Local Method Research Articles

Hybrid TOA/AOA Localization for Indoor Multipath-assisted Next-Generation Wireless Networks

The next-generation wireless communication systems (NGWCs) necessitate integrating effective communication and localization techniques. However, the multipath badly affects both communication and localization, especially in indoor NGWCs. Therefore, we propose a novel hybrid localization method based on time and angle-based ranging estimation to address this issue. This method employs an improved matrix enhancement matrix pencil algorithm (IMEMP) to obtain the time of arrival (TOA) and corresponding angle of arrival (AOA) of each path. Two distinct localization methods are presented: First arrival path-based maximum likelihood (ML) and scatterer-assisted. Both methods are designed to mitigate the adverse effects of serious non-line-of-sight (NLOS) scenarios. The proposed scatterer-assisted method demonstrates a noteworthy 20% improvement in performance compared to scenarios where only the first path is considered, particularly in specific areas. These findings highlight the potential of the proposed approach to enhance localization accuracy in challenging wireless environments, offering valuable insights for the advancement of NGWCs.

Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model

Local Discontinuous Galerkin Methods with Decoupled Implicit-Explicit Time Marching for the Growth-Mediated Autochemotactic Pattern Formation Model

A Real Time Facial Recognition and Tracking System for Personnel Presence

Abstract: Our project aims to revolutionize the conventional attendance system by implementing a facial recognition-based solution. The existing manual methods are prone to human error and require significant maintenance. By leveraging facial recognition technology, our system will offer improved precision and efficiency, reducing the need for manual work. The system will maintain a database of students' images, matching them during class to mark attendance accurately. Utilizing machine learning techniques, specially the Haar-Cascade classifier and local binary pattern histogram method for face detection and recognition, respectively, our system will ensure reliable attendance tracking. The attendance data will be stored in a MySQL database and Microsoft Excel file, providing a streamlined and secure alternative to the traditional attendance process.

Formulation and evaluation of transdermal patch of carbamazepine

Transdermal drug delivery system (TDDS) is a widely accepted mode of drug delivery method due to various advantages and one of the novel routes for systemic delivery of drugs through intact skin. Topical drug administration is a systemic and localized method of delivering drugs through skin and is considered an attractive alternative to oral and parenteral routes. The aim of present study was to formulate and evaluate Matrix type transdermal drug delivery system (TDDS) of Carbamazepine was prepared by the solvent evaporation technique. Several batches were prepared by using combination of HPMC E-15, Eudragit RL-100, and Ethyl Cellulose different ratios. Propylene glycol was used as plasticizer and DMSO was incorporated as a permeation enhancer. These Formulated transdermal patches were characterized for their physicochemical parameters like thickness, weight variation, folding endurance, percentage moisture uptake, Percentage moisture uptake and In vitro drug release studies were examined. Among the above all formulation F6 was chosen as a best Formulation, because this optimised formulation showed satisfactory drug content, physical characteristic for its thickness, weight uniformity, percentage moisture content, percentage moisture uptake, and maximum % of drug release i.e., 93.95 % in 12 hours. The optimized formulation (F6) showed maximum highest percentage of drug release.

Exploring the Substructure of the Near-surface Shear Layer of the Sun

The gradient of rotation in the near-surface shear layer (NSSL) of the Sun provides valuable insights into the dynamics associated with the solar activity cycle and the dynamo. Results obtained with global oscillation mode splittings lack resolution near the surface, prompting the use of the local helioseismic ring-diagram method. While the Helioseismic and Magnetic Imager ring-analysis pipeline has been used previously for analyzing this layer, default pipeline parameters limit the accuracy of the near-surface gradients. To address these challenges, we fitted the flow parameters to power spectra averaged over one-year periods at each location, followed by additional averaging over 12 yr. We find that the NSSL can be divided into three fairly distinct regions: a deeper, larger region with a small shear, steepening toward the surface; a narrow middle layer with a strong shear, with a gradient approximately 3 times larger; and a layer very close to the surface, where the logarithmic gradient is close to zero but becomes steeper again toward the surface. The middle layer appears to be centered at 3 Mm, but the poor resolution in these layers implies that it is potentially located closer to the surface, around 1.5 Mm deep. While our analysis primarily focused on regions along the central meridian, we also investigated systematic errors at longitudes off the center. The east–west antisymmetric component of the gradient reveals a layer of substantial differences between the east and west longitude of around 1.7 Mm, and the amplitude of the differences increases with the longitude.

