Diagonal Strategy Research Articles

Experimental behaviour of diagonally stiffened steel I-girders

This paper reports on the experimental investigation carried out at the University of Coimbra, in which the behaviour of diagonally stiffened steel I-girders dominantly subject to shear is assessed. The experimental program consists of four specimens: one reference I-girder without a diagonal stiffener, and three specimens with different stiffener geometrical and materials characteristics, placed along the diagonal of the girder web to increase their stability and load-carrying capacity in shear. Moreover, two different stiffener joining techniques are explored, namely welding and bonding-bolting. The principal objective of this research is twofold: i) to qualitatively assess and compare the effects of these different diagonal stiffening strategies in terms of the shear capacity of I-girders, and ii) to critically assess currently available methodologies from the literature for the calculation of the shear resistance of diagonally stiffened I-girders. Regardless of the stiffener properties and joining technique, in all tested specimens the inclusion of a stiffener along the compression diagonal significantly increases the shear resistance when compared to the girder without diagonal stiffeners. However, the tests performed with bonded-bolted cold-formed stiffeners seem to show less ductile behaviour than those with a welded stiffener. Finally, a comparison of the experimental results with the available calculation methods was made and the conclusion is that they do not adequately predict the shear bearing capacity of the tested girders with the diagonal stiffeners, giving a large scatter of results.

Seat belt detection using gated Bi-LSTM with part-to-whole attention on diagonally sampled patches

One of the high-risk behaviors leading to severe traffic injuries is not wearing a seat belt. It is therefore very important to be able to automatically detect seat belts from surveillance images, encourage drivers to wear seat belts, and enhance passenger safety. In this paper, a novel deep neural network, Gated Bi-directional Long Short-Term Memory network with part-to-whole attention (GBL-PA), is proposed for seat belt detection from surveillance images. The innovation of our model lies in its unique diagonal sampling strategy, which meticulously captures the seat belt’s fine details, typically oriented from top right to bottom left across the torso of vehicle occupants. Our framework’s novelty is further encapsulated by the part-to-whole attention mechanism, which intelligently harmonizes the detailed local information from seat belt-specific patches with the broader contextual insights from the regional proposals. The pioneering design of a Gated Bi-directional LSTM network facilitates the dynamic integration of interactions across patches to deliver an optimized final prediction. The superiority of GBL-PA is established through rigorous comparison with the state-of-the-art methods on a new, large benchmark dataset comprising 14,936 images from traffic surveillance footage. Our framework demonstrates a notable improvement, achieving a mean Average Precision (mAP) of 72.3%, which surpasses the second best, YOLOX, by 0.9% mAP. This significant and consistent outperformance across various metrics underscores the transformative potential of GBL-PA in the realm of traffic safety enforcement. The source code of our framework is available at ANONYMISED.

Diagonal Partitioning Strategy Using Bisection of Rectangles and a Novel Sampling Scheme

In this paper, we consider a global optimization problem where the objective function is assumed to be Lipschitz-continuous with an unknown Lipschitz constant. Building upon the recently introduced BIRECT (BIsection of RECTangles) algorithm, we propose a new diagonal partitioning and sampling scheme. Our framework, named BIRECT-V (V for vertices), combines bisection with the sampling of two points. In the initial hyper-rectangle, these points are located at 1/3 and 1 along the main diagonal. Unlike most DIRECT-type algorithms, where evaluating the objective function at vertices is not suitable for bisection, our strategy, when combined with bisection, provides more comprehensive information about the objective function. However, the creation of new sampling points may coincide with existing ones at shared vertices, resulting in additional evaluations of the objective function and increasing the number of function evaluations per iteration. To overcome this issue, we propose modifying the original optimization domain to obtain a good approximation of the global solution. Experimental investigations demonstrate that this modification positively impacts the performance of the BIRECT-V algorithm. Our proposal shows promise as a global optimization algorithm compared to the original BIRECT and two popular DIRECT-type algorithms on a set of test problems. It particularly excels at high-dimensional problems

