Coordinates Of Points Research Articles

Position query-guided cross-modal flow field prediction model of a transonic compressor cascade

The gradient of flow parameters in a transonic compressor cascade flow field varies significantly, especially in the region of shock waves, which causes a significant challenge to its high-precision flow field prediction. In this study, the position query-guided cross-modal flow field prediction model (PGCM) is proposed to effectively predict the flow field parameter distribution of a transonic compressor cascade. The PGCM utilizes the self-attention mechanism for the global and deep geometric feature extraction of configurations, which contributes to an in-depth understanding of the spatial relationships between coordinate points within the flow field, accurately capturing and analyzing the structural complexity of a compressor cascade flow. In addition, the PGCM integrates the cross-attention mechanism that establishes correlations between different input sequences, which enhances the performance of the model in querying and interpreting flow parameters at specific coordinates. The flow field prediction models are developed to predict the flow parameter distributions of different cascade geometries at Mach numbers of 0.78 and 0.93, respectively. The validation results indicate that the PGCM performs significantly better than the existing convolutional neural network and vision transformer, especially in the prediction of the pressure coefficient Cp distribution. The PGCM is adaptable to the variation of flow conditions and geometrical configurations efficiently and accurate in predicting the flow field of a compressor cascade. This paper demonstrates the promising potential of conducting the multi-modal information fusion to enhance the capability of flow field prediction.

Online landmark replacement for out-of-sample dimensionality reduction methods

A strategy to assist visualization and analysis of large and complex datasets is dimensionality reduction, with which one maps each data point into a low-dimensional manifold. However, various dimensionality reduction techniques are computationally infeasible for large data. Out-of-sample techniques aim to resolve this difficulty; they only apply the dimensionality reduction technique on a small portion of data, referred to as landmarks, and determine the embedding coordinates of the other points using landmarks as references. Out-of-sample techniques have been applied to online settings, or when data arrive as time series. However, existing online out-of-sample techniques use either all the previous data points as landmarks or the fixed set of landmarks and therefore are potentially not good at capturing the geometry of the entire dataset when the time series is non-stationary. To address this problem, we propose an online landmark replacement algorithm for out-of-sample techniques using geometric graphs and the minimal dominating set on them. We mathematically analyse some properties of the proposed algorithm, particularly focusing on the case of landmark multi-dimensional scaling as the out-of-sample technique, and test its performance on synthetic and empirical time-series data.

On-Line Measurement of Tracking Poses of Heliostats in Concentrated Solar Power Plants.

The tracking pose of heliostats directly affects the stability and working efficiency of concentrated solar power (CSP) plants. Due to occlusion, over-exposure, and uneven illumination caused by mirror reflection, traditional image processing algorithms showed poor performances on the detection and segmentation of heliostats, which impede vision-based 3D measurement of tracking poses of heliostats. To tackle this issue, object detection using deep learning neural networks are exploited. An improved neural network based on YOLO-v5 framework has been designed to solve the on-line detection problem of heliostats. The model achieves a recognition accuracy of 99.7% for the test set, outperforming traditional methods significantly. Based on segmented results, the corner points of each heliostat are found out using Hough Transform and line intersection methods. The 3D poses of each heliostat are then solved out based on the image coordinates of specific feature points and the camera model. Experimental and field test results demonstrate the feasibility of this hybrid approach, which provides a low-cost solution for the monitoring and measurement of tracking poses of the heliostats in CSP.

Analytical and geometric interpretation of the flat arrangement of points by means of metric geometry in the study of metric spaces

Abstract When studying metric spaces, students of higher education often have difficulties with understanding the basic concepts and properties of these spaces. This, to a large extent, is a consequence of the significant level of formalization of such concepts on the one hand, and the preservation of the corresponding formulations and names familiar to students from a school mathematics course. To overcome these difficulties, it is advisable to use methods of geometric interpretation and visualization of these properties. At the same time, it is appropriate to use elements of metric geometry. Its methods make it possible to interpret the geometric features of the mutual placement of points of metric space in Cartesian (rectangular) coordinate systems, which are familiar to students of higher education. Moreover, it becomes possible to visualize these features with the help of graphic editors, since they, as a rule, use numerical values of the coordinates of points to visualize them. Based on the definition of an angle as an ordered trio of points of an arbitrary metric space, and the angular characteristic of this angle, the fact of the flat placement of four points of a non-Euclidean metric space is established, and examples of digital visualization of this arrangement using the dynamic geometric environment GeoGebra 3D are given.

