Search Results (44)

This paper presents a hybrid indoor localization framework combining time difference of arrival (TDoA) measurements with a swarm intelligence optimization technique. To address the nonlinear optimization challenges in three-dimensional (3D) indoor localization via TDoA measurements, we systematically evaluate the artificial bee colony (ABC) algorithm and chimpanzee optimization algorithm (ChOA). Through comprehensive Monte Carlo simulations in a cubic 3D environment with eight beacons, our comparative analysis reveals that the ChOA achieves superior localization accuracy while maintaining computational efficiency. Building upon the ChOA framework, we introduce a multi-beacon fusion strategy incorporating a local outlier factor-based linear weighting mechanism to enhance robustness against measurement noise and improve localization accuracy. This approach integrates spatial density estimation with geometrically consistent weighting of distributed beacons, effectively filtering measurement outliers through adaptive sensor fusion. The experimental results show that the proposed algorithm exhibits excellent convergence performance under the condition of a low population size. Its anti-interference capability against Gaussian white noise is significantly improved compared with the baseline algorithms, and its anti-interference performance against multipath noise is consistent with that of the baseline algorithms. However, in terms of dealing with UWB device failures, the performance of the algorithm is slightly inferior. Meanwhile, the algorithm has relatively good time-lag performance and target-tracking performance. The study provides theoretical insights and practical guidelines for deploying reliable localization systems in complex indoor environments. Full article

This study explores analytical soliton solutions for the cubic–quintic time-fractional nonlinear non-paraxial pulse transmission model. This versatile model finds numerous uses in fiber optic communication, nonlinear optics, and optical signal processing. The strength of the quintic and cubic nonlinear components plays a crucial role in nonlinear processes, such as self-phase modulation, self-focusing, and wave combining. The fractional nonlinear Schrödinger equation (FNLSE) facilitates precise control over the dynamic properties of optical solitons. Exact and methodical solutions include those involving trigonometric functions, Jacobian elliptical functions (JEFs), and the transformation of JEFs into solitary wave (SW) solutions. This study reveals that various soliton solutions, such as periodic, rational, kink, and SW solitons, are identified using the complete discrimination polynomial methods (CDSPM). The concepts of chaos and bifurcation serve as the framework for investigating the system qualitatively. We explore various techniques for detecting chaos, including three-dimensional and two-dimensional graphs, time-series analysis, and Poincarè maps. A sensitivity analysis is performed utilizing a variety of initial conditions. Full article

The distribution of temperature-induced cracks in mass concrete structures is extensive and random, making it difficult for existing detection methods to accurately identify the specific location and initiation time of cracking. Therefore, there is an urgent need for an intelligent, precise, and efficient monitoring approach capable of acquiring real-time information on the evolution of the internal temperature field in concrete structures during their early-age curing process. A novel temperature-sensitive concrete system was developed by synchronously integrating distributed optical fibers with three-dimensional printed concrete (3DPC) to enable both temperature monitoring and signal transmission. To validate the effectiveness of the proposed method, experimental testing and numerical simulations were conducted on cubic 3D-printed fiber-reinforced concrete to analyze the temporal evolution of their internal temperature fields. The results show that, during the system calibration process, the temperature measured by the distributed temperature sensing (DTS) system was highly consistent with the environmental temperature curve, with fluctuations controlled within ±1 °C. In addition, the numerical simulation results closely aligned with the experimental data, with discrepancies maintained within 5%, demonstrating the feasibility of utilizing 3D printing technology to impart temperature sensitivity to concrete materials. This integrated approach offers a promising pathway for advancing smart concrete technology, providing an effective solution for accurate sensing and control of internal temperatures in concrete structures. It holds substantial potential for practical applications in civil engineering projects. Full article