Map-based localization for intelligent vehicles based on fusion of multiple visual features in underground parking

The ‘last mile’ problem in intelligent car localization within underground parking lots presents challenges such as localization blind spots and feature extraction difficulties. To tackle these issues, this paper proposes a mapping and multiscale matching localization method based on the fusion of multiple feature sources using a ‘binocular mapping, monocular localization’ approach. By combining traditional features with deep learning features, the proposed method enhances feature matching accuracy and addresses feature extraction challenges. A sparse three-dimensional reconstruction method based on local feature-optical flow is also proposed to mitigate localization blind spots. During the mapping process, the underground parking lot scene is segmented into several nodes to store map information, each consisting of a feature layer, scene structure layer, and trajectory layer. In the multiscale matching localization process, ORB, LoFTR, and BoW multisource features are fused to achieve feature matching, determine the nearest node, and estimate vehicle pose using the PnP model through optical flow. Finally, a localization optimization algorithm outputs the localization result. Experiments were conducted across multiple underground parking lots encompassing a total area of over 100,000 square meters. The results demonstrated that the average error of map construction using the proposed algorithm is approximately 15 mm, and the average error rate of localization is 4.45%.

Reconfigurable Intelligent Surface Assisted Target Three-Dimensional Localization with 2-D Radar

Battlefield surveillance radar is usually 2-D radar, which cannot realize target three-dimensional localization, leading to poor resolution for the air target in the elevation dimension. Previous researchers have used the Traditional Height Finder Radar (HFR) or multiple 2-D radar networking to estimate the target three-dimensional location. However, all of them face the problems of high cost, poor real-time performance and high requirement of space–time registration. In this paper, Reconfigurable Intelligent Surfaces (RISs) with low cost are introduced into the 2-D radar to realize the target three-dimensional localization. Taking advantage of the wide beam of 2-D radar in the elevation dimension, several Unmanned Aerial Vehicles (UAVs) carrying RISs are set in the receiving beam to form multiple auxiliary measurement channels. In addition, the traditional 2-D radar measurements combined with the auxiliary channel measurements are used to realize the target three-dimensional localization by solving a nonlinear least square problem with a convex optimization method. For the proposed RIS-assisted target three-dimensional localization problem, the Cramer–Rao Lower Bound (CRLB) is derived to measure the target localization accuracy. Simulation results verify the effectiveness of the proposed 3-D localization method, and the influences of the number, the positions and the site errors of the RISs on the localization accuracy are covered.

Landslide Warning Area Delineation through Seismic Signals and Landslide Characteristics: Insights from the Silabaku Landslide in Southern Taiwan

Abstract Publishing timely warnings of areas potentially affected by landslides and subsequent events remains challenging in hazard assessment. Recently, seismic monitoring has emerged as a promising technique for landslide detection and location determination. However, the effectiveness of this approach is limited by location errors. To overcome this problem, we propose a hybrid method (a three-step process) through seismic analysis and consideration of prior geomorphological characteristics of areas and aspects in a landslide inventory to constrain the potential landslide locations. The first analysis entails a grid-based single-force inversion of 0.02–0.05 Hz seismic signals by spatial grid spacings of 0.2° and 0.05° to retrieve the single-force direction, the estimated landslide area, and a wide search range for a given source. The second analysis involves two location methods for high-frequency seismic signals (>1 Hz) with a finer spatial grid spacing of 0.01°, gradually reducing the landslide search region. By integrating seismology-determined information with a landslide inventory, potential landslide locations and warning areas could be identified effectively. Then we apply the proposed the three-step analysis method to the 2021 Silabaku landslide in southern Taiwan. The results showed that the seismic techniques we used progressively condensed the initial search range from 1831 to 770 km2, converging to a small area of 99 km2. The estimated landslide area was 0.80±0.04 km2, and the force direction was 154.09° ± 6.76°. Subsequently, according to the earlier information, we identified three possible landslide source locations from the 2020 landslide inventory. These findings have implications for warning for two road sections, one of which was subsequently damaged by debris flow after the Silabaku landslide. This study highlights the effectiveness of the hybrid three-step algorithm in constraining areas potentially affected by landslides, facilitating timely assessments for warnings in southern Taiwan.