EVALUATING THE APPROPRIATENESS OF TASKS AND THE ELABORATION OF MULTIPLE SOLUTIONS TO OCCASION FOURTH-GRADERS’ MATHEMATICAL CREATIVE THINKING

Creativity is not only for gifted students, but also for regular ones. This case study was aimed to analyze the appropriateness of tasks and the elaboration of multiple solutions to occasion fourth-graders’ mathematical creative thinking through a documentary multiple-solution counting task in a figurative setting. The data came from the written report of 48 fourth graders in two classes in Taiwan, China. The appropriateness of creativity was reflected in the appropriateness of tasks and solutions, particularly suitable for complex problem solving. Elaboration was detail-dependent, and visualization was beneficial to the analysis of elaboration. The regular students who had just entered the fourth grade could show their creative thinking through different angles (horizontally or vertically) and starting points (holistic or partial), but with slightly more partial and horizontal than holistic and longitudinal, more adaptation than transformation. These fourth-grade students have had the basic mathematical creative thinking capability of adaptation, combination, change, rearrangement, extension or going back by using counting, combining, adding and reducing, overlapping, moving, and diagonal division strategies. Keywords: creative thinking, mathematical creativity, multiple-solution task, primary school students

Improved NSGA-II and its application in BIW structure optimization

Based on the crowding distance algorithm of Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), three improved algorithms are proposed: side length optimization strategy, diagonal optimization strategy, center optimization strategy. Zero-Ductility Transition (ZDT) series functions and Diode-Transistor Logic with Zener diode (DTLZ) series functions are used to calculate and compare the convergence and diversity of three improved algorithms and NSGA-II. The center optimization strategy based NSGA-II is confirmed to be the optimal algorithm. The body-in-white (BIW) optimization functions are established and optimized by center optimization strategy based NSGA-II, and the most appropriate BIW structure is calculated and verified by mode tests. The result shows: after the optimization, the BIW total mass increment is less than 3%, the first torsional mode frequency increment is more than 15%, and the torsion stiffness increment is more than 10%.

Novel diagonal scanning strategy for the laser powder bed fusion process

Novel diagonal scanning strategy for the laser powder bed fusion process

A study on a vehicle semi-active suspension control system based on road elevation identification.

A semi-active suspension system can effectively improve vehicle ride comfort and handling stability, and the active detection of road information is key to achieving semi-active suspension. To improve the road elevation perception ability of vehicles, this study proposes a continuous multiple scanning recursive matching algorithm based on a single-line LIDAR sensor. Radar recursive scanning is used to obtain the multiple superposition data of echo signals, and coordinate matching is realized between historical scanning data and current scanning data. Simultaneously, the sensor height deviation and pitch angle deviation of the sensors are regressed to obtain an accurate pavement elevation. Considering the control effect of the active vehicle suspension, a vehicle suspension model with seven degrees of freedom is established. The semi-active suspension controller is constructed using a diagonal recursive neural network algorithm, and the neural network weight is trained using a genetic algorithm. In addition, a preview diagonal recursive neural network control strategy for semi-active suspension, based on the combination of road elevation information, is proposed. The results of a hardware-in-the-loop co-simulation, which was conducted based on the Simulink control model and dSPACE real-time simulation, revealed that the ride comfort and stability of the vehicle were improved owing to a preview of the elevation information of the road ahead and the active adjustment of the shock absorber of the suspension system.

Mechanically robust lattices inspired by deep-sea glass sponges.

The predominantly deep-sea hexactinellid sponges are known for their ability to construct remarkably complex skeletons from amorphous hydrated silica. The skeletal system of one such species of sponge, Euplectella aspergillum, consists of a square-grid-like architecture overlaid with a double set of diagonal bracings, creating a chequerboard-like pattern of open and closed cells. Here, using a combination of finite element simulations and mechanical tests on 3D-printed specimens of different lattice geometries, we show that the sponge's diagonal reinforcement strategy achieves the highest buckling resistance for a given amount of material. Furthermore, using an evolutionary optimization algorithm, we show that our sponge-inspired lattice geometry approaches the optimum material distribution for the design space considered. Our results demonstrate that lessons learned from the study of sponge skeletal systems can be exploited for the realization of square lattice geometries that are geometrically optimized to avoid global structural buckling, with implications for improved material use in modern infrastructural applications.