The automated and precise classification of lung and colon cancer from histopathological photos continues to pose a significant challenge in medical diagnosis, as current computer-aided diagnosis (CAD) systems are frequently constrained by their dependence on singular deep learning architectures, elevated computational complexity, and their ineffectiveness in utilising multiscale features. To this end, the present research introduces a CAD system that integrates several lightweight convolutional neural networks (CNNs) with dual-layer feature extraction and feature selection to overcome the aforementioned constraints. Initially, it extracts deep attributes from two separate layers (pooling and fully connected) of three pre-trained CNNs (MobileNet, ResNet-18, and EfficientNetB0). Second, the system uses the benefits of canonical correlation analysis for dimensionality reduction in pooling layer attributes to reduce complexity. In addition, it integrates the dual-layer features to encapsulate both high- and low-level representations. Finally, to benefit from multiple deep network architectures while reducing classification complexity, the proposed CAD merges dual deep layer variables of the three CNNs and then applies the analysis of variance (ANOVA) and Chi-Squared for the selection of the most discriminative features from the integrated CNN architectures. The CAD is assessed on the LC25000 dataset leveraging eight distinct classifiers, encompassing various Support Vector Machine (SVM) variants, Decision Trees, Linear Discriminant Analysis, and k-nearest neighbours. The experimental results exhibited outstanding performance, attaining 99.8% classification accuracy with cubic SVM classifiers employing merely 50 ANOVA-selected features, exceeding the performance of individual CNNs while markedly diminishing computational complexity. The framework’s capacity to sustain exceptional accuracy with a limited feature set renders it especially advantageous for clinical applications where diagnostic precision and efficiency are critical. These findings confirm the efficacy of the multi-CNN, multi-layer methodology in enhancing cancer classification precision while mitigating the computational constraints of current systems. Full article

The work examines a seven-parameter, three-dimensional, autonomous, cubic nonlinear differential system. This system extends and generalizes the previously studied quadratic nonlinear Hopf–Langford-type systems. First, by introducing cylindrical coordinates in its phase space, we show that the regarded system can be reduced to a two-dimensional Liénard system, which corresponds to a second-order Liénard equation. Then, we present (in explicit form) polynomial first and second integrals of Liénard systems of the considered type identifying those values of their parameters for which these integrals exist. It is also proved that a generic Liénard equation is factorizable if and only if the corresponding Liénard system admits a second integral of a special form. It is established that each Liénard system corresponding to a Hopf–Langford system of the considered type admits such a second integral, and hence, the respective Liénard equation is factorizable. Full article

According to the World Health Organization (WHO), floods are one of the most important natural disasters in the world, resulting in the severe loss of human lives and intense destruction of infrastructure. The frequent floods in recent decades have caused most parts of Iran to be affected by periodic and destructive floods. Consequently, the casualties and financial losses of floods have increased significantly. The present study aims to investigate redesigning the fuse plug, emergency overflow, and flood system at Ramshir Dam, Iran. In this regard, using a two-dimensional mathematical model, floods with a return period of 10 and 100 years with different scenarios have been investigated. Four scenarios were analyzed, including the current situation, flood channel dredging scenario, flood channel overhaul scenario, and flood channel overhaul scenario with reservoir dredging. The results show the following: (1) The flood channel in its current state cannot even discharge flows lower than the design, i.e., 1400 m³/s, and the flow overflows from the embankments on its sides. (2) Also, the reservoir dredging prevents the failure of the second fuse plug in the 100-year return period (flow rate 4370 m³/s). (3) Discharge more than 2400 m³/s cubic meters led to the activation of the first fuse plug. (4) The present research findings are of particular and essential importance in flood management. (5) The results of this research were based on the rehabilitation and simulation of the diversion dam facilities in the control and conveyance of flood and on three factors of spillway, flood channel, and flood plain, and the correct function of the fuse plug was reviewed. Full article

In this manuscript, we investigate the (2+1)-dimensional variable-coefficient Korteweg–de Vries (KdV) system with cubic–quintic nonlinearity. Based on different methods, we also obtain different solutions. Under the help of the wave ansatz method, we obtain the exact soliton solutions to the variable-coefficient KdV system, such as the dark and bright soliton solutions, Tangent function solution, Secant function solution, and Cosine function solution. In addition, we also obtain the interactions between dark and bright soliton solutions, between rogue and soliton solutions, and between lump and soliton solutions by using the bilinear method. For these solutions, we also give their three dimensional plots and density plots. This model is of great significance in fluid. It is worth mentioning that the research results of our paper is different from the existing research: we not only use different methods to study the solutions to the variable-coefficient KdV system, but also use different values of parameter t to study the changes in solutions. The results of this study will contribute to the understanding of nonlinear wave structures of the higher dimensional KdV systems. Full article

