Non-geometric Attributes Research Articles

Exploiting geographic open data to improve urban building energy simulations: The Padova city center case study

In recent years, building stock models have been developed by researchers to examine the aggregate performance of stacks of buildings within large areas, thereby giving rise to the concept of urban building energy models (UBEMs). The input data for such models consists of geometric and non-geometric attributes of the buildings, in addition to meteorological information. In this perspective, the acquisition of precise and comprehensive data poses a challenge, as the existing datasets often lack certain parameters or are not in a standardized format. This study aims to address the challenges by proposing a workflow for generating an input data frame tailored for incorporation into UBEMs. The data frame should include all the essential parameters of the buildings, and its constitution should be reflective of the real-world data. Moreover, the proposed workflow should remain consistent with databases available at national or regional levels. Acknowledging this non-uniformity in databases across regions, the methodology proposed in this study strategically considers various alternatives. For this reason, the proposed automatized workflow ensures flexibility and adaptability to changes in data availability. The workflow proposed in this study is a QGIS based geographical calculation method. The method can combine data from various sources into one shapefile that can be used to simulate the energy performance of buildings in urban areas.

IFC-based performance data checking for ventilation system design

ABSTRACT With the development of Building information modelling (BIM) tools, the non-geometric attributes of duct elements, such as size, flow rate, and pressure loss, can be exported directly. BIM has been used in numerous building projects. However, there is no clarity in checking the performance data in mechanical, electrical, and plumbing design using the Industry Foundation Classes (IFC) data. In this study, the IFC definitions for duct system, element, distribution port, and user-defined IFC-property set (Pset) according to the IFC2x3 specification are introduced. Based on the design criteria for ventilation system, three checking rules for friction loss, duct velocity, and the diffuser’s neck velocity are extracted. A sorting algorithm for duct elements in the ventilation system is proposed by searching the connections between duct elements and the related distribution ports. Furthermore, the critical path is determined by comparing path lengths from different diffusers to the AHU. Therefore, the IFC-based performance data checking for the duct design is proposed. A case study is also presented. The results show that the performance data of the duct elements in the critical path meet the design criteria, and the total pressure loss of the ventilation system is calculated.

Impacts of nongeometric attributes on crash prediction at urban signalized intersections of developing countries

Urban crashes in the signalized intersections have become a worsening road safety problem and result in unacceptably high socioeconomic toll placing a heavy burden on health and economics. Few studies have been conducted to incorporate the nongeometric attributes in generating crash prediction model for developing countries. Hence, this research investigates the effects of such attributes, that is, traffic volume, bus passenger’s activities, on-street parking, establishments nearby intersection, on the probability of crashes in urban signalized intersections of developing countries through crash prediction models (CPMs) under Empirical Bayesian (EB) framework. Mean absolute error, root mean square error, average accuracy, and statistical correlation of crash count have been utilized for the validation of the proposed models. Total road crashes are likely to be increased by around 5.3% for 10% increase in traffic volume at the intersection whereas presence of on-street parking on major roads is causing a 34.2% reduction in predicted total collision. Low bus passenger activity has been found as a relatively higher effect on crashes than the high bus passenger activity. Such findings have the potential to provide new insights in the occurrences of crashes and quantify the effects of several unique nongeometric attribute at urban intersections.

Dual clustering: integrating data clustering over optimization and constraint domains

Spatial clustering has attracted a lot of research attention due to its various applications. In most conventional clustering problems, the similarity measurement mainly takes the geometric attributes into consideration. However, in many real applications, the nongeometric attributes are what users are concerned about. In the conventional spatial clustering, the input data set is partitioned into several compact regions and data points which are similar to one another in their nongeometric attributes may be scattered over different regions, thus making the corresponding objective difficult to achieve. To remedy this, we propose and explore in this paper a new clustering problem on two domains, called dual clustering, where one domain refers to the optimization domain and the other refers to the constraint domain. Attributes on the optimization domain are those involved in the optimization of the objective function, while those on the constraint domain specify the application dependent constraints. Our goal is to optimize the objective function in the optimization domain while satisfying the constraint specified in the constraint domain. We devise an efficient and effective algorithm, named Interlaced Clustering-Classification, abbreviated as ICC, to solve this problem. The proposed ICC algorithm combines the information in both domains and iteratively performs a clustering algorithm on the optimization domain and also a classification algorithm on the constraint domain to reach the target clustering effectively. The time and space complexities of the ICC algorithm are formally analyzed. Several experiments are conducted to provide the insights into the dual clustering problem and the proposed algorithm.

