Localized Solutions Research Articles

A study of (2+1)-dimensional variable coefficients equation: Its oceanic solitons and localized wave solutions

In this work, shallow ocean-wave soliton, breather, and lump wave solutions, as well as the characteristics of interaction between the soliton and lump wave in a multi-dimensional nonlinear integrable equation with time-variable coefficients, are investigated. The Painlevé analysis is used to verify the integrability of this model. Based on the bilinear form of this model, we use the simplified Hirota's method obtained from the perturbation approach and various auxiliary functions to construct the aforementioned solutions. Besides, the interaction between the soliton and lump wave solutions is also examined. In addition, by imposing specific constraint conditions on the N-soliton solutions, we further derive higher-order breather solutions. To show the physical characteristics of this model, several graphical representations of the discovered solutions are established. These graphs show that the time-variable coefficients result in a variety of novel dynamic behaviors that differ significantly from those for integrable equations with constant coefficients. The acquired results are useful for the study of shallow water waves in fluid dynamics, marine engineering, nonlinear sciences, and ocean physics.

Leveraging NLP and Deep Learning for Phishing Detection and Anti-Phishing Training in Nigeria: A Focus on Localized Tactics and Cultural Factors

Phishing attacks pose a significant cybersecurity threat globally, with developing nations like Nigeria facing unique challenges due to localized tactics and cultural factors. This paper presents a novel approach to phishing mitigation in Nigeria, leveraging Natural Language Processing (NLP) and Deep Learning techniques to enhance both automated detection and user training. We analyze a corpus of Nigeria-specific phishing attempts, identifying linguistic patterns and cultural references commonly exploited by attackers. Using this data, we train a deep learning model capable of detecting localized phishing content with high accuracy. Building on this technical foundation, we design a dynamic anti-phishing training program that adapts to individual user behavior and local phishing trends. A Hybrid Deep learning modelsrecurrent neural networks (RNNs) and transformer-based models (BERT), was trained on large datasets of phishing and legitimate samples to learn discriminate features and classify new instances. Our results demonstrate significant improvements in both automated phishing detection rates and user resilience to social engineering tactics. The model achieved high precision (0.89), recall (0.94), and F1-scores (0.92, 1.00).This research contributes to the field by showcasing the potential of combining advanced AI techniques with culturally informed strategies to create more effective, localized cybersecurity solutions.

DYNAMICS OF OPTICAL WAVE PROFILES TO THE FRACTIONAL THREE-COMPONENT COUPLED NONLINEAR SCHRÖDINGER EQUATION

This paper explores the truncated [Formula: see text]-fractional three-component coupled nonlinear Schrödinger (tc-CNLS) equation, that regulates the behavior of optical pulses in optical fibers. These equations are utilized in various scientific and engineering fields, including nonlinear fiber optics, electromagnetic field waves, and signal processing through optical fibers. The study of multi-component NLS equations has gained significant attention due to their ability to elucidate various complex physical phenomena and exhibit more dynamic structures of localized wave solutions. The freshly invented integration tools, known as the fractional modified Sardar subequation method (MSSEM) and fractional enhanced modified extended tanh-expansion method (eMETEM), are employed to ensure the solutions. The study focuses on extracting various types of optical solitons, including bright, dark, singular, bright-dark, complex, and combined solitons. Optical soliton propagation in optical fibers is currently a subject of great interest due to the multiple prospects for ultrafast signal routing systems and short light pulses in communications. In nonlinear dispersive media, optical solitons are stretched electromagnetic waves that maintain their intensity due to a balance between the effects of dispersion and nonlinearity. Furthermore, hyperbolic, periodic and exponential solutions are generated. The utilized methodology is effective in explaining fractional nonlinear partial differential equations (FNLPDEs) as it offers pre-existing solutions and additionally derives novel exact solutions by mixing outcomes from various procedures. Furthermore, we plot the visualizations of solutions by plotting 3D, 2D, and contour graphs with the corresponding parameter values. The findings of this paper can improve the understanding of the nonlinear dynamical behavior of a specific system and demonstrate the efficacy of the methodology used. We anticipate that our study will provide substantial benefits to a considerable group of engineering model experts. The findings demonstrate the efficacy, efficiency, and applicability of the computational method employed, particularly in dealing with intricate systems.

