Spatial Representation Method Research Articles

A cluster differences unfolding method for large datasets of preference ratings on an interval scale: Minimizing the mean squared centred residuals.

Clustering and spatial representation methods are often used in combination, to analyse preference ratings when a large number of individuals and/or object is involved. When analysed under an unfolding model, row-conditional linear transformations are usually most appropriate when the goal is to determine clusters of individuals with similar preferences. However, a significant problem with transformations that include both slope and intercept is the occurrence of degenerate solutions. In this paper, we propose a least squares unfolding method that performs clustering of individuals while simultaneously estimating the location of cluster centres and object locations in low-dimensional space. The method is based on minimising the mean squared centred residuals of the preference ratings with respect to the distances between cluster centres and object locations. At the same time, the distances are row-conditionally transformed with optimally estimated slope parameters. It is computationally efficient for large datasets, and does not suffer from the appearance of degenerate solutions. The performance of the method is analysed in an extensive Monte Carlo experiment. It is illustrated for a real data set and the results are compared with those obtained using a two-step clustering and unfolding procedure.

FIImap: Fast Incremental Inflate Mapping for Autonomous MAV Navigation

Three-dimensional mapping is an essential component of autonomous Micro Aerial Vehicle (MAV) navigation. The paper focuses on the 3D spatial representation method of MAV to overcome the collision problem caused by soft constraints, control error, and planning with the center of mass by inflating the occupancy grid map. A fast incremental inflated map construction method is proposed, which reduces the time-consumption caused by the increase of map range and inflated size. The method focuses on areas of the map that occupied state changes and introduces two arrays that record newly appearing and disappearing obstacles. Then, a series of breadth-first search algorithms are used to traverse the parts of the inflated map that need local modification to update the inflated map. Moreover, a sliding map model is designed based on the MAV position, which is suitable for large-range autonomous flight. The effectiveness of the proposed approach is verified with simulated and actual flight data. The proposed method takes about 3 ms to construct the inflated map with a local update range of 16 m × 16 m × 6 m.

DESKRIPSI PENALARAN SPASIAL MAHASISWA CALON GURU BERGAYA BELAJAR VISUAL

Spatial thinking is a skill to remember, operate, manipulate, predict, combine, interpret, transform, explore an object to solve problems in various life contexts. Spatial thinking requires three related components, namely: the concept of space, spatial representation methods, and spatial reasoning. The difficulty of students for representing ideas encourages researchers to observe the spatial reasoning of elementary teacher training program’s student. Visual learning style is closely related to exact mathematical soul. Therefore, this study focuses on describing elementary teacher training program’ student’s visual learning style. The subjects of this research are students of class 2019 A and 2019 B as many as 70 elementary teacher training program’s student who are taking elementary school mathematics learning courses at a University in Surabaya and have been grouped into high, medium groups. and below. Medium group elementary teacher training program’s student were selected to be given a learning style test, which then described their spatial reasoning. The purpose of this study was to describe the reasoning of elementary teacher training program student’s visual learning style. This research is a descriptive qualitative research. Researchers used written test, geometry problem-solving questions, and interviews to explore in-depth information on students who are elementary teacher training program’s student of visual learning style. There are 40 students in the medium group with details of 10 students with visual learning style, 30 students with auditory learning style and 10 students with kinesthetic learning style. The group of students who are elementary teacher training program student’s visual learning style are analyzed for their spatial reasoning based on the results of written tests and interviews. The results showed that the visual learning style student’s group tended to work sequentially and neatly meeting the criteria for spatial reasoning indicators. Visual learning style of elementary teacher training program’s student (KSV) could describe their spatial reasoning through the process of categorizing, generalizing, synthesizing, evaluating, define, combine, and represent in solving geometric problems. One of the main characteristics of visual learning styles appears when they manipulate objects and illustrate with sketches. They carry out the work process in detail and detail, and represent through pictures or visuals

The Evolution of the Urban Residential Space Structure and Driving Forces in the Megacity—A Case Study of Shenyang City

