Alternative Direction Research Articles

Optical waveguide analysis using alternative direction implicit (ADI) method in combination with successive over-relaxation (SOR) algorithm

Optical waveguide analysis using alternative direction implicit (ADI) method in combination with successive over-relaxation (SOR) algorithm

Nonmonotone Alternative Direction Method Based on Simple Conic Model for Unconstrained Optimization

In this paper, we propose a nonmonotone Alternative Direction Method (ADM) based on simple conic model for unconstrained optimization. Unlike traditional trust region method, the subproblem in our method is a simple conic model, where the Hessian of the objective function is replaced by a scalar approximation, the trust region subproblem is solved by ADM which was first proposed by Zhu and Ni. When the trial point isn’t accepted by trust region, line search technique is used to find an acceptable point instead of resolving the trust region subproblem. The new method needs less memory capacitance and computational complexity. The global convergence of the algorithm is established under some mild conditions. Numerical results on a series of standard test problems are reported to show the new method is effective and robust.

The contested status of theory/theorizing and humanism/posthumanism in Olga Petrovskaya's Nursing theory, postmodernism, poststructualism, and Foucault.

The contested status of theory/theorizing and humanism/posthumanism in Olga Petrovskaya's Nursing theory, postmodernism, poststructualism, and Foucault.

On the Adaptive Penalty Parameter Selection in ADMM

Many data analysis problems can be modeled as a constrained optimization problem characterized by nonsmooth functionals, often because of the presence of ℓ1-regularization terms. One of the most effective ways to solve such problems is through the Alternate Direction Method of Multipliers (ADMM), which has been proved to have good theoretical convergence properties even if the arising subproblems are solved inexactly. Nevertheless, experience shows that the choice of the parameter τ penalizing the constraint violation in the Augmented Lagrangian underlying ADMM affects the method’s performance. To this end, strategies for the adaptive selection of such parameter have been analyzed in the literature and are still of great interest. In this paper, starting from an adaptive spectral strategy recently proposed in the literature, we investigate the use of different strategies based on Barzilai–Borwein-like stepsize rules. We test the effectiveness of the proposed strategies in the solution of real-life consensus logistic regression and portfolio optimization problems.

Gradient-based concurrent topology and anisotropy optimization for mechanical structures

The present paper introduces a novel gradient-based optimization framework to obtain discrete topologies consisting of either none or complete presence of anisotropic material, modeled by means of the polar formalism. Current topology optimizations with the polar formalism are based on optimality criteria, and limited to performing compliance minimization for thermodynamically feasible materials. The proposed optimization approach uses a sequential approximations approach, based on the Methods of Moving Asymptotes. The material density, orientation and anisotropic modules are updated separately at each iteration, in parallel sub-problems constructed with different types of approximations and settings. The proposed optimization approach is successfully validated for compliance minimization against the Alternate Directions method for general orthotropic materials, defined by the thermodynamic bounds. The importance of the anisotropy initialization in the gradient-based approach is highlighted to obtain stiffer solutions. The gradient-based strategy is also extended to incorporate geometric bounds on the polar parameters, defining the domain of existence of composite laminates. Obtained results for compliance minimization with laminates are compared to published results using lamination parameters. Finally, new solutions are presented showing the improvement of the compliance with the expansion of the anisotropy design domains. This paper paves the way for strength-based topology optimization of parts made of orthotropic materials or composite laminates.

Natural convection due to lateral uniform heat flux in a slender porous cavity saturated with nanofluid: Departure from LTE state