A Novel Method of UAV-Assisted Trajectory Localization for Forestry Environments

A Novel Method of UAV-Assisted Trajectory Localization for Forestry Environments

Experiment study on focusing pattern prediction of particles in asymmetric contraction-expansion array channel.

Contraction-expansion array (CEA) microchannel is a typical structure applied on particle/cell manipulation. The prediction of the particle focusing pattern in CEA microchannel is worthwhile to be investigate deeply. Here, we demonstrated a virtual boundary method by flow field analysis and theoretical derivation. The calculating method of the virtual boundary location, related to the Reynolds number (Re) and the structure parameter RW, was proposed. Combining the approximate Poiseuille flow pattern based on the virtual boundary method with the simulation results of Dean flow, the main line pattern and the main/lateral lines pattern were predicted and validated in experiments. The transformation from the main line pattern to the main/lateral lines pattern can be facilitated by increasing Re, decreasing RW , and decreasing α. An empirical formula was derived to characterize the critical condition of the transformation. The virtual boundary method can provide a guidance for asymmetric CEA channel design and contribute to the widespread application of microfluidic particle focusing.

Node selection through upper bounding local search methods in branch & bound solvers for NCOPs

Node selection through upper bounding local search methods in branch & bound solvers for NCOPs

Observation of Grain Boundary Sliding in a Lamellar Ultrafine‐Grained Steel

The deformation behavior of a ferrite steel with ultrafine‐grained (UFG) lamellar microstructure generated by linear flow splitting is investigated and compared to a coarser cold‐worked reference state, using a set of complementary local deformation and microstructural characterizations methods. The pile‐up around indentations shows a pronounced anisotropy for the UFG lamellar microstructure indicating the relative motion of grains along their elongated boundaries. This observation is confirmed by stepwise compression testing of micropillars along the normal direction of lamellar‐shaped grains using a new faceted pillar geometry to image the initial microstructure and its evolution throughout the test. The surface roughening in pillar compression testing can be categorized into the formation of discrete steps at the surface along particular grain boundaries and a more gradual roughening that is attributed to intragranular dislocation slip. Potential mechanisms for the observed grain boundary sliding are discussed taking several factors such as the strain rate sensitivity and potential Coble creep rates into account. In conclusion, a grain boundary sliding process carried by grain boundary dislocations appears to be the most likely explanation for the observed behavior.

Topological rainbow trapping of shear horizontal waves in a phononic crystal plate with tapered surface

Abstract Topological interface states have localized field enhancement characteristics. Integrating them with the concept of rainbow trapping undoubtedly be a more effective method for elastic energy localization and collection. In this paper, the tunable interface state of shear horizontal (SH) waves is realized in a one-dimensional (1D) phononic crystal (PC) plate by modifying the structural parameters of unit cells with tapered surfaces, where the interface state emerges in the overlapping band gaps of two types of unit cells with different Zak phases. Furthermore, we assembled seven types of unit cells with gradient variations, achieving topological rainbow trapping. Meanwhile, the robustness of the rainbow state has been demonstrated, and more separated frequencies are obtained by changing the order of these unit cells. The results of the study demonstrate that the highly localized, compact, and broadband tunable topological rainbow system we designed holds promise for applications in areas such as elastic energy harvesting, filtering, and multi-frequency signal processing.