For megacities, they are in a period of transformation from extensive development to smart growth. Recognizing new characteristics and new changes of the residential space in megacities under the backdrop of new development has great practical significance for realizing the sustainable development of the city. As the only megacity in Northeast China, Shenyang was selected to be the research object, with 1989–2018 as the research period. The research comprehensively used multiple spatial representation methods and statistical methods to study the residential space pattern and driving factors in Shenyang City. The results showed that: (1) Residential space expansion can be divided into four stages: slow development, rapid expansion, speedy expansion, and stable extension. (2) The residential space structure presented a spatial evolution characteristic of overall expansion, forming multiple secondary core density centers. The east-west direction had a larger extension range than the northeast-southwest direction. There was an axisymmetric zonal distribution on both sides of the Hun River. (3) The agglomeration of different residential forms was obvious, and the spatial heterogeneity was increasingly stronger. (4) Urban planning measures and economic strength were the main driving forces of residential space expansion.

IT TECHNOLOGIES IN ARCHITECTURE AND SPACE REPRESENTATION. BRUNO ZEVI METHODS REVISED

Abstract Space representation methods as described by Bruno Zevi in “Architecture as space” are still valid today. Projections, elevations, models, photos and films are commonly used and all of them define the space in a specific way, yet none defines it completely. The development of IT technologies caused emergence of new methods which shape the picture of today’s architecture. Originally, a conventional technical drawing was adapted to the computer environment, but it was the 3D technology that revolutionized spatial representation, by restoring priority to the three-dimensional aspect of reality. Models allow us to explore the virtual reality, which is a huge progress in spatial representation. Thanks to advanced software, buildings of complex structure are formed, bearing testimony of their times – times of IT technologies. A flawless spatial representation method that perhaps will be known in the future should satisfy multi-plane needs of the observer, who experiences the represented space with all senses and impacts it as well.

Evacuation simulation using Hybrid Space Discretisation and Application to Large Underground Rail Tunnel Station

AbstractIn all evacuation simulation tools, the space through which agents navigate and interact is represented by one the following methods, namely Coarse regions, Fine nodes and Continuous regions. Each of the spatial representation methods has its benefits and limitations. For instance, the Coarse approach allows simulations to be processed very rapidly, but is unable to represent the interactions of the agents from an individual perspective; the Continuous approach provides a detailed representation of agent movement and interaction but suffers from relatively poor computational performance. The Fine nodal approach presents a compromise between the Continuous and Coarse approaches such that it allows agent interaction to be modelled while providing good computational performance. Our approach for representing space in an evacuation simulation tool differs such that it allows evacuation simulations to be run using a combination of Coarse regions, Fine nodes and Continuous regions. This approach, which we call Hybrid Spatial Discretisation (HSD), is implemented within the buildingEXODUS evacuation simulation software. The HSD incorporates the benefits of each of the spatial representation methods whilst providing an optimal environment for representing agent movement and interaction. In this work, we demonstrate the effectiveness of the HSD through its application to a moderately large case comprising of an underground rail tunnel station with a population of 2,000 agents.

Research on a Rotating Machinery Fault Prognosis Method Using Three-Dimensional Spatial Representations

Process models and parameters are two critical steps for fault prognosis in the operation of rotating machinery. Due to the requirement for a short and rapid response, it is important to study robust sensor data representation schemes. However, the conventional holospectrum defined by one-dimensional or two-dimensional methods does not sufficiently present this information in both the frequency and time domains. To supply a complete holospectrum model, a new three-dimensional spatial representation method is proposed. This method integrates improved three-dimensional (3D) holospectra and 3D filtered orbits, leading to the integration of radial and axial vibration features in one bearing section. The results from simulation and experimental analysis on a complex compressor show that the proposed method can present the real operational status and clearly reveal early faults, thus demonstrating great potential for condition-based maintenance prediction in industrial machinery.

An Object-Level Feature Representation Model for the Multi-target Retrieval of Remote Sensing Images

To address the problem of multi-target retrieval (MTR) of remote sensing images, this study proposes a new object-level feature representation model. The model provides an enhanced application image representation that improves the efficiency of MTR. Generating the model in our scheme includes processes, such as object-oriented image segmentation, feature parameter calculation, and symbolic image database construction. The proposed model uses the spatial representation method of the extended nine-direction lower-triangular (9DLT) matrix to combine spatial relationships among objects, and organizes the image features according to MPEG-7 standards. A similarity metric method is proposed that improves the precision of similarity retrieval. Our method provides a trade-off strategy that supports flexible matching on the target features, or the spatial relationship between the query target and the image database. We implement this retrieval framework on a dataset of remote sensing images. Experimental results show that the proposed model achieves competitive and high-retrieval precision.