Q-learning optimized diagonal recurrent neural network control strategy for brushless direct current motors

In order to improve the working stability of brushless direct current motors (BLDCM), a diagonal recursive neural network (DRNN) control strategy based on Q-learning algorithm is proposed in this paper which is called as Q-DRNN. In Q-DRNN, DRNN iterates over the output variables through a unique recursive loop in the hidden layer, and its key weight is optimized to speed up the iteration. Moreover, an improved Q-learning algorithm is introduced to modify the weight momentum factor of DRNN, which makes DRNN have the ability of learning and online correction so as to make the BLDCM achieve better control effect. In MATLAB/Simulink environment, Q-DRNN is tested and compared with other popular control methods in terms of speed and torque response under different operating conditions, and the results show that Q-DRNN has better adaptive and anti-interference ability as well as stronger robustness.

Add–sub pivoting triangular factorization for symmetric matrix

Commonly used diagonal pivoting strategies for general symmetric matrix would bring about triangular factorization PAP’=LDL’, in which D is block diagonal matrix with either 1 × 1 or 2 × 2 diagonal blocks. This paper proposed a modified add–sub pivoting strategy resulting in D with no 2 × 2 diagonal block and a corresponding symmetric triangular factorization algorithm for solving symmetric linear system Ax=b. The factorization algorithm is based on symmetric Gaussian elimination; The pivoting strategy involves searching two suitable columns in the trailing submatrix A k by rook method, interchanging the first one of them with column k, and then adding the second one multiplied by a scalar γ to column k. This strategy is similar to an earlier one proposed by Dax; Its comparisons required are still O(n 2 ) ∼ O(n 3 ), but the bound on elements of L is lower, and especially the growth factor is bounded by 3. The results from numerical experiments with both ill-conditioned and good-conditioned symmetric indefinite linear systems show that the new algorithm is competitive with the B–K algorithm, the BBK algorithm, and the LU factorization with partial pivoting.

A study of the sensitivity of sequence stacking strategies for the storage location assignment problem for out-bound containers in a maritime terminal

Recently, a new approach to solve the outbound container location problem motivated by the Shanghai maritime terminals was published. This approach addresses the problem by decomposing it into two stages. The first stage is a mathematical programming model and the second stage is a heuristic algorithm whose objective is to minimize the total reshuffle movements executed during the loading operation. That study reports that the diagonal stacking configuration provides the best performance. Conversely, this paper documents the results of a study to observe the performance of the various staking strategies under different conditions that can occur regularly in real ports. The parameters that are varied are the number of tiers in each stack, the number of container weight levels, and the permitted bay utilization. The results show that although the diagonal stacking strategy does provide the best performance under some conditions, it does not yield the best performance in other parameter combinations. The horizontal strategy is found to perform best for most of the parameter combinations considered in this study.

TYPOLOGY AND MARKET CONCENTRATION OF MEDIA CONGLOMERATE IN INDONESIA

The economic practices of media industry in Indonesia are inseparable from the pattern of oligopolistic market. This trend is seen from further of market media concentration, particularly market of advertising media in a number of media corporate groups. Media corporate groups apply practices of conglomeration in market control with horizontal, vertical, or diagonal integrated strategy. Criticism on these practices is often expressed, but there is no assessment based on the empirical evidence on the business behavior of media conglomeration. This paper explores the characteristics of media conglomerate by reconstructing the typology of media conglomeration introduced by Richard Bounce: Concentric Conglomerates and Diversified Conglomerates, and three models by Graham Murdock: Industrial Conglomerates, Services Conglomerates and Communications Conglomerates. Six typology models of conglomerate are formed, namely (1) Industrial-Concentric; (2) Industrial-Diversified; (3) Services-Concentric; (4) Services-Diversified; (5) Communications-Concentric; (6) Communications-Diversified. The economic performance of each conglomerate group regarding market concentration and market competition in constructing the market structure of media industry is studied based on the typologies. The study finds a new typology model of media conglomerate and manages to prove that national media conglomerate still dominates the media market in Indonesia.

