials. In this paper we would like to demonstrate that highly‐oxidized graphene oxide can be prepared much faster and, moreover, it has almost identical chemical composition compared to the previously published and currently broadly used standard procedures. We prepared two samples: one using the usual Tour's method and the other one using the novel method. The main advantage of this improved method is the shorter synthesis time which can be reduced six times allowing scaling and speeding up of large scale production. Oxidation shortening also led to reduction of defect concentration. Both graphene oxides were characterized in detail showing almost identical structure as well as chemical composition and concentration of oxygen functionalities typical for graphene oxide prepared by permanganate methods. In addition the sorption capacity towards heavy metals (zinc, cadmium and lead) was also studied showing a comparable sorption capacity with standard graphene oxide prepared by Tour method. Graphene oxide prepared by rapid oxidation can form mechanically stable transparent membranes. Our developed method of graphene oxide synthesis is time‐efficient, cost‐efficient and can help to introduce graphene oxide to industrial scale production. [ABSTRACT FROM AUTHOR]

We compare some well-known Bayesian global optimization methods in four distinct regimes, corresponding to high and low levels of measurement noise and to high and low levels of 'quenched noise' (which term we use to describe the roughness of the function we are trying to optimize). We isolate the two stages of this optimization in terms of a 'regressor,' which fits a model to the data measured so far, and a 'selector,' which identifies the next point to be measured. The focus of this paper is to investigate the choice of selector when the regressor is well matched to the data. [ABSTRACT FROM AUTHOR]

SUMMARY This paper considers the problem of placing additional phasor measurement units (PMUs) and communication links into a PMU network in a power system. The objective is for the synchrophasors (PMU outputs) across the power system to meet a prescribed availability profile with fewest new PMUs and links among them. Achieving a required synchrophasor availability profile is critical in supporting wide area monitoring, protection, and control in a power system. In our recently reported work, synchrophasor availability is solved from a controlled Markov chain where binary variables indicating placement decisions are embedded as stationary control variables. In this paper, the assumption that communication links are always available wherever needed is removed. Random interruptions in PMU communications are modeled in such a way that the reformulated placement problem remains Boolean-convex, and the computational complexity with respect to the number of buses remains O( n2). The solution to placement of PMUs and communication links into the Institute of Electrical and Electronics Engineers (IEEE) 118-bus test system is presented. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

SUMMARY Based on recent papers that have demonstrated that robust iterative learning control can be based on parameter optimization using either the inverse plant or gradient concepts, this paper presents a unification of these ideas for discrete-time systems that not only retains the convergence properties and the robustness properties derived in previous papers but also permits the inclusion of filters in the input update formula and a detailed analysis of the effect of non-minimum-phase dynamics on algorithm performance in terms of a 'plateauing' or 'flat-lining' effect in the error norm evolution. Although the analysis is in the time domain, the robustness conditions are expressed as frequency domain inequalities. The special case of a version of the inverse algorithm that can be used to construct a robust stable anti-causal inverse non-minimum-phase plant is presented and analysed in detail. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Purpose: The paper considers the fractionation problem in intensity modulated proton therapy (IMPT). Conventionally, IMPT fields are optimized independently of the fractionation scheme. In this work, we discuss the simultaneous optimization of fractionation scheme and pencil beam intensities. Methods: This is performed by allowing for distinct pencil beam intensities in each fraction, which are optimized using objective and constraint functions based on biologically equivalent dose (BED). The paper presents a model that mimics an IMPT treatment with a single incident beam direction for which the optimal fractionation scheme can be determined despite the nonconvexity of the BED-based treatment planning problem. Results: For this model, it is shown that a small α/β ratio in the tumor gives rise to a hypofractionated treatment, whereas a large α/β ratio gives rise to hyperfractionation. It is further demonstrated that, for intermediate α/β ratios in the tumor, a nonuniform fractionation scheme emerges, in which it is optimal to deliver different dose distributions in subsequent fractions. The intuitive explanation for this phenomenon is as follows: By varying the dose distribution in the tumor between fractions, the same total BED can be achieved with a lower physical dose. If it is possible to achieve this dose variation in the tumor without varying the dose in the normal tissue (which would have an adverse effect), the reduction in physical dose may lead to a net reduction of the normal tissue BED. For proton therapy, this is indeed possible to some degree because the entrance dose is mostly independent of the range of the proton pencil beam. Conclusions: The paper provides conceptual insight into the interdependence of optimal fractionation schemes and the spatial optimization of dose distributions. It demonstrates the emergence of nonuniform fractionation schemes that arise from the standard BED model when IMPT fields and fractionation scheme are optimized simultaneously. Although the projected benefits are likely to be small, the approach may give rise to an improved therapeutic ratio for tumors treated with stereotactic techniques to high doses per fraction. [ABSTRACT FROM AUTHOR]