Inventarisasi dan Pemetaan Keberagaman Tanaman Obat Keluarga di Desa Rambipuji, Kabupaten Jember: Upaya Pelestarian Pengetahuan Lokal

This study aims to map the diversity of family medicinal plants (TOGA) in Rambipuji Village, Rambipuji District, Jember Regency, East Java. TOGA is an important component in the lives of Indonesian people as an affordable and easily accessible alternative to traditional medicine. Nonetheless, in Rambipuji Village, the potential of TOGA has not been optimally utilized, and information regarding its geographical distribution is still limited. Therefore, accurate mapping is needed to support the utilization and preservation of TOGA. The research method involved three main stages: preparation, implementation, and map-making. In the preparation stage, the research team consulted with village officials to acquire permission and support. The implementation stage involved collecting coordinate point data of various medicinal plant species in the three main hamlets, namely Gudang Karang, Krajan, and Curah Ancar, utilizing the GPS Map Camera application. This data was later analyzed and imported into the QGIS application for the creation of an interactive map. The resulting map shows that there are 126 coordinate points in Gudang Karang Hamlet, 41 points in Krajan Hamlet, and 32 points in Curah Ancar Hamlet, with a total of 48 different medicinal plant species. The resulting TOGA diversity map provides a clear visual picture of the distribution of medicinal plants in Rambipuji Village, whereby it is expected to become a learning tool for the community and support the preservation and sustainable use of TOGA. This mapping is designed to improve the welfare of the community through a more targeted and coordinated utilization of medicinal plants.

Algorithm for Precise Payload Drop From FPV Drone with Account of Wind Strength and Automatic Position Correction

The work is devoted to the development of an automatic system for dropping cargo from an first-person view drone. An analysis of approaches to the construction of this type of system was performed. It is proven that this problem has not been fully solved, which requires the development of new approaches. In order to increase accuracy, it is proposed to use mathematical models that describe the process of cargo unloading. Mathematical models are given that connect such variables as Height, wind speed, drone speed, cargo weight, cargo surface area, wind direction angle relative to the drone, air density. The use of the obtained mathematical models allows you to calculate the coordinates of the reset point. The developed approach was tested in real conditions. The obtained results showed a significant improvement in the accuracy of dropping the load in the presence of a constantly acting wind.

Mapping Agricultural Land Potential Based on the Geographic Information System (GIS) in Muna Regency, Southeast Sulawesi Province

This research aims to determine the potential of agricultural land in Muna Regency based on parameters, namely level of slope, lithology, soil type, rainfall, and level of flood vulnerability. This research was carried out in Muna Regency, Southeast Sulawesi Province, for four months, from February to May 2023. The data collected consisted of secondary data obtained from agencies related to this research and primary data obtained through surveys and direct observation by taking coordinate points for each parameter observed with the help of GPS. The data analysis technique uses overlay analysis, namely overlapping land potential index parameter maps using ArcMap software. The research results show that the area of agricultural land in Muna Regency is 205,769 hectares, distributed over three land potential index classes, namely, the medium land potential class with 50,538 hectares, or 24.6%. second: low land potential class covering 149,345 hectares, or 72.6%; and third: very low land potential class covering 5,886 hectares, or 2.9%. Based on this percentage data, the potential for land for agricultural development in Muna Regency is in the medium potential category. Thus, the actions or solutions needed to increase agricultural productivity are (a) spatial planning of conservation farming systems; (b) development of crop and livestock integration; and (c) location-specific commodity selection.

