Location Of Point Research Articles

Can computer vision / artificial intelligence locate key reference points and make clinically relevant measurements on axillary radiographs?

Computer vision and artificial intelligence (AI) offer the opportunity to rapidly and accurately interpret standardized x-rays. We trained and validated a machine learning tool that identified key reference points and determined glenoid retroversion and glenohumeral relationships on axillary radiographs. Standardized pre and post arthroplasty axillary radiographs were manually annotated locating six reference points and used to train a computer vision model that could identify these reference points without human guidance. The model then used these reference points to determine humeroglenoid alignment in the anterior to posterior direction and glenoid version. The model's accuracy was tested on a separate test set of axillary images not used in training, comparing its reference point locations, alignment and version to the corresponding values assessed by two surgeons. On the test set of pre- and post-operative images not used in the training process, the model was able to rapidly identify all six reference point locations to within a mean of 2mm of the surgeon-assessed points. The mean variation in alignment and version measurements between the surgeon assessors and the model was similar to the variation between the two surgeon assessors. This article reports on the development and validation of a computer vision/artificial intelligence model that can independently identify key landmarks and determine the glenohumeral relationship and glenoid version on axillary radiographs. This observer-independent approach has the potential to enable efficient human observer independent assessment of shoulder radiographs, lessening the burden of manual x-ray interpretation and enabling scaling of these measurements across large numbers of patients from multiple centers so that pre and postoperative anatomy can be correlated with patient reported clinical outcomes. Level III Study of Diagnostic Test.

Tracking a Homeopathic Complex Formulation in the Watercourses of a Fire-Damaged State Park in Brazil.

In 2020, a 26,849-ha state park in Mato Grosso do Sul state, Brazil, had 30% of its area damaged by fire. A homeopathic complex formulation was applied at strategic point locations in the park's springs or watercourses, aiming to mitigate the fire damage to the flora and fauna as quickly as possible. The duration of the homeopathic signal at each point was assessed using an established solvatochromic dye technique. To evaluate the timing and the nature of the signal at each of nine point locations. We could thus identify the presence of any signal variations due to specified environmental features within the park. Water samples were harvested from each intervention point at different times, filtered, frozen, and sent to the laboratory, where they were prepared to 1cH using filtered 30% ethanol. Methylene violet was chosen among six dyes since it was found in preliminary tests that it could trace the homeopathic complex used. In addition to simple sample testing, samples were submitted to a static and unidirectional magnetic field of 2400 Gauss (240 mT) for 15 minutes immediately before reading, which enhanced the method's sensitivity. One-way analysis of variance/Tukey test was used to identify dye absorbance changes following the analysis of water samples from the watercourse system. A correlation matrix and the Spearman r test were employed to evaluate any correlation between tracking and the pre-existing anthropic interventions at harvesting points. In all cases, α = 0.05. Four tracking patterns using the sample magnetization process were observed in relation to water samples and their effect on methylene violet solutions: no response (P2, P4), early transitory response (P5, P6, P8), late response (P1, P9), and constant response (P3, P7). P2 and P4, which could not be tracked, were correlated with permanent local anthropic disturbance. Methylene violet was the best dye to track the homeopathic complex prepared specifically for this case. Tracking was facilitated by prior magnetic treatment of samples, but anthropic disturbances to the environment seem to interfere with it.

Modeling and Optimization of NO2 Stations in the Smart City of Barcelona

The growing problem of nitrogen dioxide (NO2) pollution in urban environments is driving cities to adopt smart and sustainable approaches to address this challenge. To quantify and compare the effect of environmental policies, cities must be able to make informed decisions with real-time data that reflect the actual situation. Therefore, the objective of this work is threefold: The first is to study the behavior of the key performance indicator (KPI) of NO2 concentrations per station in Barcelona through exploratory analysis and clustering. The second is to predict NO2 concentration behavior, considering meteorological data. Lastly, a new distribution of current and new stations will be proposed using an optimization algorithm that maximizes the distance between them and covers the largest area of the city. As a result of this study, the importance of the location of measurement points and the need for better distribution in the city are highlighted. These new spatial distributions predict an 8% increase in NO2 concentrations. In conclusion, this study is a comprehensive tool for obtaining an accurate representation of NO2 concentrations in the city, contributing to informed decision-making, helping to improve air quality, and promoting a more sustainable urban environment.