We focus on higher-order matched asymptotic expansions of a one-dimensional classical Poisson–Nernst–Planck system for ionic flow through membrane channels with two oppositely charged ion species under relaxed electroneutrality boundary conditions. Of particular interest are the current–voltage (I–V) relations, which are used to characterize the two most relevant biological properties of ion channels—permeation and selectivity—experimentally. Our result shows that, up to the second order in $\epsilon =\sqrt{\lambda /r}$, where $\lambda$ is the Debye length and r is the characteristic radius of the channel, the cubic I–V relation has either three distinct real roots or a unique real root with a multiplicity of three, which sensitively depends on the boundary layers because of the relaxation of the electroneutrality boundary conditions. This indicates more rich dynamics of ionic flows under our more realistic setups and provides a better understanding of the mechanism of ionic flows through membrane channels. Full article

Three-dimensional cancer cell cultures have been a valuable research model for developing new drug targets in the preclinical stage. However, there are still limitations to these in vitro models. Scaffold-based systems offer a promising approach to overcoming these challenges in cancer research. In this study, we show that two-photon polymerization (TPP)-assisted printing of scaffolds enhances 3D tumor cell culture formation without additional modifications. TPP is a perfect fit for this task, as it is an advanced 3D-printing technique combining a μm-level resolution with complete freedom in the design of the final structure. Additionally, it can use a wide array of materials, including biocompatible ones. We exploit these capabilities to fabricate scaffolds from two different biocompatible materials—PEGDA and OrmoClear. Cubic spheroid scaffolds with a more complex architecture were produced and tested. The biological evaluation showed that the human ovarian cancer cell lines SKOV3 and A2780 formed 3D cultures on printed scaffolds without a preference for the material. The gene expression evaluation showed that the A2780 cell line exhibited substantial changes in CDH1, CDH2, TWIST, COL1A1, and SMAD3 gene expression, while the SKOV3 cell line had slight changes in said gene expression. Our findings show how the scaffold architecture design impacts tumor cell culture 3D spheroid formation, especially for the A2780 cancer cell line. Full article

The precise mapping of magnetic fields emitted by various objects holds critical importance in the fabrication of industrial products. To meet this requirement, this study introduces an advanced magnetic detection device boasting high spatial resolution. The device’s sensor, an array comprising 256 unpackaged gallium arsenide (GaAs) Hall elements arranged in a 16 × 16 matrix, spans an effective area of 19.2 mm × 19.2 mm. The design maintains a 1.2 mm separation between adjacent elements. For enhanced resolution, the probe scans the sample via a motorized rail system capable of executing specialized movement patterns. A support structure incorporated into the probe minimizes the measurement distance to below 0.5 mm, thereby amplifying the magnetic signal and mitigating errors from nonparallel probe–sample alignment. The accompanying interactive software utilizes cubic spline interpolation to transform magnetic readings into detailed two- and three-dimensional magnetic field distribution maps, signifying field strength and polarity through variations in color intensity and amplitude sign. The device’s efficacy in accurately mapping surface magnetic field distributions of magnetic and magnetized materials was corroborated through tests on three distinct samples: a neodymium–iron–boron magnet, the circular magnetic array from a smartphone, and a magnetized 430 steel plate. These tests, focused on imaging quality and magnetic field characterization, underscore the device’s proficiency in nondestructive magnetic field analysis. Full article

First, a recently developed eigenfunction expansion technique, based in part on the separation of the thickness variable and partly utilizing a modified Frobenius-type series expansion technique in conjunction with the Eshelby–Stroh formalism, is employed to derive three-dimensional singular stress fields in the vicinity of the front of an interfacial crack weakening an infinite bicrystalline superlattice plate, made of orthorhombic (cubic, hexagonal, and tetragonal serving as special cases) phases of finite thickness and subjected to the far-field extension/bending, in-plane shear/twisting, and anti-plane shear loadings, distributed through the thickness. Crack-face boundary and interface contact conditions as well as those that are prescribed on the top and bottom surfaces of the bicrystalline superlattice plate are exactly satisfied. It also extends a recently developed concept of the lattice crack deflection (LCD) barrier to a superlattice, christened superlattice crack deflection (SCD) energy barrier for studying interfacial crack path instability, which can explain crack deflection from a difficult interface to an easier neighboring cleavage system. Additionally, the relationships of the nature (easy/easy, easy/difficult, or difficult/difficult) interfacial cleavage systems based on the present solutions with the structural chemistry aspects of the component phases (such as orthorhombic, tetragonal, hexagonal, as well as FCC (face-centered cubic) transition metals and perovskites) of the superlattice are also investigated. Finally, results pertaining to the through-thickness variations in mode I/II/III stress intensity factors and energy release rates for symmetric hyperbolic sine-distributed loads and their skew-symmetric counterparts that also satisfy the boundary conditions on the top and bottom surfaces of the bicrystalline superlattice plate under investigation also form an important part of the present investigation. Full article

