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1994, Computers & Industrial Engineering
In this electronic age, the manufacturing sector has been searching for a unique data structure scheme which can easily represent different data types relating to design, process and inventory management. In this paper, an efficient way of representing the hierarchically significant data, especially in manufacturing, is investigated. Unlike the contemporary tree structure representation using pointers, this approach adopts a unique arithmetic encoding scheme to represent individual paths. The encoded nodes will have the capability to regenerate the entire paths (of a tree) using simple arithmetic procedures. The most significant benefits of this approach are increased data processing efficiency and ease of navigation of data paths in hierarchical data structures. The preliminary testing of this approach on a simulated factory data have indicated significant improvement on data representation and processing efficiency. This structure promises application in Computer Aided Design, Manufacturing Resources Planning, and Hypermedia Data Structure.
Advances in Engineering Software (1978), 1989
A new data structure, which combines a hierarchical organization with a hypergraph-based representation, is presented. This structure, called a structured hypergraph, is a hierarchy of hypergraphs and combines the two concepts of modular decomposition and of description of an entity at different levels of abstraction. Two basic transformations, called refinement and abstraction, are described. These latter are the basic tools for defining and modifying a structured hypergraph. Applications of this structure as a hardware system model, as a description of the symbol table of modular language, as a hierarchical representation of solid objects, and as a model of computer networks are discussed.
A data structure is proposed to maintain a collection of vertex-disjoint trees under a sequence of two kinds of operations: a link operation that combines two trees into one by adding an edge, and a cut operation that divides one tree into two by deleting an edge. The tree is one of the most powerful of the advanced data structures and it often pops up in even more advanced subjects such as AI and compiler design. Surprisingly though the tree is important in a much more basic application-namely the keeping of an efficient index. This research paper gives us brief description of importance of tree in data structure, types of trees, implementation with their examples.
The paper analyzes and compares three different computing platforms for processing tree-like data structures, namely: general purpose computers, embedded processors, and direct mapping of the relevant algorithms to hardware in application-specific circuits. Tree-based recursive data sorting is considered as a case study. The results demonstrate that application-specific hardware is the fastest and processorbased implementation is the slowest. This gives motivation for developing new optimization techniques in the scope of application-specific hardware circuits, which is especially beneficial for FPGA-based design.
International Journal for Simulation and Multidisciplinary Design Optimization, 2021
Searching and handling geometric data are basic requirements of any Computer Aided Engineering application (CAE). Spatial search and local search has greater importance in CAD and CAE applications for reducing the model preparation time. There are many efficient algorithms being made to search geometrical data. Current neighbour search strategy is limited and not efficient in different CAE platforms. R-tree is tree data structure used for spatial access methods. This paper presents a review of R-tree data structure with its implementation in one of the CAE tool for neighbour search and local search. It satisfies current neighbour search requirements in CAE tools. Results shows considerable amount of time saving compared to the conventional approach. This work concludes that R-tree implementation can be helpful in identifying neighbour part and reducing model preparation time in CAD and CAE tools.
Procedia Manufacturing, 2017
In additive manufacturing, the digital information of required object model is transferred to additive manufacturing (AM) machine using a technology-independent de facto file format called STL. The approximation of the actual object surface employing STL file causes loss of geometrical and topological information and introduces error to the digital model. This may also limit the manufacturing repeatability between AM machine and processes. This research focuses on building a common data generation platform directly from the commonly used parametric surface model (B-rep). The generic data structure named as Hierarchical Scanning Data Structure (HSDS) is proposed in this research. HSDS will store the actual digital scanning information systematically and sequentially. A common application program interface (API) platform is also proposed in this research, which can access the HSDS and generate machine readable file for different existing AM control systems. The data stored in HSDS can be retrieved remotely and be used by different existing AM controller supporting the cloud/cyber manufacturing process and ensure the platform-independent object repeatability. The proposed framework is implemented with examples and results are compared with the existing system.