UWB time of flight-based indoor IoT localisation solution with deep learning optimised by meta-heuristics

UWB time of flight-based indoor IoT localisation solution with deep learning optimised by meta-heuristics

Physically Admissible and Inadmissible Exact Localized Solutions in Problems of Nonlinear Wave Dynamics of Cylindrical Shells

It is shown that, when studying nonlinear longitudinal deformation waves in cylindrical shells, it is possible to obtain physically admissible solitary wave solutions using refined shell models. In the article, a physically admissible exact localized solution based on the Flügge – Lurie – Byrne model is constructed. An analysis of the influence of the external nonlinear elastic medium on the exact solutions obtained is carried out. It is established that the use of quadratic and cubic nonlinear deformation laws leads to nonintegrable equations with exact soliton-like solutions. However, the amplitudes of the exact solutions exceed the values of permissible displacements corresponding to the maximum points on the curves of the deformation laws of the external medium, which leads to the physical inadmissibility of these solutions.

UWB Time of Flight based indoor IoT localization solution with Deep Learning optimized by meta-heuristics

UWB Time of Flight based indoor IoT localization solution with Deep Learning optimized by meta-heuristics

Attractive Impurity as a Generator of Wobbling Kinks and Breathers in the $\varphi^{4}$ Model

The $\varphi^{4}$ theory is widely used in many areas of physics, from cosmology and elementary particle physics to biophysics and condensed matter theory. However, in the $\varphi^{4}$ model, there are no spatially localized solutions in the form of breathers. Topological defects, or kinks, in this theory describe stable, solitary wave excitations. In practice, these excitations, as they propagate, necessarily interact with impurities or imperfections in the on-site potential. In this work, with the help of numerical calculations using the method of lines, the interaction of the kink in the $\varphi^{4}$ model with extended impurities is considered. The case of an attractive rectangular impurity is analyzed. It is found that after the kink-impurity interaction, an internal mode with frequency $\sqrt{\frac{3}{2}}$ is excited on the kink and it becomes a wobbling kink. It is shown that with the help of kink-impurity interaction, an extended rectangular attracting impurity, as well as a point impurity, can be used as a generator for excitation of long-lived high-amplitude localized breather waves. The structure of the excited wobbling breather (or wobbler), which consists

Localization of Nash-type equilibria for systems with partial variational structure

In this paper, we aim to generalize an existing result by obtaining localized solutions within bounded convex sets, while also relaxing specific initial assumptions. To achieve this, we employ an iterative scheme that combines a fixed-point argument based on the Minty-Browder Theorem with a modified version of the Ekeland variational principle for bounded sets. An application to a system of second-order differential equations with Dirichlet boundary conditions is presented.

Multisoliton interactions approximating the dynamics of breather solutions

AbstractNowadays, breather solutions are generally accepted models of rogue waves. However, breathers exist on a finite background and therefore are not localized, while wavefields in nature can generally be considered as localized due to the limited sizes of physical domain. Hence, the theory of rogue waves needs to be supplemented with localized solutions, which evolve locally as breathers. In this paper, we present a universal method for constructing such solutions from exact multisoliton solutions, which consists in replacing the plane wave in the dressing construction of the breathers with a specific exact N‐soliton solution converging asymptotically to the plane wave at large number of solitons N. On the example of the Peregrine, Akhmediev, Kuznetsov–Ma, and Tajiri–Watanabe breathers, we show that constructed with our method multisoliton solutions, being localized in space with characteristic width proportional to N, are practically indistinguishable from the breathers in a wide region of space and time at large N. Our method makes it possible to build solitonic models with the same dynamical properties for the higher order rational and super‐regular breathers, and can be applied to general multibreather solutions, breathers on a nontrivial background (e.g., cnoidal waves), and other integrable systems. The constructed multisoliton solutions can also be generalized to capture the spontaneous emergence of rogue waves through the spontaneous synchronization of soliton norming constants, though finding these synchronization conditions represents a challenging problem for future studies.