Market Typology, Concentration, and Competition of National Media Conglomerate in Indonesia

The economic practices of media industry in Indonesia are inseparable from the pattern of oligopolistic market competition and control. This trend is seen from further centralized market control of media, particularly advertising media in a number of media corporate groups. Media corporate groups apply practices of conglomeration in market control with horizontal, vertical, or diagonal integrated strategy. Criticism on these practices is often expressed, but there is no assessment based on the empirical evidence on the business behavior of media conglomeration. This paper explores the characteristics of media conglomerate by reconstructing the typology of media conglomeration introduced by Richard Bounce: Concentric Conglomerates and Diversified Conglomerates, and three models by Graham Murdock: Industrial Conglomerates, Services Conglomerates and Communications Conglomerates. Six typology models of conglomerate are formed, namely (1) Industrial-Concentric; (2) Industrial-Diversified; (3) Services-Concentric; (4) Services-Diversified; (5) Communications-Concentric; (6) Communications-Diversified. The economic performance of each conglomerate group regarding market concentration and market competition in constructing the market structure of media industry is studied based on the typologies. The study finds a new typology model of media conglomerate and manages to prove that national media conglomerate still dominates the media market in Indonesia.

A finite crack with arbitrarily varied surface piezoelectricity

We study the contribution of arbitrarily varied surface piezoelectricity to the anti-plane deformation and in-plane electric fields of a hexagonal piezoelectric material containing a finite crack. The varied surface piezoelectricity is incorporated by using an extended version of the continuum-based surface/interface model of Gurtin and Murdoch. In our discussion, the surface properties, including the surface elastic stiffness, the surface piezoelectric modulus and the surface dielectric permittivity, are assumed to be varied arbitrarily along the crack surfaces. By using the Green’s function method, the original boundary value problem is reduced to a system of two coupled first-order Cauchy singular integro-differential equations. Through a diagonalization strategy, the coupled system is transformed into two independent singular integro-differential equations, each of which can be numerically solved by using the collocation method. Our results indicate that the variation of the surface electroelastic moduli exerts a significant influence on the crack opening displacement, the electric potential jump across the crack faces and on the strengths of the logarithmic singularity in stresses and electric displacements at the crack tips.

Global optimization based on bisection of rectangles, function values at diagonals, and a set of Lipschitz constants

We consider a global optimization problem for Lipschitz-continuous functions with an unknown Lipschitz constant. Our approach is based on the well-known DIRECT (DIviding RECTangles) algorithm and motivated by the diagonal partitioning strategy. One of the main advantages of the diagonal partitioning scheme is that the objective function is evaluated at two points at each hyper-rectangle and, therefore, more comprehensive information about the objective function is considered than using the central sampling strategy used in most DIRECT-type algorithms. In this paper, we introduce a new DIRECT-type algorithm, which we call BIRECT (BIsecting RECTangles). In this algorithm, a bisection is used instead of a trisection which is typical for diagonal-based and DIRECT-type algorithms. The bisection is preferable to the trisection because of the shapes of hyper-rectangles, but usual evaluation of the objective function at the center or at the endpoints of the diagonal are not favorable for bisection. In the proposed algorithm the objective function is evaluated at two points on the diagonal equidistant between themselves and the endpoints of a diagonal. This sampling strategy enables reuse of the sampling points in descendant hyper-rectangles. The developed algorithm gives very competitive numerical results compared to the DIRECT algorithm and its well know modifications.