The present article deals with the influence of the local thermal nonequilibrium (LTNE) state on natural convection in an enclosure filled with nanofluid-saturated porous medium. The flow is induced due to the maintenance of constant heat flux on the vertical walls and insulation of horizontal walls. The Darcy model has been adopted to describe the flow governing equations. These equations are solved numerically by using the alternate direction implicit method and analytically by applying parallel flow assumptions valid for large aspect ratios. Boundary layer analysis is performed to report the boundary layer thickness ( δ x ∼ 2 1 / 2 ( k nf / k f ) 1 / 10 ( R a T ) − 1 / 5 ) as well as the heat transfer rate of nanofluid ( N u nf ∼ ( k nf / k f ) − 1 / 5 R a T 2 / 5 ) . The combined effect of LTNE state parameters (interface heat transfer coefficient (H), porosity scaled thermal conductivity ratio (γ)) and volume fraction of nanoparticle ( ϕ ) is addressed on the flow dynamics and heat transfer mechanism. Rigorous analysis, indicates that the average heat transfer rate of nanofluid and solid porous matrix are increasing function of H and γ, however, the role of γ is accelerated for a relatively high value of H. For increasing the value of γ from 1 to 10, the enhancement in the heat transfer rate of nanofluid is reported to be up to 27% at 10% volume fraction of nanoparticles. The average Nusselt number of nanofluid, as well as solid phase, are reduced when the value of ϕ is increased under the LTNE circumstances. Furthermore, the flow structure is controlled by unicellular structure with rotating anticlockwise direction in the entire study. For the very small value of H the temperature distribution in the solid porous matrix is mainly by conduction mode and distribution is linear, however, for a relatively high value of H the distribution in the same is controlled by both conduction as well as convection, and it will be more pronounced for the higher value of γ.

Economic Security, Sanctions and Reorientation of Russian Foreign Trade Flows

Relevance. Under the conditions of sanctions pressure, Russia needs to protect its economic interests and strengthen economic security. Therefore, the reorientation of foreign trade flows requires additional analysis. The purpose is to consider the direction of reorientation of Russian foreign trade flows in the context of anti‒ Russian sanctions.Objectives: to determine the main agenda of world trade policy; to identify common priorities of world trade; to provide quantitative data on the volume of trade of countries, to analyze the specifics of trade agreements over a decade, to identify the main economic method of pressure on states; to provide data on Russia's trade with other countries; to consider the Russian export commodity structure; to identify the relationship between the share in the commodity structure goods and growth rates in stable and crisis periods; identify priority export Russian goods in modern conditions.Methodology. The research methodology included the use of methods of analysis of quantitative and qualitative characteristics, correlation analysis, description, retrospective analysis, abstraction, generalization of the analyzed information.Results. The reasons for the forced change in the direction of foreign trade flows are not only direct pressure on the Russian economy, but also global trends of deglobalization and regionalization. The current trading partners, despite the restrictions imposed, continue to trade with Russia. When finding potential allies, the focus is primarily on the reliability, security and strength of partners on the world stage. The Russian economy should not deviate from the current export structure, as the demand for energy resources continues to be high. And Russia retains the role of one of the guarantors of global energy security.Conclusions. The issue of reorientation of Russian trade flows to alternative directions will remain one of the prevailing ones today. This is able to stabilize the economy and protect the economic interests of the country, to ensure the economic security of Russia. By diversifying and transforming trade flows by changing channels, the Russian economy will be able to discover new opportunities for the development of the world market.

A novel large-scale EV charging scheduling algorithm considering V2G and reactive power management based on ADMM

Electric vehicle aggregators (EVAs) that utilize vehicle-to-grid (V2G) technologies can function as both controllable loads and virtual power plants, providing key energy management services to the distribution system operator (DSO). EVAs can also balance the grid’s reactive power as a virtual static VAR compensator (SVC) and provide voltage stability by utilizing advanced electric vehicle (EV) chargers that are capable of four-quadrant operations to provide reactive power management. Finally, managed charging can benefit EVAs themselves by minimizing power factor penalties in their electricity bills. In this paper, we propose a novel EV charging scheduling algorithm based on a hierarchical distributed optimization framework that minimizes peak load and provides reactive power compensation for the DSO by collaboration with EVAs that manage both the active and the reactive charging and discharging power of participating EVs. Utilizing the alternative direction method of multipliers (ADMM), the proposed distributed optimization approach scales well with increased EV charging infrastructure by balancing active and reactive power while decreasing computational burden. In our proposed hierarchical approach, each EVA schedules the active and reactive EV charging and discharging power for 1) reactive power compensation in order to minimize power factor penalty and electricity cost accrued by the EVA, 2) satisfaction of each EV’s energy demand at minimal charging cost, and 3) peak shaving and load management for the DSO. When compared with an uncoordinated charging model, the efficacy of this proposed model is successfully demonstrated through a 300% decreased peak EV load for the DSO, 28% lower electricity costs for EV users, and 98.55% smaller power factor penalty, along with 17.58% lower overall electricity costs, for EVAs. The performance of our approach is validated in a case study with 50 EVs at multiple EVAs in an IEEE 13-bus test case and compared the results with uncoordinated EV charging.