Model and method for representing complex dynamic information objects based on LMS-trees in NoSQL databases, 2021
The article analyzes the existing approaches to the description of large dynamic information objects in the construction of Automated control systems. Introduced and defined the concept of a Complex Dynamical Information Object. A comparative analysis of the temporal complexities of tree-like structures is carried out and the optimal one for working with Complex Dynamical Information Object is selected. Most modern automated control systems use various approaches to describe automation objects for their operation. Under the automation object, we mean functional objects that are described in the form of structural models that reflect the properties of physical objects. Thus, for optimal work with complex dynamic information objects, we have developed our own model and method for describing the LMS-tree (Log-structured merge-tree), with the ability to split and store down to elementary levels. One of the features of our approach to describing objects is the presence of tree-like levels-the so-called "leaves", by which we mean special tree elements that expand the description of the tree structure of a particular tree level. The minimal elements of the leaves of the tree-"veins"-are details, that is, elementary information elements. A leaf is a combination of "veins" (details) according to certain characteristics, which provide extended information about the level of the tree object. An atomic-level descriptor is a multiple NoSQL database field (array) where the tree level number is the index of the database array. This approach allows you to retrieve and group objects according to the element level of the tree definition.
The Need for Data Structures is to organize data more efficaciously for complex applications. Many data structures exist but we need to select the confiscated data structure to meet the solution. A survey has been carried out on different types of data structures to identify their qualities and demarcations. This paper describes prominent data structures in a consistent manner to provide a concise comparison on performance of data structures. This paper presents a brief study on performance, time complexity and applications of data structures. This paper classifies data structures into seven categories that group them according to their time complexity.
A tree is a non-linear data structure for fast storing and retrieval of data in primary memory. It represents data in the form of hierarchical form. Data are stored in a tree i.e. called as a node, in which topmost node is called root and each node has one or more nodes lying on the left or right side of a tree. Except for root node each node has a parent node. The information can be extracted from a tree through various traversal algorithms. Tree traversal means visiting the nodes of a tree at once. In this paper, we are studying different algorithms for tree traversal
Procedia Manufacturing, 2017
STEP-NC is a new standard for Computer Numerical Control (CNC) machine tool programming. It contains many elaborated data models for milling and turning, including the representation of parameters and geometry of machining features. The paper presents the use of STEP-NC data model for CAPP system under the development. The structure of manufacturing process was analyzed and the method to represent it using STEP-NC entities was proposed. New entities were added to store the information required by CAPP system, including the manufacturing process other than machining. Express-G data modelling language was used for this purpose.
Advances in Engineering Software, 1997
Layered manufacturing (LM) is an emerging technology for fabricating parts, layer by layer. This technique offers several advantages over conventional manufacturing. The data representation and exchange issues in LM are crucial, and currently the STL format is used as an industry standard. In this paper, we consider 3-D and slice data formats in LM and analyse their strengths and weaknesses. We perform an in-depth analysis of the STL format and comment on the perceived need for its replacement. We also propose metrics for the evaluation of the 3-D and slice formats and compare them. The study reported in this paper can provide guidelines for the development of new representations and formats for use in LM. 8 1997 Elsevier Science Limited. All rights reserved.
2016
There are many situations in which information has a hierarchical or nested structure like that found in family trees or organization charts. The abstraction that models hierarchical structure is called a tree and this data model is among the most fundamental in computer science. It is the model that underlies several programming languages, including Lisp. Trees of various types appear in many of the chapters of this book. For instance , in Section 1.3 we saw how directories and files in some computer systems are organized into a tree structure. In Section 2.8 we used trees to show how lists are split recursively and then recombined in the merge sort algorithm. In Section 3.7 we used trees to illustrate how simple statements in a program can be combined to form progressively more complex statements. The following themes form the major topics of this chapter: 3 The terms and concepts related to trees (Section 5.2). 3 The basic data structures used to represent trees in programs (Sect...
2002
This paper describes some improvements over the original Space-Optimized Tree technique for the visualization and manipulation of very large hierarchies. The new system uses an improved algorithm to calculate geometrical layouts and it also provides better navigation capability. We introduce our new layout algorithm that can make more consistence of the display than the original layout technique made. We also combine DualView (a new focus+context technique) with the current modified semantic zooming in order to interactively navigate through the large and very large hierarchies.
People and Computers XXEngage, 2007
This paper describes the first full implementation and evaluation of an area-based tree visualization known as the PieTree. The PieTree was first proposed in papers in 1998 and 2000 but has never been fully implemented and evaluated. Informal evaluation was used to enhance the usability of the PieTree and compare it with the more well-known TreeMap. A controlled experiment considered parallel views' effect on task performance time. There were substantial differences between kinds of tasks and in participants' styles of use. Whilst suggesting that further development of PieTrees is worthwhile the experiments underline the importance of careful task fit.