Measurement and machining error assessment method for cycloid pump rotor profile based on STEP

Abstract The contour shape and machining precision of the rotor of an cycloid pump directly determine the sealing performance of the pump cavity. Precise measurement of contour machining errors is a crucial step in the manufacturing process. However, rotor contour curves are often designed by enterprises based on actual engineering needs, leading to inconsistency between the measured baseline contour and the designed contour, thus failing to accurately reflect the actual machining condition of the rotor. Therefore, this paper proposes a method for measuring the contour of the cycloid pump rotor and evaluating machining errors based on the standard for the exchange of product (STEP) files necessary for product design in manufacturing. Firstly, utilizing NX/OPEN API functions, contour coordinate points and unit normal vectors are obtained from the rotor’s STEP design data. Subsequently, by planning the process of measuring the closed continuous contour of the rotor, the transformation between the workpiece coordinate system and the measurement coordinate system is achieved to position the tested rotor, followed by analyzing the influence of different starting points on error measurement and evaluation determines the optimal starting point. Finally, a measurement sampling point strategy is established to collect data points of the actual machining contour of the rotor. By achieving the best matching between the actual machining contour and the measured baseline contour, a contour deviation calculation model is established. Utilizing gauge blocks enables accurate assessment of pitch deviation, radial runout, and tooth-to-tooth distance deviation, resulting in assessment results that better fit the actual meshing situation of the rotor. Experimental results verifies consistency between the measurements of the one-dimensional probe and Gleason measurements. This theory and method not only expand the measurement range of the one-dimensional probe but also provide more accurate and efficient guidance for the flexible machining of the rotor.

Automatic multi-storey building partitioning from point cloud via bidirectional cloth simulation

With the advancements in scanning technology, the rapid acquisition of point cloud spanning multiple storeys of buildings has become feasible. Accurately dividing the building into individual storeys deepens the understanding of the building environment, accelerates the processing of the vast point cloud, and is crucial for numerous fields such as model reconstruction, indoor navigation, and building management. However, it remains a challenge to handle the building with rooms across multiple storeys. This study presents a novel method to partition complex multi-storey building from cluttered point cloud. First, the non-vertical structural elements are detected by taking the difference of height and normal vector as growth conditions. Next, we iteratively employ bidirectional cloth with height variation constraints to simulate the floor and ceiling trend surface. In this step, candidate ceiling patches are obtained through the optimization of a cost function. Finally, the irregular boundary between adjacent storeys that used for partitioning the point cloud is rasterized in terms of the ceilings at lower storey and the floors at upper storey. Each point is orderly classified into the correspond storey with reference to the elevation of the estimated boundary. Through comprehensive evaluation and analysis, our method has demonstrated its effectiveness and adaptability across various datasets. Our method yields superior results compared to the advanced methods, achieving an approximate value of 99 % on the weighted recall, weighted precision and weighted F1-score. Besides, the proposed method is not limited to Manhattan world buildings and requires only the spatial coordinate of points.

Identification of land fertility and farmer income after an earthquake natural disaster

Liquefaction is a phenomenon where saturated sand and silt take on the characteristics of a liquid during the intense shaking of an earthquake. It takes place when a quake has increased water pressure in saturated soil and made particles in the soil lose contact with each other, making the soil, particularly sandy soil, act like a liquid. On September 28, 2018, an earthquake was occurred which caused liquefaction and a tsunami in Central Sulawesi, Indonesia. This incident triggered a new phenomenon, namely liquefaction in several residential areas in Palu City, especially in the Balaroa and Petobo areas. The liquefaction phenomenon in Petobo Village caused changes in the shape of the land surface. The changes that occurred had an impact on decreasing soil fertility levels in the area along with low crop production and decreased farmer incomes. Soil fertility is a quality value of the soil's ability to provide nutrients for growth. This research aims to determine the level of fertility of agricultural land and the amount of farmer income as well as the best efforts to overcome changes in agricultural land after natural disasters. This research used a descriptive method with a population of all farmers living in the Petobo area affected by the earthquake and liquefaction. There were 25 informants who were determined using a purposive sampling technique. Soil samples were analyzed at the Soil Science laboratory, Faculty of Agriculture, Tadulako University, Palu. The method used in this study is a direct survey method in the field, then continued soil sampling at several points according to the coordinate points carried out by purposive sampling techniques. The status of soil chemical properties at 4 sample points affected by liquefaction and 2 sample point not affected by liquefaction in Petobo Village, which classified as very low to very high. Areas affected by liquefaction had neutral to slightly alkaline soil pH content, very low to low C-organic content, very low N-total content, very high P-total content, low K-total content, and have medium to high CEC content. Meanwhile, areas that are not affected by liquefaction had neutral soil pH content, very low to low C-organic content, very low N-total content, very high P-total content, low K-total content, and have medium to high CEC. The low level of soil fertility in this area means that crop production is also low. Changes in the amount of income experienced by affected farmers who initially had around 77.26 USD- 186.71 USD/month declined to 61.16 USD-77.26/month. This is due to changes in the polarization of farmers' work. Actions that can be implemented to increase soil fertility are correct soil management, use of organic fertilizers such as compost, manure, harvest residues such as (legume plant stover, rice straw) and the addition of chemical fertilizers according to the dosage.

