Convex Form Research Articles

Spatial large-span structures

Objective. This article discusses spatial large-span structures; provides features of their work; as well as layout examples. General dimensions and ways of stabilizing displacements are given.Method. The features of the work and layout of spatial large-span structures; as well as calculation formulas are given. The types of sections and nodes of conjugation of elements are presented. A technique is described that allows stabilizing the movements of largespan pavements.Result. The given structural schemes; as well as the analysis of their work; allow designing large-span spatial systems in the form of convex and concave structures that have high reliability; minimal weight; and high manufacturability in manufacturing; transportation and installation.Conclusion. The proposed rational design solutions make it possible to reduce the own weight of spatial convex and concave coatings; which have the necessary rigidity; strength and stability. The types of structural schemes; sections and junctions of elements considered in the article are widely used in the practice of design and construction.

Relationship between development of the condylar cortex and the changes in condyle morphology: a cone-beam computed tomography (CBCT) observational study.

A correct understanding of the mandibular condyle morphology may help clinicians judge the normal range of morphological variations of asymptomatic patients or the pathological conditions correctly. Hence, the aim of the present study was to evaluate the status of condyle cortication and condyle morphology, and to investigate the relationship between the development of the condylar cortex and the changes of condyle morphology. The present study was an observational study. A total of 1,010 temporomandibular joint (TMJ) cone-beam computed tomography (CBCT) images were collected retrospectively. The mandibular condyle morphology was observed in axial (concave, convex, plane and others for anterior and posterior facets), coronal (plane, convex, angled and round for superior facet) and sagittal (round and plane for superior facet) views, and the condylar cortication was grouped into three types (undeveloped, developing and developed). Analytical statistics were performed to detect a relationship between the cortication status and morphology of the condyles. For males and females, the mean age was 15.11±2.71 and 14.25±2.60 years (for condylar bone without cortication), 19.45±3.92 and 18.65±3.45 years (with developing cortical bone), 23.63±3.36 and 23.86±3.73 years (with developed cortical bone), respectively. The condyle morphology with a plane form in the anterior aspect, a convex form in the posterior aspect, a convex form in the coronal view and a round form in the sagittal view was the most often recorded condyle morphologies (13.2%). After the cortical bone of condyle completely forms, the plane form was significantly increased in the superior surface in both sagittal and coronal views. The condylar shape gradually changes with growth and development of the condyle bone cortex. The more mature the bone cortex is, the higher the probability that the condyle will have an uneven shape, which may mean that the condyle morphology may change due to remodeling during growth and development.

Task offloading under deterministic demand for vehicular edge computing

AbstractIn vehicular edge computing (VEC) networks, the rapid expansion of intelligent transportation and the corresponding enormous numbers of tasks bring stringent requirements on timely task offloading. However, many tasks typically appear within a short period rather than arriving simultaneously, which makes it difficult to realize effective and efficient resource scheduling. In addition, some key information about tasks could be learned due to the regular data collection and uploading processes of sensors, which may contribute to developing effective offloading strategies. Thus, in this paper, we propose a model that considers the deterministic demand of multiple tasks. It is possible to generate effective resource reservations or early preparation decisions in offloading strategies if some feature information of the deterministic demand can be obtained in advance. We formulate our scenario as a 0‐1 programming problem to minimize the average delay of tasks and transform it into a convex form. Finally, we proposed an efficient optimal offloading algorithm that uses the interior point method. Simulation results demonstrate that the proposed algorithm has great advantages in optimizing offloading utility.

Achievable Rates and Resource Allocation for CDMA-Based Overlay Cognitive Radio With RF Energy Harvesting

This article introduced a cognitive wireless powered communication network with an uplink (UL) code-division multiple access (CDMA) scheme consisting of one hybrid access point (H-AP) and multiple energy harvesting secondary users (SUs), which are coexisted with a primary wireless network. The frame structure is coordinated through the two-phase harvest-then-transmit protocol. The energy-limited SUs first harvest wireless energy in the downlink phase and then transmit their information signals simultaneously to H-AP with the CDMA scheme in the UL phase. An overlay spectrum sharing model is also considered where H-AP has access to the primary transmitter's codebook and primary network's channel. Our goal is to maximize the sum-throughput optimization problem of SUs via jointly optimizing power and time allocation. The considered joint optimization problem is generally nonconvex due to coupled variables. As a solution, we first transform it into the equivalent convex form using proper variables and then we solve it using the convex optimization technique. The closed-form solutions for time and power allocations are given. We also confirm from various simulations’ results that our proposed CDMA scheme is superior to the conventional time-division multiple access schemes.