Change point detection in INAR(p) models via likelihood ratio scanning method

In this paper, we consider an integer-valued autoregressive (INAR) model. Based on the likelihood ratio scanning method (LRSM), the numbers and locations of the piecewise stationary INAR process change points are discussed. The minimum description length (MDL) function of the INAR model is given. Moreover, we also study the case when the sum of coefficients in each segment of the model tends to 1 and make adjustments to the MDL criterion in the LRSM. In this way, the accuracy of change point detection is improved. In the end, simulation experiments and real data analysis are conducted to illustrate the efficiency of the LRSM.

Real-time location of acupuncture points based on anatomical landmarks and pose estimation models

IntroductionPrecise identification of acupuncture points (acupoints) is essential for effective treatment, but manual location by untrained individuals can often lack accuracy and consistency. This study proposes two approaches that use artificial intelligence (AI) specifically computer vision to automatically and accurately identify acupoints on the face and hand in real-time, enhancing both precision and accessibility in acupuncture practices.MethodsThe first approach applies a real-time landmark detection system to locate 38 specific acupoints on the face and hand by translating anatomical landmarks from image data into acupoint coordinates. The second approach uses a convolutional neural network (CNN) specifically optimized for pose estimation to detect five key acupoints on the arm and hand (LI11, LI10, TE5, TE3, LI4), drawing on constrained medical imaging data for training. To validate these methods, we compared the predicted acupoint locations with those annotated by experts.ResultsBoth approaches demonstrated high accuracy, with mean localization errors of less than 5 mm when compared to expert annotations. The landmark detection system successfully mapped multiple acupoints across the face and hand even in complex imaging scenarios. The data-driven approach accurately detected five arm and hand acupoints with a mean Average Precision (mAP) of 0.99 at OKS 50%.DiscussionThese AI-driven methods establish a solid foundation for the automated localization of acupoints, enhancing both self-guided and professional acupuncture practices. By enabling precise, real-time localization of acupoints, these technologies could improve the accuracy of treatments, facilitate self-training, and increase the accessibility of acupuncture. Future developments could expand these models to include additional acupoints and incorporate them into intuitive applications for broader use.

A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems

This research study presents the application of the FC-PCC (Fuzzy Logic Predictive Current Control) algorithm in the context of maximum power point tracking (MPPT) for a proton exchange membrane fuel cell system employing a three-level boost converter (TLBC). The proposed approach involves the integration of an intelligent fuzzy controller with a predictive current control strategy in order to improve the performance of MPP tracking. Initially, the utilization of fuzzy logic involves the utilization of data values obtained from the PEMFC. The maximum point (P-I) of the PEMFC polarization curve is determined, followed by the selection of the reference current. A predictive current control technique employs the reference current to ensure the voltage balance of the output capacitor in the three-level converter. The hardware-in-the-loop system utilizes a real-time and high-speed simulator, specifically the PLECS RT Box 1, to obtain the findings. The computational cost of the overall system is rather low, making it feasible to construct using PLECS RT Box 1. The new MPPT algorithm quickly finds the maximum power point (MPP) and balances the voltage of capacitors in a number of different proton exchange membrane fuel cells. The suggested MPPT technique has been verified to demonstrate rapid tracking of the maximum power point (MPP) location, as well as precise balancing of capacitor voltage and robustness to environmental variations. This approach was tested and found to outperform conventional MPPT methods like Perturb and Observe (P&O) and Incremental Conductance (IC) in terms of tracking duration, precision, and voltage balancing, achieving a 15% reduction in tracking duration, a 5% deviation from the MPP value for voltage, and superior stability under changing temperature and pressure.