An efficient and automatic method based on monocular camera and GNSS for collecting and updating geographical coordinates of mileage pile in highway digital twin map

Abstract The high-precision positioning of mileage piles on a digital map ensures accurate data for high-speed event releases, toll audits, and road condition monitoring. This paper introduces an efficient and automatic system for positioning highway mileage piles. The self-developed data acquisition system collects mileage pile images and road trajectory. Considering the limited variety of mileage piles, a Simplified-YOLOv5m (S-YOLOv5m) is proposed. Then a high-precision character detection network of S-YOLOv5m is proposed to enhance feature extraction and improve the accuracy of character detection on mileage piles. Thirdly, the end-to-end monocular distance measurement combines the target detection with the distance estimation, enabling simultaneous object detection and distance measurement. Fourthly, by combining with the geographical coordinates of the acquisition point, the direct solution to geodetic problems is applied to calculate the spatial coordinates of the mileage piles. Finally, the missing mileage piles are compensated for using the road curve and equal distance interpolation. The complete mileage piles and geographical information list of the inspection trajectory are output. Through a series of verification tests, the average positioning error of the mileage pile system is 1.265 m. The contribution of the automatic positioning system of mileage piles is to construct the relationship between mileage piles and geographical coordinates, match mileage piles with digital maps to realize the full-featured, real-scene, and high-dynamic management of road attributes.

Error Analysis of Non-Time-Synchronized Lightning Positioning Method

Since the non-time-synchronized lightning positioning method does not rely on the time synchronization of the stations in the positioning system, it eliminates the errors arising from the pursuit of time synchronization and potentially achieves higher positioning accuracy. This paper provides a comprehensive overview of the errors present in the three-dimensional lightning positioning system. It compares the results of traditional positioning methods with those of non-time-synchronized lightning positioning algorithms. Subsequently, a simulation analysis of the positioning errors is conducted specifically for the non-time-synchronized lightning positioning method. The results show that (1) the non-time-synchronized lightning positioning method exhibits greater errors when utilizing two randomly positioned radiation sources for location determination. Consequently, the resulting positioning outcomes only provide a general overview of the lightning discharge. (2) The positioning outcomes resemble those of the traditional method when employing a fixed-coordinate beacon point. However, the errors in the three-dimensional positional coordinates of these fixed-coordinate beacon points significantly impact the deviations in the positioning results. This impact is positively correlated with the positional error of the beacon point, considering both the orientation and magnitude. (3) Similarly to the traditional method, the farther away from the center of the positioning network, the larger the radial error. (4) The spatial position of the selected fixed-coordinate beacon point has little influence on the error.

The visual measurement method of the hole diameter and center-to-center distance of the box based on simplified external parameter calibration

Abstract The hole is a significant mechanical structure type. In this paper, two visual measurement models are established for chamfered and non-chamfered holes. A concentric cylinder with a known diameter is used as a calibration object to obtain the external parameters corresponding to the end face of the measured hole. This approach overcomes limitations associated with using calibration plates for external parameter calibration and aligns better with requirements in production sites. By utilizing the obtained external parameters, three-dimensional coordinates of edge points on the measured hole can be determined, and an ellipse fitting algorithm is employed to obtain aperture and center point coordinates. In the experiment, gearbox housing is used to measure hole diameter and center-to-center distance. The measurements are compared with a coordinate measuring machine, demonstrating a measurement accuracy up to 0.1 mm. The experimental results confirm both feasibility and effectiveness of measurement model while maintaining low operational complexity.