Downlink Power Minimization in Intelligent Reflecting Surface Aided Security Classification Wireless Communications System

User privacy protection is considered a critical issue in wireless networks, which drives the demand for various secure information interaction techniques. In this paper, we introduce an intelligent reflecting surface (IRS)-aided security classification wireless communication system, which reduces the transmit power of the base station (BS) by classifying users with different security requirements. Specifically, we divide the users into confidential subscribers with secure communication requirements and general communication users with simple communication requirements. During the communication period, we guarantee the secure rate of the confidential subscribers while ensuring the service quality of the general communication users, thereby reducing the transmit power of the BS. To realize such a secure and green information transmission, the BS implements a beamforming design on the transmitted signal superimposed with artificial noise (AN) and then broadcasts it to users with the assistance of the IRS's reflection. We develop an alternating optimization framework to minimize the BS downlink power with respect to the active beamformers of the BS, the AN vector at the BS, and the reflection phase shifts of the IRS. A successive convex approximation (SCA) method is proposed so that the nonconvex beamforming problems can be converted to tractable convex forms. The simulation results demonstrate that the proposed algorithm is convergent and can reduce the transmit power by 20\% compared to the best benchmark scheme.

A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs.

Surface electromyography (sEMG) is a signal consisting of different motor unit action potential trains and records from the surface of the muscles. One of the applications of sEMG is the estimation of muscle force. We proposed a new real-time convex and interpretable model for solving the sEMG-force estimation. We validated it on the upper limb during isometric voluntary flexions-extensions at 30%, 50%, and 70% Maximum Voluntary Contraction in five subjects, and lower limbs during standing tasks in thirty-three volunteers, without a history of neuromuscular disorders. Moreover, the performance of the proposed method was statistically compared with that of the state-of-the-art (13 methods, including linear-in-the-parameter models, Artificial Neural Networks and Supported Vector Machines, and non-linear models). The envelope of the sEMG signals was estimated, and the representative envelope of each muscle was used in our analysis. The convex form of an exponential EMG-force model was derived, and each muscle's coefficient was estimated using the Least Square method. The goodness-of-fit indices, the residual signal analysis (bias and Bland-Altman plot), and the running time analysis were provided. For the entire model, 30% of the data was used for estimation, while the remaining 20% and 50% were used for validation and testing, respectively. The average R-square (%) of the proposed method was 96.77 ± 1.67 [94.38, 98.06] for the test sets of the upper limb and 91.08 ± 6.84 [62.22, 96.62] for the lower-limb dataset (MEAN ± SD [min, max]). The proposed method was not significantly different from the recorded force signal (p-value = 0.610); that was not the case for the other tested models. The proposed method significantly outperformed the other methods (adj. p-value < 0.05). The average running time of each 250ms signal of the training and testing of the proposed method was 25.7 ± 4.0 [22.3, 40.8] and 11.0 ± 2.9 [4.7, 17.8] in microseconds for the entire dataset. The proposed convex model is thus a promising method for estimating the force from the joints of the upper and lower limbs, with applications in load sharing, robotics, rehabilitation, and prosthesis control for the upper and lower limbs.

User Grouping, Precoding Design, and Power Allocation for MIMO-NOMA Systems

In this paper, we study user grouping, precoding design, and power allocation for multiple-input multiple-output (MIMO) nonorthogonal multiple access (NOMA) systems. An optimization problem is formulated to the maximize the sum rate under a transmit power constraint at a base station and rate constraints on users, which are nonconvex and combinatorial and thus very challenging to solve. To tackle this problem, we carry out the optimization in two steps. In the first step, exploiting the machine learning technique, we develop an efficient iterative algorithm for user grouping and precoding design. In the second step, we develop a power-allocation scheme in closed form by recasting the original problem into a useful and tractable convex form. The numerical results demonstrate that the proposed joint scheme, including user grouping, precoding design, and power allocation, considerably outperforms the existing schemes in terms of sum rate maximization, which increases the sum-rate up to 8–18%. In addition, the results show the larger the number of antennas or users, the bigger the performance gap, at the cost of less computational complexity.