Heterogeneous object modeling through direct face neighborhood alteration

Two recent advances—the use of functionally gradient materials in parts and layered manufacturing technology—have brought to the forefront the need for design and fabrication methodologies for heterogeneous objects. However, current solid modeling systems, a core component of computer-aided design and fabrication tools, are typically purely geometry based, and only after the modeling of product geometry, can a part's non-geometric attributes such as material composition be modeled. This sequential order of modeling leads to unnecessary operations and over-segmented 3D regions during heterogeneous object modeling processes. To enable an efficient design of heterogeneous objects, we propose a novel method, direct face neighborhood operation. This approach combines the geometry and material decisions into a common computational framework as opposed to separate and sequential operations in existing modeling systems. We present theories and algorithms for direction face neighborhood alteration, which enables direct alteration of face neighborhood before 3D regions are formed. This alteration is based on set membership classification (SMC) and region material semantics. The SMC is computationally enhanced by the usage of topological characteristics of heterogeneous objects. After the SMC, boundary evaluation is performed according to the altered face neighborhood. In comparison with other solid modeling methods, the direct face neighborhood alteration method is computationally effective, allows direct B-Rep operations, and is efficient for persistent region naming. A prototype system has been implemented to validate the method and some examples are presented.

The development of an integrated and intelligent cad/ capp/ cafp environment using logic-based reasoning

The integration of design and manufacturing poses to the researchers in the fields of cad, cam and cim a series of challenges. This paper introduces a methodology and a prototype system that allows for the integration of product design with manufacturing process planning. The task is achieved through an intelligent cad- capp- cafp environment where a designed model from the cad system can be analysed, and manufacturing process plans with specifications of machining and fixturing methods can be automatically determined. The manufacturing information of a part required for process and fixture planning is extracted from the 3D geometric model and the 2D engineering drawing, thereby both geometric and non-geometric attributes of a part can be obtained. An integrated approach to process and fixture planning is adopted to ensure that the process plan for a machined part is generated on the basis of a workable fixture plan. The overall integration is achieved through the underlying unified logical representation.

Interactive Learning of a Multiple-Attribute Hash Table Classifier for Fast Object Recognition

Multiple-attribute hashing is now considered to be a powerful approach for the recognition and localization of 3D objects on the basis of their invariant properties. In the systems developed to date, the structure of the hash table is fixed and must be created by the system developer—an onerous task especially when the number of attributes is large, as it must in systems that use both geometric and nongeometric attributes. Another deficiency of previous systems is that uncertainty is treated as a fixed value and not modeled. In this paper, we will present a system, named MULTI-HASH, which uses the tools of decision trees and uncertainty modeling for the automatic construction of hash tables. The decision-tree framework in MULTI-HASH is based on a hybrid method that uses both qualitative attributes, such as the shape of a surface, and quantitative attributes such as color, dihedral angles, etc. The human trainer shows objects to the vision system and, in an interactive mode, tells the system the model identities of the various segmented regions, etc. Subsequently, the decision-tree-based framework learns the structure of the hash table.

INTEGRATION OF GEOMETRIC AND NON-GEOMETRIC ATTRIBUTES FOR FAST OBJECT RECOGNITION

Both man-made and natural objects are described by both their geometric shapes and by their non-geometric attributes such as color. The objective of the proposed research is to create a system which integrates geometric and non-geometric attribute information for fast 3D model-based object recognition. Hashing is employed in a hypothesize and verify approach to the 3D model-based object recognition problem. Viewpoint independent attributes are used in the hypothesis generation stage to eliminate model objects from consideration during hypothesis formation. Utilizing more than one attribute in the proposed hashing scheme helps to ensure a reduction in the actual execution time for object recognition over a larger number of model bases. A nice feature of the system is that new object attributes can be added with relative ease. Issues concerning the ranking of attributes by their distinctiveness with respect to the objects in the model base are discussed. Current work on the use of an information theoretic measure in the design of an optimal multiple attribute hash table is presented.

A relational database for non-manipulative representation of solid objects

As the heart of any solid modelling system, much effort has been spent on formulating the data models which represent the shape of a polyhedral solid object within the computer in an accurate, unique and complete manner. Most of this effort has been devoted to make the models manipulateable in terms of computational efficiency, and preserve their semantic integrity. The price paid for achieving these goals is a proliferation of cross-reference data links which, coupled with multiple redundancy, renders the models inefficient for storage or transmission over communication channels. Moreover, the interrogation of these models by non-manipulative applications is usually unsupported functionally, requiring direct accesses to the data, which involves extensive pointer chasing and therefore high familiarity with the manipulative data structure. This paper presents an example relational model as a complementary logical scheme for viewing the shape database that facilitates compact storage and supports non-manipulative query operations through the projection, selection and join operators defined for the relational model, without requiring expert knowledge of the manipulative structure. The flexibility of the relational model, compared with that of the hierarchical, manipulative one, allows easy extensibility and the association of non-geometric attributes with each data item.