Spatial heterogeneity in the potential distribution of Aedes mosquitoes in India under current and future climatic scenarios

Aedes is the most globally distributed mosquito genus in the 21st century and transmits various arboviral diseases. The rapid expansion of Ae. Aegypti and Ae. albopictus breeding habitats is a significant threat to global public health, driven by temperature and precipitation changes. In this study, bioclimatic variables were employed to predict the spatial distribution of Ae. aegypti and Ae. albopictus in India. The reference coordinate points of (n = 583) Aedes occurrences at a scale of ∼1 km and nineteen bioclimatic factors were retrieved to train SDM (Species Distribution Models) for both species. Maximum entropy modelling was used to predict the species’ fundamental climatic niche distributions. Future projections were made using global climate models for 2021–2040 and 2081–2100 separately. The models performed reasonably well (AUC > 0.77). Both species thrived in reduced diurnal temperature and higher annual mean temperatures, with suitability increasing alongside precipitation. Ae. aegypti’s projected present and future distribution was broader than that of Ae. Albopictus. The expansion of Aedes suitability varied under different future climatic scenarios. Suitability for Ae. aegypti could expand from between 17.6 and 41.1 % in 2100 under SSP (shared socioeconomic pathways) scenarios 1 and 3, respectively, whereas for Ae. albopictus suitability increased from between 10.2 and 25 % under SSP scenarios 1 and 3 respectively. Preparing for future epidemics and outbreaks requires robust vector distribution models to identify high-risk areas, allocate resources for surveillance and control, and implement prevention strategies.

Design and three-dimensional simulation of flat-knitted sports uppers based on loop structure

PurposeThe purpose of this paper is to solve the diverse and complex problems of flat-knitting sports upper process design, improve the design ability of upper organization, and realize three-dimensional simulation function.Design/methodology/approachFirstly, the matrix is used to establish the corresponding pattern diagram and organizational diagram model, and the relationship between the two is established by color coding as a bridge to completed the transformation of the flat-knitted sports upper process design model. Secondly, the spatial coordinates of the loop type value points are obtained through the establishment of loop mesh model, the index of two-dimensional and three-dimensional models of uppers and the establishment of spatial transformation relationship. Finally, using Visual Studio as a development tool, use the C# language to implement this series of processes.FindingsDigitizing the fabric into a matrix model, combined with matrix transformation, can quickly realize the design of the flat-knitting process. Taking the knitting diagram of the upper process as the starting point, the loop geometry model corresponding to the element information is established, and the three-dimensional simulation effect of the flat-knitted upper based on the loop structure is realized under the premise of ensuring that it can be knitted.Originality/valueThis paper proposes a design and modeling method for flat-knitted uppers. Taking the upper design process and 3D simulation effect as an example, the feasibility of the method is verified, which improves the efficiency of the development of the flat-knitted upper product and lays the foundation for the high-end customization of the flat-knitted upper.

An Algorithm for Generating Outdoor Floor Plans and 3D Models of Rural Houses Based on Backpack LiDAR.

As the Rural Revitalization Strategy continues to progress, there is an increasing demand for the digitization of rural houses, roads, and roadside trees. Given the characteristics of rural areas, such as narrow roads, high building density, and low-rise buildings, the precise and automated generation of outdoor floor plans and 3D models for rural areas is the core research issue of this paper. The specific research content is as follows: Using the point cloud data of the outer walls of rural houses collected by backpack LiDAR as the data source, this paper proposes an algorithm for drawing outdoor floor plans based on the topological relationship of sliced and rasterized wall point clouds. This algorithm aims to meet the needs of periodically updating large-scale rural house floor plans. By comparing the coordinates of house corner points measured with RTK, it is verified that the floor plans drawn by this algorithm can meet the accuracy requirements of 1:1000 topographic maps. Additionally, based on the generated outdoor floor plans, this paper proposes an algorithm for quickly generating outdoor 3D models of rural houses using the height information of wall point clouds. This algorithm can quickly generate outdoor 3D models of rural houses by longitudinally stretching the floor plans, meeting the requirements for 3D models in spatial analyses such as lighting and inundation. By measuring the distance from the wall point clouds to the 3D models and conducting statistical analysis, results show that the distances are concentrated between -0.1 m and 0.1 m. The 3D model generated by the method proposed in this paper can be used as one of the basic data for real 3D construction.