Turbulence Characteristics in Mild and Steep Entrance Slopes of Pool-Riffle Sequences

This study investigates the distributions of velocity and Reynolds stress in an artificial pool-riffle sequence for two entrance slopes of 5° and 20° in a laboratory and compares the results with a similar pool-riffle sequence in a gravel-bed river in central Iran. Quadrant analysis is applied to find out the contributions of different events on turbulent flow structures. At an entrance slope of 5°, the velocity distribution follows an exponential trend without flow separation, but for the entrance slope of 20°, the velocity distribution indicates a S-shaped pattern with flow separation. Variation of entrance slope does not influence the convex form of Reynolds stress (RS) distribution, but it influences the location of the maximum value of RS and the flow separation zone length. The results reveal that outward and ejection are the dominant events for both field and laboratory settings. The sweep displays a decreasing trend from near the bed toward the water surface, however, the outward contribution indicates an increasing trend from the bed toward the water surface. The agreement between laboratory and field results in velocity and Reynolds stress will help the river engineers to better manage complex fluvial processes. Bursting process events depend on the aspect ratio for the same entrance pool slope. The agreement in the results of velocity and Reynolds stress distributions and the dominant events of bursting process in the laboratory and field are encouraging for better restoration of rivers and decreasing the cost of projects.

Sidelobe-Level Minimization With Power Gain Constraint via a Wide-Beam Antenna Array

To minimize the sidelobe level (SLL) of a wide-beam antenna array, the conventional approaches usually solve the shaped-beam pattern synthesis (SBPS) problem. These SBPS-based approaches focus on synthesizing a beam pattern that is similar to the desired one. However, the power gain except the beam shape is also an important concerning factor in array applications. This letter proposes an SLL minimization approach to obtain a lower SLL while achieving the similar minimum power gain in the wide-beam mainlobe as being obtained via the SBPS-based approaches. The proposed approach takes the power gain instead of the beam shape as the cost function and set up the synthesis optimization problem. An auxiliary variable is introduced to relax this nonconvex formulated problem into convex form. As a result, the original optimization problem can be solved iteratively. Even though the optimal solution cannot be theoretically guaranteed, numerical examples demonstrate that the proposed approach is able to further suppress the SLL by more than 10 dB for the flat-topped beam pattern and more than 3 dB for the cosecant squared beam pattern.

A semantic universal for modality

This paper articulates a new semantic universal for modal expressions in natural language, dubbed the Independence of Force and Flavor (IFF). This property accommodates counterexamples to Nauze 2008’s proposed universal from variable-force variable-flavor modals (Bochnak 2015a,b) and attitude verbs (Močnik &amp; Abramovitz 2019), while still ruling out unattested modals. It may also be seen as a form of convexity applied to modals. EARLY ACCESS

Economic Potential for Hybrid Electric Vehicles in Urban Signal-free Intersections with Decentralized MPC

The development of electric and connected vehicles as well as automated driving technologies are key towards the smart city, providing convenient urban mobility and high energy economy performance. However, the global rise in electricity price provokes renewed interest on CAVs with hybrid electric powertrains rather than considering battery electric powertrains. This paper proposes a decentralized coordination strategy for a group of connected and autonomous vehicles (CAVs) with a series hybrid electric (sHEV) powertrain at urban signal-free intersections. The problem is formulated as a convex form with suitable relaxation and approximation of the powertrain model and solved by decentralized model predictive control (DMPC), which enables rapid search and a unique solution in real-time. Numerical examples validate the effectiveness of the proposed methods concerning physical and safety constraints. By utilizing the petrol fuel and battery charging prices over the last year, the performance of the proposed approach is evaluated against the optimal results produced by two benchmark solutions, conventional vehicles (CVs) and battery electric vehicles (BEVs). The comparison results demonstrate that the traveling cost of sHEVs approaches and, even under some circumstances, reaches the same level as for BEVs, which indicates the importance of hybridization, particularly under the current rising electricity price situation.

Frequency Response Data Based Disturbance Observer Design: With Application to a Nonminimum Phase Motion Stage

Disturbance observer based control system, which utilizes estimated disturbance to compensate the influence of real disturbance, is widely applied in industrial systems. In this article, a frequency response data based auto-tuning method is proposed to design a bandwidth-optimized disturbance observer. The identification of a nominal plant model and the design of a low-pass filter are accomplished simultaneously in the discrete domain. This significantly reduces the design effort required in existing parametric model-based and experience-based methods. A convex optimization problem is formulated by converting all the original constraints into convex form to save calculation time. Finally, the efficacy of the proposed method is verified by comparing the experimental results of existing methods with those of the proposed method in a nonminimum phase motion stage.