A novel cell phone localization solution for trapped victims based on compressed RSSI fluctuation range and PSO-BP neural network

With the frequent occurrence of global earthquake disasters in recent years, quickly and accurately locating trapped people is the key to reducing the mortality rate of earthquake disasters. This paper proposes a cell phone localization solution for trapped people that can be rapidly deployed after an earthquake. This solution locates the buried cell phone by collecting its received WiFi signal strength indication (RSSI) data. Reducing the fluctuation of RSSI value is crucial to accurately locating the buried cell phone. We filter RSSI data outliers by hybrid filtering and propose a fluctuation range compression factor Q to reduce the fluctuation range of RSSI data. In order to adapt to the compressed RSSI data fluctuation range, the processed RSSI data were grouped. The grouped data are then imported into the PSO-BP neural network training to build the ranging model. So that there is a mapping relationship between RSSI data and trapped distance. The established ranging model is denoted as the HFQBP ranging model. After establishing the ranging model, the cell phone is localized by an Optimized Multilateration (OM) algorithm. For simplicity, this algorithm is named HFQBP-OM. In the experimental phase, we combined the method proposed in this paper with other methods, resulting in three different localization algorithms: HFQBP-WSC, PL-OM, and PL-WSC. And compared with the algorithms in this paper. The results indicate that the algorithm HFQBP-OM proposed in this paper has improved the total average accuracy of the nine localization points by 34.7%, 54.8%, and 58.9% compared to HFQBP-WSC, PL-OM, and PL-WSC, respectively. The HFQBP-OM algorithm has higher accuracy and stability. Also, it should be noted that the localization solution proposed in this paper uses smartphones connected to WiFi probes to collect RSSI data of the WiFi signal of the buried cell phone. Use a laptop computer to solve the localization coordinates. Smartphones and laptops are so popular that WiFi probes are the only special equipment needed. WiFi probe is inexpensive. It reduces the difficulty of implementing the localization solution in this paper and increases the generalizability of the solution.

Various types of discrete exact localized wave solutions and dynamical analysis for the discrete complex modified Korteweg-de Vries equation

Under consideration is the second-order integrable discretization of complex modified Korteweg-de Vries (mKdV) equation which is regarded as the discrete counterpart of the mKdV equation having an essential role in describing the propagation behavior of water waves and acoustic waves in nonlinear media. First of all, based on the known linear spectral problem, the discrete generalized (n,N−n)-fold Darboux transformation is constructed to derive various types of discrete exact localized wave solutions, including soliton and semi-rational soliton solutions on vanishing background, breather, rogue wave and hybrid interaction solutions on plane wave background, and rational soliton solution on constant background, and the relevant evolution structures are studied graphically. Secondly, the asymptotic analysis is used to discuss the elastic interaction for two-soliton solutions and limit states for rational soliton solutions. Finally, the numerical simulation is utilized to investigate the dynamical behavior and propagation stability of some exact solutions. The findings presented in this paper may contribute to explaining physical phenomena described by the mKdV equation.

Perception and Navigation in Autonomous Systems in the Era of Learning: A Survey.

Autonomous systems possess the features of inferring their own state, understanding their surroundings, and performing autonomous navigation. With the applications of learning systems, like deep learning and reinforcement learning, the visual-based self-state estimation, environment perception, and navigation capabilities of autonomous systems have been efficiently addressed, and many new learning-based algorithms have surfaced with respect to autonomous visual perception and navigation. In this review, we focus on the applications of learning-based monocular approaches in ego-motion perception, environment perception, and navigation in autonomous systems, which is different from previous reviews that discussed traditional methods. First, we delineate the shortcomings of existing classical visual simultaneous localization and mapping (vSLAM) solutions, which demonstrate the necessity to integrate deep learning techniques. Second, we review the visual-based environmental perception and understanding methods based on deep learning, including deep learning-based monocular depth estimation, monocular ego-motion prediction, image enhancement, object detection, semantic segmentation, and their combinations with traditional vSLAM frameworks. Then, we focus on the visual navigation based on learning systems, mainly including reinforcement learning and deep reinforcement learning. Finally, we examine several challenges and promising directions discussed and concluded in related research of learning systems in the era of computer science and robotics.