A crack with surface effects in a piezoelectric material

We study the contribution of surface piezoelectricity to the anti-plane deformations of a hexagonal piezoelectric material weakened by a crack. The surface piezoelectricity is incorporated by using an extended version of the continuum-based surface/interface model of Gurtin and Murdoch. The original boundary value problem is finally reduced to a system of two coupled first-order Cauchy singular integro-differential equations by considering a distribution of line dislocations and electric-potential-dislocations on the crack. Through a diagonalization strategy, the coupled system can be transformed into two independent singular integro-differential equations, each of which contains only one single unknown function and can be numerically solved by the collocation method. Our solution demonstrates that the stresses, strains, electric displacements and electric displacements exhibit the logarithmic singularity at the crack tips. The obtained solution is further used to predict the size-dependent effective electroelastic properties of a piezoelectric solid containing multiple nanocracks with surface piezoelectricity within the framework of non-interaction approximation.

A REVIEW OF APPLICATION ELECTRICAL RESISTANCE TOMOGRAPHY FOR ROOTED HERB TREE DETECTION

This paper presents the measurement strategy of Electrical Resistance Tomography (ERT) for a system using underground investigation and comparison with other application such as conducting vessel pipe and concrete. Measurement of electrical strategy commonly used are adjacent strategy, opposite strategy, diagonal strategy and bounding conducting. This paper also discussed in measurement strategy for underground such as the Wenner-alpha configuration, Pole-Dipole array, cross bore-hole ERT and pseudo-section. This paper focuses on the principle and advantages measurement strategy for underground investigation and for other system such as conducting vessel pipe. The soil resistivity testing was described for related with rooted tree detection in soil.

Mitigating Estimation Risk in Asset Allocation: Diagonal Models Versus 1/N Diversification

AbstractRecent literature suggests that optimal asset‐allocation models struggle to consistently outperform the 1/N naïve diversification strategy, which highlights estimation‐risk concerns. We propose a dichotomous classification of asset‐allocation models based on which elements of the inverse covariance matrix that a model uses: diagonal only versus full matrix. We argue that parsimonious diagonal‐only strategies, which use limited information such as volatility or idiosyncratic volatility, are likely to offer a good tradeoff between incorporating limited information while mitigating estimation risk. Evaluating five sets of portfolios over 1926–2012, we find that 1/N is generally not optimal when compared with these diagonal strategies.

Mitigating Estimation Risk in Asset Allocation: Diagonal Models Versus 1/N Diversification

DeMiguel, Garlappi, and Uppal (DGU, 2009) evaluate 14 models of optimal asset allocation and find that none can consistently outperform the 1/N naive diversification strategy, which highlights estimation-risk concerns. Building from Stevens (1998), we provide a useful dichotomous classification of asset-allocation models based on which elements of the inverse covariance matrix that a model uses: diagonal-only vs. full-matrix. In DGU (2009), the competing active strategies all belong to the full-matrix class. We argue that parsimonious diagonal-only strategies, that use limited information such as volatility or idiosyncratic volatility, are likely to offer a good tradeoff between incorporating limited data information while mitigating estimation risk. Using five different data sets of disaggregate portfolio returns over the 1926-2012 period, we find that 1/N is generally not optimal when compared with these simple diagonal strategies.

Max-plus singular values

In this paper we prove a new characterization of the max-plus singular values of a max-plus matrix, as the max-plus eigenvalues of an associated max-plus matrix pencil. This new characterization allows us to compute max-plus singular values quickly and accurately. As well as capturing the asymptotic behavior of the singular values of classical matrices whose entries are exponentially parameterized we show experimentally that max-plus singular values give order of magnitude approximations to the classical singular values of parameter independent classical matrices.We also discuss Hungarian scaling, which is a diagonal scaling strategy for preprocessing classical linear systems. We show that Hungarian scaling can dramatically reduce the 2-norm condition number and that this action can be explained using our new theory for max-plus singular values.