Lüders band evolution in geometrically graded NiTi plates

This study investigated the process of the Lüders band formation and propagation within geometrically graded plate samples of a pseudoelastic NiTi during the stress-induced martensitic transformation by means of digital image correlation full-field strain measurement. The geometrically graded plate samples had parabolic width profiles in concave and convex forms along the length. Such sample geometries created a situation of progressively increasing applied load and a continuous variation of the sample width during the process of the stress-induced transformation. The size (along the sample length direction) of the Lüders band front transition zone was found to remain unchanged with variation of the sample width during the process, but the local strain rate across the transition zone was varied. The transition zone of the martensite Lüders band during the forward transformation was wider than that of the austenite Lüders band on the reverse transformation, and the local strain rate was lower than that of the latter.

3D beamforming in Intelligent Reflecting Surface (IRS)-assisted multi-user cognitive radio networks

In this paper, we consider a multi-user cognitive radio network (CRN) equipped with an intelligent reflecting surface (IRS). We examine the network performance by evaluating the fairness of the secondary system, which is satisfying the minimum required signal to interference and noise ratio (SINR) for each secondary user (SU). The minimum SINR of the SUs is maximized by joint optimization of the beamforming vector and three-dimensional beamforming (3DBF) angles at the secondary base station (SBS) and also the phase shifts of the IRS elements. This optimization problem is highly non-convex. To solve this problem, we utilize Dinkelbach’s algorithm along with an alternating optimization (AO) approach to achieve some sub-problems. Accordingly, by further applying a semi-definite relaxation method, we convert these sub-problems to equivalent convex forms and find a solution. Furthermore, analytically we propose an algorithm for optimizing 3DBF angles at the SBS. Through numerical results, the improvement of the sum SINR of the secondary system using the proposed method is illustrated. Moreover, it is shown that as the number of reflecting elements of IRS increases, the sum SINR significantly augments while satisfying fairness. Also, the convergence of the proposed algorithm is verified utilizing numerical results.

Minimum Power Control Allocation for Incremental Control of Over-Actuated Transition Aircraft

Existing control allocation approaches usually minimize an or norm of the actuator commands that is loosely related to the thrust produced or the aerodynamic drag. This paper proposes a novel incremental control allocation method that directly minimizes the total power required for an over-actuated, propeller-driven transition aircraft. The minimum power cost function is derived in a convex form and leads to a closed-form algebraic solution for an additional command increment in the null space of the local control effectiveness matrix. The complete control allocation procedure consists of a two-step approach that is direction-preserving in the presence of actuator saturations and nonlinear due to the incremental formulation. The proposed control allocation is particularly advantageous in the case of a transition aircraft, where the tradeoff between using aerodynamic lift and vertical thrust can be solved naturally by including incremental attitude commands as virtual inputs in the minimum power control allocation. The resulting control allocation scheme allows to both maximize control authority and find minimum power trim solutions. Flight tests are performed on an over-actuated transition aircraft, showcasing the minimum power trim and control allocation without the use of flight mode switching or blending functions throughout all flight regimes.

A Time-Optimal Trajectory Planning Strategy for an Aircraft With a Suspended Payload via Optimization and Learning Approaches

In this article, a real-time interactive time-optimal trajectory planning (TOTP) strategy is proposed for aircraft slung-load systems, in which the practical performance is guaranteed by taking advantage of convex optimization and reinforcement learning (RL) techniques. To the best of our knowledge, it is the first TOTP solution for an aircraft suspension system subject to path, velocity, acceleration, and cable tension constraints, where a practice-oriented RL policy is designed to interact with the system online. Specifically, by exploring the differential flatness property of the system, the states are projected into path coordinate space, where all the physical constraints are formulated in the TOTP with convex forms. Then, the TOTP is transformed into a large sparse optimization problem after discretization, which can be efficiently solved using convex solvers. Subsequently, a deep RL network is designed to optimize the TOTP results, where efficient learning is achieved in the solution space, thereby guaranteeing practical reliability and strong robustness via online interaction in applications. In addition, by incorporating convex optimization and learning techniques, the gap between simulation and experiment is successfully bridged, where the physical feasibility and efficient learning are ensured in the framework. Finally, comparative simulations and experimental results are included to show the effectiveness of the proposed strategy.