By the method of molecular dynamics, computer simulation of the processes of isobaric cooling of argon particle systems under initial conditions with a temperature of 150 K at pressure values from 0.1 to 4 MPa to a temperature of 40 K with cooling rates of 10⁸, 10⁹, 10¹⁰, 10¹¹ and 10¹² K/s was performed. As a result of a computer experiment, coordinate arrays of particles were obtained, which were subjected to the procedure of three-dimensional Voronoi partitioning to identify and calculate the number of elementary cells of the crystal structure. Analysis of the structure of argon solid phases formed during isobaric cooling allowed us to deduce an estimated pattern between the concentration of FCC (face-centered cubic) cells in solid argon and the cooling rate from the liquid state. The evaluation of the orientation of the axes of translation of crystal cells in the array of particle coordinates made it possible to classify the solid phases formed as a result of cooling as single crystals, glassy media with the inclusion of clusters and single cells of FCC structures. It was revealed that during isobaric cooling at a rate not exceeding 10⁸ K/s, argon completely crystallizes, at isobaric cooling rates of 10⁹–10¹⁰ K/s, the union of elementary cells of the crystal structure into clusters is observed in glassy argon, and at rates of 10¹¹ K/s and higher at pressures of 1 MPa and lower, solid vitreous phases of argon are formed in which no crystal structure cells are detected. Full article

A new nanocomposite system based on Fe₃O₄ nanoparticles confined in three-dimensional (3D) dual-mode cubic porous carbon is developed using the nanocasting and wet-impregnation methods to assess its performance as an anode for lithium-ion batteries. Several Fe₃O₄ precursor concentrations are chosen to optimize and determine the best-performing nanocomposite composition. The cubic mesoporous carbon CMK-9 offers a better ability for the Fe₃O₄ nanoparticles to be accommodated inside the mesopores, efficiently buffering the variation in volume and equally enhancing electrode/electrolyte contact for rapid charge and mass transfer. Among the prepared nanocomposites, the Fe₃O₄(13)@C9 anode delivers an excellent reversible discharge capacity of 1222 mA h g⁻¹ after 150 cycles at a current rate of 100 mA g⁻¹, with a capacity retention of 96.8% compared to the fourth cycle (1262 mA h g⁻¹). At a higher current rate of 1000 mA g⁻¹, the nanocomposite anode offers a superior discharge capacity of 636 mA h g⁻¹ beyond 300 cycles. The present study reveals the use of a 3D mesoporous carbon material as a scaffold for anchoring Fe₃O₄ nanoparticles with impressive potential as an anode for new-generation lithium-ion batteries. Full article

This paper proposes a stereo matching method enhanced by object detection and instance segmentation results obtained through the use of a deep convolutional neural network. Then, this method is applied to generate a picking plan to solve bin picking problems, that is, to automatically pick up objects with random poses in a stack using a robotic arm. The system configuration and bin picking process flow are suggested using the proposed method, and it is applied to bin picking problems, especially those involving tiny cubic workpieces. The picking plan is generated by applying the Harris corner detection algorithm to the point cloud in the generated three-dimensional map. In the experiments, two kinds of stacks consisting of cubic workpieces with an edge length of 10 mm or 5 mm are tested for bin picking. In the first bin picking problem, all workpieces are successfully picked up, whereas in the second, the depths of the workpieces are obtained, but the instance segmentation process is not completed. In future work, not only cubic workpieces but also other arbitrarily shaped workpieces should be recognized in various types of bin picking problems. Full article

The main purpose of this paper is to study the dynamics and embedded solitons of stochastic quadratic and cubic nonlinear susceptibilities in the Itô sense, which can further help researchers understand the propagation of soliton nonlinear systems. Firstly, a two-dimensional dynamics system and its perturbation system are obtained by using a traveling wave transformation. Secondly, the phase portraits of the two-dimensional dynamics system are plotted. Furthermore, the chaotic behavior, two-dimensional phase portraits, three-dimensional phase portraits and sensitivity of the perturbation system are analyzed via Maple software. Finally, the embedded solitons of stochastic quadratic and cubic nonlinear susceptibilities are obtained. Moreover, three-dimensional and two-dimensional solitons of stochastic quadratic and cubic nonlinear susceptibilities are plotted. Full article