An agent based evacuation model utilising hybrid space discretisation

Egress models typically use one of three methods to represent the physical space in which the agents move: coarse network, fine network or continuous. In this work, we present a novel approach to represent space, which we call the ‘Hybrid Spatial Discretisation’ (HSD), in which all three spatial representations can be utilised to represent the physical space of the geometry within a single integrated software tool. The aim of the HSD approach is to encompass the benefits of the three spatial representation methods and maximise computational efficiency while providing an optimal environment to represent the movement and interaction of agents.

A comparison of methods to spatially represent pelagic longline fishing effort in catch and bycatch studies

Bycatch in fisheries has been recognized as a threat to many endangered populations of sea turtles, sea birds and marine mammals. Interactions between pelagic longline fisheries and critically endangered populations of leatherback sea turtles ( Dermochelys coriacea) have led to temporary closures of the Hawaiian pelagic longline swordfish fishery and severe bycatch quotas. The negative impact of these events on both the populations of certain endangered species and the economic livelihood of the fishermen has resulted in a strong push from all sides to better understand bycatch events. Typically, analyses of longline catch and bycatch have examined fishing effort summarized over large areas (≥1°). Although aggregation of effort to this level may be necessary to account for uncertainty, confidentiality concerns, or to make comparisons across regions, it specifically limits the researcher's ability to characterize the local oceanographic factors that may drive individual bycatch events. Higher resolution analyses must be undertaken to identify such features. However, for these higher resolution analyses, the methods currently used to spatially represent pelagic longline fishing effort may significantly affect researcher's results. Here, we look at different methods to represent this fishing effort (i.e., points, centroids, polylines and polygons) at various resolutions (2 km to 5°) to better understand which method and spatial resolution are most appropriate. Our results validate the use of point features to represent fishing effort in previous low resolution studies of the Hawaiian pelagic longline fishery by showing that the set point method is suitable for studies with resolutions lower than 15 km. However, at higher resolutions (≤15 km) and in areas with more sparsely distributed fishing, aggregated effort values differed significantly between spatial representation methods. We demonstrate that the use of polygons to describe pelagic longline fishing effort is more representative and necessary for such high resolution analyses.

Image database design based on 9D-SPA representation for spatial relations

Spatial relationships between objects are important features for designing a content-based image retrieval system. We propose a new scheme, called 9D-SPA representation, for encoding the spatial relations in an image. With this representation, important functions of intelligent image database systems such as visualization, browsing, spatial reasoning, iconic indexing, and similarity retrieval can be easily achieved. The capability of discriminating images based on 9D-SPA representation is much more powerful than any spatial representation method based on minimum bounding rectangles or centroids of objects. The similarity measures using 9D-SPA representation provide a wide range of fuzzy matching capability in similarity retrieval to meet different user's requirements. Experimental results showed that our system is very effective in terms of recall and precision. In addition, the 9D-SPA representation can be incorporated into a two-level index structure to help reduce the search space of each query processing. The experimental results also demonstrated that, on average, only 0.1254 percent /spl sim/ 1.6829 percent of symbolic pictures (depending on various degrees of similarity) were accessed per query in an image database containing 50,000 symbolic pictures.

A fast spatial representation method (applied to fixture design)

A type of cellular-decomposition, solid-model representation based on variable orthorhombic cells and using a threedimensional matrix data structure is presented. It was developed to do two things that other representation methods cannot do easily or quickly. This method directly provides information concerning intersecting components, and it is fast enough to allow checks for intersection to be made in iterative routines. The method has application to layout design where interference checking is important. The method and the essential algorithms are described. An application to fixture design is presented.

Representing Bipolar And Complex Imagery In Noncoherent Optics Image Processing Systems: Comparison Of Approaches

Noncoherent-optics systems are linear in irradiance, which is a nonnegative, real quantity; bipolar and complex data must be indirectly represented. We compare spatial representation methods and evaluate their relative merits.