On the secrecy rate balancing problem of two‐way multiple‐input multiple‐output relaying networks using rank‐1 beamforming strategy

AbstractThe physical layer security of a two‐way relay network (TWRN) in the presence of an eavesdropper is considered, where two multi‐antenna nodes try to exchange messages via a multi‐antenna two‐way relay node. It is assumed that the transmission occurs in two hops. Throughout the first hop, the messages are concurrently transmitted at the same time from two transmitting nodes to the relay, while an eavesdropper tries to overhear the signals. Throughout the second hop, to prevent eavesdropping, the relay broadcasts a combination of the received signals in the null‐space of the eavesdropper's channel gain vector. The objective is to explore the proper power allocation policy at transmitting ends as well as an effective beamforming strategy at the relay to address the secrecy rate balancing (SRB) problem. The radio frequency multiple‐input multiple‐output (RF‐MIMO) architecture design is proposed in which the relay can merely process one data stream; hence, the relay beamforming matrix is of rank‐one. The underlying problem is non‐convex. To tackle this issue, the original problem is divided into two sub‐problems, where using semi‐definite relaxation (SDR) and sequential parametric cone approximation (SPCA) techniques, are converted into convex forms, where suboptimal solutions are derived. Numerical results demonstrate effectiveness of the proposed method compared to the existing works addressed in the literature and also show that our proposed solution has better performance even for the secrecy energy efficiency (SEE) metric.

Seismic evidence of gas hydrate and seafloor fluid escape on the upper Amazon deep-sea fan, Brazilian equatorial margin

The Amazon fan contains a gas hydrate province known from a bottom-simulating reflection (BSR) that lies within an upper slope compressional belt. In this study, the extent and character of the BSR and its relation to thrust-fold structures is examined using a grid of 2D and 3D seismic data. We show the BSR to comprise a series of elongate patches up to 16 km wide that are present along 300 km of the slope in water depths of 750-2250 m and extend over a total area of 6800 km2. The elongate BSR patches show a strong spatial correspondence with the arcuate crests of thrust-fold anticlines. In profile, the BSR patches exhibit convex forms and/or locally irregular relief that rises toward the seafloor. In plan, 3D seismic horizon maps reveal columnar BSR elevations up to 1 km wide, which rise beneath seafloor mounds and depressions, up to 0.5 km wide and 30 m in relief, interpreted as small mud volcanoes and possible pockmarks. The elongate BSR patches are interpreted to record the structurally-controlled rise of warm, gas-rich fluids into the crests of thrust-folds and their leakage into the gas hydrate stability zone, and in places to seafloor, through a near-surface system of faults, hydrofractures and vents.

Energy-Efficient UAV-Aided Ocean Monitoring Networks: Joint Resource Allocation and Trajectory Design

The Internet of Underwater Things (IoUT) plays a key role in maritime monitoring systems, but energy-efficient data-uploading has been a challenging task owing to energy-constrained and expensive facilities, such as buoys and underwater sensors. In this article, we present an energy-efficient data collection scheme for unmanned aerial vehicle (UAV)-aided ocean monitoring networks (OMNs), where underwater acoustic and aerial radio frequency (RF) links are considered collaboratively. Our goal is to maximize energy efficiency (EE) of the entire OMN by jointly optimizing the transmit power of buoys and sensors, scheduling their transmissions, as well as designing the UAV's trajectory; the objective function is constrained by minimum throughput thresholds, power consumption budgets, and the UAV's kinematic conditions. Furthermore, we introduce a tradeoff between the energy consumption of buoys and sensors to bridge the gap between acoustic and RF links. The formulated problem is decomposed into three subproblems and they are solved alternatively. In each iteration, we leverage Dinkelbach's method and successive convex approximation (SCA) technique to tackle the fractional program (FP) and transform an original subproblem into a convex form, respectively. Extensive simulations confirm the convergence of our proposed scheme, reveal the influence of the tradeoff on EE, and show that our scheme outweighs other benchmarks in different scenarios.

Information Rate Optimization for the Non-Regenerative Linear MIMO Relay Channel With a Direct Link and Variable Duty Cycle

We consider the optimization of a two-hop linear relay channel based on an amplify-and-forward Multiple-Input Multiple-Output (MIMO) relay. The relay is assumed to derive the output signal by applying a Relay Transform Matrix (RTM) applied to the input signal. Assuming perfect channel state information about the channel at the relay and iid transmitted symbols, the RTM is optimized according to two different criteria: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i)</i> MIMO information rate; <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ii)</i> information rate based on Orthogonal Space–Time Block Codes. The two assumptions have been addressed in part in the literature. The optimization problem is reduced to a manageable convex form, whose KKT equations are explicitly solved. Then, a parametric solution is given, which yields the power constraint and the information rate achieved with uncorrelated transmitted symbols as functions of a positive indeterminate. The solution for a given average power constraint at the relay is amenable to a <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">water-filling-like</i> algorithm, and extends earlier literature results addressing the case without the direct link. The duty cycle of the two-hop relaying process is also addressed in the general form of the achievable rate. Simulation results are reported, which are relevant to a Rayleigh fading MIMO relay channel and the role of the direct link SNR is precisely assessed. Duty cycle optimization is also considered by a numerical example.