Optimal planning and configuration of adiabatic-compressed air energy storage for urban buildings application: Techno-economic and environmental assessment

As urbanization and demand for energy increase, the importance of localized renewable energy resources and energy storage system solutions becomes more prominent. Adiabatic-compressed air energy storage (A-CAES) has been identified as a promising option, but its effectiveness in decentralized applications is not widely concerned. This study aims to plan and design a decentralized A-CAES system to enhance its significance within urban building infrastructure. The focus is on the optimal design of a decentralized A-CAES system for urban building utilization through a comprehensive analysis of its thermodynamic, techno-economic, and environmental aspects. A sizing-designing approach inducing simulation and optimization is proposed to customize the A-CAES system according to the specific application requirement. To do so, this study investigates several energy management operation strategies (EMOS) toward different potential applications of decentralized A-CAES to maximize the system's value and adaptability during the project's lifetime. Multiple scenarios concerning managing solar PV-surplus power are proposed to investigate the overall performance of the proposed model. Additionally, a sensitivity analysis (post-optimization) is conducted to ensure the model's applicability across different case studies. The results demonstrate that an energy cost saving in the range of 0.015–0.021 $/kWh is achieved for the optimal hybrid system in which the A-CAES system is planned for solar photovoltaic (PV) integration and seasonal load shifting, leading to shaving the grid peak demand. Adopting such an A-CAES-PV hybrid system allows for achieving a 52 % electrical load management ratio and 65 % carbon emission reduction compared to the primary power system (grid). Furthermore, under the worst-case scenario (zero selling back), such an optimal hybrid energy system (HES) achieves a PV self-consumption rate of around 92 % and a payback time of 15.5 years. This analysis provides useful insights for policymakers, building owners, and energy planners interested in implementing sustainable and energy-efficient solutions, especially in the feasibility study phase.

Exploration of interactional phenomena and multi‐wave solutions of the fractional‐order dual‐mode nonlinear Schrödinger equation

This work concerns the fractional‐order dual‐mode nonlinear Schrödinger equation (FDMNLSE), which portrays the augmentation or absorption of dual waves. This model dissects the concurrent generation of two characteristic waves dealing with dual modes and introduces three physical parameters: nonlinearity, phase velocity, and dispersive factor. In the context of photonics, NLSE models the propagation of soliton pulses over intercontinental distances. Throughout this work, the fractional derivative is given in terms of time and space conformable sense. We analyze the multi‐waves method, homoclinic breather approach, and interactional solution with the double ‐functions procedure, and their applications for this equation are obtained using logarithmic transformation. The multi‐wave method is a well‐known phenomenon in nonlinear science that describes the interaction of three waves that satisfy certain resonance conditions. A breather wave is a localized and oscillatory solution that maintains its shape over time. Finally, we will discuss the dynamics of our newly obtained solutions with the help of graphs by assigning appropriate values to the parameters. The proposed methods are straight and aggressive, so the approved form can be extended for more nonlinear models. The findings are exceptional in comparison to previous findings in the literature. These outcomes may have significance for additional investigation of such frameworks to handle the nonlinear issues in applied sciences. The obtained results help us understand fluid propagation and incompressible fluids.

Transformation- and twinning-induced plasticity in phase-separated bcc Nb-Zr alloys: an atomistic study