Robust DOA Estimation Using Multi-Scale Fusion Network with Attention Mask

To overcome the limitations of traditional methods in reverberant and noisy environments, a robust multi-scale fusion neural network with attention mask is designed to improve direction-of-arrival (DOA) estimation accuracy for acoustic sources. It combines the benefits of deep learning and complex-valued operations to effectively deal with the interference of reverberation and noise in speech signals. The unique properties of complex-valued signals are exploited to fully capture inherent features and rich information is preserved in the complex field. An attention mask module is designed to generate distinct masks for selectively focusing and masking based on the input. After that, the multi-scale fusion block efficiently captures multi-scale spatial features by stacking complex-valued convolutional layers with small size kernels, and reduces the module complexity through special branching operations. Experimental results demonstrate that the model achieves significant improvements over other methods for speaker localization in reverberant and noisy environments. It provides a new solution for DOA estimation for acoustic sources in different scenarios, which has significant theoretical and practical implications.

Automatic State Interaction with Large Localized Active Spaces for Multimetallic Systems.

The localized active space self-consistent field method factorizes a complete active space wave function into an antisymmetrized product of localized active space wave function fragments. Correlation between fragments is then reintroduced through localized active space state interaction (LASSI), in which the Hamiltonian is diagonalized in a model space of LAS states. However, the optimal procedure for defining the LAS fragments and LASSI model space is unknown. We here present an automated framework to explore systematically convergent sets of model spaces, which we call LASSI[r, q]. This method requires the user to select only r, the number of electron hops from one fragment to another, and q, the number of fragment basis functions per Hilbert space, which converges to CASCI in the limit of r, q → ∞. Numerical tests of this method on the trimetal oxo-centered complexes [Fe(III)Al(III)Fe(II)(μ3-O)(HCOO)6] and [Fe(III)2Fe(II)(μ3-O)(HCOO)6] show efficient convergence to the CASCI limit with 4-10 orders of magnitude fewer states than CASCI.

Complete Solutions for the Approximate Synthesis of Spherical Four-Bar Function Generators

Abstract Kinematic synthesis to meet an approximate motion specification naturally forms a constrained optimization problem. Instead of using local methods, we conduct global design searches by direct computation of all critical points. The idea is not new, but performed at scale is only possible through modern polynomial homotopy continuation solvers. Such a complete computation finds all minima, including the global, which allows for a full exploration of the design space, whereas local solvers can only find the minimum nearest to an initial guess. We form equality-constrained objective functions that pertain to the synthesis of spherical four-bar linkages for approximate function generation. We consider the general case where all mechanism dimensions may vary and a more specific case that enables the placement of ground pivots. The former optimization problem is shown to permit 268 sets of critical points, and the latter permits 61 sets. Critical points are classified as saddles or minima through a post-process eigenanalysis of the projected Hessian. The discretization points are contained within the coefficients of the stationarity polynomials, so the algebraic structure of the synthesis equations remains invariant to the number of points. The results of our computational work were used to design a mechanism that coordinates the folding wings. We also use this method to parameterize mechanism dimensions for a family of hyperbolic curves.

Quantitative evaluation of 90Y-PET/CT and 90Y-SPECT/CT-based dosimetry following Yttrium-90 radioembolization.