Modeling of the interaction of stressful components agricultural production

There is a completely natural, organic nonlinear relationship between crop production and animal husbandry, which are crucial components of agricultural production in Ukraine. Timely and appropriate management of these subsystems contributes to the stable growth of the country’s agriculture with minimal risk. This approach requires improvements in terms of the digitalization of the economy, particularly in the context of applying computer modeling to the nonlinear processes of interaction between these components. The article develops a modern methodology for computer modeling of an economic management object—a thorough study of a nonlinear dynamic model of the VolterraLotka class, featuring a component that characterizes the increase in livestock profitability due to feed supply. The model takes into account various influencing factors, allowing for the assessment of the efficiency of the interaction between crop production and animal husbandry at different stages of agricultural production. The study examines the behavior of the dynamic model in the vicinity of the leverage point, analyzing the modeled trend dependencies and statistical components: in the vicinity of the equilibrium point, there are oscillatory movements with a certain defined period, and the solutions of the mathematical model, i.e., integral curves, over time reflect the seasonal nature of the interaction between crop production and animal husbandry. The behavior of virtual scenarios—integral curves and phase portraits based on the mathematical model of nonlinear interaction of agricultural production components—wasstudied, showing the location of the equilibrium point, extreme points, and other critical points for the respective curves in a specific coordinate system. A transition to a dimensionless dynamic model and an economic interpretation of its implicit solution were indicated. Additionally, the impact of external economic factors on the stability of the system was analyzed, allowing for better forecasting of potential risks and the preparation of appropriate strategies to minimize them. For the first time, an approximate numerical estimate of the economic risk measure of the evolution of the interaction and interplay of agricultural subsystems over time was carried out in the study of the nonlinear dynamic model of the economic management object. The obtained results can be used to improve management strategies in the agricultural sector, particularly to enhance the stability of production processes and reduce economic risks in the context of market instability and climate change. This research provides new opportunities for effective planning and the implementation of innovations in Ukraine’s agricultural sector.

Research on Resource Allocation Algorithm for Non-Orthogonal Multiple Access Visible Light Communication

In order to satisfy the large-scale access of visible light communication (VLC) users, as well as the demand for user request rate, the resource allocation problem of visible light communication with drone-assisted non-orthogonal multiple access (NOMA) technique is investigated. An efficient scheme for joint optimization of power allocation and access point (AP) location is proposed. According to the state of user channel information, a user pairing strategy with uniform channel gain difference for any number of users is designed, and an objective function of maximizing the average user data rate with constraints is constructed. For this non-convex NP-hard problem, the optimization problem with constraints is transformed into an optimization problem without constraints by introducing the idea of a penalty function and then solved by the Harris Hawk Optimization (HHO) algorithm based on the nonlinear energy convergence factor, and ultimately, the optimal user power allocation factor, as well as the location of the AP, are found. The simulation results show that the scheme in this paper can improve the average user data rate better compared to other classical schemes. The system performance of the HHO algorithm is improved by about 20.31% compared to the Particle Swarm Optimization (PSO) algorithm. The HHO algorithm based on the nonlinear energy convergence factor improves the convergence speed by about 50% compared to the classical HHO algorithm.

Underground XLPE coaxial cable length calculation and fault detection based on broadband impedance spectroscopy

Abstract Accurately determining the tested cable's total length is important in cable fault detection and localization. Therefore, an iterative method of relative propagation coefficients based on broadband impedance spectroscopy (BIS) is proposed to solve the actual length of the cable and a phase difference integral transform method for fault detection. First, the overall detection process framework is designed. Then, the cable distribution parameter model and the characteristics of the input impedance spectroscopy are analyzed. The calculation methods for determining the cable length and propagation coefficients are explained, followed by a demonstration of the fault localization process. Finally, the model LCR1000A impedance analyzer is used to measure cable length and actual faults in cables with lengths of 35 m, 100 m, and 500 m. The final fault location error is less than 0.67%, proving that the method can calculate the length of cables and various fault point locations.