Several high-temperature body-centered cubic (bcc) structural materials such as Nb-, Zr- and Ti-based alloys undergo phase separation, which is a second-order phase transformation, whereby the host lattice decomposes into distinct bcc domains with different compositions. Using atomistic simulations, we studied the high-strain-rate response of bcc-forming Nb–xZr (x = 0, 25, 50 at.%) alloys. To induce phase separation in our starter alloy, we first employed hybrid Monte Carlo/Molecular Dynamics simulations in single crystals of Nb–xZr at 1000 K. Subsequently, these crystals were deformed along different crystallographic orientations (⟨001⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 001\\rangle$$\\end{document}, ⟨110⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 110\\rangle$$\\end{document} and ⟨111⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 111\\rangle$$\\end{document}) at a strain rate of 10+8s-1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$10^{+8} s^{-1}$$\\end{document}, to investigate orientation dependent mechanical response. The phase-separated Nb–xZr microstructures exhibited distinct bcc domains enriched in either Zr or Nb. Notably, Nb-50 at.%Zr contained coarser Zr-domains compared to Nb-25 at.%Zr. The Zr-rich domains acted as “soft” inclusions, resulting in reduced peak strengths in the following order: pure Nb (Nb-0 at.%Zr) > Nb-25 at.%Zr > Nb-50 at.%Zr. This implies that phase separation causes softening in Nb–xZr. We also discovered two deformation pathways that depended on the crystallographic orientation: (i) For deformation along ⟨110⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 110\\rangle$$\\end{document} and ⟨111⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 111\\rangle$$\\end{document} directions: Elastic deformation was followed by dislocation plasticity on {110}⟨111⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\{110\\}\\langle 111\\rangle$$\\end{document} slip systems; and (ii) For deformation along ⟨001⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 001\\rangle$$\\end{document} direction: Elastic deformation was followed by the formation of a volumetric fcc structure, twinning on {112}⟨111⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 111\\rangle$$\\end{document} system, and the formation fcc-phase at the twin/matrix interfacial regions. This was ultimately accompanied by dislocation plasticity on {110}⟨111⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\{110\\}\\langle 111\\rangle$$\\end{document} slip system. The bcc→\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\rightarrow$$\\end{document}fcc displacive transformation facilitated {112}⟨111⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 111\\rangle$$\\end{document} twinning when Nb–xZr was deformed along ⟨001⟩\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\langle 001\\rangle$$\\end{document}. Our investigation shows that softening of bcc alloys can result from a coupling of mechanisms involving local solute segregation, displacive phase transformation and twinning occurring across multiple slip planes.

Net Zero Corridors: A Case Study Approach from Perth, Australia to Decarbonize Urban Power and Transport

The transition to net zero cities is a pivotal challenge in the face of climate change. This research introduces a novel methodology termed "Net Zero Corridors," which emphasizes a bottom-up approach to decarbonize urban power and transport systems. By focusing on urban corridors, this method integrates distributed power systems with urban transport, offering a localized solution to the broader challenge of urban decarbonization. Drawing from urban fabric theory and urban metabolism data, the study provides insights into the application of various renewable technologies in diverse urban settings, particularly in automobile-dominated cities like Perth, Australia. The net zero city agenda is gathering momentum but faces the issues of transition using either top-down large-scale technologies or bottom-up local-scale technologies that make the most out of the small-scale niches that have been created around renewables. This paper seeks to show how a bottom-up process can be used to start a more effective local scale approach using net zero corridors that can enable more net zero precincts with distributed power systems and at the same time integrate and decarbonize transport systems. Data on Perth are collected and processed to show the economic viability of such net zero projects though they are not yet linked to good transit systems. The net zero corridor concept is demonstrated and shows how to enable a series of net zero precincts that create large steps in removing fossil fuels. These corridor precincts can spread into surrounding suburbs through expanding the local microgrids and their local governance embracing more and more of the city. The net zero corridor concept can be used to transition to net zero cities using bottom-up approaches that link the transformation of power systems and the transformation of transport systems.

RETRACTED:Optimum planning of energy hub with participation in electricity market and heat markets and application of integrated load response program with improved particle swarm algorithm