Following yttrium-90 radioembolization (90Y-RE), 90Y-PET/CT and 90Y-SPECT/CT imaging provide the means to calculate the voxelized absorbed dose distribution. Given the widespread use of the two imaging modalities and lack of well-established standardized dosimetry protocols for 90Y-RE, there is a clinical need to systematically investigate and evaluate differences in the performance of voxel-based dosimetry between 90Y-PET/CT and 90Y-SPECT/CT. To quantitatively analyze and compare 90Y-PET/CT and 90Y-SPECT/CT-based dosimetry following 90Y-RE. 90Y-PET/CT and90Y-SPECT/CT imaging was acquired for 35 patients following 90Y-RE with TheraSphere for the treatment of unresectable hepatocellular carcinoma. Dosimetry was performed using the local deposition method with known activity and the mean dose (Dmean) was calculated for perfused liver volumes (PV), tumors (T), and perfused normal livers (NL). Additionally, the absorbed dose to x% of the volume (Dx, x [5%, 10%, …, 90%, 95%]) and the volume receiving y Gy (Vy, y [10Gy, 20Gy, …, 190Gy, 200Gy]) were calculated for T and NL, respectively. Dose metrics were compared using linear regression, Bland-Altman analysis, and statistical testing. Both 90Y-SPECT/CT and 90Y-PET/CT-based tumor Dmean were strongly correlated (R2 ≥ 0.90) with Dx, excluding metrics on the extrema. Intra-modality comparisons of various Dx and Vy metrics yielded statistically significant differences (ANOVA, p<0.001) for both90Y-PET/CT and90Y-SPECT/CT. Based on statistical testing, only Dx metrics separated by greater than 20%-30% coverage, and only Vy metrics separated by greater than 40-70Gy, reported significant differences. For PV, there was a strong correlation (R2 ≥ 0.99) between Dmean derived separately from 90Y-PET/CT and 90Y-SPECT/CT imaging. The strength of the correlation was slightly reduced for T and NL with R2=0.91 and R2=0.95, respectively. For PV, the mean bias±standard error (SE) and 95% limits of agreement (LOA) between Dmean from the two modalities was effectively zero with -0.8±0.4% (±2.5%). For T and NL, the mean bias±SE (±LOA) was -14.5±3.7% (±24%) and 9.4±4.7% (±27%), respectively. The strong correlation between Dmean and Dx suggests information from multiple dose metrics (e.g., D70 and Dmean) is largely redundant when establishing dose-response relationships in 90Y-RE. Dmean is highly correlated between 90Y-PET/CT and 90Y-SPECT/CT-based dosimetry, for all liver VOIs. Relative to 90Y-SPECT/CT, 90Y-PET/CT, on average, yielded higher Dmean to tumors (14%) and lower Dmean to perfused normal livers (9%). Absorbed dose differences for perfused liver volumes between 90Y-SPECT/CT and 90Y-PET/CT were negligible.

Holistic and localized preparation methods for triboelectric sensors: principles, applications and perspectives

Abstract With the arrival of intelligent terminals, triboelectric nanogenerators (TENGs), as a new kind of energy converter, are considered one of the most important technologies for the next generation of intelligent electronics. As a self-powered sensor, it can greatly reduce the power consumption of the entire sensing system by transforming external mechanical energy to electricity. However, the fabrication method of triboelectric sensors largely determines their functionality and performance. This review provides an overview of various methods used to fabricate triboelectric sensors, with a focus on the processes of micro-electro-mechanical systems (MEMS) technology, three-dimensional (3D) printing, textile methods, template-assisted methods, and material synthesis methods for manufacturing. The working mechanisms and suitable application scenarios of various methods are outlined. Subsequently, the advantages and disadvantages of various methods are summarized, and reference schemes for the subsequent application of these methods are included. Finally, the opportunities and challenges faced by different methods are discussed, as well as their potential for application in various intelligent systems in the Internet of Things (IoT).

Coordinated Control of the Onboard and Wayside Energy Storage System of an Urban Rail Train Based on Rule Mining

AbstractThere are three major challenges to the broad implementation of energy storage systems (ESSs) in urban rail transit: maximizing the absorption of regenerative braking power, enabling online global optimal control, and ensuring algorithm portability. To address these problems, a coordinated control framework between onboard and wayside ESSs is proposed in this study, and the related control strategy is obtained by transforming the global optimization problem into a combination of rule-based and local optimization problems. The design process of the strategy is divided into three parts: offline optimization, rule extraction, and local optimization. First, a genetic algorithm is used to optimize the charge/discharge threshold curves under typical operational conditions. Then, the rules of offline optimization results are obtained from an expert system, and the nonlinear rules are mined with local optimization methods. Finally, a coordinated strategy is presented based on the outcomes of the three parts. A power hardware-in-the-loop (PHIL) experimental platform based on RTLAB is built, and the above coordination strategy is verified based on data for the Beijing Metro Batong Line. The experimental results show that the strategy can effectively improve the energy-saving rate and reduce the regeneration failure rate substantially, with the effect being close to the offline global optimal solution. The algorithm proposed in this paper achieves near global optimal energy-saving optimization results with lower computational costs, and has strong portability, providing a good solution for the large-scale application of onboard and wayside energy storage coordination control.