A compact data structure to keep large transactions is very important. One of the alternatives is to use tree data structure. However, not all of them can effort to handle the incremental online transactions and still limited to offline processes such as to build frequent pattern tree (FP-Tree). The main drawback of typical FP-Tree is it must rely on the offline databases. Therefore, this paper suggested Fast Online Trie Algorithm (FOLTA) to build our predefined incremental tree data structure, Disorder Support Trie Itemset (DOSTrieIT). Experiments with the UCI datasets show that the FOLTA can replace th e dependency of offline database, up to 2 times faster than the benchmarked CanTree algorithm.
B-tree and R-tree are two basic index structures; many different variants of them are proposed after them. Different variants are used in specific application for the performance optimization. In this paper different variants of B-tree and R-tree are discussed and compared. Index structures are different in terms of structure, query support, data type support and application. Index structure’s structures are discussed first. B-tree and its variants are discussed and them R-tree and its variants are discussed. Some structures example is also shown for the more clear idea. Then comparison is made between all structure with respect to complexity, query type support, data type support and application.
2012 19th IEEE International Conference on Electronics, Circuits, and Systems, ICECS 2012, 2012
The paper evaluates tree-based implementations of data sorting algorithms in FPGA circuits using hierarchical finite state machine (HFSM) as a computational core. We focus here on experiments which show effectiveness of sorting algorithms over data structures represented in form of N-ary trees (N≥2). The presented results compare different types of data representation and processing in terms of performance and memory requirements. It is shown that using advanced FPGAs and the proposed address-based methods the number of sorted items with size 32-64 bits can reach 2 32 .
ACM SIGARCH Computer Architecture News, 1983
A VLSI chip for performing relational data base operations is proposed. The chip is a tree of processors (TOP), where each chip has elementary storage and processing capabilities. A relation will be stored in the lowest levels of a TOP. More precisely, every m-tuple will occupy a subtree whose root is s= [log 2 (m+1)] =1 levels above the leaves. Denoting by h the height of the tree, the upper h-s levels will be used for routing and bookkeeping purposes. A number of basic operations such as allocate and deallocate subtrees, insert and compare m-tuples etc., are defined for the TOP's. Relational operations are effectively performed as simple combinations of basic operations. The architecture of a data base machine based on TOP's is also sketched. Such a machine is feasible with the current VLSI technology and could become attractive in few years if density and performance of VLSI keep improving at the current rate.
Automation in Construction, 2020
The Industry Foundation Classes (IFC) are a prevalent data model in which Building Information Models can be exchanged, typically with a file-based nature. Processing the full extent of these models can be time-consuming. Considering the multidisciplinary nature of the construction industry, stakeholders will typically only be interested in a small subset, depending on the purpose of the exchange. Therefore, the retrieval of relevant subsets, whether spatially, based on discipline, or others, is necessary to effectively consume such datasets in downstream applications. Prevalent encoding forms of IFC models are text-based and do not facilitate random-access seeking within the file and do not impose an ordering on the definition of elements within the file. Therefore, typically, the entire file needs to be read in order to find the data of interest. Furthermore, text-based data is slower to parse in comparison to binary data. This paper assesses a binary serialization format originating from the family of EXPRESS standards. It is based on an existing open, binary, hierarchical data format called HDF5 that allows random access to specific instances and therefore efficient retrieval of relevant subsets. The block-level, transparent compression yields a reduction of file sizes as compared to traditional serializations. Fully specified datatypes embedded in the exchange guarantee interoperable use. In this paper, several serialization profiles are introduced that cater to specific use cases by governing storage settings. Advanced functionality from the HDF5 library is applied to offer novel paradigms for fine-grained access rights, varying level of detail, revision management and aggregation of aspect models.
ACM Computing Surveys, 1976
This survey paper discusses the facilities provided by hierarchical data-base management systems. The systems are based on the hierarchical data model which is defined as a special case of the network data model. Different methods used to access hierarchically organized data are outlined. Constructs and examples of programming languages are presented to illustrate the features of hierarchical systems. This is followed by a discussion of techniques for implementing such systems. Finally, a brief comparison is made between the hierarchical, the network, and the relational systems.
Computers & Graphics, 1988
The search for better representational and display techniques has been and continues to be one of the major problems in solid modelling. This paper presents a new constructional technique for representation and display of any 3-D objects through Hex-tree, using a single cubical cell as primitive. The memory requirement for representation/manipulation is less, and the Boolean operations, geometric operations and display from any point in the space are simple. This developmental work was carded out in FORTRAN language on VAX-11/780 system using Tektronic-4027 color graphics terminal.
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