Computer simulation of the truck cabin tests to find ways to meet the requirements of the UNECE Regulation 29

BACKGROUND: Ensuring the required level of passive safety of trucks is a relevant task. To solve this problem, it is necessary to use computer simulation methods. AIM: Search for the ways to ensure the passive safety of trucks by choosing the appropriate cabin design. MATERIALS AND METHODS: During the study, the method of virtual simulation of the truck cabin tests was used in accordance with the requirements of the UNECE Regulation 29. RESULTS: A simulation model of a truck cabin has been developed, which makes it possible to conduct the computer simulation of the tests according to the UNECE Regulation 29. The main requirement of the UNECE Regulation 29 is retaining sufficient space in the cabin to accommodate the driver’s dummy inside it after its testing. As a part of the study, the properties of the material (steel) used for manufacturing of prototype cabins of the truck under development were determined, and the tested specimens were obtained by dissecting the prototype of the cabin, so the obtained results take into account the technological history of the material. The obtained data on the properties of the materials were used in the development of the simulation model of the cabin. The developed and used simulation model takes into account all the design features of the cabin under study, including the location and properties of welding points. Various options of cabin design changes and their impact on the ability to meet the requirements of the UNECE Regulations 29 are investigated. It has been found that it is not possible to fully comply with the requirements of the UNECE Regulation 29 only by increasing (within reasonable limits) the thickness of individual elements of the cabin frame and/or using high-strength steel for their manufacturing. Based on the analysis of the deformation of the prototype cabin frame during the Test C according to the UNECE Regulation 29 Revision 2, proposals for changes to the cabin design to meet the requirement of the UNECE Regulation 29 are formulated. CONCLUSION: The results of the study indicate the prospects of the proposed changes to the cabin design.

Bayesian location of the QCD critical point from a holographic perspective

Bayesian location of the QCD critical point from a holographic perspective

Geometric flow control in lateral flow assays: Macroscopic two-phase modeling

Lateral flow assays (LFAs) are widely employed in a diverse range of applications, including clinical diagnostics, pharmaceutical research, forensics, biotechnology, agriculture, food safety, and environmental analysis. A pivotal component of LFAs is the porous polymeric membrane, which facilitates the capillary-driven movement of fluids, known as “imbibition,” in which a wetting fluid displaces a non-wetting fluid within the pore space of the membrane. This study presents a multi-scale modeling framework designed to investigate the imbibition process within LFAs. The framework integrates microscopic membrane characteristics into a macroscopic two-phase flow model, allowing the simulation of imbibition in membranes with different micro-scale properties and macro-scale profiles. The validity of the model was established through comparative analysis with documented case studies, a macro-scale single-phase flow model, and experimental observations, demonstrating its accuracy in simulating the imbibition process. The study also examines imbibition in various geometric configurations, including bifurcated (Y-shaped) and multi-branch geometries commonly found in multiplexed LFAs. The influence of geometric features such as length ratio, width ratio, branching angle, bifurcation point location, and asymmetry on fluid transport is investigated. Results indicate that membranes with larger branching angles exhibit slower imbibition. In addition, the influence of membrane type on macroscopic flow patterns is evaluated, showing that membranes with lower permeability require longer imbibition times. The insights gained from this research support a data-driven strategy for manipulating wetting behavior within LFAs. This approach can be leveraged to optimize the performance of LFAs and increase their effectiveness in various applications.