Purpose: Recent research has shown that the optimization model hitherto used in high-dose-rate (HDR) brachytherapy corresponds weakly to the dosimetric indices used to evaluate the quality of a dose distribution. Although alternative models that explicitly include such dosimetric indices have been presented, the inclusion of the dosimetric indices explicitly yields intractable models. The purpose of this paper is to develop a model for optimizing dosimetric indices that is easier to solve than those proposed earlier. Methods: In this paper, the authors present an alternative approach for optimizing dose distributions for HDR brachytherapy where dosimetric indices are taken into account through surrogates based on the conditional value-at-risk concept. This yields a linear optimization model that is easy to solve, and has the advantage that the constraints are easy to interpret and modify to obtain satisfactory dose distributions. Results: The authors show by experimental comparisons, carried out retrospectively for a set of prostate cancer patients, that their proposed model corresponds well with constraining dosimetric indices. All modifications of the parameters in the authors' model yield the expected result. The dose distributions generated are also comparable to those generated by the standard model with respect to the dosimetric indices that are used for evaluating quality. Conclusions: The authors' new model is a viable surrogate to optimizing dosimetric indices and quickly and easily yields high quality dose distributions. [ABSTRACT FROM AUTHOR]

SUMMARY Many problems in mining and civil engineering require using numerical stress analysis methods to repeatedly solve large models. Widespread acceptance of tunneling methods, such as New Austrian Tunneling Method, which depend heavily on numerical stress analysis tools and the fact that the effects of excavation at the face of a tunnel are distinctively three-dimensional (3D), necessitates the use of 3D numerical analysis for these problems. Stress analysis of a practical mining problem can be very lengthy, and the processing time can be measured in days or weeks at times. A framework is developed to facilitate efficient modeling of underground excavations and to create an optimal 3D mesh by reducing the number of surface and volume elements while keeping the result of stress analysis accurate enough at the region of interest, where a solution is sought. Fewer surface and volume elements mean fewer degrees of freedom in the numerical model, which directly translates into savings in computational time and resources. The mesh refinement algorithm is driven by a set of criteria that are functions of distance and visibility of points from the region of interest, and the framework can be easily extended by adding new types of criteria. This paper defines the framework, whereas a second companion paper will investigate its efficiency, accuracy and application to a number of practical mining problems. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Balancing the load among sensor nodes is a major challenge for the long run operation of wireless sensor networks. When a sensor node becomes overloaded, the likelihood of higher latency, energy loss, and congestion becomes high. In this paper, we propose an optimal load balanced clustering for hierarchical cluster-based wireless sensor networks. We formulate the network design problem as mixed-integer linear programming. Our contribution is 3-fold: First, we propose an energy aware cluster head selection model for optimal cluster head selection. Then we propose a delay and energy-aware routing model for optimal inter-cluster communication. Finally, we propose an equal traffic for energy efficient clustering for optimal load balanced clustering. We consider the worst case scenario, where all nodes have the same capability and where there are no ways to use mobile sinks or add some powerful nodes as gateways. Thus, our models perform load balancing and maximize network lifetime with no need for special node capabilities such as mobility or heterogeneity or pre-deployment, which would greatly simplify the problem. We show that the proposed models not only increase network lifetime but also minimize latency between sensor nodes. Numerical results show that energy consumption can be effectively balanced among sensor nodes, and stability period can be greatly extended using our models. [ABSTRACT FROM AUTHOR]

Accumulating evidence suggests that intraluminal thrombus plays many roles in the natural history of abdominal aortic aneurysms. There is, therefore, a pressing need for computational models that can describe and predict the initiation and progression of thrombus in aneurysms. In this paper, we introduce a phenomenological metric for thrombus deposition potential and use hemodynamic simulations based on medical images from 6 patients to identify best-fit values of the 2 key model parameters. We then introduce a shape optimization method to predict the associated radial growth of the thrombus into the lumen based on the expectation that thrombus initiation will create a thrombogenic surface, which in turn will promote growth until increasing hemodynamically induced frictional forces prevent any further cell or protein deposition. Comparisons between predicted and actual intraluminal thrombus in the 6 patient-specific aneurysms suggest that this phenomenological description provides a good first estimate of thrombus deposition. We submit further that, because the biologically active region of the thrombus appears to be confined to a thin luminal layer, predictions of morphology alone may be sufficient to inform fluid-solid-growth models of aneurysmal growth and remodeling. [ABSTRACT FROM AUTHOR]