The drive for improved energy efficiency and flexibility has birthed an innovative solution: an energy hub. This hub operates in sync with natural gas and electricity grids, integrating batteries and thermal storage to optimize renewable energy use, reduce costs, and bolster network stability. In addressing these objectives, a mathematical optimization model for energy hub operation is developed in this paper. This model captures the intricate interplays between electricity and natural gas networks, accounting for the intricacies posed by uncertainties and variations in renewable energy sources and demand profiles. Also, this paper uniquely delves into the integration of load response programs, an approach geared towards amplifying the energy hub system's flexibility and reliability. Through these programs, subscribers gain the agency to calibrate their energy consumption based on real-time pricing signals and incentives dispensed by the energy hub. The simulation findings serve as a compelling testament to the efficacy of the proposed system. Operating costs witness a substantial reduction, the adoption of renewable energy sources is markedly heightened, and the stability and reliability of the upstream energy networks are tangibly ameliorated. The integration of load response programs emerges as a particularly effective strategy in mitigating peak demand and augmenting the system's overall energy efficiency. Underpinning the entirety of this innovative solution is the transformation of the challenges into an optimization problem. This catalyzes the employment of a newly developed particle community algorithm, custom-tailored to surmount the challenges of local optima. This algorithm inherently bolsters the system's search capabilities, minimizing the risk of entrapment within localized solutions. Ultimately, the proposed energy hub system encapsulates a promising trajectory toward the realization of a sustainable and adaptable energy landscape. By seamlessly integrating diverse energy sources and storage systems, augmenting energy flexibility and efficiency, and aligning with broader energy transition and decarbonization goals, this solution presents a formidable contender. The simulation outcomes underscore its potential by showcasing a substantial 4.57 % reduction in the cost of procuring energy from the upstream electrical network.

MagLoc-AR: Magnetic-based Localization for Visual-free Augmented Reality in Large-scale Indoor Environments.

Accurate localization of a display device is essential for AR in large-scale environments. Visual-based localization is the most commonly used solution, but poses privacy risks, suffers from robustness issues and consumes high power. Wireless signal-based localization is a potential visual-free solution, but its accuracy is not enough for AR. In this paper, we present MagLoc-AR, a novel visual-free localization solution that achieves sufficient accuracy for some AR applications (e.g., AR navigation) in large-scale indoor environments. We exploit the location-dependent magnetic field interference that is ubiquitous indoors as a localization signal. Our method requires only a consumer-grade 9-axis IMU, with the gyroscope and acceleration measurements used to recover the motion trajectory, and the magnetic measurements used to register the trajectory to the global map. To meet the accuracy requirement of AR, we propose a mapping method to reconstruct a globally consistent magnetic field of the environment, and a localization method fusing the biased magnetic measurements with the network-predicted motion to improve localization accuracy. In addition, we provide the first dataset for both visual-based and geomagnetic-based localization in large-scale indoor environments. Evaluations on the dataset demonstrate that our proposed method is sufficiently accurate for AR navigation and has advantages over the visual-based methods in terms of power consumption and robustness. Project page: https://github.com/zju3dv/MagLoc-AR/.

Combined RF-Based Drone Detection and Classification

Abstract: Despite various positive uses, drones are also utilised for illegal purposes like as drug trafficking, weapon smuggling, and posing dangers to security-sensitive locations such as airports and nuclear power plants. Existing drone localisation and neutralisation solutions are predicated on the drone having previously been discovered and categorised. Despite significant progress in the sensor sector over the last decade, no viable drone detection and classification approach has been suggested in the literature. The frequency signature of the sent signal is used in this research to identify and classify drones using radio frequency (RF). Using commercial drones, we built an unique drone RF dataset and provided a comprehensive comparison of a two-stage and integrated detection and classification framework. Both frameworks' detection and classification results are demonstrated for a single-signal and simultaneous multi-signal situation. We demonstrate that the You Only Look Once (YOLO) framework outperforms the Goodness-of-Fit (GoF) spectrum sensing framework in a simultaneous multi-signal situation, and that it outperforms the Deep Residual Neural Network (DRNN) framework in classification

Wellposedness for a (1+1)-dimensional wave equation with quasilinear boundary condition

We consider the linear wave equation on with initial conditions and a nonlinear Neumann boundary condition at x = 0. This problem is an exact reduction of a nonlinear Maxwell problem in electrodynamics. In the case where is an increasing homeomorphism we study global existence, uniqueness and wellposedness of the initial value problem by the method of characteristics and fixed point methods. We also prove conservation of energy and momentum and discuss why there is no wellposedness in the case where f is a decreasing homeomorphism. Finally we show that previously known time-periodic, spatially localized solutions (breathers) of the wave equation with the nonlinear Neumann boundary condition at x = 0 have enough regularity to solve the initial value problem with their own initial data.