Intrinsic characteristics of three-dimensional flow around a wall-mounted conical cylinder

To investigate the flow characteristics around a wall-mounted conical cylinder, three-dimensional direct numerical simulations are carried out for a conical cylinder with an end diameter ratio ranging from 0.5 to 1.5 at three low Reynolds numbers (Re = 100, 150, 200). The flow features are examined in terms of time-mean streamlines, singularity points location, topological structure, time-mean streamwise vortices, and instantaneous spanwise vortices denoted with different vortex identification methods. The downwash effect also happens even without a free end. The upwash streamlines clash with the downwash streamlines and then coalesce to the saddle (impingement) point P2. The occurrence of the symmetry plane belongs to a new topology, where the saddle point on the bottom wall is an attachment point (NA), instead of the separation point (SS). The singular point verifies the topological existence of the attachment–attachment combination of the horseshoe vortex system. The “Quadrupole Type,” “Sextupole Type,” and “Octupole Type” are identified. The “Octupole Type” is reported first, consisting of a pair of “time-mean streamwise tip vortices,” two pairs of “time-mean streamwise base vortices” and a pair of “time-mean streamwise bottom vortices.” Moreover, the vorticity magnitude cannot represent the occurrence of vortices. The instantaneous iso-surfaces of Q = 0.2 and λ2 = –0.2 in the wake are similar to the threshold of Ω = 0.52. In contrast, the Liutex/Rortex method is easier to identify the streamwise bottom vortices than the former two methods.

Target-point interpolation of a program control in the approach problem

For a no Krasovskii Institute of Mathematics and Mechanics, Ural Branch, Russian Academy of Sciences, 620108, Yekaterinburg, Russianlinear controlled system, a fixed-time approach problem is considered in which the target point location becomes known only at the start of motion. According to the proposed solution method, node resolving program controls corresponding to a finite collection of target points from the set of their admissible locations are computed in advance and a refined control for the target point given at the start of motion is determined via linear interpolation of the node controls. The procedure for designing such a resolving control is formulated in the form of two algorithms, one of which is run before the start of the motion, and the other is executed in real time while the system is moving. The error in the transfer of the system’s state to the target point by applying these algorithms is estimated. As an example, we consider the approach problem for a modified Dubins car model and a target point about which only a compact set of its admissible locations is known before the start of motion.

Hanging Cables and Spider Threads

Summary It has been known for more than 300 years that the shape of an inelastic hanging cable, chain, or rope of uniform linear mass density is the graph of the hyperbolic cosine, up to scaling and shifting coordinates. But given two points at which the ends of the cable are attached, how exactly should we scale and shift the coordinates? Many otherwise excellent expositions of the problem are vague about that. They might, for instance, give the answer in terms of the tension at the lowest point, but without explaining how to compute that tension. Here we discuss how to obtain all necessary parameters. To obtain the tension at the lowest point, one has to solve a nonlinear equation numerically. When the two ends of the cable are attached at different heights, a second nonlinear equation must be solved to determine the location of the lowest point. When the cable is elastic, like a thread in a spider’s web, the two equations can no longer be decoupled, but they can be solved using two-dimensional Newton iteration.

Research on multi-stage rocket debris localization and recovery based on three-sphere localization

Advances in modern rocket technology have created challenges in the field of spaceflight with regard to the localization and recovery of rocket debris. In particular, in multi-stage rocket structures, transonic sonic booms are generated after the separation of the next stage or booster, which increases the difficulty of wreckage recovery. To solve this problem, a mathematical model based on multi-sensor data and three-sphere localization technique is proposed for accurately determining the location of the sonic boom point. The theoretical equations were constructed from monitoring equipment data and transformed into an optimization problem for numerical solution, and the longitude, latitude, altitude and time of the sonic boom birth were successfully determined. In addition, the localization and differentiation methods of multiple wrecks are studied, and the alignment and repeated verification strategies are used to improve the localization accuracy and reliability. Finally, the model validation is carried out by adding random perturbations, and the results show that the new model can still effectively locate the wreckage under a small range of perturbations, which provides an important support for the development of rocket wreckage recovery technology.