Effective implication of evolutionary techniques in primary steel making process optimization is due, although the scope of its utilization in this sector is enormous. The multi-objective optimization technique is adopted in this paper for addressing important issue of achieving low phosphorus content along with high-end blow temperature in basic oxygen steel making process. The intend of this study is to predict optimal solution for the conflicting objectives namely minimization of end blow phosphorous content and maximization of end blow bath temperature considering initial hot metal temperature, hot metal tonnage, scrap, lime, and dolomite quantity as input variables. The meta-models have been created using evolutionary neural network (EvoNN) algorithm through training of a data set containing 120 steel plant data entries concerning different input as well as output variables. The analysis of Pareto front reveals that a low level of end blow phosphorous content is possible up to a certain critical value of end blow temperature. This study has a strong potential for providing an effective guideline for maintaining bath temperature just less than a critical temperature level during BOS steel making in order to control the phosphorous reversion along with attainment of necessary super heat. [ABSTRACT FROM AUTHOR]

This paper investigates a novel simulation-optimization (S-O) framework for identifying optimal treatment levels and treatment processes for multiple wastewater dischargers to rivers. A commonly used water quality simulation model, Qual2K, was linked to a Genetic Algorithm optimization model for exploration of relevant fuzzy objective-function formulations for addressing imprecision and conflicting goals of pollution control agencies and various dischargers. Results showed a dynamic flow dependence of optimal wastewater loading with good convergence to near global optimum. Explicit considerations of real-world technological limitations, which were developed here in a new S-O framework, led to better compromise solutions between conflicting goals than those identified within traditional S-O frameworks. The newly developed framework, in addition to being more technologically realistic, is also less complicated and converges on solutions more rapidly than traditional frameworks. This technique marks a significant step forward for development of holistic, riverscape-based approaches that balance the conflicting needs of the stakeholders. [ABSTRACT FROM AUTHOR]

To optimize a benchmark commercial dishwashing formulation, this paper presents a fractional factorial design procedure coupled with a mixture design in order to obtain a formulation with better properties and cost, as well as to provide an example of quick formula optimization that may also be useful for other cleaning and personal hygiene sectors. First, a fractional factorial design was performed to determine the significant effects for each response variable: viscosity, performance, foaming, and Krafft temperature. Then, a mixture design was used to determine the compositions that feature the best results for each property of interest. The determined compositions that meet the requirements with 90-95% confidence showed that improvements in the compositions can be adopted. It was possible to estimate compositions based on commercial formulations that meet the same cost per kilogram of product but with gains in detergency, foaming, and viscosity volume. [ABSTRACT FROM AUTHOR]

Precipitation is one of the most important drivers in watershed models. Our objective was to compare two sources of interpolated precipitation data in terms of their effect on calibration and validation of two Soil and Water Assessment Tool (SWAT) models. One model was a suburban watershed in metropolitan Atlanta, Georgia. The precipitation sources were Parameter-elevation Relationships on Independent Slopes Model ( PRISM) data on a 4-km grid and climate forecast system reanalysis ( CFSR) data on a 38-km grid. The PRISM data resulted in a better fit to the calibration data (Nash Sutcliffe efficiency [ NSE] = 0.64, Kling-Gupta efficiency [ KGE] = 0.74, p-factor = 0.84, and r-factor = 0.43) than the CFSR data ( NSE = 0.47, KGE = 0.53, p-factor = 0.67, and r-factor = 0.39). Validation results were similar. Sensitive parameters were similar in both the PRISM and CFSR models, but fitted values indicated more rapid groundwater flow to the streams with the PRISM data. The same comparison was made in the Big Creek watershed located approximately 1,000 km away, in central Louisiana. Results were similar with a more responsive groundwater system indicating PRISM data may produce better predictions of streamflow because of a more accurate estimate of rainfall within a watershed or because of a denser grid. Our study implies PRISM is providing a better estimate than CFSR of precipitation within a watershed when rain gauge data are not available, resulting in more accurate simulations of streamflows at the watershed outlet. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series. [ABSTRACT FROM AUTHOR]

Diagnostics imaging is an essential component of patient selection and treatment planning in oral rehabilitation by means of osseointegrated implants. In 2002, the EAO produced and published guidelines on the use of diagnostic imaging in implant dentistry. Since that time, there have been significant developments in both the application of cone beam computed tomography as well as in the range of surgical and prosthetic applications that can potentially benefit from its use. However, medical exposure to ionizing radiation must always be justified and result in a net benefit to the patient. The as low a dose as is reasonably achievable principle must also be applied taking into account any alternative techniques that might achieve the same objectives. This paper reports on current EAO recommendations arising from a consensus meeting held at the Medical University of Warsaw (2011) to update these guidelines. Radiological considerations are detailed, including justification and optimization, with a special emphasis on the obligations that arise for those who prescribe or undertake such investigations. The paper pays special attention to clinical indications and radiographic diagnostic considerations as well as to future developments and trends. [ABSTRACT FROM AUTHOR]