Two-Dimensional Hexagonal Structure of Boron Nitride Nanotubes and BNNT-Induced Phase Transition of Block Copolymer in BNNT/Block Copolymer Complex for Energy Harvesting

Since boron nitride nanotubes (BNNTs) were first manufactured, they have gained considerable attention for their wide-scale application as reinforcing composites, piezoelectric materials, electrical insulating materials, thermal conductors, and neutron shielding materials because of their excellent mechanical, electrical, thermal, and neutron absorption properties. Despite the remarkable properties and broad application scope of BNNTs, their use has been limited because of their ineffective structural control due to the presence of one-dimensional nanoparticles. To overcome this limitation, we investigated an approach for the collective self-assembly of BNNTs by using block copolymers (Pluronic P65 and Pluronic P85) as a template and studied the BNNT-induced phase behavior of the block copolymer. For homogenous mixtures of BNNTs and block copolymers, the BNNTs were encapsulated by the in situ polymerization of surfactants (p-BNNTs), where their overall structures were confirmed by small-angle neutron scattering (SANS) and atomic force microscopy (AFM) measurements. The p-BNNTs were mixed with the block copolymers (at 50%, Pluronic P65 or Pluronic P85) by centrifugation in alternative directions to form homogeneously mixed complexes. Polarized optical microscopy (POM) and small-angle X-ray scattering (SAXS) measurements confirmed a two-dimensional hexagonal structure of the BNNTs in the block copolymer matrix that self-assembled upon heating, which can give a possibility of being used as effective piezoelectric materials for energy harvesting. Moreover, upon the addition of BNNTs, the phase behavior of the block copolymer can be controlled, allowing the formation of hexagonal, face-centered cubic, and body-centered cubic structures depending on the BNNT concentration and temperature. This study provides a new and simple method to control the collective BNNT structure.

Improvement and Application of Fusion Scheme in Automatic Medical Image Analysis

The research in this paper provides generalization and new ideas for research topics in computer-assisted medicine. The main improvement efforts in deep learning-based multimodal fusion schemes, which provide alternative directions and robust feature fitting performance for fusion schemes, are building complex structures, migrating knowledge or experience, processing and enhancing data, and targeting features for semantic correction based on contextual features. At the application level, the brain, liver, and lungs are the main targets of scientific research, so this paper surveys related work and analyzes the reasons for performance gains. Taken together, deep learning-based image fusion schemes can assist physicians in understanding information about lesion sites, lesion types, and sizes, providing an important basis for developing personalized treatment plans, which is important for improving diagnosis and specifying precise treatment plans. Therefore, the investigation of medical image fusion schemes is promising and beneficial.

Just transition and welfare states: a largely unexplored relation

Climate emergency has been recognised as a top policy priority by more and more policy-makers and the restructuring process it entails is seen as the main challenge of the coming decades. The welfare state that emerged in the context of a fossil fuel-based extractive economic model, based on a belief in sustained growth, cannot remain unaffected by the ongoing transition to a net-zero economy (Gough et al., 2008). Possible linkages between the welfare state and climate and environmental issues largely remain unexplored and until very recently discussion of social welfare systems in Europe has been disconnected from ecological concerns and policies and as well from the just transition narrative that took a prominent role in shaping the social dimension of climate policies. Both on the other hand assume continuing economic growth. This article aims to present a broad mapping of the current debates mainly at EU level, highlighting possible alternative directions (from green growth to sustainable welfare; from technology to behavioural changes). It proceeds through selected literature reviews offering a dialogue between different perspectives and opening successive routes of questioning. It also highlights the current limitations in the analysis of the role and the shape of welfare states in tackling environmental challenges and labour market transitions.