Unchained Catenaries

Summary Catenaries are the curves formed by a uniform chain or cable suspended from two ends. They are seen in the natural world in structures such as spider webs, and they also occur in engineered structures, including bridges and overhead power lines. Catenaries and catenary arches are also employed in architecture for their beauty and strength. In this article, we look at catenaries where a chain is fixed at one endpoint but free to move over the other. Such catenaries will either be supported by the weight of the tail end of the chain and hence be “stable,” or else unwind off the free end and adopt the configuration of a vertically hanging chain. We develop two models, which are analyzed to determine the conditions under which a particular system will be either stable or unstable and determine the widest span for which a stable catenary exists. The predictions made here may be explored experimentally with relatively inexpensive apparatus. The models presented also invite extensions, such as more general free point locations and the addition of friction, which could dissipate the system energy.

Critical Points in the Noiseberg Achievable Region of the Gaussian Z-Interference Channel

The Gaussian signaling strategy with power control for the Gaussian Z-interference channel with weak interference is reviewed in this paper. In particular, we study the various communication strategies that may arise at various points of the capacity region and identify the locations of the phase transitions between the various strategies. The Gaussian Z-interference channel with weak interference is known to have two critical points in its capacity region, where the slope of the region shows a sudden change. They occur at the points of the unconditional maximum rate for one of the users and the maximum rate that can be accommodated by the other user. In this paper, we discuss additional critical points (locations of phase transitions) in the achievable region of this channel. These turn out to be second-order phase transitions, i.e., we do not observe a discontinuous slope in the achievable rate region, but there is a discontinuity in the second derivative of the rate contour of the achievable region. This review paper is mainly based on some of our ITA (Information Theory and Applications Workshop, UCSD, San Diego, CA, USA) papers since 2011.

Two-Phase Flow Modelling Based on Roughness Surface Effect of Roller Compacted Concrete

One of the most important considerations that are interest to researchers on the stepped spillway in hydraulic structure is the location of the point at which the flow begins to transform into two phase-flow and the development of boundary layers. In this study, an unconventional rough surface was used (RCC materials), which has completely different properties from what is used in previous laboratory studies, which uses smooth surfaces in reality to represent the actual roughness of the surface. Benchmark mixes are evaluated as a reference standard concrete to determine the optimal combination proportions for RCC according to The U.S. Army Corps of Engineers Standard. A laboratory study of different models enhanced by a mathematical model CFD with VOF technics to described the two- phase interaction to investigate the location of the inception point and compare the results with the proposed equations assumed by different researchers in this topic. The results obtained from the study showed a clear effect of surface roughness on the location of the inception point and the formation of the boundary layer for laboratory models. It’s clearly found that the two-phase flow starts with closer locations than it is for conventional models and the ratios vary (10 % - 20 %) according to the discharge values (where the effect of surface roughness is evident in the low discharges compared to the high discharges in which the boundary Lear effect begins to fade.

Isothermal compressibility and water self-diffusion coefficient in supercooled salt aqueous solutions using the Madrid-2019 model

The isothermal compressibility and self-diffusion coefficient of water in Li + , Na + , K + , Mg 2 + and Ca 2 + chloride and sulfate salts aqueous solutions is calculated by means of molecular simulations using the Madrid-2019 force-field, that uses TIP4P/2005 model for water and assigns scaled charges for ions. Our simulations predict that the isothermal compressibilities of these salts retain the anomalous behaviour of water, i.e. compressibility increases as temperature decreases, contrary to the behaviour of normal liquids. A maximum in the isothermal compressibility, analogous to that of pure water, is observed for some of the salt solutions. For the 1 m NaCl solution, simulations are performed at several pressures up to 1000 bar to estimate the location of the second critical point. We estimate that the liquid-liquid critical point is located at 190 K and 1000 bar, i.e. it is shifted to slightly higher temperatures and lower pressures with respect to the most accurate estimation of its location in pure TIP4P/2005 water (172 K and 1861 bar). Regarding the self-diffusion of water, all salts increase water mobility in the very supercooled regime (at temperatures within 200–230 K), with K 2 SO 4 producing the largest increase in water mobility, while MgCl 2 and MgSO 4 are the least effective in enhancing the self-diffusion coefficient of water.