Examination of the complementary energy principle in modified couple stress theory and its application for analysis of size effects in the internal force field of functionally graded microbeams

The precise quantification of the internal force field in MEMS piezoresistive sensor micro structure is crucial for ensuring accurate signal output. This paper proposes and proves the complementary energy principle associated with modified couple stress theory (MCST) based on the linear elasticity assumption. And this principle is used to discuss and analyze whether there is a size effect in the internal force field of functionally graded (FG) micro beams for the MEMS piezoresistive sensor. The results show that the size effects exist in the internal forces and the stationary point coordinate x of the total moment for the micro beam. The size effects are related to the dimensionless material scale parameter l/h, the supported spring stiffness, the temperature and the support rotational movements. Intuitive explanations of the size effects are given for the internal force fields and its stationary point coordinates. Behaviors of the solutions agree with the published data when the MCST degenerates into the classical theory (CT).

Multifunctional double network hydrogel with multi-directional actuation and high-precision sensing

Conductive hydrogels have gained great attention for applications in flexible electronics, electronic skins, and as human-machine interfaces. However, poor environmental tolerance of traditional hydrogels and defects in hydrogel actuator make them unfit for use in certain environments. Herein, a small natural molecule, proline (ZP), was introduced into the PAA/CS dual network system to prepare multifunctional hydrogel materials with high concentration of physically crosslinked metal coordination points. The elongation at break and mechanical strength of the hydrogel with optimized structure were 1277 % and 202 kPa, respectively. The effect of ZP on the destruction of hydrogen bonds of free water in the hydrogel provided the hydrogel with excellent temperature resistance. Multiple reversible interactions endowed the PAA/CS/Al0.5/ZP8 hydrogel with excellent self-healing properties at room temperature and even at −40 ℃. The PAA/CS/Al0.5/ZP8 hydrogel sensor with excellent comprehensive performance could be applied for the monitoring of a variety of human motions, small shape changes of flexible objects, and detection of vibrations in rigid pipes. The interactions between Fe3+, ascorbic acid, and -COOH groups on the hydrogel surface were used to record information and erase it repeatedly at low temperature and showed excellent shape memory. Based on the self-healing property, the hydrogel with gradients of swelling rates and water loss rates was assembled into a double-layer actuator, which could complete the actuation process in opposite directions in air and also underwater. This work provides a new idea for the design of soft robots and intelligent switches.

A mathematical model of the combination of lateral tilt and rotation of the vertebra

An important section of spinal biomechanics is the analysis of various types of movements in spinal segments, which are difficult to observe, and setting up experiments is quite complex. There are few articles devoted to this topic, and the methodological approaches outlined in these studies are so heterogeneous that they do not allow for a comparative analysis. In this situation, the abstract language of mathematics allows us to objectively answer the questions that arise. Aim of the study was to develop a mathematical model of a spinal segment to calculate the combination of rotation angles and lateral inclination of the vertebra, as well as to identify factors influencing these parameters. Material and methods. The developed mathematical model of the motion segment of the spine was used as the main tool for the study. The initial data for this model were the coordinates of the reference points of the vertebrae, which makes it possible to determine a number of parameters describing their complex structure. Using this model, the parameters of the combination of vertebral movement in the frontal and horizontal planes were calculated. Results and discussion. The developed model of the combination of movements in the spinal segment is adequate to the ideas about the nature of movements in the spinal segments. The coefficient of combination of lateral tilt and rotation of the vertebra for the cervical vertebrae is from 0.5 to 0.7, for the thoracic vertebrae from 0.3 to 0.5, and for the lumbar vertebrae from 0.0 to 0.1. Fluctuations in the value of this coefficient depend on the angle of inclination of the upper articular surfaces of the underlying vertebra. Reducing the size of the articular surfaces leads to a decrease in the magnitude of the angular movements of the vertebra, and their convergence leads to an increase in mobility in the spinal segments. A negative angle of inclination of the articular surfaces causes opposite rotation of the vertebra.

Strategi Pengembangan Usaha Ningsih Florist Di Kelurahan Kakaskasen Dua Kota Tomohon

This research aims to analyze the business development strategy of Ningsih Florist, which took place during religious and government activities, namely Deville Hardiknas 2024 in Kakaskasen Dua Village, Tomohon City. The research will take place from April to June 2024. The data collection method is by interview method and using a questionnaire. The data collected in this research is primary data obtained from direct interviews with respondents using a list of questions and secondary data in the form of other information related to this research through literature studies. The results of the research show that the strategy for developing the Ningsih Florist business in Kakaskasen Dua Subdistrict, Tomohon City, using SWOT analysis, obtained a matrix at coordinate points (1.88, 1.46), which means that the position is in quadrant 1, namely supporting the growth strategy.