LPI Radar Waveform Design With Desired Cyclic Spectrum and Pulse Compression Properties

This paper considers the practical LPI radar waveform design problem for jointly achieving a desired cyclic spectrum and pulse compression properties. In this work, the weighted cyclic frequency sidelobe (WCFS) level is minimized to achieve the LPI purpose while the similarity constraint regarding a known radar waveform that occupies the desired detection properties is considered. The waveform design problem is then formulated as a quartic optimization problem with heterogeneous quadratic inequality constraints. These properties make the problem NP-hard in general. To solve this problem efficiently, by introducing necessary auxiliary variables, the original problem is converted into several quadratic optimization problems with respect to each independent variable under a separated linear inequality constraint, which can be efficiently solved by leveraging the alternation direction method of multipliers (ADMM) framework. Finally, the performance of the proposed method is demonstrated via numerical examples.

Alternative Direction Implicit Method for Solving First Order 2D Hyperbolic Delay Differential Equations

Alternative Direction Implicit Method for Solving First Order 2D Hyperbolic Delay Differential Equations

ALTERNATIVE DIRECTION IMPLICIT METHOD FOR SOLVING FIRST ORDER 2D HYPERBOLIC DELAY DIFFERENTIAL EQUATIONS

This article considers delayed two-dimensional first order hyperbolic differential equations. The propagation of the discontinuity of the solution is also established. An alternating implicit finite difference method and backward Euler finite difference methods are presented. We proved that this method is first-order convergent. Illustrating numerical examples are given for validation. We also present an application of the proposed approach to the variable delay problem.

Alternative window wall ratio of glasses with different solar heat gain coefficient and solar transmittance and their effect on total energy consumption in alternative directions

Energy simulation model of the building of Eskişehir Technical University Industrial Engineering Department Academic and Administrative Staff rooms were created in this study carried in the scope of energy efficiency and performance of buildings. In the aforementioned energy simulation mode, in line with the International Measurement, Verification and Energy Needs Standards and Protocol (IPMVP) “energy consumption verification”; heating energy, indoor-outdoor environment and climate data were defined, energy consumption verification was carried out and a realistic model was achieved. Using the realistic model achieved, alternative directions were applied to alternative window wall ratios thereby calculating “reference energy consumptions” in “reference building models”. Energy consumptions, calculated by applying alternative glass types to reference models, were then compared with reference energy consumptions

Parameter identification for a model for multi-functional materials with hysteresis and thermodynamic compatibility

Multifunctional materials have tremendous potential for engineering applications as they are able to convert mechanical to electromagnetic energy and vice-versa. One of the features of this class of materials is that they show significant hysteresis, which needs to be modeled correctly in order to maximize their application potential. A method of modeling multifunctional materials that exhibit the phenomenon of hysteresis and is compatible with the laws of thermodynamics was developed recently. The model is based on the Preisach hysteresis operator and its storage function and may be interpreted as a two-input, two-output neural net with elementary hysteresis operators as the neurons. The difficulty is that the parameters in the model appear in a non-linear fashion, and there are several constraints that must be satisfied by the parameters for thermodynamic compatibility. In this article, we present a novel methodology that uses the rate-independent memory evolution properties of the Preisach operator to split the parameter estimation problem into three numerically well-conditioned, linear least squares problems with constraints. The alternative direction method of multipliers (ADMM) algorithm and accelerated proximal gradient method are used to compute the Preisach weights. Numerical results are presented over data collected from experiments on a Galfenol sample. We show that the model is able to fit not only experimental data for strain and magnetization over a wide range of magnetic fields and stress but also able to predict the response for stress and magnetic fields not used in the parameter estimation.