#1118 Direct delivery of novel gene therapy to podocytes enables pathway to clinical translation for the treatment of glomerular diseases

Abstract Background and Aims Adeno associated vector (AAV) gene therapy has the potential to treat a wide range of kidney diseases via the targeted delivery of genes to kidney cells to repair cellular and renal function. Despite the potential to impact many kidney conditions, kidney AAV gene therapy has proven challenging due to technical and physiological hurdles limiting the ability of AAV to be effectively delivered to podocytes. We have developed a novel AAV gene therapy, PS-001, and local method of administration, to effectively and safely deliver the podocin gene NPHS2 to podocytes. Biallelic NPHS2 mutations are the most common cause of monogenic childhood nephrotic syndrome. Curative efficacy and resolution of disease phenotype was demonstrated in transgenic murine models following PS-001 gene therapy treatment. The potential for translation of this approach to NPHS2 nephropathy patients in the clinic was also demonstrated in pre-clinical studies in Gottingen Minipigs. Method Transgenic murine models representative of NPHS2-driven nephropathy were treated with an AAV gene therapy encoding NPHS2, including a knock in mouse model (Nphs2R140Q/−) which introduces a R140Q mutation in the podocin gene. Mice were assessed for improvement in disease phenotype via analysis of proteinuria, serum albumin, renal histopathology and survival. Mice were treated with an analogue of PS-001, as the PS-001 capsid is not permissive in rodents. Gottingen minipigs were treated with PS-001 and followed for 4 weeks. Clinically relevant doses and a procedure for local administration specifically to the kidney were established. In-life safety assessments from blood and urine were monitored and at study end pig tissues were assessed for podocin biodistribution using multiple assays (qPCR, RT-qPCR, ELISA, RNAScope and IF) and for toxicological effects via histopathological analysis. Results Using our AAV gene therapy platform, which includes a capsid that is highly effective at transducing human podocytes and promoter that drives gene expression specifically in the podocyte, the gene therapy product PS-001 encoding NPHS2 was generated. Using a murine analogue of PS-001, in vivo proof of concept studies in a translationally relevant murine disease model (Nphs2R140Q/−) showed NPHS2 delivery and podocin expression in glomeruli and efficacy in terms of renal function rescue. This was demonstrated by resolution of severe proteinuria (mean ACR ug/mg 6049 ± 2803 vs 192 ± 51 in PS-001 treated animals, n = 11), improved serum albumin (g/L 27.50 ± 3.33 g/L vs 30.75 ± 2.46 in PS-001 treated animals, P = .021) and reduction in glomerulosclerosis (mean sclerosed glomeruli 81% ± 19 vs 18.75% ± 12 in PS-001 treated animals, P &amp;lt; .0001). The methods to translate the approach to the clinical setting using a local administration were established in pigs. Administration of PS-001 resulted in transgene mRNA expression across 89% ± 11% of kidney glomeruli as assessed by RNAScope (n = 3 pigs), and transgene derived podocin could be specifically detected in podocytes as assessed by IF analysis. Using qPCR, RT-PCR and ELISA it was shown that using local administration, podocin gene expression was restricted exclusively to the kidney glomerulus, with gene expression undetectable in off-target organs including the liver. Additional toxicological assessments of renal and other organ function from urine and blood, and post-study histopathological assessments revealed no pre-clinical treatment-related safety concerns. Conclusion We present data showing development of an AAV gene therapy and method of administration for the delivery of transgenes specifically to podocytes. We have shown transgenes can be efficiently targeted to podocytes to replace defective genes or to use the podocyte as a protein factory to modulate glomerular biology. This technology therefore provides an important novel modality for potentially treating a broad range of glomerular disease. PS-001 is being developed as a novel approach to treat steroid resistant nephrotic syndrome caused by mutated NPHS2, and may become the first podocyte targeted gene therapy to enter clinical development.