BroadBand-Adaptive VMD with Flattest Response

A mixed signal with several unknown modes is common in the industry and is hard to decompose. Variational Mode Decomposition (VMD) was proposed to decompose a signal into several amplitude-modulated modes in 2014, which overcame the limitations of Empirical Mode Decomposition (EMD), such as sensitivity to noise and sampling. We propose an improved VMD, which is simplified as iVMD. In the new algorithm, we further study and improve the mathematical model of VMD to adapt to the decomposition of the broad-band modes. In the new model, the ideal flattest response is applied, which is derived from the mathematical integral form and obtained from different-order derivatives of the improved modes’ definitions. The harmonics can be treated via synthesis in our new model. The iVMD algorithm can decompose the complex harmonic signal and the broad-band modes. The new model is optimized with the alternate direction method of multipliers, and the modes with adaptive broad-band and their respective center frequencies can be decomposed. the experimental results show that iVMD is an effective algorithm based on the artificial and real data collected in our experiments.

Parallel Alternating Direction Primal-Dual (PADPD) Algorithm for Multi-Block Centralized Optimization

Abstract In this article, a centralized two-block separable convex optimization with equality constraint and its extension to multi-block optimization are considered. The first fully parallel primal-dual discrete-time algorithm called Parallel Alternating Direction Primal-Dual (PADPD) is proposed. In the algorithm, the primal variables are updated in an alternating fashion like Alternating Direction Method of Multipliers (ADMM). The algorithm can handle non-smoothness of objective functions with strong convergence. Unlike existing discrete-time algorithms such as Method of Multipliers (MM), ADMM, Parallel ADMM, Bi-Alternating Direction Method of Multipliers (Bi-ADMM), and Primal-Dual Fixed Point (PDFP) algorithms, all primal and dual variables in the proposed algorithm are updated independently. Therefore, the time complexity of the algorithm can be significantly reduced. It is shown that the rate of convergence of the algorithm for quadratic or linear cost functions is exponential or linear under suitable assumptions. The algorithm can be directly extended to any finite multi-block optimization without further assumptions while preserving its convergence. PADPD algorithm not only can compute more iterations (since it is fully parallel) for the same time-step but it is also possible that PADPD algorithm can have a faster convergence rate than that of ADMM. Finally, two numerical examples are provided in order to show advantage of PADPD algorithm.

Some power allocation algorithms for cognitive uplink satellite systems

Cognitive satellite communication (SatCom) is rapidly emerging as a promising technology to overcome the scarcity of the exclusive licensed band model in order to fulfill the increasing demand for high data rate services. The paper addresses power allocation methods for multi-operator multi-beam uplink satellite communication systems co-existing with a Ka-band terrestrial network, using cognitive radio paradigm. Such a scenario is especially challenging because of (i) the coexisting multiple SatCom operators over the cognitive band need to coordinate the use of their resources under limited inter-operator information exchange, and (ii) nonlinear onboard high power amplifier (HPA) which leads to nonlinear interference between users and beams. In order to tackle the first challenge, we propose distributed power allocation algorithms including the standard Alternate Direction Multiplier Method (ADMM); Regarding the HPA nonlinear impairment, we propose nonlinear-aware power allocation based on Signomial Programming. The proposed solutions outperform state-of-the-art in both cases.

Dense urbanism and economic multi-centrism at third-millennium BC Lagash

Studies of ancient Mesopotamian cities have long focused on their institutions. Here, instead, the authors draw on recent investigations at the third-millennium BC site of Lagash (modern Tell al-Hiba, Iraq) to explore urban density, economy and sustainability at one of the largest ancient urban centres of the region. Drawing on excavation, environmental and remote-sensing data, the authors adopt a multi-scalar approach, revealing dense urban occupation, with subdivision into distinct walled quarters, as well as evidence for multiple foci of intensive industrial production and the exploitation of a rich mosaic of surrounding micro-environments. The study emphasises how a combination of new field data and alternative research directions offers novel insights into early urbanism.